Towards personalized treatment planning of chemotherapy: [ … 1 - 10... · not. Positron emission tomography (PET) is an imaging technique that may be useful for personalized treatment

Towards personalized treatment planning of chemotherapy: [11C]docetaxel PET studies

in lung cancer patients

Astrid A.M. van der Veldt

The studies presented in this thesis were performed at the Department of Nuclear Medicine & PET Research and the Department of Pulmonology, VU University Medical Center, Amsterdam, the Netherlands.

The research presented in this thesis was supported by a grant of the Cancer Center Amsterdam.

Publication of this thesis was financially supported by: Amgen B.V., Astellas Pharma B.V., Bayer HealthCare, Boehringer Ingelheim B.V., Janssen-Cilag B.V., Philips Healthcare Nederland, Roche Nederland B.V., and Stichting Ina Veenstra-Rademaker. Cover design by Guusje Bertholet Printed by Ipskamp Drukkers B.V., Enschede. ISBN 978-94-6191-319-7 Copyright © 2012 Astrid A.M. van der Veldt, [email protected] All rights reserved. No part of this publication may be reproduced, stored in retrieval system or transmitted in any form or by any means, electronically, mechanically, by photocopying, recording or otherwise, without prior written permission of the author.

VRIJE UNIVERSITEIT

Towards personalized treatment planning of chemotherapy: [11C]docetaxel PET studies

in lung cancer patients

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam,

op gezag van de rector magnificus prof.dr. L.M. Bouter,

in het openbaar te verdedigen ten overstaan van de promotiecommissie

van de Faculteit der Geneeskunde op woensdag 4 juli 2012 om 13.45 uur

in de aula van de universiteit, De Boelelaan 1105

door

Astrid Aplonia Maria van der Veldt

geboren te Rotterdam

promotoren: prof.dr. A.A. Lammertsma

prof.dr. E.F. Smit

copromotor: dr.ir. M. Lubberink dr. N.H. Hendrikse

Contents

Chapter 1 General introduction and outline of the thesis 7

Chapter 2 Individualized treatment planning in oncology: role of PET and 27 radiolabelled anticancer drugs in predicting tumour resistance Curr Pharm Des 2008;14:

2914-31

Chapter 3 Quantitative parametric perfusion images using 15O-labeled water 49 and a clinical PET/CT scanner: test-retest variability in lung cancer J Nucl Med 2010;51:1684-90 & Eur Radiol 2011;21:2148-9

Chapter 4 [11C]docetaxel and positron emission tomography for noninvasive 63 measurements of docetaxel kinetics

Clin Cancer Res 2007;13:7522

Chapter 5 Biodistribution and radiation dosimetry of 11C-labeled docetaxel in 67 cancer patients

Eur J Nucl Med Mol Imaging 2010;37:1950-8

Chapter 6 Absolute quantification of [11C]docetaxel kinetics in lung cancer 79

patients using positron emission tomography Clin Cancer Res 2011;17:4814-24

Chapter 7 Towards prediction of efficacy of chemotherapy: a proof of concept 95

study in lung cancer using [11C]docetaxel and positron emission tomography Submitted for publication

Chapter 8 Rapid decrease in delivery of chemotherapy to tumors after 119

anti-VEGF therapy: implications for scheduling of anti-angiogenic drugs

Cancer Cell 2012;21:82-91

Chapter 9 Summary 133 Chapter 10 Discussion and future perspectives 139 Nederlandse samenvatting 159 Dankwoord 167 Curriculum vitae 175 Publications 179

5

Chapter 1

General introduction and outline of the thesis

1.0 Background

2.0 Positron emission tomography (PET)

2.1 Principles of PET

2.2 Kinetic modeling of PET data

2.3 PET imaging in oncology

3.0 Docetaxel

3.1 Mechanism of action

3.2 Administration of docetaxel

3.3 Docetaxel for treatment of cancer

3.4 Side-effects associated with docetaxel treatment

4.0 [11C]docetaxel PET microdosing

4.1 Radiolabeling of docetaxel

4.2 Validation of [11C]docetaxel PET in lung cancer patients

5.0 Lung cancer

5.1 Epidemiology

5.2 Histology

5.3 Staging and survival

5.4 Treatment of lung cancer

6.0 Outline of the thesis

8

1.0 Background

Over the past decades, the development of new drugs and treatment modalities has

improved the perspectives of many cancer patients. At present, numerous drugs are

available for the treatment of these patients. The ever increasing number of available

anticancer drugs, however, has not necessarily made it easier to treat patients, as it can

be difficult to decide on the optimal treatment regimen for an individual patient. Most

systemic anticancer treatments fail in a substantial number of patients and are

associated with several toxicities, which can be severe. Therefore, refinement is needed

to identify those patients who are likely to benefit from a specific drug and those who do

not. Positron emission tomography (PET) is an imaging technique that may be useful for

personalized treatment planning in cancer patients. In particular, radiolabeling of

anticancer drugs with a positron emitter is promising for individualized treatment

planning. In this chapter, the principles of PET and the applications of several PET tracers

in oncology are introduced. Thereafter, the development of carbon-11 labeled docetaxel

([11C]docetaxel), a newly radiolabeled anticancer drug, and its validation in patients with

lung cancer is described. Finally, the other chapters of this thesis, in which [11C]docetaxel

PET studies in lung cancer patients are reported, will be introduced.

2.0 Positron emission tomography (PET)

2.1 Principles of PET

PET is a highly sensitive nuclear imaging technique that is suited for non-invasive in vivo

monitoring of dynamic processes. A PET scanner usually consists of a ring of detectors

and is capable of detecting high-energy gamma-rays that are emitted from tissue after

administration of a PET tracer (usually by intravenous injection) to a patient (1). PET

tracers are molecules of interest that are labeled with a positron emitting radionuclide.

Such a radionuclide decays and produces two gamma-rays, following emission of a

positron from its nucleus. For PET imaging, frequently short-lived radionuclides, such as

carbon-11 (11C), fluorine-18 (18F) and oxygen-15 (15O), are used. These radionuclides are

generated by a specific particle accelerator, called cyclotron. In tissue, an emitted

positron can travel at most a few mm and eventually it combines with a nearby electron.

In the following annihilation reaction, the masses of the positron and electron are

converted into energy in the form of two photons of 511 keV, which are emitted in

opposite directions to each other (Figure 1).

9

Figure 1. Schematic illustration of an annihilation reaction and the subsequent in coincidence

detection. Positrons released from the nucleus of the radionuclide annihilate with electrons in

tissue, releasing two coincidence photons of 511 keV, which are detected by scintillation crystals

(blue rectangles).

These photons are simultaneously detected (in coincidence) by two opposing detectors of

the PET scanner. Coincidence detection of annihilated photons identifies a line-of-

response and makes it possible to localize the source of the annihilation. After

reconstruction, data obtained provide information on the three-dimensional (3D) tracer

concentration within the body. To date, a PET scanner is combined with an integrated

computed tomography (CT) scanner [Figure 2; (2)]. The CT scanner is used to estimate

tissue attenuation, a process in which gamma rays are absorbed by tissue as they pass

through the patient.

Figure 2. Combined PET/CT scanner consisting of a PET (right) and a CT (left) component.

Electron

511 keVgamma ray

511 keVgamma ray

Positron-emittingradionuclide

Annihilation

Positron

Gamma raydetectors

Positron emission andpositron-electron annihilation

PET scanner

Electron

511 keVgamma ray

511 keVgamma ray

Positron-emittingradionuclide

Annihilation

Positron

Gamma raydetectors

Positron emission andpositron-electron annihilation

PET scanner

10

When a positron is emitted from a structure deeper in the body, gamma rays are more

likely to be attenuated than from superficial structures. Consequently, without

attenuation correction, reconstructed images would show falsely low tracer uptake in

deeper structures. A low-dose CT scan can be used to correct for this tissue attenuation.

In addition, the CT scan provides anatomical localization of the functional data that are

obtained from the PET image.

2.2 Kinetic modeling of PET data

Although, in clinical practice, a PET image can be extremely useful for diagnosis and

staging, absolute quantification of tracer kinetics in tissue is necessary for complete

characterization of biochemical, physiological and pharmacological processes in vivo. This

requires measurement of tracer uptake in tissue as function of time. To this end, PET

data need to be acquired in dynamic rather than statical scans. For diagnostic purposes,

usually whole body scans are performed, which consist of a series of static scans by

moving the scanner bed over multiple bed positions. Dynamic scans, however, are

limited by the field of view of the PET scanner, which is ~ 15-20 cm. As patients are

scanned in only one bed position, only information on a selected part of the body is

obtained. Hence, the tissue of interest needs to be defined prior to acquisition of the PET

data. Net tracer uptake in tissue is determined by its delivery, extraction from blood, and

washout from tissue as function of time. Each tracer has its own distinct behavior in vivo,

which can be described by tracer kinetic models (3). These models are used to estimate

underlying biologic parameters by fitting the (mathematical) model equations to the

time-activity curves of a defined region of interest. In practice, most tracer kinetic

models are compartmental models, in which the compartments are used to describe the

distribution of the tracer in tissue. Several compartmental models have been developed

to describe PET data. In Figure 3, schematic diagrams of standard single-tissue and two-

tissue compartment models are presented. The kinetic rate constants in these models

can be estimated from dynamic PET data. To this end, a tissue time-activity curve (TAC;

Figure 4) is fitted to the appropriate model equation using the arterial plasma TAC as

input function, and the best fit then provides estimates of these kinetic parameters

(Figure 5). The arterial input function can be obtained from arterial blood sampling using

an online detection system [Figure 6; (4)]. Arterial blood sampling, however, is an

invasive and cumbersome procedure. In principle, the time course of the tracer in a large

arterial blood structure, e.g. the ascending aorta, can also be used to generate a non-

invasive image derived input function (IDIF). For appropriate estimation of the kinetic

parameters, the input function needs to be corrected for changing plasma/blood ratios

and the development of radiolabeled metabolites of the tracer during the course of the

scan.

11

Figure 3. Compartment models to describe the behavior of the tracer in tissue.

(A) Schematic diagram of a single-tissue compartment model in which only one tissue

compartment can be distinguished, such as in the case of a flow tracer. According to this model,

the tracer concentration in tissue (CTissue) depends on plasma concentration (CPlasma), influx from

plasma (K1 or rate constant for transfer from plasma to tissue) and clearance from tissue to plasma

(k2 or rate constant for transfer from tissue to plasma).

(B) Schematic diagram of a two-tissue compartment model. CTissue consists of tracer concentrations

in compartments 1 and 2, representing free (C1) and bound or metabolized tracer (C2),

respectively. Tracer kinetics in tissue are regulated by CPlasma and four kinetic rate constants K1, k2,

k3, and k4. K1 is the rate constant for transport from plasma to tissue, k2 for transport from tissue

to plasma, and k3 and k4 are kinetic rate constants describing exchange between the two tissue

compartments. For an irreversible two-tissue compartment model k4 = 0.

Figure 4. Example of time-activity curves of radioactivity concentrations in plasma and two

different tissues of interest.

Cplasma C1 C2

K1

k2 k4

k3

Tissue

Cplasma

K1

k2

TissueA

B

CTissue

Cplasma C1 C2

K1

k2 k4

k3

Tissue

Cplasma

K1

k2

TissueA

B

CTissue

Tissue 1

Tissue 2

Plasma

Tissue 1

Tissue 2

Plasma

12

Figure 5. Schematic diagram of data required for analysis of PET data (TAC: time-activity curve).

Figure 6. Illustration of set-up for arterial sampling during a dynamic PET scan, using the space

between PET (left) and CT (right) scanners. The radioactivity concentration in arterial blood is

monitored using a fully programmable blood sampling device (4). Blood is withdrawn from the

radial artery through 1 mm internal diameter tubing using a pump that can be operated at rates

varying from 0 to 600 mL·h-1. Radioactivity is measured using a bismuth germanate crystal of 6 cm

thickness. This crystal is connected to a photomultiplier and a multichannel analyzer, which are

positioned within 6 cm lead shielding.

13

2.3 PET imaging in oncology

Over the past decade, clinical applications of PET have expanded, particularly in oncology

(1). To date, 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) is the most widely used PET

tracer for evaluation of cancer. It is used for staging of various cancers (5) and for

monitoring tumor response to therapy (6). The high [18F]FDG uptake in tumors is based

on altered glucose metabolism in most cancer cells (7). In contrast to glucose, [18F]FDG

lacks the hydroxyl group. As a result, the metabolite of [18F]FDG, FDG 6-phosphate,

cannot act as a substrate for further glycolysis and is trapped in the cell, usually resulting

in high contrast images of tumor tissue (Figure 7).

Figure 7. Example of an [18F]FDG PET-CT fusion image in a patient with lung cancer. Arrow

indicates intense [18F]FDG uptake in the primary tumor in the left upper lobe.

As [18F]FDG uptake in tissue is not specific for malignancy and does not provide

information on other biological characteristics of tumors, other PET tracers have been

developed. For example, 3-deoxy-3-[18F]fluorothymidine ([18F]FLT) has been developed

to measure tumor proliferation (8). In addition, radioactive water ([15O]H2O) can be used

to measure tumor perfusion (9), whereas hypoxia tracers such as [18F]fluoroazo-

mycinarabinofuranoside ([18F]FAZA) and [18F]fluoromisonidazole ([18F]FMISO) can be

used to determine hypoxic areas in tumors (10). Although these PET tracers may provide

additional information on various tumor characteristics and could be useful for response

evaluation, they are not specific enough to predict tumor response to specific anti-cancer

drugs. As an alternative, anti-cancer drugs themselves can also be labeled with positron

14

emitters. Using PET, these radiolabeled drugs can then be used to monitor drug

pharmacokinetics and pharmacodynamics in patients non-invasively. Preliminary PET

studies using fluorine-18 labeled 5-fluorouracil ([18F]5-FU) (11,12) and tamoxifen

([18F]fluorotamoxifen) (13), showed that high tumor uptake of the radiolabeled anti-

cancer drug was associated with improved tumor response following corresponding

therapy. These studies suggest that radiolabeled anticancer drugs may be useful for

prediction of outcome prior to start of treatment. Consequently, an increasing number of

anticancer drugs has now been radiolabeled for PET imaging. At the VU University

Medical Center, Van Tilburg et al (14,15) succeeded in radiolabeling the anti-cancer drug

docetaxel, which nowadays is one of the most important chemotherapeutic agents in the

clinic.

3.0 Docetaxel

3.1 Mechanism of action

Docetaxel (Taxotere®) is a taxane, a class of drugs consisting of microtubule stabilizing

agents that function primarily by interfering with microtubule dynamics, inducing cell

cycle arrest and apoptosis (16,17). Microtubules consist of long protein polymers, which

have important functions in cellular activities, including maintenance of cell shape,

cellular movement, cell signaling and mitosis (18). These key roles make microtubules an

effective target for treatment of cancer. Microtubules are hollow cylindrical cores

composed bulin heterodimers (19). Polymerization and depolymerization of

microtubules are important for cellular division and chromosome aggregation during

mitosis. Docetaxel binds to the subunit of the tubulin heterodimer (20) and promotes

the assembly of stable microtubule bundles, whilst simultaneously inhibiting their

disassembly (Figure 8). This results in the production of stable, but dysfunctional

microtubules, leading to the inhibition of mitosis in cells.

Figure 8. Docetaxel acts by disrupting the microtubular network in cells. It promotes

polymerization of microtubules, while simultaneously inhibiting depolymerization. This leads to

disruption of cellular activities including cell cycle arrest and inhibition of mitosis.

Docetaxel

Polymerization

Depolymerization

Tubulin subunits Microtubule

Docetaxel

Polymerization

Depolymerization

Tubulin subunits Microtubule

15

3.2 Administration of docetaxel

In the clinic, docetaxel is administered as a 1 hour intravenous infusion in a solution with

polysorbate 80 and ethanol. Usually, the drug is given at a dose of 75 or 100 mg·m-2 in a

three-weekly regimen (21). The duration of this three-weekly regimen depends on the

indication and varies from four (22) to ten (23) cycles of treatment. In addition,

docetaxel can be given weekly, but this schedule is rather poorly tolerated (24). Prior to

administration of docetaxel, all patients need to be premedicated with oral cortico-

steroids, as this reduces the incidence and severity of docetaxel-induced fluid retention

and hypersensitivity reactions significantly (25,26).

3.3 Docetaxel for treatment of cancer

In 1996, docetaxel was first approved for the treatment of anthracycline-refractory

metastatic breast cancer (27,28). Thereafter, the drug was registered for treatment of

platinum-refractory stage IIIB and IV non-small cell lung cancer (NSCLC) (29,30). To

date, docetaxel has also been approved for combination strategies. In combination with

other drugs, docetaxel has been approved for the following indications: (i) with

doxorubicin and cyclophosphamide for the adjuvant treatment of patients with operable

node-positive breast cancer (31); (ii) with cisplatin for the first-line treatment of patients

with non-resectable, locally advanced or metastatic NSCLC (32); (iii) with prednisone for

the treatment of patients with androgen independent (hormone refractory) metastatic

prostate cancer (23); (iv) with cisplatin and fluorouracil for first-line treatment of

patients with advanced gastric adenocarcinoma (33); (v) with cisplatin and fluorouracil

for induction treatment of patients with locally advanced squamous cell carcinoma of the

head and neck (22,34). In these malignancies, docetaxel has shown proven efficacy,

including tumor response and improved survival. Nevertheless, failure of docetaxel

therapy occurs and patients are often subjected to docetaxel related toxicities without

gaining benefit.

3.4 Side-effects associated with docetaxel treatment

As single agent, docetaxel is associated with numerous hematological and non-

hematological toxicities. At a dose of 75 mg·m-2, non-hematological toxicities that are

most frequently [i.e. 20% of all grades according to Common Terminology Criteria for

Adverse Events (CTCAE) and Common Toxicity Criteria (CTC)] associated with docetaxel

treatment include fever without infection (62%), asthenia (55%), nausea (36%),

diarrhea (36%), infection (31%), stomatitis (26%), vomiting (24%) and neurosensory

toxicity (20%) (30). Among these toxicities, severe (grade 3-4) asthenia is reported in

approximately 18% of patients (30). At the same dose, severe (grade 3-4) hematological

toxicities are neutropenia (54-67%), febrile neutropenia (2-8%), and anemia [0-6%;

16

(29,30)]. Combining docetaxel with other anti-cancer drugs may lead to more (severe)

toxicities, depending on the drug that is co-administered with docetaxel. Based on both

experienced toxicities and the (combination) schedule in which docetaxel is administered,

dose reduction or discontinuation of docetaxel treatment can be required in case of

severe toxicity.

4.0 [11C]docetaxel PET microdosing

4.1 Radiolabeling of docetaxel

Docetaxel has been radiolabeled with the radionuclide carbon-11 (14,15). As a stable

carbon atom is replaced by carbon-11 (Figure 9), the chemical structure of

[11C]docetaxel is identical to that of the drug docetaxel.

Figure 9. [11C]docetaxel is synthesized by replacing a stable carbon atom by carbon-11 (14,15).

Hence, pharmacokinetics of the tracer [11C]docetaxel and the drug docetaxel are also

identical. To date, [11C]docetaxel can be produced according to Good Manufacturing

Practice (GMP) standards, allowing for administration to patients. At time of injection, the

specific activity is approximately 10 GBq·μmol-1, which leads to a dose of 30 μg docetaxel

for a typical administration of 370 MBq [11C]docetaxel. This is about 0.02% of a

therapeutic dose of docetaxel. Consequently, no docetaxel related toxicities are expected

after administration of [11C]docetaxel. Therefore, a microdosing PET study using

[11C]docetaxel may be useful to predict benefit from docetaxel therapy in individual

patients without the risk of docetaxel related toxicities.

4.2 Validation of [11C]docetaxel PET in lung cancer patients

Before implementation of a new PET tracer in the clinic, technical and biological validation

of the tracer is required. To this end, the optimal patient population should be selected

based on patient characteristics and technical issues. To evaluate the clinical relevance of

[11C]docetaxel PET scans, these scans need to be performed in patients who are planned

for docetaxel therapy. In addition, a non-invasive IDIF needs to be validated, as arterial

docetaxel [11C]docetaxel

OOH O H

O

O

O

O

O H

NH

O

O

O

O

OH

11C

OOH O H

O

O

O

O

O H

NH

O

O

O

O

OH

docetaxel [11C]docetaxel

OOH O HO H

O

O

O

O

O H

NHNH

O

O

O

O

OH

11C

OOH O HO H

O

O

O

O

O H

NHNH

O

O

O

O

OH

17

blood sampling, which is required for quantification of [11C]docetaxel kinetics, is too

invasive and too cumbersome for clinical practice. To this end, a large arterial blood

structure, e.g. the ascending aorta, needs to be located in the same field of view as the

tumor. For adequate validation of an IDIF, patients should be physically able to undergo

venous and arterial sampling from two different arms simultaneously. In this respect,

most breast cancer patients will not be able to participate, as both injury and infection of

the arm are significant risk factors for developing lymph edema after sentinel lymph node

biopsy and axillary lymph node dissection (35). Considering these issues, patients with

lung cancer seem most eligible for validation of [11C]docetaxel PET, as patients with

advanced NSCLC are eligible for docetaxel therapy (29,30,32). In addition, a tumor in

the lungs is located in the same field of view as the ascending aorta, making it possible

to validate a non-invasive IDIF for [11C]docetaxel.

5.0 Lung cancer

5.1 Epidemiology

Worldwide, lung cancer is the most common cause of cancer related death among men

and women (36). Every year, approximately 1.2 million new cases of lung cancer are

diagnosed globally and 1.1 million patients die of this disease (37). It has been

determined that tobacco smoking is the main cause of lung cancer, probably accounting

for 85% of all lung cancer cases (38-40). In non-smokers, genetic factors, asbestos,

radon gas, passive smoking, and air pollution are thought to attribute to the

development of lung cancer (41-48). Patients with lung cancer frequently present with

symptoms such as malaise, weight loss, dyspnea, cough and hemoptoe. Lung cancer can

be detected by chest radiography or CT, but the final diagnosis needs to be confirmed by

histological or cytological examination. To that end, usually bronchoscopy or fine needle

aspiration is performed.

5.2 Histology

The main histological types of lung cancer are NSCLC and small cell lung cancer (SCLC).

NSCLC accounts for about 85% of cases and is subdivided in subtypes, including

squamous cell carcinoma, adenocarcinoma, large cell carcinoma and bronchioloalveolar

carcinoma (49). Among these NSCLC subtypes, adenocarcinoma has become the most

prevalent subtype. SCLC represents approximately 15% of lung cancer cases (50).

5.3 Staging and survival

NSCLC and SCLC are staged by two different systems. For staging of NSCLC, the Tumor-

Node-Metastases (TNM) classification is used (51). This staging system takes into

18

account size and degree of spread of the primary tumor (T), involvement of lymph nodes

(N) and presence of distant metastases (M). Based on the TNM staging system, NSCLC

can be categorized into stages, varying from local (I and IIA) to locally advanced (IIB

and IIIA) and advanced disease (IIIB and IV). SCLC is staged according to a simpler

system that is divided into limited and extensive stage of the disease (52). The prognosis

of both NSCLC and SCLC is very poor. For NSCLC, the 5-year overall survival is 67% for

patients with stage IA and 55% for patients with stage IIA (53). For IIIA disease, 23% of

patients is alive five years after surgery, whereas only 1% of patients with stage IV is

alive after five years (53). Among patients with SCLC, the 5-year overall survival is

approximately 10% and 2% for limited and extensive disease, respectively (52).

5.4 Treatment of lung cancer

Treatment of lung cancer depends on histological type, stage, and performance status.

Treatment options include surgery, radiotherapy and chemotherapy, or a combination of

these modalities. Early stage NSCLC (stages I and II) can be treated with curative

surgery, whereas in general surgical interventions are not used for SCLC. Commonly,

SCLC is treated with chemotherapy and/or radiation therapy, as this tumor type usually

is metastatic at presentation (52). For pre-operative staging of patients with NSCLC,

[18F]FDG PET is routinely performed in the initial staging work-up (54), as PET improves

the rate of detection of local and distant metastases in these patients (55,56), thereby

reducing the number of unnecessary surgeries. NSCLC patients with unresectable and

metastatic disease usually are treated with chemotherapy. First-line chemotherapy

consists mainly of a platinum-based doublet, such as cisplatin or carboplatin, in

combination with a third generation cytotoxic drug such as gemcitabine, pemetrexed,

paclitaxel or docetaxel (57,58). In addition, targeted agents have been introduced for the

treatment of advanced NSCLC. Gefitinib and erlotinib were the first targeted agents

approved for treatment of advanced and metastatic NSCLC (59-61). These drugs target

the tyrosine kinase domain of the epidermal growth factor receptor (EGFR) and have

demonstrated proven efficacy in NSCLC patients with activated EGFR mutations (62-64).

In 2006, another targeted drug, bevacizumab, was approved for systemic treatment of

NSCLC (65). The anti-angiogenic drug bevacizumab is a humanized monoclonal antibody

directed against the vascular endothelial growth factor (VEGF), which has been approved

in combination with paclitaxel and carboplatin for first-line treatment of non-squamous

NSCLC (65).

19

6.0 Outline of the thesis

In this chapter, the rationale for PET scans using [11C]docetaxel has been introduced. In

the following chapters, several studies are described in which this novel PET tracer was

validated for use in lung cancer patients, with the ultimate goal to determine its potential

clinical implications.

In Chapter 2, the role of PET and radiolabeled anticancer drugs for prediction of tumor

resistance is reviewed.

In Chapter 3, tumor perfusion measurements in lung cancer patients are validated using

[15O]H2O and a clinical PET/CT scanner. This is necessary, as tumor perfusion may be an

important factor in the delivery of radiolabeled drugs, including [11C]docetaxel. As tumor

perfusion may change after an intervention, test-retest variability of perfusion

measurements is also determined in order to evaluate whether a therapy induced change

in tumor perfusion reflects a ‘real’ change or methodological variation.

Chapters 4 to 7 describe successive steps in the evaluation of [11C]docetaxel for use in

clinical PET studies. In preparation of humans studies, the biodistribution of

[11C]docetaxel in healthy rats is investigated in Chapter 4. In Chapter 5, biodistribution

and radiation dosimetry of [11C]docetaxel are determined in cancer patients. Chapters 6

and 7 describe the initial clinical validation of quantitative [11C]docetaxel studies in

cancer patients as a tool to predict response to docetaxel therapy. In Chapter 6, the

feasibility of quantitative [11C]docetaxel PET scans is evaluated in 34 patients with lung

cancer. First, the optimal tracer kinetic model for [11C]docetaxel uptake in tumor tissue is

developed using a dynamic scanning protocol and arterial sampling. Next, the use of a

non-invasive IDIF is validated, as arterial sampling is less suited for clinical practice.

Finally, the relationship between [11C]docetaxel kinetics and tumor perfusion, tumor size

and premedication of dexamethasone is assessed. However, kinetics of a tracer

(microdose) amount of [11C]docetaxel do not necessarily reflect kinetics of docetaxel

during a therapeutic infusion. Therefore, Chapter 7 provides an assessment in lung

cancer patients to investigate whether an [11C]docetaxel PET scan can predict tumor

uptake of cold docetaxel during a therapeutic infusion.

Within the context of combination therapy, in Chapter 8, the effects of the anti-

angiogenic drug bevacizumab on tumor perfusion and [11C]docetaxel uptake in lung

tumors is investigated in NSCLC patients. Finally, results of all these investigations are

summarized in Chapter 9 and future perspectives are discussed in Chapter 10.

20

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24

Chapter 2

Individualized treatment planning in oncology: role of PET and radiolabelled anticancer drugs

in predicting tumour resistance

Astrid A.M. van der Veldt, Gert Luurtsema, Mark Lubberink, Adriaan A. Lammertsma, N. Harry Hendrikse

Curr Pharm Des 2008;14:2914-31.

2914 Current Pharmaceutical Design, 2008, 14, 2914-2931

1381-6128/08 $55.00+.00 © 2008 Bentham Science Publishers Ltd.

Individualized Treatment Planning in Oncology: Role of PET and Radiolabelled Anticancer Drugs in Predicting Tumour Resistance

Astrid A.M. van der Veldt1, Gert Luurtsema1,*, Mark Lubberink1, Adriaan A. Lammertsma1 and N. Harry Hendrikse1,2

Departments of 1Nuclear Medicine & PET Research and 2Clinical Pharmacology & Pharmacy, VU University Medical Centre, Amsterdam, the Netherlands

Abstract: Tumour resistance to anticancer agents remains a challenge in oncological practice, because it results in expo-sure to toxicities, unnecessary costs and, most importantly, delay of a potentially more effective treatment. Drug uptake by tumours may be impaired by several resistance pathways. Reasons for primary resistance may be that the drug is not de-livered to the tumour or that its uptake by the tumour is not sufficient. Drug delivery depends on its distribution within the body, its bioavailability in the circulation and its transport to the tumour. Binding of drugs to circulating cells and pro-teins, formation of inactive metabolites as well as a rapid drug clearance may limit bioavailability. Furthermore, drug de-livery to tumours is regulated by tumour vascularisation. Finally, tumour targets such as hormone receptors and efflux pumps also influence drug uptake by tumours.

The use of specific PET tracers such as radiolabelled anticancer drugs (e.g. [18F]fluoropaclitaxel and [18F]5-fluorouracil) provide a unique means for individualized treatment planning and drug development. Combining these specific tracers with other less specific tracers, such as tracers for blood flow (e.g. [15O]H2O) and efflux (e.g. [11C]verapamil), may pro-vide additional information on drug resistance mechanisms. Furthermore, radiolabelled anticancer agents may be valuable to evaluate the optimal timing of combination therapies. This review will focus on how PET can reveal different mecha-nisms of tumour resistance and thus may play a role in drug development and prediction of tumour response.

INTRODUCTION

A number of systemic anticancer agents have been intro-duced for both curative and palliative cancer treatment. Un-fortunately, failure of anticancer therapy can occur because of primary (intrinsic) or secondary (acquired, following a temporary initial response) resistance. Tumour resistance to anticancer agents remains a major challenge in oncological practice, because it results in exposure to toxicities, unneces-sary costs and, most importantly, delay of a potentially more effective treatment. To optimise cancer treatment, primary resistance to anticancer drugs is increasingly measured by early response monitoring.

The arrival of new targeted therapies such as imatinib imposes new challenges to response evaluation criteria com-pared to their use with conventional anticancer agents [1, 2]. Response Evaluation Criteria in Solid Tumours (RECIST) are widely used and are based on the sum of the longest di-ameters of appointed target lesions in a transversal plane [3]. Since most of these novel drugs are cytostatic instead of cy-totoxic, morphological imaging is not appropriate for meas-uring tumour response. Objective responses may be missed or underestimated by RECIST, as several targeted therapies can cause extensive tumour necrosis [4-8] without a marked decrease in tumour size. However, treatment-induced necro-sis is not part of the RECIST criteria and may even mimic progressive disease [6].

*Address correspondence to this author at the VU University Medical Cen-tre, Nuclear Medicine & PET Research, P.O. Box 7057, 1007 MB Amster-dam, the Netherlands; Tel: + 31 20 444 3999; Fax: + 31 20 444 3090; E-mail: [email protected]

Currently, new response criteria and imaging techniques are investigated to evaluate tumour response. 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG) positron emission tomogra-phy (PET), which is able to measure glucose metabolism has an increasing role in (early) response evaluation and predic-tion of treatment outcome [9-11]. Besides [18F]FDG, 3-deoxy-3-[18F]fluorothymidine ([18F]FLT), which visualizes proliferative activity, is under investigation for evaluating tumour response [12, 13]. The increasing availability of PET scanners provides the impetus for developing molecular im-aging probes that are more specific for various cancers and their therapies.

Effective use of anticancer agents requires that efficacy can be predicted early during treatment. Clinical response evaluation methodology is too slow and inaccurate to relia-bly predict treatment outcome. Ideally, tumour response should be predicted before initiating treatment, thereby pre-venting that patients are subjected to inadequate treatment with unnecessary toxicities. Although [18F]FDG and [18F]- FLT are promising tracers for monitoring response early during therapy, they are not specific enough to predict tu-mour response to a specific anticancer agent. However, more specific PET tracers such as radiolabelled anticancer drugs provide a unique means for individualized treatment plan-ning and drug development. Combining these specific tracers with other less specific tracers for blood flow (e.g. [15O]H2O) and efflux (e.g. [11C]verapamil) may provide additional in-formation on drug specific resistance mechanisms.

This review aims to outline the current and future role of PET in prediction of tumour response as well as drug devel-

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Individualized Treatment Planning in Oncology Current Pharmaceutical Design, 2008, Vol. 14, No. 28 2915

opment. PET tracers for assessing different mechanisms of drug resistance will be reviewed. Furthermore, processes that influence drug delivery to tumours (biodistribution of a drug within the body, bioavailability in the circulation and tumour vascularisation) as well as processes that regulate drug up-take by tumours (tumour pharmacokinetics, drug targets and efflux pumps) will be discussed.

2. RADIOLABELLED ANTICANCER AGENTS FOR PET IMAGING

The heterogeneity of tumour response to anticancer drugs led to the suggestion that treatment failure might be due to differences in tumour pharmacokinetics. Obtaining such knowledge requires a non-invasive method to study drug pharmacokinetics in tumour tissue in vivo. The PET tech-nique is ideally suited for such measurements. PET is able to monitor pharmacokinetics (measurement of drug distribution in tumours and normal tissue) as well as pharmacodynamics (measurement of efficacy) of drugs. Therefore, it has been attempted to radiolabel anticancer drugs, resulting in more specific radiotracers.

2.1. Principles of Positron Emission Tomography In contrast to morphological imaging modalities such as computed tomography (CT), PET is a functional and quanti-tative imaging technique. PET is based on the use of biologi-cally relevant compounds radiolabelled with short-lived positron emitting radionuclides such as carbon-11 (11C), nitrogen-13 (13N), oxygen-15 (15O) and fluorine-18 (18F) (Table 1). In clinical applications, a tracer (i.e. minute) amount of a labelled compound of interest (radiopharmaceu-tical or radiotracer) is introduced into the patient, usually by intravenous injection.

A PET scanner can measure the concentration of ra-diotracer in tissue. During its decay process, the radiotracer emits a positron which, after travelling a short distance (~ mm), encounters an electron from the surrounding environ-ment. The two particles combine and "annihilate" each other resulting in the emission of two -rays (each 511 keV) in opposite directions. The acquisition of 3D images is based on external “in coincidence” detection of the emitted pair of -rays. A valid annihilation event requires a coincidence

between two detectors at opposite sides of the PET scanner. Accepted coincidences are allocated to so-called lines of response connecting the coincidence detectors. Counts along these lines of response are used to reconstruct an image of the distribution of radioactivity in the body. A correction for tissue attenuation is performed using a separate transmission scan or, in case of a PET-CT scanner, a CT scan [14]. For oncological applications, a PET-CT scanner allows for the combination of both anatomical (CT) and functional (PET) information, which significantly improves tumour localiza-tion.

Other functional imaging techniques such as single photon emission computed tomography (SPECT) and gado-linium-enhanced magnetic resonance imaging (MRI) are available to investigate compounds of interest in vivo. While the basic principles of SPECT are similar to those of PET, SPECT systems are generally less sensitive than PET sys-tems and have a less accurate spatial resolution and attenua-

tion correction. Using gadolinium labelled compounds of interest, MRI could in principle be an alternative to PET. However, gadolinium-enhanced MRI has an inferior sensi-tivity, does not enable absolute quantification and requires a considerable change of the molecular structure for gadolin-ium labelling. Since PET has a high sensitivity and is able to quantify tracer concentrations in absolute units, it is superior for quantitative imaging.

Table 1. Positron Emitters and their Half-Lifes

Radioisotope Half-Life Positron Abundance (%)

Carbon-11 20.4 min 100

Nitrogen-13 10.0 min 100

Oxygen-15 2.03 min 100

Fluorine-18 109.8 min 97

Iron-52 8.3 h 57

Cobalt-55 17.5 h 77

Copper-62 9.7 min 98

Copper-64 12.7 h 19

Gallium-66 9.5 h 56

Gallium-68 68.1 min 90

Bromine-75 98.0 min 76

Bromine-76 16.1 h 57

Rubidium-82 1.25 min 96

Yttrium-86 14.7 h 34

Zirconium-89 78.4 h 25

Technetium-94m 53 min 72

Indium-110m 69 min 63

Iodine-124 4.2 days 25

2.2. Positron Emitters

A number of positron emitters can be used for the devel-opment of successful PET radiotracers (Table 1). 18F is the most widely used positron emitter. Its ability to provide high resolution images, relatively high labelling yields, and ac-ceptable radiation dosimetry together with its physical half-life (110 minutes) makes 18F a very popular positron emitter for clinical studies. Furthermore, 18F is widely available and can be used for automated routine synthesis. However, an important limitation of 18F is that a fluorine atom is not al-ways present in the molecular structure. Therefore, incorpo-ration of 18F may result in changed pharmacokinetics of the radiolabelled molecule as compared to the natural com-pound.

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2916 Current Pharmaceutical Design, 2008, Vol. 14, No. 28 van der Veldt et al.

Radiotracers should be designed in such a way that their administration does not disturb the biochemical process un-der investigation. It is important to realize that careful design and development of radiotracers is necessary to preserve target specificity and in vivo metabolism. For example, ra-diolabelling 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU) by 13N was not advantageous because it was converted too fast into [13N]N2 or [13N]NO3 to permit differential retention in tumours [15, 16]. Fortunately, 11C labelling provided unique information on the pharmacokinetic and metabolic behaviour of BCNU in brain tumours [15, 17].

When the chemical structure of a radiotracer is identical to the clinically applied drug, pharmacokinetics of drug and radiotracer are assumed identical. 11C is an ideal nuclide for radiolabelling molecules of biological interest, because it can replace the abundantly present 12C-atom. Furthermore, the radiation dose of 11C is lower than that of 18F. This is due to a lower half-life as compared to 18F, even when corrected for the higher beta energy of 11C. Interestingly, both [18F]fluoropaclitaxel and [11C]paclitaxel have been synthesized from the taxane paclitaxel [18-20]. Since the molecular structure of paclitaxel does not contain a fluoride atom, [11C]paclitaxel would be expected to provide clinically more relevant results than [18F] fluoropaclitaxel. Paradoxically however, only [18F] fluoropaclitaxel, has been used for studies in vivo [21-23]. This may be explained by the physical half-life of 11C (20 minutes), which can be too short for measurement of tumour kinetics at late time points.

2.3. Radiolabelled Anticancer Agents

In 1973, 5-fluorouracil (5-FU) was the first anticancer agent that was labelled with 18F [24]. Since then, pharma-cokinetics of [18F]5-FU have been studied extensively [25-39]. Furthermore, other conventional anticancer agents as well as targeted therapies such as tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (MAbs) have been radio-labelled with PET isotopes (Table 2).

2.3.1. Radiolabelled Monoclonal Antibodies

Therapeutic MAbs represent a different class of antican-cer agents that are targeted to receptors, antigens and growth factors on which the survival of tumours is dependent. Ra-diolabelling therapeutic MAbs provides visualization and quantification of MAb biodistribution with PET (immuno-PET). In choosing the most appropriate positron emitter, MAbs have different requirements than other anticancer agents. Intact MAbs have a long residence time in humans ranging from a few days to weeks. Therefore, the physical half-life of the positron emitter should be compatible with the time needed for a MAb or MAb fragment to achieve op-timal tumour-to-nontumour ratios (typically 2-4 days and 2-6 hours, respectively). Given these considerations, the follow-ing positron emitters for labelling MAbs are under investiga-tion: copper-64 (64Cu), yttrium-86 (86Y), bromine-76 (76Br), zirconium-89 (89Zr) and iodine-124 (124I). 76Br and 124I can be labelled directly to MAbs, while the other positron emit-ters are coupled by indirect methods. However, the unfa-vourable decay characteristics of many of these long-lived isotopes may affect PET image quality and quantitative ac-curacy [40]. In general, radiolabelling MAbs is less difficult than radiolabelling other anticancer agents: MAbs are radio-

labelled by coupling isotopes (bridging), while other drugs are radiolablled by incorporation of a positron emitter into the molecule itself (exchange). This favourable characteristic of MAbs not only makes them promising to predict tumour response, but also to deliver therapeutic radioactivity by ra-dioimmmunotherapy (RIT) [41].

2.3.2. Ideal Labelling Position of an Anticancer Drug

Given the possibility of different radioactive metabolites, the ideal labelling position within a drug molecule should be considered. The effects of different labelling positions was investigated for 11C labelled temozolomide. The amount of [11C]CO2 in exhaled air was significantly higher for [4-carbonyl-11C]temozolomide than for [3-N-methyl-11C]temozolomide [42]. Based on this study, it was postulated that label-ling temozolomide in the 3-N-methyl position results in in-corporation of the radiolabel into DNA, whereas labelling in the 4-cabonyl position results in loss of label as [11C]CO2 in expired air, prior to its incorporation in DNA.

2.3.3. Considerations in Labelling Anticancer Drugs

In contrast to the relatively large number of radiolabelled anticancer agents that have been developed, a few studies have evaluated these tracers in vivo, particularly in humans. Complex synthesis, low radiochemical yield, low specific activity and low reproducibility might have been factors im-peding further (pre-)clinical studies in vivo. Furthermore, this discrepancy may be explained by the formation of radio-labelled metabolites, which complicates quantitative analy-sis.

While the majority of targeted agents such as TKIs are administered orally on an outpatient basis, radiolabelled drugs are usually administered intravenously. Intravenous administration of the radiolabelled drug may result in differ-ent pharmacokinetics, since orally administered drugs have to pass the gastrointestinal tract before entering the blood circulation. The development of radiolabelled anticancer agents for oral administration should be considered, as there is no principal objection against oral administration of PET tracers, provided the half-life is long enough.

3. DRUG RESISTANCE

Drug resistance remains a significant problem that limits efficacy in cancer patients. Causes of resistance may be im-paired drug delivery or an insufficient uptake by tumours. Drug delivery depends on distribution within the body, bioavailability in the circulation as well as transport into tumours. Bioavailability is regulated by binding to circulat-ing cells and proteins, drug metabolism and total body clear-ance. Furthermore, tumour vasculature controls drug deliv-ery to tumours. In the tumour, drug pharmacokinetics and tumour targets such as hormone receptors regulate drug up-take by the tumour. When drugs are substrates for efflux pumps, they can immediately be transported out of tumour cells. The following sections will elaborate on how PET tracers provide information on these different processes of tumour resistance (Fig. 1 and Table 3).

3.1. Drug Delivery: Biodistribution

Biodistribution within the body influences the efficacy of an anticancer agent (Fig. 1A). The degree of drug uptake can

31


Table 2. Radiolabelled Anticancer Drugs for PET Studies

Class of Drugs PET Tracer Mechanism of Action Tumour Uptake1 Predictive Value2

[11C]BCNU4 [171, 172] DNA cross-linking, DNA polymerase repair,

RNA synthesis inhibition Animals [173],

Humans [15, 17, 174] Humans [17]

[13N]BCNU4 [175] DNA cross-linking, DNA polymerase repair,

RNA synthesis inhibition n.a.3 n.a.3

[13N]cisplatin [176] DNA cross-linking, intercalation, DNA precursor

inhibition, alteration of cellular membranes Humans [43] n.a.3

[18F]fluorocyclophosphamide [177] DNA cross-linking Animals [44] Animals [44]

Alk

ylat

ing

agen

ts

[11C]temozolomide [178, 179] DNA methylation, alkylation Animals [46], humans [42] n.a.3

[11C]daunorubicin [144, 154] DNA intercalation, preribosmal DNA and RNA

inhibition, alteration of cell membranes, free radical formation

Animals [145] Animals [145]

[11C]docetaxel [180] Microtubule polymerization n.a.3 n.a.3

[11C]paclitaxel [20] Microtubule polymerization n.a.3 n.a.3

[18F]fluoropaclitaxel [18, 19] Microtubule polymerization Animals [21, 22], humans

[23] Animals [22], humans [23] N

atur

al p

rodu

cts

[11C]vinblastine [56] Tubulin binding, inhibition of microtubule as-

sembly, dissolution of mitotic spindle Humans [56] Humans [56]

[18F]capecitabine [181] Inhibition of thymidylate synthase n.a.3 n.a.3

[11C]5-fluorouracil [182] Inhibition of thymidylate synthase n.a.3 n.a.3

Ant

imet

abol

ites

[18F]5-fluorouracil [24, 183, 184] Inhibition of thymidylate synthase Animals [26, 27, 38, 39],

humans [25, 28-37] Animals [38, 39], humans [29, 36]

Con

vent

iona

l cyt

otox

ic a

gent

s

TI6

[11C]DACA5 [185] Binds DNA by intercalation and stimulates DNA

cleavage by inhibition topoisomerase I and II Animals [47],

humans [55, 122] n.a.3

[18F]derivative of dasatinib [186] Abl, Src, c-KIT Animals [186] n.a.3

[18F]gefitinib [187] EGFR10 Animals [49] n.a.3

[N-11C-methyl]imatinib [188] c-KIT, PDGFRs11 n.a.3 n.a.3 TK

Is7

[18F]sunitinib [189] VEFGFRs12, PDGFRs10, c-KIT, flt-3 n.a.3 n.a.3

[18F]fulvestrant [190] ER13 n.a.3 n.a.3

SHR

Ms8

[18F]fluorotamoxifen [191, 192] ER13 Humans [53] Humans [53]

[64CU]abegrin [51] v 3 intergrin Animals [51] n.a.3

[89Zr]bevacizumab [54, 193] VEGF14 Animals [54] n.a.3

[64CU]cetuximab [52] EGFR10 n.a.3 n.a.3

[89Zr]cetuximab [194] EGFR10 Animals [194] n.a.3

[68Ga]trastuzumab [48]15 HER216 Animals [48] n.a.3

[76Br]bromo-NBI-trastuzumab [139, 195]17

HER216 n.a.3 n.a.3

[89Zr]trastuzumab [138, 193] HER216 Animals [138], humans [138]

n.a.3

Tar

gete

d ag

ents

MA

bs9

[89Zr]ibritumomab tiuxetan [41] CD20 Animals [41] , humans [41]

n.a.3

1 Tumour uptake, studies investigating the uptake of the labelled anticancer agent by tumours; 2 Predictive value, studies investigating the ability of the tracer to predict tumour re-sponse; 3 n.a., to our knowledge not available; 4 BCNU, (1,3-bis(2-chloroethyl)-1-nitrosourea) (also known as carmustine); 5 DACA, N-[2-(dimethylamino)ethyl] acridine-4-carboxamide (also known as XR5000); 6 TI, topoisomerase inhibitor; 7 TKIs, tyrosine kinase inhibitors; 8 SHRMs, selective hormone receptor modulators; 9 MAbs, monoclonal anti-bodies; 10 EGFR, epidermal growth factor receptor; 11 PDGFR, platelet-derived growth factor receptor; 12 VEGFR, vascular endothelial growth factor receptor; 13 ER, oestrogen recep-tor; 14 VEGF, vascular endothelial growth factor; 15 DOTA-conjugated Herceptin fragment (DCHF); 16 human epidermal growth factor receptor; 17 NBI, undecahydro-bromo-7,8-dicarba-nido-undecaborate(1-).

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Fig. (1). Potential processes of tumour resistance as revealed by a radiolabelled anticancer agent. The figure represents an example of a patient with a primary breast tumour who is injected with a radiolabelled anticancer agent. Several processes that influence tumour resistance are visualized. Drug delivery depends on distribution of drugs in the body (A), binding of drugs to cells and circulating proteins (B), formation of metabolites (C), and clearance by biliary and renal excretion. Furthermore, tumour vascularisation, which is dependent on angiogenesis and hypoxia, affect drug delivery (D1). Moreover, targets such as hormone receptors (D2) and efflux pumps (D3) regulate drug uptake by the tumour.

33


Table 3. Role of PET Tracers in Revealing Processes that Contribute to Drug Resistance

Potential Process of Resistance PET Tracers Procedure Information Obtained

Radiolabelled anticancer drugs Dynamic

(whole body) PET Drug uptake in organs

(e.g. brain) Biodistribution body (§3.1)

Barriers prevent-ing drug uptake

Radiolabelled metabolites Dynamic (whole body)

PET Uptake of metabolites in

organs

Binding to cells and proteins

(§3.2.1) Radiolabelled anticancer drugs Serial blood sampling Blood plasma ratio

Serial blood sampling Metabolites in blood Formation of metabolites

(§3.2.2) Radiolabelled anticancer drugs Dynamic (whole body)

PET Drug uptake in metabolic

organs (e.g. liver)

Serial blood sampling Clearance from

circulating blood

Circulating blood (§3.2)

Clearance (§3.2.3)

Radiolabelled anticancer drugs Dynamic (whole body)

PET Drug uptake by liver,

kidney, bladder

Angiogenesis (§3.3.1)

[18F]galacto-RGD, [18F]FB-RGD, [89Zr]bevacizumab, [64Cu]DOTA-VEGF,

[64Cu]DOTA-VEGF(DEE), [64CU]abegrin PET pharmacokinetics

Degree of tumour angiogenesis

Tumour blood flow (§3.3.2)

[15O]H2O, [15O]CO2, [62Cu]PTSM PET pharmacokinetics Tumour blood flow

Drug delivery

Tumour vasculature

(§3.3)

Hypoxia (§3.3.3) [18F]FMISO, [18F]FAZA, [18F]FETNIM,

[62Cu]ATSM, [18F]FEAU PET pharmacokinetics Tumour hypoxia

Tumour pharmacokinetics (§3.4) Radiolabelled anticancer drugs PET pharmacokinetics Drug pharmacokinetics

in tumours

Tumour targets (§3.5)

[18F]gefitinib, [18F]FES,[18F]FENP, [18F]FDHT, [7 -18F]FMDHT, [18F]fulvestrant,

[18F]fluorotamoxifen, [64CU]abegrin, [64Cu]cetuximab, [89Zr]cetuximab,

[68Ga]trastuzumab, [76Br]bromo-NBI-trastuzumab, [89Zr]trastuzumab, [89Zr]ibritumomab tiuxetan

PET pharmacokinetics Presence of drug targets Tumour uptake

Drug efflux by efflux pumps (§3.6) [11C]colchicine, [11C]daunorubicin,

[11C]loperamide, [94mTc]sestamibi, [11C]paclitaxel, [18F]fluoropaclitaxel, [11C]verapamil

PET pharmacokinetics Presence of efflux pumps

be organ specific and is dependent on physical aspects such as blood flow, active and passive diffusion, receptor binding and metabolism. A number of studies in animals and humans have successfully investigated biodistribution of several ra-diolabelled anticancer drugs by sacrifice experiments [16, 21, 38, 43-50] as well as PET imaging [21, 26, 37, 41, 49, 51-56] (Fig. 2). In addition, serial whole-body PET scans may provide information on the biodistribution over time [57].

Clinically, an anticancer drug can adequately control tumours in most organs of the body, but fail at specific sites such as brain and testis. Failure of disease control in the brain due to the inability of drugs to pass the blood-brain barrier is a common problem for anticancer agents [58, 59]. Biodistribution studies with the radiolabelled taxanes

[18F]fluoropaclitaxel [21] and [11C]docetaxel [50] have re-vealed that these drugs have low penetration in the brain, which is in line with clinically observed isolated tumour progression in the central nervous system [58].

Knowledge of the biodistribution of a drug is important and may have implications for drug development as well as clinical treatment. For example, if a drug intended for brain tumours does not enter the brain in pre-phase I studies, modifications of the molecular structure of this drug should be attempted in order to increase cerebral uptake. Further-more, if studies with radiolabelled drugs reveal that a drug does not appear to enter the brain in sufficient amounts, pre-ventive strategies (e.g. prophylactic cranial irradiation for patients at high risk for brain metastases) may be applied [60].

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Finally, the biodistribution of a drug is important to pre-dict dose-limiting toxicities [55] and organ-protective bene-fits [61]. High cardiac, brain, liver or vertebral body uptake may be indicative of potential dose-limiting toxicity to these organs. Such foreknowledge of toxicities is important to an-ticipate potential toxicities in phase-I studies.

3.2. Drug Delivery: Bioavailability

Knowledge of the bioavailability of a drug in the circulat-ing blood may reveal potential mechanisms of resistance. If a drug appears to have a rather low bioavailability, this may have clinical implications for the dosing schedule of a drug: it may be necessary to administer a drug at higher frequen-cies.

3.2.1. Drug Binding

Tumour uptake is assumed to be driven by the free un-bound concentration of drug in circulating blood [62]. High concentrations of free drug are required to guarantee its bioavailability, but interactions with blood constituents (e.g. cells and proteins) may affect their efficacy (Fig. 1B). For example, the cytotoxic agents cisplatin, paclitaxel and doxorubicin bind to albumin [63], while docetaxel and gem-citabine can be found in erythrocytes [64]. After administra-tion of a radiotracer, accumulation in circulating cells can easily be demonstrated by assessing the ratio of radioactivity in whole blood and plasma. Ideally, the blood:plasma ratio is 1 [45], indicating that there is no accumulation of drug in circulating cells.

3.2.2. Drug Metabolism

Metabolism can induce rapid breakdown of drugs, result-ing in reduced bioavailability. Detailed information on the formation of metabolites for each individual drug is essen-tial. PET studies with radiolabelled anticancer drugs can increase our knowledge of drug metabolism in several ways. From serial blood samples obtained during PET scanning, the fractions of radiolabelled parent drug and its radiola-

belled metabolites (Fig. 1C) can be measured using rapid high-performance liquid chromatography (HPLC) or liquid chromatography-mass spectrometry (LC-MS). If necessary, urine samples can also be collected and analysed.

Although PET lacks in vivo chemical specificity (i.e. the ability to distinguish radiolabelled parent drug from its radio-labelled metabolites), it can be useful to investigate metabo-lism by assessing radioactivity in highly metabolic organs such as the liver. PET can reveal whether tissue uptake in these organs parallels formation of metabolites and/or plasma clearance of radioactivity. In addition, PET studies investigating pharmacokinetics of several analogues of an anticancer drug can contribute to the selection of the most potent analogue based on the most favourable distribution, kinetics and metabolic stability [47]. In this way, PET stud-ies have improved the understanding of the metabolism of several drugs [25-27, 37, 45].

Finally, pharmacokinetics of radiolabelled metabolites can be determined separately. This can be necessary to de-velop and validate the pharmacokinetic model for the radio-labelled parent compound or to follow the kinetics of a me-tabolite [65]. [18F]FBAL, the radiolabelled anabolite of [18F]5-FU, has been isolated from rat urine and injected into other rats to investigate its pharmacokinetics using PET [66]. Obviously, a more appropriate approach for studies in hu-mans would be to radiolabel chemically synthesized metabo-lites of a drug.

3.2.3. Drug Clearance

Drugs can be rapidly cleared from circulating blood by the hepatobiliary and renal systems (Fig 1A). During PET scanning, arterial and venous plasma sampling at several time points can provide information about drug clearance. Additionally, dynamic PET studies can provide information on time activity curves (TACs) in liver, kidney and bladder. High uptake in these organs immediately after injection of the radiolabelled drug may indicate rapid clearance and ex-cretion. For most radiolabelled anticancer agents, high he-

Fig. (2). Time course of [18F]fluoropaclitaxel biodistribution in a normal male volunteer [23]. Reprinted from Nucl Med Biol, Vol. 34, Kurdziel et al., Imaging multidrug resistance with 4-[18F]fluoropaclitaxel, pages 823-31, copyright 2007, with permission from Elsevier.

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patic and renal radioactivity has been measured in animal [16, 21, 38, 44-46, 48-50, 54] as well as human [23, 28, 30, 32, 35, 36, 53, 55, 56] experiments.

3.3. Drug Delivery: Tumour Vasculature

3.3.1. Tumour Angiogenesis

Angiogenesis (Fig. 1D1), the formation of new blood vessels is essential for tumour growth and metastasis forma-tion. Numerous stimulating and inhibitory growth factors regulate this complex process [67-69] in which vascular en-dothelial growth factor (VEGF) is the key stimulator. Tu-mour angiogenesis, especially VEGF signalling, has become an interesting therapeutic target and several antiangiogenic strategies have proven to be effective, including an anti-VEGF MAb and several inhibitors of the tyrosine kinase (TK) VEGF receptor(s).

In general, tumours have immature vessels which are leaky, dilated and tortuous [68, 70]. These morphological abnormalities are accompanied by functional changes: in-creased interstitial fluid pressure and decreased tumour oxy-genation. High interstitial pressure contributes to limited drug penetration [71, 72], which may subsequently lead to drug resistance [73]. Originally, it was hypothesized that inhibitors of VEGF signalling would destroy tumour vascu-

lature, thereby depriving the tumour of oxygen and nutrients. A completely opposing theory was proposed by Jain. [70, 74]. He suggested that VEGF inhibitors might prune imma-ture vessels, leading to a more normalized vasculature (Fig. 3). This theory is based on findings that the anti-VEGF MAb bevacizumab reduces blood flow, microvascular density, vascular volume and interstitial fluid pressure in tumours, but without a concurrent decrease in [18F]FDG uptake [75]. Jain ascribed the enhanced tumour response following a combination of bevacizumab and cytotoxic drugs to a nor-malization effect. Inhibition of VEGF signalling in tumours might revert tumour vasculature to a more “normal” state [70, 76], i.e. less leaky, less dilated and less tortuous vessels with more normal basement membrane and decreased inter-stitial fluid pressure. As a result, increased drug penetration would improve delivery and subsequent efficacy of chemo-therapy. Continued or aggressive antiangiogenic therapy, however, may destroy tumour vessels, leading to tumour vasculature that is inadequate for drug and oxygen delivery. Therefore, exploring the normalization window is important to decide on the optimal timing of drug administration in combination schedules.

With the development of antiangiogenic therapies, inter-est in imaging tumour vasculature is increasing. Many angi-ogenic targets for PET imaging have been identified [77],

Fig. (3). Normal vasculature composed of mature vessels (A). Tumour vasculature is structurally and functionally abnormal, composed of immature vessels which are leaky, dilated and tortuous (B). Antiangiogenic therapy might prune immature vessels, leading to a more normal-ized tumour vasculature (C). Sustained or aggressive antiangiogenic regimens may eventually prune away these vessels, resulting in a vascu-lature that is both resistant to further treatment and inadequate for the delivery of drugs or oxygen (D). Reprinted by permission from Mac-millan Publishers Ltd: Nature Medicine [74], copyright 2001.

36


including v 3 integrin [51, 78-90] and VEGF and its recep-tors [54, 91, 92]. Although these PET tracers are at an early stage of development, their potential to quantitatively image expression of angiogenic targets may have future applica-tions in patient stratification, drug development, and treat-ment monitoring of antiangiogenic agents.

In the next two paragraphs PET tracers for assessing tu-mour blood flow and hypoxia will be discussed. Although these tracers are not drug specific, they are important for prediction tumour response when used in combination with radiolabelled anticancer agents.

3.3.2. Tumour Blood Flow

Tumour blood flow is an important determinant of drug tumour exposure, as indicated by several PET studies on [18F]5-FU and [11C]DACA [30, 31, 33, 55]. PET is a sensi-tive technique to quantify tumour blood flow using [15O]- H2O, which can be administered either as inhaled [15O]CO2 [93, 94] or intravenous [15O]H2O [95-101]. Since [15O]H2O is a freely diffusible tracer, its uptake specifically reflects tissue perfusion. However, for the same reason [15O]H2O cannot be used to measure vascular permeability, but other PET tracers such as [68Ga]transferrin [102] and [11C]methylalbumin [103] are available for this purpose. [15O]H2O PET is a useful tool to investigate drug delivery of radiolabelled anticancer agents by correlating uptake of radiolabelled drugs with [15O]H2O perfusion data [30, 31, 33, 55] .

3.3.3. Hypoxia

A consequence of abnormal tumour vasculature is that some tumour areas become hypoxic (Fig. 1D1) [104]. Fur-thermore, hypoxia is considered to be caused by an impaired diffusion flux, as more oxygen is consumed by rapidly pro-liferating cells. Hypoxia impairs drug delivery, and hence increases tumour resistance to systemic therapy [105, 106]. Hypoxia also induces resistance to radiotherapy, since the radiotherapy-induced DNA damage depends on the reaction of oxygen molecules with free-radicals [107]. Non-invasive tests to detect hypoxic areas within tumours may potentially have a major impact on treatment planning. For example, patients with highly hypoxic tumours could be directed to-ward radiotherapy strategies with dose painting or trials with hypoxic cell sensitizers. Several PET tracers have been de-veloped for imaging hypoxic regions within tumours, includ-ing [18F]fluoromisonidazole ([18F]FMISO) [108-111], [18F]- fluoroazomycin arabinoside ([18F]FAZA) [112, 113], [18F]- fluoroerythronitroimidazole ([18F]FETNIM) [114-116], [60Cu]- diacetyl-bis(N(4)-methylthiosemicarbazone) ([60Cu]ATSM) [117-119], and [18F]-2-fluoro-2deoxy-1beta-D-arabinofura- nosyl-5-ethyl-uracil ([18F]FEAU) [120]. For detailed informa-tion on imaging of hypoxia, the reader is referred to another review in the current issue of Current Pharmaceutical De-sign. When combined with radiolabelled anticancer agents, assessment of tumour hypoxia with PET may be of addi-tional value to predict tumour response [108, 110, 116-119].

3.4. Drug Uptake: Tumour Pharmacokinetics

3.4.1. Predictive Value of Drug Uptake

Improved drug delivery to a tumour does not necessarily result in increased drug uptake. To have insight into tu-

moural drug kinetics, quantitative data on the time-activity pattern of radiolabelled anticancer drugs in tumours can be obtained using PET. The first study on [18F]5-FU, an ex-periment in mice, demonstrated that drug-responsive tu-mours had higher tumour-to-blood ratios of [18F]5-FU than drug-resistant tumours (20:1 versus 4:1) [38]. In another murine tumour model, carrying a 5-FU sensitive and a 5-FU resistant colorectal tumour xenograft in either flank, faster drug efflux was observed from the less responsive tumour xenograft [39]. In patients with liver metastases from colo-rectal cancer, a dedicated pharmacokinetic model was devel-oped to allow assessment of [18F]5-FU trapping using dy-namic PET data [35]. This model was able to separate the total 18F pool in liver and aorta into its 5-FU and -fluoro- -alanine (FBAL) components (Fig. 4), illustrating that a suit-able pharmacokinetic model can overcome the lack of chemical specificity of PET. In liver metastases from colo-rectal cancer, it was demonstrated that patients with high [18F]5-FU standardized uptake values (SUV) were more likely to have a favourable outcome upon 5-FU treatment [29, 36]. A complicating factor in prediction of response was the varying [18F]5-FU uptake in the different metastases within the same patient [29, 35, 36]. Therefore, it is likely that in an individual patient the metastasis with the lowest drug uptake will determine patient outcome.

In addition, the predictive value of tumour uptake of [18F]fluorocyclophosphamide [44] and [18F]fluoropaclitaxel [22, 23] in animals, and [11C]BCNU [17], [18F]fluoropaclitaxel [23], [18F]fluorotamoxifen [53] and [11C]vinblastine [56] in humans has been investigated (Table 2). Although these studies, especially those in humans, were very limited in the number of subjects included, the preliminary results of these studies were promising; high uptake of the radiola-belled anticancer agent appeared to be related to better tu-mour response.

Special attention should be paid to the anticancer agent bevacizumab, an FDA approved MAb which binds to circu-lating VEGF, preventing VEGF from binding to its receptor. Although VEGF circulates through the whole body, it has been shown that [89Zr]bevacizumab has higher uptake in tumours than in normal tissue [54]. This local deposition of [89Zr]bevacizumab in tumours reflects the high VEGF levels around tumours. It would be interesting to investigate effects of VEGFR TKIs, e.g. sunitinib or sorafenib, on local tumour deposition of [89Zr]bevacizumab, as administration of VEGFR TKIs is known to result in an increase of circulating VEGF. In a human xenograft model in mice, Ebos et al. [121] have demonstrated that the sunitinib-induced increase in VEGF levels had two origins, namely the human tumour (measured by human VEGF) and the mouse itself (measured by mouse VEGF). At present, the exact mechanism of the VEGFR TKI-induced increase of VEGF levels is still un-clear. Future studies with [89Zr]bevacizumab may reveal the site of VEGF production in the body.

It is unknown whether tumour uptake of every radiola-belled anticancer agent is representative of its clinically ob-served efficacy, as several factors can confound the assess-ment of tumour uptake using PET: high background levels adjacent to the tumour and uptake of radiolabelled metabo-lites. Furthermore, tumour cells could be relatively more

37


sensitive to anticancer drugs and their active metabolites than normal cells, a phenomenon that cannot be solely de-fined by tumour uptake. Larger studies in humans are neces-sary to assess whether PET with radiolabelled anticancer agents can be used in routine clinical practice to individual-ize treatment.

3.4.2. Tracer Dose Versus Therapeutic Dose

Assessment of pharmacokinetics of drugs in vivo may be performed following administration of the radiolabelled drug alone (tracer dose with high specific activity) or mixed with cold (non-radioactive) drug (therapeutic dose with low spe-cific activity). Preferably, tumour response should be pre-dicted before initiating active treatment to prevent exposure to unnecessary toxicities. The administration of a radiola-belled tracer dose may be valuable for this purpose. How-ever, it should be investigated whether the distribution of a tracer dose is representative for a therapeutic dose. A few studies have explored the effects of a therapeutic dose on the kinetics of the radiolabelled tracer.

Therapeutic doses decreased [18F]5-FU [33] and [11C]vinblastine [56] uptake by the liver and myocardial and splenic uptake of [11C]DACA [55, 122]. Tumour uptake of tracer doses of [18F]fluorocyclophosphamide [44] and [18F]fluoropaclitaxel [21] was not affected by the therapeutic dose, while the therapeutic dose increased [11C]DACA uptake by tumours [55, 122]. These studies demonstrated that the effect of the therapeutic dose on the tracer dose is highly dependent on the chosen drug. For determination of pharmacokinetics, a comparison between tracer and therapeutic dose should be performed for any new radiolabelled anticancer agent.

3.5. Targets for Treatment: Tumour Receptors

Treatment failure can occur when a tumour lacks the tar-get at which an anticancer drug is aimed (Fig. 1D2). Cur-

rently, immunohistochemistry assays are the basis for deter-mining the status of tumour receptors to predict tumour re-sponse. For example, the status of hormone receptors (oes-trogen and progesterone) and human epidermal growth factor receptor 2 (HER2) is critical in the management of patients with breast cancer. Although immunohistochemistry is very cost-effective, it may have disadvantages in metastatic dis-ease. Immunohistochemistry is usually performed on tissue from one tumour site (e.g. primary tumour or one metastatic site), because obtaining biopsies from all lesions is not pos-sible. Non-invasive PET may be of additional value in as-sessing the receptor status in all metastases.

Several tumour types have their own tumour specific targets. The neuro-endocrine tumour (NET) can express so-matostatin receptors. Both unlabelled and radiolabelled so-matostatin analogues have demonstrated clinical efficacy. Although, somatostatin receptor scintigraphy with Oc-treoScan has been recommended as the best imaging tech-nique for NETs, PET tracers for somatostatin receptors have been developed [123-128]. Given the superior resolution and sensitivity of PET, these latter tracers could be promising for treatment planning of neuro-endocrine tumours.

Hormone receptors are often over-expressed in breast cancer and prostate cancer. Several selective hormone recep-tor modulators (SHRMs) such as tamoxifen and fulvestrant have proven to be effective in these cancer types. Numerous positron emitting tracers have been developed to image hor-mone receptors: [18F]fluoroestradiol ([18F]FES) [129-131] for oestrogen receptors, 21-[18F] fluoro-16 -ethyl-19-norprogesterone ([18F]FENP) [132] for progesterone receptors, and 16 -[18F]fluoro-5 -dihydrotestosterone ([18F]FDHT) [133, 134] and [7 -18F]fluoro-17 -methyl-5 -dihydrotestosterone ([7 -18F]FMDHT) [135] for androgen receptors. In breast cancer, the uptake value of [18F]FES was predictive of re-sponse to hormonal therapy [129, 131].

Fig. (4). Formation of metabolites from 5-fluorouracil (5-FU).

38


Amplification of the HER2 gene, a member of the erbB family, is present in approximately 25%-30% of breast can-cer patients [136, 137] and is an adverse prognostic factor. The addition of trastuzumab to chemotherapy has signifi-cantly improved the survival of HER2 positive breast cancer patients. Therapeutic MAbs have been developed against other members of the erbB family receptors. The epidermal growth factor receptor (EGFR) is over-expressed in many cancers and cetuximab has been approved for treatment of several cancers with EGFR expression, e.g. colorectal cancer and head and neck cancer. Currently, several PET tracers of trastuzumab and cetuximab are under investigation [48, 52, 138, 139]. A high correlation was found between [64Cu] cetuximab uptake and EGFR expression [52].

Finally, radiolabelling TKIs may have a role in imaging receptors. However, uptake values of [18F]gefitinib, the posi-tron emitter of the EGFR TKI gefitinib, did not correlate with EGFR expression levels of functional status. This was caused by a high non-specific cellular uptake [49], which is a common problem for PET receptor tracers. To determine whether tracer uptake is due to specific binding, the receptor can be saturated with unlabelled drug before administration

of the tracer. Although TKIs have been named as targeted agents, they are known to have multiple targets. This charac-teristic makes positron emitters of these drugs inappropriate for pharmacokinetic studies of specific receptors, but may still be valuable to investigate drug pharmacokinetics for drug development and prediction of tumour response. Addi-tional reviews on imaging tumour targets can be found in other contributions to this issue of Current Pharmaceutical Design.

3.6. Drug Efflux

3.6.1. Multidrug Resistance Phenotype

On exposure to an anticancer agent, tumours may be-come cross-resistant to a number of structurally and func-tionally unrelated drugs. Multidrug resistance (MDR) in-cludes a large number of anticancer agents such as etoposide, dactinomycin, anthracyclines, vinca alkaloids and paclitaxel. The MDR phenotype usually is a multifactorial phenomenon and many physiological mechanisms can neutralize the ac-tion of anticancer agents. Known examples are decreased topoisomerase II enzyme levels, increased glutathione and glutathione S-transferase levels in tumours and the presence of efflux pumps (Fig. 1D3). The most clearly defined mecha-nism of the MDR phenotype occurs as a result of the ampli-fication of the MDR1 gene, which encodes the transmem-brane glycoprotein, P-glycoprotein (Pgp) [140, 141]. This protein belongs to the ATP-binding cassette (ABC) family. ABC transporters are membrane proteins that utilize energy derived from the hydrolysis of ATP to drive transport of compounds over biological membranes. Three other ABC transporter proteins are known to contribute to the MDR phenotype: the protein associated to the multidrug resis-tance-associated protein (MRP1), the canalicular multis-pecific organ anion transporter (cMOAT) or MRP2, and the breast cancer resistance protein (BCRP).

Most of the mechanisms involved in MDR have first been described in normal tissues. Pgp plays an important role in the protection of cells from toxins. Pgp expression in

normal tissue is variable and high levels are found at the blood-brain barrier, the proximal tubules of the kidney, the intestinal lumen and the biliary surface of hepatocytes [142, 143]. High levels in the blood-brain barrier may explain the relatively high failure rate of anticancer agents in the brain.

Nowadays, several detection assays such as polymerase chain reaction, Northern blotting, Western blotting and im-munohistochemistry are available to detect the MDR pheno-type. However, these techniques have some known limita-tions. Serial tumour biopsies are not generally performed for ethical reasons, resulting in lack of information on the MDR phenotype during and following treatment with anticancer drugs. Furthermore, assessment of mRNA and protein ex-pression does not necessarily provide information on the functionality of MDR efflux pumps. It is evident that the MDR phenotype is not defined by expression of ABC trans-porter proteins, but by the functional transport capacity of these efflux pumps.

3.6.2. PET Imaging of the Multidrug Resistance Phenotype

PET studies can show in vivo functionality of MDR pumps and give quantitative information on Pgp-mediated pharmacokinetics [144-147]. In SPECT studies with [99mTc]-sestamibi it was possible to predict tumour response to drugs affected by the MDR phenotype [148, 149]. These promising results have stimulated the development of PET tracers to image the MDR phenotype. Parallel to the SPECT tracer [99mTc]sestamibi, the PET tracer [94mTc]sestamibi has shown lower accumulation in drug-resistant tumours than in drug-sensitive tumours [150]. In the development of PET tracers for MDR imaging, incorporation of conventional PET radi-onuclides into drugs, that are known to interact with MDR, is a frequently used approach. Employing this strategy, various PET tracers including [11C]verapamil [146, 151], [11C] colchicine [152, 153], [11C]daunorubicin [144, 145, 154], [11C]loperamide [155], [11C] paclitaxel and [18F]fluoropaclitaxel [18-20] have been developed and applied to investigate the blood-brain barrier [147, 156, 157] as well as tumours [21, 23, 144, 145, 153]. For [11C]colchicine, a 2-fold differ-ence between [11C]colchicine accumulation in sensitive and resistance tumours was observed [153]. In vitro experiments in ovarian carcinoma cell lines (A2780) and its Pgp express-ing counterpart (A2780AD) demonstrated that the accumula-tion of [11C]verapamil and [11C]daunomycin were a 5-fold and 16-fold higher in A2780 than in 2789AD, respectively [144]. [18F]fluoropaclitaxel was also able to differentiate between drug-sensitive and drug-resistant tumours in mice [23].

Pgp blockade with inhibitors such as cyclosporine A, PSC833 and tariquidar can give quantitative information on Pgp-mediated pharmacokinetics. Administration of cyclosporine increased tumour uptake of [18F]fluoropaclitaxel in MCF-7 breast cancer xenografts [21] as well as [11C]verapamil and [11C]daunomycin uptake in Pgp expressing small cell lung cancer [145].

Although effects of Pgp inhibitors on MDR have been disappointing in treatment of cancer patients [158], early diagnosis of MDR may serve to improve the efficacy of the chemotherapeutic intervention and the quality of life of pa-tients. Furthermore, PET can be used to develop better in-hibitors of MDR for clinical use.

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4. BIOMODULATION

4.1. Principles

Drug resistance to anticancer cancer agents has stimu-lated research into approaches to increase the response rate. The ultimate goal of enhancing anti-tumour activity can be achieved by pharmacological manipulation of an anticancer drug by another compound, an approach that is named bio-modulation. PET and its radiolabelled anticancer drugs can contribute to the rational development of biomodulation strategies by exploring whether tumour uptake of a radiola-belled drug can be increased by biomodulating agents. Fur-thermore, these studies can provide information on the ef-fects of the biomodulator on plasma and organ pharmacoki-netics as well as tumour blood flow [31, 33].

4.2. Improving Drug Delivery

Limited drug penetration is an important mechanism of tumour resistance of anticancer drugs [72, 73]. Several drugs have been investigated to increase the delivery of radiola-belled anticancer agents. PET studies using both [15O]H2O and [18F]5-FU have demonstrated that nicotinamide, car-bogen as well as interferon-alpha were able to increase tu-mour perfusion, while a decrease was observed with N-phosphonacetyl-L-aspartate (PALA) [31, 33]. Moreover, administration of PALA and interferon-alpha induced changes in plasma, tumour and liver pharmacokinetics of [18F]5-FU [33]. Blood flow and tumour TACs increased upon interferon-alpha administration, whereas they de-creased when PALA was administered. Although nicotina-mide and carbogen administration increased perfusion and [18F]5-FU delivery to colorectal cancer metastases, these effects did not increase [18F]5-FU retention [31]. Interest-ingly, tumour perfusion and consequently drug delivery may rely on organ specific perfusion. Moreover, biomodulators may affect organ perfusion selectively [159].

The induction of hypertension is another approach to improve drug delivery to tumours [160]. Treatment with angiotensin II, a drug that induces hypertension, resulted in a selective increase in [15O]H2O and [62Cu]pyruvaldehyde bis-(N4-methyl)thiosemicarbazone ([62Cu]PTSM) tumour blood flow without increasing blood flow in normal tissue [161-163]. This phenomenon is due to a lack of autoregulation in tumour vessels [160]. Inhibitors of VEGF signalling are known to induce hypertension [164, 165], possibly due to peripheral vasoconstriction [166, 167]. PET studies with [15O]H2O are of interest to explore whether antihypertensive medication will abrogate the change in tumour blood flow and drug delivery induced by treatment with VEGF(R) in-hibitors.

As mentioned before, therapy targeted against VEGF signalling may improve drug delivery [168] by normaliza-tion of tumour vasculature [70]. Optimal scheduling of antiangiogenic therapy combined with chemotherapy re-quires knowledge of the time window during which vessels become normalized. PET studies with [15O]H2O and radiola-belled anticancer agents may be able to reveal effects of antiangiogenic treatment on drug uptake. Following antian-giogenic treatment, an increase in tumour uptake of radiola-belled agents may be expected as a result of better drug

penetration and decreased interstitial fluid pressure. Since rapid changes in vascular parameters are seen during treat-ment with VEGF(R) inhibitors [169], optimal timing of drug administration may be within hours after administrating a VEGF(R) inhibitor.

4.3. Influencing Drug Metabolism

Rapid and extensive drug metabolism may limit the availability of a drug. Therefore, approaches have been in-vestigated to decrease drug metabolism. The effects of enilu-racil, an inhibitor that suppresses catabolism of 5-FU by in-activating dihydropyrimidine dehydrogenase (DPD) (Fig. 4), have been explored using [18F]5-FU PET [25-27, 37]. Ca-tabolism of 5-FU into anabolite fluorouridine-5’-monophos- phate (FUMP) and catabolite -fluoro- -alanine (FBAL) can result in the loss of up to 80% of systemically administered drug [170]. Administration of eniluracil in patients decreased [18F]5-FU uptake in normal liver, indicating inactivation of DPD in the liver. Uptake in kidneys also decreased, while there was a large increase in plasma uracil and unmetabo-lised [18F]5-FU. The uptake of radioactivity in tumours in-creased, possibly as a result of improved tumour uptake of [18F]5-FU, its radiolabelled anabolites [66] or both [37].

4.4. Further Considerations

Remarkably, clinical efficacy of biomodulation is not necessarily reflected by changes in tumour pharmacokinetics as measured by PET. Although combining 5-FU with folic acid has proven to be clinically effective, administration of folic acid did not cause any changes in the clearance and tumour pharmacokinetics of [18F]5-FU [33]. It is possible that improved clinical efficacy of biomodulation is not al-ways mirrored by increased tumour retention of the antican-cer agent, e.g. when the biomodulator has cytotoxic capaci-ties and does not change the tumour pharmacokinetics of the investigated drug. In that case, PET should be seen as a tool that can reveal limitations of biomodulation strategies due to unforeseen disadvantages of pharmacokinetics. Moreover, the discrepancy between clinical efficacy and observed PET pharmacokinetics may be attributable to the inability of PET to discriminate between the radiolabelled parent drug and radiolabelled metabolite. Finally, poor reproducibility may cause conflicting results.

Before initiating paired biomodulation studies, repro-ducibility of a specific radiotracer method should be as-sessed. When small modulation effects are expected, high test-retest reproducibility is required. Only tracer doses, which are considered therapeutically ineffective, are suitable for biomodulation studies in the same patient. Otherwise, the effects of a therapeutic dose during the first PET scan (be-fore biomodulation) may affect the results of the second PET scan (after biomodulation).

The promising role of PET to assess effects of biomodu-lation strategies and to optimize the timing of treatment schedules highlights the need for tracer dose reproducibility studies.

5. CONCLUSIONS

Development of personalised medicine for cancer is closely linked to techniques that can predict tumour response

40


to anticancer agents. Currently, a few PET studies with ra-diolabelled anticancer agents have successfully investigated the predictive value of these tracers, indicating the promising role of radiolabelled anticancer agents for individualized treatment planning. For patient selection, PET may be of additional value as compared to immunohistochemistry, be-cause it is drug specific, and can be used to assess drug up-take in all tumour lesions and normal tissues non-invasively, quantitatively and over time (four dimensional). Further-more, radiolabelled anticancer agents may contribute to morphological imaging techniques (e.g. CT) to monitor tu-mour response: when the uptake of a radiolabelled anticancer agent decreases during treatment with the (unlabelled) agent, this may be the first sign of acquired tumour resistance. Drug resistance is a multifactorial phenomenon and radiolabelled anticancer agents can help to reveal several resistance path-ways.

Integration of radiolabelled anticancer agents into selec-tion of cancer patients may alter and improve therapeutic management, prevent unnecessary morbidity, and lead to substantial cost savings and, most importantly, better patient outcome. Furthermore, it is envisaged that PET studies with radiolabelled anticancer agents may be important for optimi-sation and development of combined treatment schedules by investigating the optimal timing of drug administration.

However, PET studies with radiolabelled anticancer agents are expensive. The development of radiolabelled anti-cancer agents takes time (especially in case of a complex synthesis) and requires special facilities (e.g. presence of a cyclotron) and highly qualified personnel. Furthermore, (pre)clinical evaluation of a new radiotracer can be logisti-cally complex and the development of an appropriate phar-macokinetic model can be challenging.

Despite these disadvantages, costs of PET studies could outweigh the costs of passing drugs through phase 1 and 2, since the potency of an anticancer agent would be known early during development. PET can speed up drug develop-ment by providing valuable information on the biodistribu-tion, bioavailability and pharmacokinetics of a new drug. More studies are warranted to investigate the promising role of PET with radiolabelled anticancer agents in drug devel-opment and individualized treatment planning.

ACKNOWLEDGEMENTS

We thank Guusje Bertholet for illustrating the manuscript and K.A. Kurdziel and R.K. Jain for permission to reproduce Figs. (2 and 3), respectively. Furthermore, we thank S.A. Kleijn for valuable comments on the manuscript.

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Chapter 3

Quantitative parametric perfusion images using 15O-labeled water and a clinical PET/CT scanner: test-retest variability in lung cancer

Astrid A.M. van der Veldt, N. Harry Hendrikse, Hans J. Harms, Emile F.I. Comans, Pieter E. Postmus, Egbert F. Smit , Adriaan A. Lammertsma , Mark Lubberink

J Nucl Med 2010;51:1684-90. Eur Radiol 2011;21:2148-9 (Appendix).

Quantitative Parametric Perfusion Images Using15O-Labeled Water and a Clinical PET/CT Scanner:Test–Retest Variability in Lung Cancer

Astrid A.M. van der Veldt1, N. Harry Hendrikse2,3, Hendrik J. Harms1, Emile F.I. Comans1, Pieter E. Postmus3,Egbert F. Smit3, Adriaan A. Lammertsma1, and Mark Lubberink1

1Department of Nuclear Medicine and PET Research, VU University Medical Center, Amsterdam, The Netherlands; 2Department ofClinical Pharmacology and Pharmacy, VU University Medical Center, Amsterdam, The Netherlands; and 3Department of PulmonaryDiseases, VU University Medical Center, Amsterdam, The Netherlands

Quantification of tumor perfusion using radioactive water(H2

15O) and PET is a promising method for monitoring treatmentwith antiangiogenic agents. However, use of dynamic H2

15Oscans together with a fully 3-dimensional clinical PET/CT scan-ner needs to be validated. The purpose of the present studywas to assess validity and reproducibility of dynamic H2

15OPET/CT scans for measuring tumor perfusion and validatethe quantitative accuracy of parametric perfusion images.Methods: Eleven patients with non–small cell lung cancer wereincluded in this study. Patients underwent 2 dynamic H2

15O(370 MBq) PET scans on the same day. During the first scan,arterial blood was withdrawn continuously. Input functions werederived from blood sampler data and the ascending aorta asseen in the images themselves (image-derived input function[IDIF]). Parametric perfusion images were computed using abasis function implementation of the standard single-tissue-compartment model. Volumes of interest (VOIs) were delineatedon low-dose CT (LD-CT) and parametric perfusion images.Results: VOIs could be accurately delineated on both LD-CT and parametric perfusion images. These parametric per-fusion images had excellent image quality and quantitativeaccuracy when compared with perfusion values determinedby nonlinear regression. Good correlation between perfusionvalues derived from the blood sampler input function and IDIFwas found (Pearson correlation coefficient, r 5 0.964; P ,0.001). Test–retest variability of tumor perfusion was 16%and 20% when delineated on LD-CT and parametric perfusionimages, respectively. Conclusion: The use of ascendingaorta IDIFs is an accurate alternative to arterial blood sam-pling for quantification of tumor perfusion. Image qualityobtained with a clinical PET/CT scanner enables generationof accurate parametric perfusion images. VOIs delineated onLD-CT have the highest reproducibility, and changes of morethan 16% in tumor perfusion are likely to represent treatmenteffects.

Key Words: tumor perfusion; PET-CT; radioactive water; lungcancer; parametric perfusion images

J Nucl Med 2010; 51:1684–1690DOI: 10.2967/jnumed.110.079137

Angiogenesis, or formation of new blood vessels, isessential for tumor growth, tumor progression, and develop-ment of metastases (1,2). Many proangiogenic factors reg-ulate this process, with vascular endothelial growth factorbeing the most important. Consequently, it has been shownthat antiangiogenic therapy, particularly when targeting thevascular endothelial growth factor signaling pathway, pro-vides a survival benefit in patients with solid malignanciesincluding non–small cell lung cancer (NSCLC) (3–9).

Response evaluation of antiangiogenic drugs, however,remains a challenge, because response to antiangiogenictherapy is not necessarily reflected by drug-induced changesin tumor size (10–13). Therefore, new imaging tools areneeded to assess the efficacy of antiangiogenic drugs to selectcancer patients who may benefit from those agents early dur-ing treatment.

Previous studies have shown that quantification of tumorperfusion using radioactivewater (H2

15O) and PET is a promis-ing method to monitor antiangiogenic treatment (14–18). Theshort half-life of 15O enables serial measurements within a sin-gle scan session. Because contrast between tumor and back-ground in H2

15O images usually is low, these scans often arefollowed by a second PET scan using, for example, 18F-FDG(19) or 3-deoxy-3-18F-fluorothymidine (18F-FLT) (20). Theseadditional scans are required to define appropriate regions ofinterest, which subsequently are copied onto theH2

15O images.To date, most PET scanners are combined with CT, which

enables tumor localization on a low-dose CT (LD-CT) scan.In addition, these scanners allow for 3-dimensional (3D) PETwith much lower doses of H2

15O (,400 MBq) than that (.1GBq) usually administered in the case of older stand-alone2-dimensional (2D) PET scanners. At present, however, PET/

Received May 16, 2010; revision accepted Aug. 3, 2010.For correspondence or reprints contact: Astrid A.M. van der Veldt, VU

University Medical Center, Nuclear Medicine and PET Research, P.O. Box7057, 1007 MB Amsterdam, The Netherlands.E-mail: [email protected] ª 2010 by the Society of Nuclear Medicine, Inc.

1684 THE JOURNAL OF NUCLEAR MEDICINE • Vol. 51 • No. 11 • November 2010

51

CT has primarily been used for whole-body 18F-FDG studiesusing, at best, a semiquantitative approach for analyzing data.Only a few studies have addressed full quantification of tracerkinetics using a 3D PET/CT scanner.Although test–retest variability of H2

15O perfusion studieshas been reported previously for a stand-alone 2D scanner,those results are not necessarily valid for a state-of-the-art3D PET/CT scanner because of the higher scatter fraction ofthe PET/CT device. On the other hand, the superior imagequality of 3D PET/CT provides the potential of performinganalyses at the voxel level, thereby generating parametricperfusion images.The aims of the present study were to validate the use of

an image-derived input function (IDIF) in the case of 3Dacquisitions, assess the accuracy of parametric perfusionimages, and assess test–retest variability of tumor perfusionmeasured using a state-of-the-art PET/CT scanner.

MATERIALS AND METHODS

PatientsBetween September 2008 and May 2009, 11 patients (9 men, 2

women; mean age 6 SD, 59 6 12 y) with advanced-stage NSCLCparticipated in this prospective study. Inclusion criteria were 18 y ofage or older, life expectancy of at least 12 wk, a malignant lesion ofat least 1.5 cm in diameter in the chest, Karnofsky performancestatus scale score greater than 60%, thrombocyte count more than100 · 109 L21, and hemoglobin more than 6.0 mmol�L21. Exclusioncriteria included patients who were claustrophobic, pregnant, or lac-tating; had metal implants (e.g., pacemakers); used coumarin deriv-atives or inhibitors of thrombocyte aggregation; were undergoingconcurrent treatment with experimental drugs; or had participatedin a clinical trial with any investigational drug within 30 d beforestudy entry. Before inclusion, each patient signed a protocol-specificinformed consent form that had been approved by the Medical EthicsReview Committee of the VU University Medical Center.

Scanning ProtocolStudies were performed on a Gemini TF-64 PET/CT scanner

(Philips) (21). This scanner has an axial field of view of 18 cm,divided into 45 contiguous planes. Ten of 11 patients underwent 2H2

15O scans on the same day. Patients received an indwellingradial artery catheter for arterial blood sampling and a venouscatheter for tracer injection. Patients were positioned supine inthe scanner bed, with both tumor and aortic arch in the centerof the axial field of view. Elastic body-restraining bandages wereused to minimize movement during scanning. After a 50-mAs LD-CT scan for attenuation correction, a 10-min dynamic scan wasstarted simultaneously with an intravenous injection of 370 MBqof H2

15O (22) (5 mL at 0.8 mL�s21), followed by 35 mL of saline(2 mL�s21). Data were normalized, and all appropriate correctionswere applied for dead time, randoms, scatter, and attenuation.Each emission scan was reconstructed into 26 frames (1 · 10, 8· 5, 4 · 10, 2 · 15, 3 · 20, 2 · 30, and 6 · 60 s) using the 3D row-action maximum-likelihood reconstruction algorithm with areconstructed resolution of 6.5 mm.

Arterial Blood SamplingTo compare the use of an IDIF with the blood sampler input

function (BSIF), arterial blood was sampled during the first scan.

Arterial blood was withdrawn continuously at a rate of 5 mL�min21

during the first 5 min and 1.7 mL�min21 thereafter, using an onlinedetection system (23). In addition, at 5, 8, and 10 min after injection,10 mL arterial blood samples were collected manually. These sampleswere counted in awell-counter thatwas cross-calibrated against thePETscanner and were subsequently used to calibrate the online blood curve.

Input FunctionsVolumes of interest (VOIs) (diameter, 1 cm) were drawn over the

ascending aorta in approximately 10 consecutive image planes ofthe frame in which the first pass of the bolus was best visualized.Projection of the resulting VOI onto all image frames yielded thearterial time–activity curve or IDIF CA(t). Applying a similarapproach to the right ventricular cavity and pulmonary artery pro-vided a time–activity curve for the pulmonary circulation CV(t).Blood sampler data were corrected for delay and dispersion byfitting the early part of the sampler curve to the ascending aortatime–activity curve, convolved with a single exponential dispersionfunction and including a delay parameter. The sampler curve wassubsequently shifted and corrected for dispersion using these fitteddelay and dispersion constants. The resulting delay- and dispersion-corrected sampler curve was calibrated using the manually drawnsamples, finally providing the BSIF.

Parametric ImagesParametric perfusion images were generated using IDIFs and a

basis function implementation of the standard single-tissue-compartment model (24–26), applying corrections for both arterialand pulmonary artery blood volumes (27):

CPETðtÞ5ð1 � VA � VVÞ � F � CAðtÞ � e� F

VTt 1VACAðtÞ1VVCVðtÞ;

Eq. 1

where F represents perfusion, VA arterial blood volume, VV pul-monary circulation blood volume, and VT the distribution volumeor partition coefficient of water in tumor tissue. In the presentstudy, 30 logarithmically spaced precomputed basis functions withF/VT values ranging from 0.1 to 2 min21 were used. Parametricperfusion images were postsmoothed with a gaussian filter of10 mm in full width at half maximum.

Definition of Tumor VOIsAll LD-CT images were converted to ECAT 7 format. Tumor

VOIs were drawn on the LD-CT image by an experienced nuclearmedicine physician unaware of patients’ histories and outcomes,using the CAPP software package (CTI/Siemens). On parametricperfusion images, focally enhanced perfusion other than physiologicperfusion was interpreted as potentially malignant. VOIs weredefined by the same nuclear medicine physician using softwaredeveloped in-house, applying a semiautomatic threshold technique(50% of the maximum pixel value with correction for local back-ground) (28).

Data AnalysisAll tumor VOIs were projected onto the dynamic H2

15Oimages, thereby generating tumor time–activity curves. In addi-tion, VOIs defined on parametric perfusion images were copiedto parametric VT images. Using nonlinear regression (NLR),tumor time–activity curves were fitted to the standard single-tissue-compartment model for H2

15O (Eq. 1) with or without(i.e., VV set to 0) correction for pulmonary circulation blood

TUMOR PERFUSION WITH 15O-WATER PET/CT • van der Veldt et al. 1685

52

volume, yielding F and VT. Perfusion values obtained using BSIFand IDIF were compared for CT-based VOIs. The need to includea correction for pulmonary circulation blood volume in the modelwas assessed for CT-based VOIs using the Akaike and Schwartzcriteria (29,30). The quantitative accuracy of parametric imageswas validated by comparing (unweighted) average VOI perfusionand distribution volume values directly extracted from the para-metric images to tumor perfusion and distribution volumeobtained by NLR of the corresponding tumor time–activity curve.

Correlations were explored using the Pearson correlation coeffi-cient. Level of agreement between test and retest values wasdetermined using an intraclass correlation coefficient (ICC) with a2-way randommodel. The Bland and Altman method (31) was used toanalyze the difference between the 2 measurements and to test therepeatability of each measurement. The repeatability coefficient wascalculated as 1.96 times the SD of the differences. For comparison, therepeatability coefficient is also given as a percentage of the averagevalue of the 2 measurements. For correlation and test–retest analyses,only the primary tumor in each patient was used, whereas only IDIF-based values were entered into test–retest analyses.

RESULTS

Delineation of Tumors

Eleven primary tumors and 7 mediastinal metastaseswere in the field of view of the dynamic scan. Ten of 11primary tumors could be delineated on the LD-CT scan(Supplemental Table 1; supplemental materials are avail-able online only at http://jnm.snmjournals.org), whereas 1could not be defined because of postobstruction atelectasis,which could not be distinguished from the primary tumor.In addition, 3 of 7 mediastinal metastases could be delin-eated on the LD-CT scan. On the parametric perfusionimages, fewer lesions could be defined than on the LD-CT scan (11 vs. 13 VOIs; Supplemental Table 2).

IDIF Versus Arterial Sampling

Arterial sampling was successfully performed, except for1 patient in whom online sampling was difficult because offormation of a thrombus in the line of the detection system.Therefore, this patient was excluded from BSIF analyses.The IDIF curve was isomorphic to the BSIF curve (Fig. 1).However, the IDIF peak was sharper because of dispersionin the blood-sampling system. A high correlation betweenIDIF and blood sample activity concentrations was found(r 5 0.954; P , 0.001). Tumor perfusion and VT based onthe ascending aorta IDIF showed high correlations withcorresponding values based on arterial sampling (r 50.964 and 0.835, respectively; P , 0.001). In addition,agreement between BSIF- and IDIF-based tumor perfusionand distribution volume values was high, with ICCs of0.956 (95% confidence interval [CI], 0.819–0.990) and0.850 (95% CI, 0.491–0.964), respectively. Figure 2presents scatter and Bland–Altman plots of tumor perfusionderived using ascending aorta IDIF vs. BSIF.

Pulmonary Blood Volume Correction

In 9 of 11 patients, VOIs for pulmonary blood volumecorrection were defined in both the pulmonary artery and

the right ventricular cavity. In 1 patient, VOIs could bedefined only in the pulmonary artery because the rightventricular cavity was not in the field of view. In anotherpatient, both the pulmonary artery and the right ventriclewere outside the field of view, and the superior caval veinwas used instead. In all delineated lesions (n 5 24), Akaikeand Schwarz analyses showed better fits when a pulmonaryblood volume parameter was included, but its inclusion didnot affect absolute values of tumor perfusion (correlationbetween tumor perfusion with and without pulmonaryblood volume parameter: r 5 1.000; P , 0.001).

Validation of Parametric Images

Perfusion and distribution volumes as determined di-rectly from the parametric images, using an ascending aortaIDIF, were compared with those obtained using the NLRof Equation 1 to the VOI time–activity curve. Correlation(F: r 5 0.979; VT: r 5 0.950; P , 0.001) and agreement(F: ICC, 0.979; 95% CI, 0.917–0.995; VT: ICC, 0.949; 95%CI, 0.791–0.988) between parametric images and NLRwere excellent. Figure 3 shows scatter and Bland–Altmanplots of tumor perfusion values as determined directly fromthe parametric images versus values determined by NLRof tumor time–activity curves. Furthermore, parametricimages clearly showed increased perfusion in the tumor(Fig. 4).

Test–Retest Reproducibility

When VOIs were defined on the LD-CT scan, tumorperfusion, distribution volume, and tumor size showed goodreproducibility, with ICCs of 0.997 (95% CI, 0.986–0.999),0.880 (95% CI, 0.560–0.972), and 0.998 (95% CI, 0.993–

FIGURE 1. Typical example of IDIF based on ascending aorta and

corresponding BSIF (not corrected for dispersion) derived fromsame dynamic dataset.


53

1.000), respectively (Table 1). When VOIs were defined onparametric perfusion images, reproducibility of tumor per-fusion was comparable (ICC, 0.980; 95% CI, 0.915–0.996).For parametric-based VOIs, the ICCs for tumor size anddistribution volume were 0.811 (95% CI, 0.367–0.954) and0.871 (95% CI, 0.532–0.969), respectively. In addition, per-fusion values directly taken from parametric perfusionimages showed good reproducibility, with an ICC of 0.977(95% CI, 0.901–0.995). Distribution volumes taken directlyfrom parametric VT images, using VOIs defined on perfusionimages, showed slightly better reproducibility (ICC, 0.908;95% CI, 0.649–0.979) than VT values calculated using NLR.Figure 5 shows Bland–Altman plots of tumor perfusion val-ues for CT- and parametric-based VOIs. The repeatabilitycoefficient of tumor perfusion was 16% and 20% whendelineated on LD-CT and parametric perfusion images,respectively (Table 1).

Correlation Between CT- and Parametric-Based VOIs

In 8 of 10 primary tumors, tumor perfusion was higherfor parametric-based VOIs than for CT-based VOIs (0.2960.23 mL�cm23�min21 vs. 0.35 6 0.17 mL�cm23�min21;mean 6 SD). Nevertheless, correlation between both setsof perfusion data was high (r 5 0.835; P 5 0.003).

DISCUSSION

In this study, the use of low-dose dynamic H215O scans for

assessment of tumor blood flow using a clinical, fully 3DPET/CT scanner was evaluated. In NSCLC patients, the LD-CT scan enabled delineation of appropriate VOIs, whichmakes additional PET scans with 18F-FDG or 18F-FLT fordelineation of VOIs obsolete, resulting in decreased radiationburden and scanning time. In addition, quantitative H2

15OPET/CT tumor perfusion measurements had excellent repro-ducibility. Image quality obtained with the relatively lowdose of 370 MBq of H2

15O (compared with the usual doseof 1,100 MBq for 2D scanners) was such that accurate para-metric perfusion images with good statistics could be pro-duced. On the basis of the present results, changes in tumorperfusion of more than 16% in CT-based VOIs or 20% inparametric-based VOIs are likely to reflect treatment effects.

For quantification of perfusion, an arterial input functionis needed. This can be obtained using either arterialsampling or an IDIF. Arterial sampling is invasive andlimits clinical applicability. On the other hand, IDIFs areprone to partial-volume effects and can be used only when alarge structure containing arterial blood is visible in thefield of view. In the present study, noninvasive IDIFs of the

FIGURE 2. Scatter (A) and Bland–Altman(B) plots of tumor perfusion derived using

ascending aorta IDIF vs. BSIF. Solid line

(A) represents linear fit through data points.

Dotted lines (B) represent 6 1.96 · SD val-ues. Difference was absolute change

between test and retest scans, and mean

perfusion was mean tumor perfusion of testand retest scans.

FIGURE 3. Scatter (A) and Bland–

Altman (B) plots of tumor perfusion valuesdirectly from parametric images vs. perfu-

sion values determined by NLR of tumor

time–activity curves, using 50% isocontour

VOIs defined on parametric perfusionimages. Parametric images were generated

using IDIFs. Solid line (A) represents linear fit

through data points. Dotted lines (B) repre-sent 6 1.96 · SD values. Difference was

absolute change between test and retest

scans, and mean perfusion was mean tumor

perfusion of test and retest scans.


54

ascending aorta were compared with arterial concentrationsobtained using invasive BSIFs. Resulting tumor perfusionvalues agreed well with each other (Fig. 2), indicating thatuse of ascending aorta IDIFs is a valid noninvasive alterna-tive to arterial blood sampling. Although manual IDIF def-inition is time-consuming, automated IDIF definition hasrecently been shown to be feasible for myocardial perfusionimaging with H2

15O (32) and may similarly be applied forquantification of tumor perfusion in the thorax.Inclusion of a pulmonary blood volume parameter in Equa-

tion 1 resulted in improved fits, whereas tumor perfusionvalues were not affected significantly. Because blood vesselsof the pulmonary circulation are erroneously depicted asareas with high perfusion in parametric images when nopulmonary blood volume parameter is applied, inclusion ofa pulmonary blood volume parameter also improves the qual-ity of parametric images. Consequently, the application ofthis parameter facilitates delineation of tumors that are closeto large blood vessels on parametric images.In contrast to a stand-alone 2D PET scanner (20), the

present 3D PET/CT scanner did produce parametric perfu-sion images of good quality. This can be explained bydifferences in noise-equivalent count rates. During the firstpass of 370 MBq of H2

15O, the observed noise-equivalent

count rate was 5 times higher than that during the first passof 1,100 MBq of H2

15O on the stand-alone 2D PET scannerused previously (20). This difference is mainly due to themuch lower random coincidence rate on the 3D PET/CTscanner, because of its narrower coincidence time window(6 vs. 12 ns) and the use of lutetium yttrium orthosilicateinstead of bismuth germinate crystals.

As can be seen from Figure 3, measured perfusion wasvariable between different tumors, as is in line with pre-vious studies investigating perfusion in lung cancer (19,20).In addition, reproducibility of perfusion measurementsusing the present 3D PET/CT scanner was comparable tothe results of a previous study in NSCLC patients on astand-alone 2D PET scanner (20). In that study, an addi-tional 18F-FLT PET scan was used for delineation oflesions, and changes of more than 18% in tumor perfusionand 32% in distribution volume were likely to representbiologic effects (20). The reproducibility of distributionvolume, however, was better using a 2D PET scanner thanusing CT-based values of the PET/CT scanner, which had areproducibility of 47%. However, the reproducibility of dis-tribution volume was better than for CT-based VOIs andmore comparable to the previous study for VOIs defined onparametric perfusion images.

FIGURE 4. PET/CT images of primarytumor in 54-y-old man (patient 6) with meta-

static NSCLC. Parametric perfusion image

(A; 10 mm in full width at half maximum filter)

shows increased perfusion in primary tumorin left upper lobe. B and C represent corre-

sponding CT and PET/CT fusion images,

respectively.

TABLE 1Reproducibility of Tumor Measurements Using Dynamic H2

15O PET/CT Scans

Repeatability coefficient

Measurement ICC 95% CI Absolute value Relative value (%)

Tumor perfusion (F)CT-based VOI, NLR 0.997 0.986–0.999 0.030 mL�cm23�min21 15.8

Parametric VOI, NLR*,† 0.980 0.915–0.996 0.074 mL�cm23�min21 19.9

Direct parametric VOI*,‡ 0.977 0.901–0.995 0.084 mL�cm23�min21 40.9

Volume of distribution (VT)CT-based VOI, NLR 0.880 0.560–0.972 0.20 mL�cm23 47.3

Parametric VOI, NLR*,† 0.871 0.532–0.969 0.19 mL�cm23 37.0

Direct parametric VOI*,‡ 0.908 0.649–0.979 0.17 mL�cm23 36.8

Tumor sizeCT-based VOI 0.998 0.993–1.000 14.2 cm3 27.3

Parametric VOI* 0.811 0.367–0.954 29.5 cm3 98.6

*Parametric perfusion images with 10-mm filter were used.†Values were obtained by projecting parametric-based VOI onto dynamic H2

15O images.‡Values were obtained by direct extraction from parametric image.n 5 9 lesions.


55

When compared with parametric-based VOIs, applicationof CT-based VOIs resulted in larger tumor volumes withlower perfusion values. Delineation of lesions on the LD-CTscan results in average perfusion values over the whole CTvolume, which may include nonvital necrotic tissue (Fig. 6).Parametric perfusion images, on the other hand, preservespatial information and enable visual assessment of a perfu-sion image, allowing selective delineation of well-perfusedparts in heterogeneous tumors. In addition, delineation on aPET scan with a second tracer such as 18F-FDG or 18F-FLT(20) may facilitate the identification of vital tumor tissue,giving perfusion only in metabolically active or only inhighly proliferative tumor tissue, respectively.Although dynamic H2

15O PET/CT measurements arefeasible, there are 2 practical limitations to use in NSCLCpatients. First, the image quality of an LD-CT scan may betoo low to adequately distinguish tumor from mediastinalstructures. In addition, high (physiologic) perfusion in post-obstruction atelectasis may even mirror tumor perfusion onparametric perfusion images. In such cases, a diagnostic CTscan with a higher radiation dose or an additional 18F-FDGPET scan may be required to define lesions accurately.Second, quantification of tumor perfusion within the thoraxmay be affected by respiration, resulting in respiration-averaged images with lower perfusion values. Pulmonarygating might overcome this issue but remains a challengewhen used in combination with dynamic scans.Several methods are available to delineate VOIs on

H215O PET/CT scans, including LD-CT, parametric perfu-

sion images, and even PET scans with a second tracer.

However, it is currently not clear which delineation methodbest characterizes treatment-induced changes in tumor per-fusion, especially in the case of spatially varying heteroge-neous responses. Therefore, studies are warranted thatcompare the predictive value of these different delineationmethods in patients treated with antiangiogenic agents.

CONCLUSION

In NSCLC patients, it is feasible to assess tumor perfusionusing dynamic H2

15O PET on a clinical PET/CT scanner. Inthis case, the use of an ascending aorta time–activity curve asthe input function is an accurate alternative to arterial bloodsampling. The high image quality allows generation of para-metric perfusion images with good statistics. Tumors canconveniently be delineated on both LD-CT and parametricperfusion images, but CT-based VOIs result in the highestreproducibility of tumor perfusion.

ACKNOWLEDGMENTS

We thank Suzette van Balen, Amina Elouahmani, Judithvan Es, Femke Jongsma, Rob Koopmans, Nasserah Sais, andAnnemiek Stiekema for assistance with scanning; NatasjaKok, Ilona Pomstra, and Atie van Wijk for help with logisticplanning and patient care; Dennis Boersma, Arthur vanLingen, and Maqsood Yaqub for technical assistance; OttoHoekstra for critical reading of the manuscript; SebastiaanKleijn for assistance with the figures; and Henri Greuter,Gert Luurtsema, Kevin Takkenkamp, and Robert Schuit forproduction of H2

15O and analysis of blood samples.

FIGURE 5. Bland–Altman plots of tumor

perfusion based on delineation on LD-CT

scan (A) and parametric perfusion images

(B). Dotted lines represent 6 1.96 · SD val-ues. Difference was percentage change

between test and retest scans, calculated

by subtracting values of morning scans from

those of afternoon scans; mean perfusionwas mean tumor perfusion of test and retest

scans.

FIGURE 6. PET/CT images of primary

tumor in 73-y-old man (patient 3) with meta-

staticNSCLC. Parametric perfusion image (10

mm in full width at half maximum filter) showshigh perfusion in peripheral zone of tumor (A;

arrow) but low perfusion in central region. B

and C represent corresponding CT and PET/

CT fusion images, respectively. Because ofdispersion, high perfusion is erroneously

shown in descending aorta (*).


56

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LETTER TO THE EDITOR

Comment on Cho et al.: Usefulness of FDG PET/CTin determining benign from malignantendobronchial obstruction

Astrid A. M. van der Veldt & Mark Lubberink &

Adriaan A. Lammertsma & Egbert F. Smit

Received: 26 March 2011 /Accepted: 23 April 2011 /Published online: 18 June 2011# The Author(s) 2011. This article is published with open access at Springerlink.com

Dear Sir,With interest we read the study by Cho et al [1], evaluatingthe usefulness of FDG PET/CT for differentiating malig-nant endobronchial lesions with distal atelectasis frombenign bronchial stenosis. In this retrospective study, theyadequately demonstrated the additional value of FDG PET/CT in this challenging clinical problem. Besides differen-tiation of endobronchial lesions, accurate discriminationbetween malignant tumours and atelectatic lung tissue canfacilitate the definition of radiotherapy target volumes. As aresult, the size of radiotherapy fields can be decreased [2],potentially reducing radiotherapy-induced side-effects.

For these purposes, the PET technique may be ofadditional value to discriminate the obstructive lesion fromthe atelectatic lung tissue. Although Cho et al [1]mentioned different patterns of FDG uptake in atelectaticlung tissue, we wonder whether the FDG uptake in theobstructive lesions could be adequately distinguished fromthe FDG uptake in the atelectatic lung tissue. As FDGuptake is dependent on perfusion for its delivery to tissue,variation in tissue vascularity may contribute to variableFDG uptake in obstructive atelectasis. In a previous PET/CT study, we quantified tumour perfusion in lung cancerpatients using radiolabelled water ([15O]H2O) [3]. Themeasured perfusion values in atelectatic lung tissue differedsignificantly as compared with perfusion values in malig-nant tumours. Figure 1 shows an example of a patient withrelatively high perfusion in atelectatic lung tissue ascompared with the malignant tumour. These observationssuggest that perfusion measurements may have additionalvalue to discriminate atelectatic lung tissue from malignantlesions. Therefore, we believe that additional perfusionmeasurements of atelectatic lung tissue may improvediagnosis and radiotherapy planning of malignant endo-bronchial lesions.

A reply to this letter can be found at doi:10.1007/s00330-011-2170-y.

A. A. M. van der Veldt (*) :M. Lubberink :A. A. LammertsmaDepartment of Nuclear Medicine & PET Research,VU University Medical Center,P.O. Box 7057, 1007 MB Amsterdam, The Netherlandse-mail: [email protected]

E. F. SmitDepartment of Pulmonary Diseases,VU University Medical Center,Amsterdam, The Netherlands

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Open Access This article is distributed under the terms of the CreativeCommons Attribution Noncommercial License which permits anynoncommercial use, distribution, and reproduction in any medium,provided the original author(s) and source are credited.

References

1. Cho A, Hur J, Kang WJ, Cho HJ, Lee JH, Yun M, Lee JD (2011)Usefulness of FDG PET/CT in determining benign from malignantendobronchial obstruction. Eur Radiol 21:1077–1087. doi:10.1007/s00330-010-2006-1

2. Nestle U, Walter K, Schmidt S, Licht N, Nieder C, Motaref B,Hellwig D, Niewald M, Ukena D, Kirsch CM, Sybrecht GW,Schnabel K (1999) 18F-deoxyglucose positron emission tomogra-phy (FDG-PET) for the planning of radiotherapy in lung cancer:high impact in patients with atelectasis. Int J Radiat Oncol BiolPhys 44:593–597

3. Van der Veldt AA, Hendrikse NH, Harms HJ, Comans EF, PostmusPE, Smit EF, Lammertsma AA, Lubberink M (2010) Quantitativeparametric perfusion images using 15O-labeled water and a clinicalPET/CT scanner: test-retest variability in lung cancer. J Nucl Med51:1684–1690

Fig. 1 PET-CT images of obstructive atelectasis in a 52-year old malepatient with metastatic non-small cell lung cancer. The parametricperfusion image in Fig. 1a demonstrates high perfusion (arrow) in

obstruction atelectasis, whereas the perfusion in the primary tumour(*) is substantially lower. Figs. 1b and c represent corresponding low-dose CT and fused PET-CT images, respectively

Eur Radiol (2011) 21:2148–2149 2149

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Chapter 4

[11C]docetaxel and positron emission tomography for noninvasive measurements of

docetaxel kinetics

Astrid A.M. van der Veldt, Adriaan A. Lammertsma, N. Harry Hendrikse

Clin Cancer Res 2007;13:7522.

[11C]DocetaxelandPositronEmissionTomography for NoninvasiveMeasurements of Docetaxel Kinetics

To the Editor: We read with great interest the article byBradshaw-Pierce and colleagues (1) reporting a physiologicallybased pharmacokinetic (PBPK) model for docetaxel. Becausedocetaxel is frequently used for the treatment of several cancers,more often, recently, in combination with other anticanceragents, a comprehensive technique to evaluate the effects ofother agents on docetaxel pharmacokinetics and pharmacody-namics is required. In view of this development, the PBPKmodel for docetaxel by Bradshaw-Pierce and colleagues is ofgreat value. This model was developed based on measurementsof docetaxel concentrations in plasma and some tissues of miceby using liquid chromatography–tandem mass spectrometry.We would like to point out, however, that the method

used might not be ideal for collecting the data to develop aPBPK model. Although liquid chromatography–tandem massspectrometry is a sensitive technique for measuring docetaxellevels in plasma and tissue, for the latter measurements it canonly be applied to animals because an extensive number ofbiopsies in humans is too invasive. Second, to develop aPBPK model, organ volumes and organ blood flow need tobe fixed to predefined values. Furthermore, only a limitednumber of organs can be investigated and the validity of themodel depends on an appropriate selection of these organs(before experimentation). For example, in the study byBradshaw-Pierce and co-workers, the spleen was not selected.Uptake of docetaxel in spleen, however, is high, therefore,the spleen should be taken into account in developing thePBPK model. Finally, with liquid chromatography–tandemmass spectrometry, it might be difficult to achieve highextraction efficiency for tissue (extraction efficiency fromtissues was only 40-90%), resulting in potential inaccuraciesin the PBPK model (e.g., systematic errors up to 200%between simulation and measured data in the study byBradshaw-Pierce and colleagues).Another technique to measure drug concentrations in tissue

is positron emission tomography (PET). Using this noninvasivetechnique, it is possible to quantify pharmacokinetics andpharmacodynamics in vivo in animals and humans (2). Overthe years, several therapeutic drugs have been labeled withshort-lived positron-emitting radionuclides. Note that with thisimaging modality, only tracer doses of the radiolabeled drug

need to be administered, making it possible to predict andevaluate a dose in the same animal or human. PET measure-ments do not require assumptions about organ volumes andorgan blood flow. In addition, the number of organs that canbe investigated is not limited because a whole-body scan caneasily be done. Furthermore, PET has high accuracy andsensitivity (picomolar level).To investigate tracer kinetics of docetaxel, we have labeled this

drug with carbon-11 at high specific activity (>18.5 GBq/Amol;ref. 3). This enables sensitive and appropriate measurements of[11C]docetaxel uptake in tissues. Using [11C]docetaxel, we havedone a preliminary biodistribution study in healthy male Wistarrats at 5, 15, 30, and 60 min and found that the spleen had thehighest uptake followed by urine, lung, and liver. Brain andtestes showed the lowest uptake. Within less than 5 min,[11C]docetaxel had already cleared from blood and plasma by>99%. Because docetaxel binds intracellulary to tubulin,knowledge of the uptake of docetaxel in the separate organs ofthe intracellular component (e.g., heart, liver, spleen, lung, butalso tumor tissue) is required. We agree with Bradshaw-Pierceand co-workers that this will contribute to a better understand-ing of the toxicity and tumor response of docetaxel. We believe,however, that PET is a more accurate and sensitive technique formeasuring docetaxel kinetics. Therefore, we have embarked on[11C]docetaxel PET studies in animals and humans withadvanced solid tumors with the ultimate goal of predictingresponse to docetaxel therapy in individual patients.

Astrid A.M. van der VeldtAdriaan A. LammertsmaN. Harry HendrikseDepartment of Nuclear Medicine andPET Research, VU University Medical Center,Amsterdam, the Netherlands

F2007 American Association for Cancer Research.doi:10.1158/1078-0432.CCR-07-1626

References1. Bradshaw-Pierce EL, Eckhardt SG, Gustafson DL. A physiologically based phar-macokinetic model of docetaxel disposition: from mouse to man. Clin Cancer Res2007;13:2768^76.

2.Gupta N, Price PM, Aboagye EO. PET for in vivo pharmacokinetic andpharmaco-dynamic measurements. EurJCancer 2002;38:2094^107.

3.VanTilburg EW, Franssen EJF, van der Hoeven JJM, et al. Radiosynthesis of[11C]docetaxel. JLabel Compd Radiopharm 2004;47:763^77.

Letters to the Editor

www.aacrjournals.orgClin Cancer Res 2007;13(24) December15, 2007 7522

American Association for Cancer Research Copyright © 2007 on November 14, 2011clincancerres.aacrjournals.orgDownloaded from

DOI:10.1158/1078-0432.CCR-07-1626

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Chapter 5

Biodistribution and radiation dosimetry of 11C-labeled docetaxel in cancer patients

Astrid A.M. van der Veldt, N. Harry Hendrikse, Egbert F. Smit, Martien P. Mooijer, Anneloes Y. Rijnders, Winald R. Gerritsen, Jacobus J.M. van der Hoeven,

Albert D. Windhorst, Adriaan A. Lammertsma, Mark Lubberink

Eur J Nucl Med Mol Imaging 2010;37:1950-8.

ORIGINAL ARTICLE

Biodistribution and radiation dosimetry of 11C-labelleddocetaxel in cancer patients

Astrid A. M. van der Veldt & N. Harry Hendrikse & Egbert F. Smit &Martien P. J. Mooijer & Anneloes Y. Rijnders & Winald R. Gerritsen &

Jacobus J. M. van der Hoeven & Albert D. Windhorst & Adriaan A. Lammertsma &

Mark Lubberink

Received: 30 November 2009 /Accepted: 27 April 2010 /Published online: 27 May 2010# The Author(s) 2010. This article is published with open access at Springerlink.com

AbstractPurpose Docetaxel is an important chemotherapeutic agentused for the treatment of several cancer types. As radio-labelled anticancer agents provide a potential means forpersonalized treatment planning, docetaxel was labelledwith the positron emitter 11C. Non-invasive measurementsof [11C]docetaxel uptake in organs and tumours mayprovide additional information on pharmacokinetics andpharmacodynamics of the drug docetaxel. The purpose ofthe present study was to determine the biodistribution andradiation absorbed dose of [11C]docetaxel in humans.Methods Biodistribution of [11C]docetaxel was measured inseven patients (five men and two women) with solidtumours using PET/CT. Venous blood samples were

collected to measure activity in blood and plasma. Regionsof interest (ROI) for various source organs were defined onPET (high [11C]docetaxel uptake) or CT (low [11C]docetaxel uptake). ROI data were used to generate time-activity curves and to calculate percentage injected doseand residence times. Radiation absorbed doses werecalculated according to the MIRD method usingOLINDA/EXM 1.0 software.Results Gall bladder and liver demonstrated high [11C]docetaxel uptake, whilst uptake in brain and normal lungwas low. The percentage injected dose at 1 h in the liverwas 47±9%. [11C]docetaxel was rapidly cleared fromplasma and no radiolabelled metabolites were detected.[11C]docetaxel uptake in tumours was moderate and highlyvariable between tumours.Conclusion The effective dose of [11C]docetaxel was4.7 μSv/MBq. As uptake in normal lung is low, [11C]docetaxel may be a promising tracer for tumours in thethoracic region.

Keywords [11C]docetaxel . Biodistribution .

Radiation dose . Cancer . PET/CT

Introduction

Tumour resistance to chemotherapy remains a majorchallenge, because it results in unnecessary toxicity andcosts and, most importantly, delay in initiating potentiallymore effective treatment. In the last decade, there has beengrowing interest in molecular imaging for tumour responsemonitoring at an early stage during treatment. For example,glucose metabolism as measured by the commonly usedpositron emission tomography (PET) tracer 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG) has been accepted as a

A. A. M. van der Veldt (*) :N. H. Hendrikse :M. P. J. Mooijer :A. Y. Rijnders :A. D. Windhorst :A. A. Lammertsma :M. LubberinkDepartment of Nuclear Medicine & PET Research,VU University Medical Center,P.O. Box 7057, 1007 MB Amsterdam, The Netherlandse-mail: [email protected]

N. H. HendrikseDepartment of Clinical Pharmacology & Pharmacy,VU University Medical Center,Amsterdam, The Netherlands

E. F. SmitDepartment of Pulmonology, VU University Medical Center,Amsterdam, The Netherlands

W. R. GerritsenDepartment of Medical Oncology, VU University Medical Center,Amsterdam, The Netherlands

J. J. M. van der HoevenDepartment of Internal Medicine, Medical Center Alkmaar,Alkmaar, The Netherlands

Eur J Nucl Med Mol Imaging (2010) 37:1950–1958DOI 10.1007/s00259-010-1489-y

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surrogate end-point for the evaluation of new drugs inoncology [1]. However, [18F]FDG PET can only measuretumour response after treatment has already been started bycomparing a response scan with the corresponding baselinescan. Ideally, response to anticancer drugs should bepredicted before initiating therapy. Anticancer agents thatare labelled with a positron emitter may be promisingtracers for predicting treatment outcome before initiatingtreatment [2]. A few studies have suggested that radio-labelled anticancer agents may provide a unique means forpersonalized treatment planning in cancer patients [2], butmore studies are needed to substantiate this concept. Inaddition, radiolabelled anticancer agents may contribute todrug development and the rational development of combi-nation therapy strategies by exploring whether drugpharmacokinetics can be modulated by other agents. Theanticancer drug docetaxel has been radiolabelled with 11C[3–5]. Docetaxel belongs to the taxanes, one of the mostactive classes of cytotoxic agents, and has been approvedfor the treatment of several cancer types, including breast,prostate and lung cancer [6]. Docetaxel acts by disruptingthe microtubular network which results in the inhibition ofmitosis in cells. In spite of this effective mechanism ofaction in tumours, the efficacy of docetaxel treatment incancer patients is not optimal. Appropriate selection ofpatients and addition of biomodulating agents may improveefficacy of docetaxel therapy. PET using [11C]docetaxelmay be valuable, as it allows for measurement of docetaxeluptake in tumours and for investigating effects of otheragents on this uptake. In preparation for kinetic studies incancer patients, the purpose of the present study was todetermine biodistribution and radiation absorbed doses of[11C]docetaxel in humans.

Materials and methods

Patients

Patients with advanced solid tumours, due to undergochemotherapy, were eligible for this study. Inclusion criteriawere: 18 years of age or older, malignant lesion of at least1.5 cm in diameter within the chest as measured by ResponseEvaluation Criteria in Solid Tumors (RECIST) [7], lifeexpectancy of at least 12 weeks, Karnofsky performancestatus scale>60%, platelets>100×109/l and haemoglobin>6.0 mmol/l. Exclusion criteria included previous treatmentwith taxanes, claustrophobia, pregnant or lactating patients,patients having metal implants (e.g. pacemakers), use ofcoumarin derivatives or inhibitors of platelet aggregation,use of drugs that are inhibitors of or substrates for P-glycoprotein (Pgp), concurrent treatment with experimentaldrugs and participation in a clinical trial with any

investigational drug within 30 days prior to study entry.The study was approved by the Medical Ethics ReviewCommittee of the VU University Medical Center. Five maleand two female patients with a mean age (± SD) of 63±10 years and a mean body weight (± SD) of 78±15 kg (range:66–94 kg) were included in the study. All patients werediagnosed with metastatic cancer including non-small celllung cancer (NSCLC) (n=5), malignant pleural mesothelio-ma (n=1) and prostate cancer (n=1). Prior to inclusion, eachpatient signed a protocol-specific informed consent.

Synthesis of [11C]docetaxel

[11C]docetaxel was synthesized according to Good Manu-facturing Practice (GMP) standards as described in detailpreviously [4, 5]. For the preparation of the precursor, the drugdocetaxel was obtained from Green Plantchem Company Ltd.(Hangzhou, China). Briefly, the 11C isotope was introduced inthe side chain by a [11C]tert-butoxycarbonylation of the freeamine of docetaxel, and [11C]docetaxel was produced with adecay-corrected overall radiochemical yield of 10±1% prior topurification. The mean specific activity at time of injectionwas 7±5 GBq/μmol.

Scan protocol

Patients were asked to fast over midnight before scanning.A light breakfast before 8.00 a.m. and water and tea wereallowed. Due to the fact that only sub-pharmacological(tracer) doses of [11C]docetaxel were administered, no sideeffects were expected. The Medical Ethics Review Com-mittee, however, required that dexamethasone be given toprevent potential allergic reactions. Two dosages of 4 mgdexamethasone were given; one in the evening and theother in the morning before [11C]docetaxel administration.Whole-body scans were performed on a Gemini TF-64PET/CT scanner (Philips Medical Systems, Best, TheNetherlands) [8]. Each patient was positioned on thescanner bed using elastic body-restraining bandages tominimize body movement during the scans. Following a50 mAs low-dose CT (LD-CT) scan, a mean (± SD) singlebolus of 178±79 MBq [11C]docetaxel (dissolved in amaximum volume of 12 ml saline) was injected intrave-nously and four serial whole-body PET scans from head tomid-thigh were acquired over a 1-h period with progressiveincrease of scan durations per bed position of 0.5, 1, 1.5and 2 min, respectively. The axial field of view of thescanner is 18 cm and a 50% overlap between bed positionsis applied in whole-body scans, resulting in an average of11 bed positions per scan. Resulting mean durations of thefour consecutive whole-body PET scans were 6.9±1.2,12.6±2.3, 18.3±3.3 and 24.0±4.3 min, respectively. Onepatient was able and willing to undergo a fifth whole-body

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scan with duration of 2.5 min per bed position. Data wasnormalized and all appropriate corrections were applied fordead time, randoms, scatter, attenuation and scannercalibration, and whole-body scans were corrected for decayrelative to the start of each scan. Images were reconstructedusing time-of-flight ordered subsets expectation maximiza-tion (TF-OSEM).

Analysis of blood samples

After each whole-body scan, a venous blood sample (7 ml)was collected for measuring blood and plasma concen-trations as well as radiolabelled metabolites. To avoidcontamination of activity remaining in the catheter, 3–5 mlblood was withdrawn prior to each sample and the line wasflushed with 2 ml saline after sampling, as describedpreviously [9]. A cross-calibrated gamma counter was usedto determine activity concentrations and plasma to wholeblood ratios. The presence of radiolabelled metabolites inplasma was assessed using solid phase extraction (SPE)combined with high-performance liquid chromatography(HPLC) using offline detection.

Region of interest definition

PET and LD-CT images were converted to ECAT 7 formatand regions of interest (ROIs) were drawn using CAPPsoftware (CTI/Siemens, Knoxville, TN, USA) to obtainmean activity concentration in each region at each of thefour time points. For organs with activity concentrationsclearly exceeding background levels [liver, gall bladder,upper large intestine (ULI), urinary bladder, heart wall,bone marrow in vertebrae], ROIs were defined on the PETscan with the highest tracer uptake (Fig. 1) using a 50%isocontour. For organs with lower tracer uptake (brain,lung, spleen, kidney) that could easily be identified on theLD-CT scan, ROIs were drawn manually on the LD-CTscan and subsequently copied to the PET scans (Fig. 2). Foreach patient, a ROI of one tumour of at least 1.5 cm in

diameter that could easily be identified on the LD-CT scanwas determined. All ROIs were projected onto all scans. Asthe volume of the urinary bladder increased duringscanning, bladder ROIs were separately drawn on eachPET image except for the first image. The bladder ROI ofthe second image was projected onto the first PET scan.

Calculation of [11C]docetaxel uptake

ROIs were used to generate time-activity curves (TAC) foreach source organ. The time of measurement of eachindividual organ in each scan was calculated based on theorgan position in the whole-body image and the totalduration of that scan. All organ TACs were then correctedfor decay relative to the time of injection of the tracer. Toassess biodistribution, the mean standardized uptake value(SUV) normalized to body weight and the percentageinjected dose (%ID) in each organ were calculated at eachtime point. For organs with ROIs covering less then theentire organ (ULI, myocardial wall, red marrow), thepercentage of injected activity per cm3 was multiplied withthe organ volumes of the adult male reference phantom,scaled with the ratio of the patient’s weight and thereference man weight [10, 11]. Since bones not containingactive marrow were not visible in the images, all activity invertebrae ROIs was assumed to be in red marrow. Fortumours, the maximum SUV (SUVmax) was calculated.

Residence time and absorbed dose calculations

For each organ, TACs were uncorrected for decay andresidence times were computed as the trapezoidal sum ofthe TAC with the assumption that, after the last time point,activity decreased only by physical decay (i.e. no biologicalclearance after the last time point). Residence time for theremainder of the body was calculated as the total bodyresidence time without voiding (one divided by the decayconstant) minus the sum of the residence times of alldefined organs. Residence times for each patient were

Fig. 1 For organs with activity clearly exceeding background (e.g.liver) ROIs were defined on the PET scan with the highest uptake.PET/CT fusion image (a) and PET image (b) demonstrate high [11C]

docetaxel uptake in liver. The liver ROI as determined on the PETimage is presented in green (b)

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entered into the OLINDA/EXM 1.0 software package [12]to compute absorbed doses using the adult male referencephantom. Since the small intestine (SI) was difficult todelineate in both PET and LD-CT images due to thevicinity to the liver and the poor contrast of the LD-CTimages, the ICRP 30 GI [13] tract model was used toestimate residence times in SI and lower large intestine(LLI) based on those found for ULI. According to thismodel, ratios of SI to ULI and LLI to ULI residence timesare 8.45 and 0.039, respectively, for 11C-labelled tracers[12]. OLINDA/EXM 1.0 provides effective dose valuesaccording to ICRP 60 [14] and does not provide effectivedose values according to the latest definition (ICRP 103,[15]). Therefore, effective doses according to ICRP 103were calculated manually using target organ doses asreported by OLINDA/EXM 1.0 and ICRP 103 weightingfactors. Since not all target organs are included inOLINDA/EXM 1.0 (skin, salivary glands, oesophagus),the sum of weighting factors was 0.94 and effective dosevalues were divided by 0.94 [16].

Results

Biodistribution

Figure 3 shows the typical biodistribution of [11C]docetaxelover time, as obtained from the four sequential PETacquisitions over about 1 h. Liver, gall bladder, intestineand urinary bladder were visually identified as organs withrelatively high activity, whilst [11C]docetaxel uptake inbrain and normal lung was low. Between the third andfourth PET scans, [11C]docetaxel uptake in gall bladder andintestine was still increasing. Figure 4 shows TACs forvarious organs [%ID versus time post-injection (p.i.)].Percentage ID at 1 h p.i. was highest in liver (47±9%) andgall bladder (7.2±3.6%), with 35% of all disintegrationsoccurring in the liver. The highest peak activity concentrationswere measured in gall bladder (SUVmean 96±49), liver(SUVmean 24±3) and ULI (SUVmean 9±6), whereas concen-trations were smallest in brain (SUVmean 0.05±0.03) andlung (SUVmean 0.7±0.2).

Fig. 2 For organs with lower tracer uptake (e.g. lung), ROIs weredrawn on the LD-CT scan and subsequently copied onto the PETscans. PET/CT fusion image (a) and PET image demonstrate low

[11C]docetaxel uptake in lungs. The lung ROIs were drawn on the CTimage (b) and projected onto the PET image (c). The lung ROIs asdetermined on the LD-CT scan are presented in green (b, c)

Fig. 3 Maximum intensity pro-jections of the biodistribution of[11C]docetaxel in a 71-year-oldmale patient with metastaticmalignant pleural mesothelioma.The four successive whole-bodyPET scans (0–6, 8–19, 23–39and 42–63 min p.i.) demonstratehigh liver uptake at all timepoints and low uptake in brainand normal lung. On the fourthscan, [11C]docetaxel uptake isobserved in intestine


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Blood clearance

[11C]docetaxel was rapidly cleared from the blood pool andwithin 30 min %ID/ml was less than 0.001, as shown inFig. 5. After the first PET scan, plasma values were higherthan those of whole blood, but after the second scan andonwards whole blood values were higher. No radiolabelledmetabolites were detected in plasma, with the HPLCchromatogram showing a single peak due to [11C]docetaxelitself. Recovery of radioactivity in the HPLC analysis was94±5%.

Safety

Patients did not report any side effect or discomfort afterthe [11C]docetaxel injection and during the imagingprocedure.

Radiation dosimetry

Table 1 summarizes average organ residence times calcu-lated from the whole-body images of the seven patients.Organ absorbed dose estimates are displayed in Table 2.Estimated radiation absorbed doses were highest in liverand gall bladder wall at 35.2±6.6 and 34.6±9.9 μGy/MBq,respectively. Based on these results, the mean effective dosefor [11C]docetaxel was estimated at 4.7±0.2 μSv/MBq.

Tumour uptake

[11C]docetaxel uptake was observed in tumours. Figure 6shows a patient with [11C]docetaxel uptake in a mediastinalmetastasis of a malignant pleural mesothelioma. In eachpatient, one tumour was selected for further analysis,consisting of primary NSCLC (n=3), mediastinal lymph

Fig. 4 Decay-corrected TACs of [11C]docetaxel (%ID versus time p.i.) (n=7) in a liver, b ULI and gall bladder, c brain, lung, heart contents andmyocardial wall, and d urinary bladder, spleen, kidney and red marrow. Vertical bars indicate standard deviation


73

node metastasis of NSCLC (n=1), supraclavicular lymphnode metastasis of NSCLC (n=1), mediastinal lymph nodemetastasis of malignant pleural mesothelioma (n=1) andlung metastasis of prostate cancer (n=1).The TACs forthese seven tumours are shown in Fig. 7. The highestmeasured SUVmax was 5.1.

Discussion

In the present study, the biodistribution of [11C]docetaxelwas measured in seven patients with metastatic solidtumours using whole-body PET/CT scans, and radiationabsorbed doses were estimated. The LD-CT scan was of additional value to identify organs with low [11C]docetaxel

uptake. Uptake of [11C]docetaxel appeared to be highest ingall bladder and liver, whilst uptake in normal lung andbrain was very low. Furthermore, [11C]docetaxel uptake intumours was moderate and highly variable betweendifferent tumours. The results of the present study showedpromising biodistribution and radiation dosimetry of [11C]docetaxel. For a typical administration of 370 MBq [11C]docetaxel, the estimated dose is 1.7 mSv, which is withinthe 1–10 mSv range of effective doses that are acceptablefor volunteers in biomedical research [17]. The tracer wasrapidly cleared from the blood pool which resulted inimages of high quality and reliable statistics for quantifica-tion. The main route of elimination of the tracer was thehepatobiliary pathway which contributed to a relativelyhigh radiation burden to gall bladder and liver. During thesuccessive PET scans, extensive hepatic uptake andsubsequent excretion into gall bladder and intestine wereobserved (Fig. 3). The SUVmean of [11C]docetaxel washighest in gall bladder, which is also the dose-limiting organfor [11C]docetaxel. For an administration of 370 MBq, the

Fig. 5 Decay-corrected TACs of [11C]docetaxel (%ID/ml versus timep.i.) in plasma and whole blood

Table 2 Radiation absorbed dose estimates for [11C]docetaxel

Target organ μGy/MBq (mean±SD)

Adrenals 4.1±0.2

Brain 0.5±0.1

Breast 1.6±0.1

Gall bladder wall 34.6±9.9

Lower large intestine wall 2.1±0.3

Small intestine 9.5±3.8

Stomach 2.6±0.1

Upper large intestine wall 5.1±1.2

Heart wall 6.0±1.0

Kidney 10.7±1.5

Liver 35.2±6.6

Lung 4.1±1.0

Muscle 1.9±0.2

Ovary 2.4±0.3

Pancreas 4.0±0.1

Red marrow 3.2±0.2

Bone surface 3.1±0.3

Skin 1.3±0.2

Spleen 7.4±2.3

Testis 1.3±0.3

Thymus 1.8±0.2

Thyroid 1.4±0.3

Urinary bladder wall 3.1±1.1

Uterus 2.3±0.3

Total body 2.9±0.0

Effective dose (μSv/MBq) 4.7±0.2

Table 1 Average (± SD) organ residence times for [11C]docetaxeluptake (n=7)

Organ Organ residence time (h)

Brain 0.0008±0.0003

Gall bladder 0.0124±0.0045

Small intestine 0.0243±0.0133

Upper large intestine 0.0029±0.0016

Lower large intestine 0.0001±0.0001

Heart contents 0.0046±0.0016

Heart wall 0.0032±0.0006

Kidney 0.0085±0.0016

Liver 0.2047±0.0401

Lung 0.0095±0.0038

Red marrow 0.0128±0.0018

Spleen 0.0041±0.0015

Urinary bladder 0.0023±0.0015

Remainder of body 0.2002±0.0421


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absorbed dose to the gall bladder wall is 12.8±3.7 mGy.This equals 26% of the maximum allowed dose of 50 mGyto a single organ for a single administration to an adultresearch subject [18]. The high liver uptake of [11C]docetaxel suggests extensive metabolism of the tracer. Thefact that no radioactive metabolites were measured in plasmashows that if radioactive metabolites are produced, none ofthese enter the bloodstream during the course of the PETscan and, consequently, none are transported to tumours. Infact, radioactivity was nearly completely cleared fromplasma within the first 20 min. This does not rule out thepresence of re-circulating non-radiolabelled metabolites inplasma, as has been observed in earlier studies withtherapeutic doses of cold docetaxel [19].

Uptake in all organs except gall bladder and ULI reached aplateau within 10 min after injection, after which %IDremained nearly constant during the rest of the scan. Therefore,

further clearance according to physical decay only appears tobe a valid assumption. During the fourth PET scan (∼60 minafter injection), uptake in gall bladder and ULI was stillincreasing, indicating that the absorbed dose of [11C]docetaxelin gall bladder and intestine might be underestimated. In thepatient who underwent a fifth whole-body scan, however, gallbladder and ULI uptake decreased rapidly during the lastscan. Inclusion of this fifth scan resulted in a decreasedeffective dose (4.0 vs 4.1 mSv/MBq), although giving a smallincrease in absorbed dose to the gall bladder (Fig. 8). Thisindicates that exponential extrapolation according to physicaldecay after the fourth measurement yields conservativeeffective dose values. The use of more and faster whole-body scans within the first hour after injection, as has beenpublished for similar studies with other tracers [20, 21],would not have led to major differences in the results becauseof the near constant uptake in most organs.

Fig. 7 Decay-corrected TACs of [11C]docetaxel for seven differenttumours (SUVmax versus time p.i.) including mediastinal metastasis ofmalignant pleural mesothelioma (a), metastasis of NSCLC (b, d),primary tumour of NSCLC (c, e, f) and lung metastasis of prostatecancer (g)

Fig. 6 PET/CT images of [11C]docetaxel in a 71-year-old male patient with metastatic malignant pleural mesothelioma. Mediastinal metastasis(arrow) on CT scan (a) with [11C]docetaxel uptake on PET scan (b) and on PET/CT fusion image (c)

Fig. 8 Total activity (non-decay-corrected) in gall bladder in a singlepatient who underwent an additional fifth whole-body scan. Solid linesshow the interpolated data from which the trapezoidal integral wascomputed, assuming physical decay after the fourth whole-body scan,whereas dashed lines show the integral after inclusion of the fifthwhole-body scan


75

As most anticancer agents are eliminated by liver,extensive hepatic clearance and subsequent excretion intothe gall bladder and intestine may also be expected forother radiolabelled anticancer drugs. Due to the resultinghigh background and low contrast in the abdomen, thevalue of these radiolabelled anticancer drugs for tumours inthe abdominal and pelvic region may be limited.

Paclitaxel, another taxane, has been radiolabelled with18F [22, 23]. To our knowledge, the radiation absorbed doseof [18F]fluoropaclitaxel has not been reported yet. Limiteddata on the biodistribution of [18F]fluoropaclitaxel inhumans [24], however, appeared to be comparable withthe present biodistribution data of [11C]docetaxel. Follow-ing intravenous administration of [18F]fluoropaclitaxel,PET scans were performed in three healthy volunteers.High [18F]fluoropaclitaxel uptake was observed in liver,gall bladder and intestine, whilst uptake in brain and lungappeared to be low. Seventy-five minutes after injection,[18F]fluoropaclitaxel had been cleared from liver andsubsequently excreted into intestine. When comparingbiodistribution and pharmacokinetics of [18F]fluoropacli-taxel and [11C]docetaxel, it is important to realize that thechemical structure of [11C]docetaxel is identical to that ofclinically used, non-labelled docetaxel, whilst [18F]fluoro-paclitaxel is not identical to paclitaxel itself [22]. Introduc-tion of a fluoride atom into the paclitaxel moleculeeffectively creates a different chemical structure and mayresult in a molecule with different pharmacokinetic andpharmacodynamic characteristics as compared to thepaclitaxel molecule that is usually administered for thetreatment of patients.

The present biodistribution results for [11C]docetaxel arein line with three clinical observations in cancer patientswho are treated with docetaxel. First, the extensive hepaticclearance of [11C]docetaxel indicates that caution iswarranted when treating patients with liver dysfunction.Indeed, in patients with clinical chemistry findings sugges-tive of mild to moderate liver function impairment [SGOTand/or SGPT > 1.5 × upper limit of normal (ULN),concomitant with alkaline phosphatase > 2.5 × ULN], totalbody clearance of the drug docetaxel is known to belowered significantly. Second, [11C]docetaxel uptake inbone marrow may mirror neutropenia, which was the dose-limiting toxicity in previous phase I clinical trials ofdocetaxel [25]. Third, [11C]docetaxel uptake in brain waslow. The blood-brain barrier is likely to be the major causeof this poor uptake. An important component of the blood-brain barrier is Pgp [26, 27], which acts as a drug effluxpump and for which docetaxel is a substrate [28]. This isreflected by the limited efficacy of systemic treatment withdocetaxel for tumours or metastases in the brain [29]. Inaddition, Pgp-mediated efflux in the blood-testis barrier isknown to maintain low drug concentrations in the testis

[30]. Indeed, visual inspection of the [11C]docetaxel PETimages did not reveal any [11C]docetaxel uptake in thetesticular region, indicating that [11C]docetaxel uptake inthe testis is probably low.

Although not the primary aim of this study, [11C]docetaxel uptake was also measured in tumours. Tumouruptake was highly variable, which may mirror differentialsensitivity of tumours to docetaxel treatment. Studies withother radiolabelled anticancer agents such as [18F]5-fluorouracil (FU) and [18F]fluorotamoxifen [2] have shownthat higher uptake of these radiolabelled agents in tumoursappeared to be related to better tumour response. Radio-labelled anticancer agents could potentially predict treatmentoutcome and may contribute to individualized treatmentplanning. As patients in the present study were not scheduledto undergo docetaxel treatment, further studies are warrantedto investigate whether tumour uptake of [11C]docetaxel ispredictive of outcome of docetaxel therapy. As backgrounduptake of [11C]docetaxel in the chest is low, it may be auseful tracer to predict docetaxel efficacy for tumours in thethoracic region, such as lung and breast cancer.

Conclusion

The highest uptake of [11C]docetaxel was measured in gallbladder and liver, whilst uptake in brain and lung was verylow. Administration of [11C]docetaxel was safe with a meaneffective dose of 4.7 μSv/MBq. [11C]docetaxel uptake intumours was moderate and highly variable betweendifferent tumours.

Acknowledgements The authors would like to thank Suzette vanBalen, Amina Elouahmani, Judith van Es, Femke Jongsma, RobKoopmans, Nassearah Sais and Annemiek Stiekema for scanning thepatients, Henri Greuter, Kevin Takkenkamp and Robert Schuit foranalysing the blood samples and Natasja Kok, Ilona Pomstra and Atievan Wijk for help with logistic planning and patient care.

Conflicts of interest None.

Open Access This article is distributed under the terms of theCreative Commons Attribution Noncommercial License which per-mits any noncommercial use, distribution, and reproduction in anymedium, provided the original author(s) and source are credited.

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Chapter 6

Absolute quantification of [11C]docetaxel kinetics in lung cancer patients using positron

emission tomography

Astrid A.M. van der Veldt, Mark Lubberink, Henri N.J.M. Greuter, Emile F.I. Comans, Gerarda J.M. Herder, Maqsood Yaqub, Robert C. Schuit, Arthur van Lingen,

S. Nafees Rizvi, Martien P. Mooijer, Anneloes Y. Rijnders, Albert D. Windhorst, Egbert F. Smit, N. Harry Hendrikse, Adriaan A. Lammertsma

Clin Cancer Res 2011;17:4814-24.

Imaging, Diagnosis, Prognosis

Absolute Quantification of [11C]docetaxel Kinetics in Lung CancerPatients Using Positron Emission Tomography

Astrid A.M. van der Veldt1, Mark Lubberink1, Henri N. Greuter1, Emile F.I. Comans1, Gerarda J.M. Herder4,Maqsood Yaqub1, Robert C. Schuit1, Arthur van Lingen1, S. Nafees Rizvi1, Martien P.J. Mooijer1,Anneloes Y. Rijnders1, Albert D. Windhorst1, Egbert F. Smit2, N. Harry Hendrikse1,3, and Adriaan A. Lammertsma1

AbstractPurpose: Tumor resistance to docetaxel may be associated with reduced drug concentrations in tumor

tissue. Positron emission tomography (PET) allows for quantification of radiolabeled docetaxel

([11C]docetaxel) kinetics and might be useful for predicting response to therapy. The primary objective

was to evaluate the feasibility of quantitative [11C]docetaxel PET scans in lung cancer patients. The

secondary objective was to investigate whether [11C]docetaxel kinetics were associated with tumor

perfusion, tumor size, and dexamethasone administration.

Experimental Design: Thirty-four lung cancer patients underwent dynamic PET–computed tomogra-

phy (CT) scans using [11C]docetaxel. Blood flow was measured using oxygen-15 labeled water. The first 24

patients were premedicated with dexamethasone. For quantification of [11C]docetaxel kinetics, the optimal

tracer kinetic model was developed and a noninvasive procedure was validated.

Results: Reproducible quantification of [11C]docetaxel kinetics in tumors was possible using a non-

invasive approach (image derived input function). Thirty-two lesions (size �4 cm3) were identified, having

a variable net influx rate of [11C]docetaxel (range, 0.0023–0.0229mL�cm�3�min�1). [11C]docetaxel uptake

was highly related to tumor perfusion (Spearman’s r ¼ 0.815; P < 0.001), but not to tumor size

(Spearman’s r ¼ �0.140; P ¼ 0.446). Patients pretreated with dexamethasone showed lower

[11C]docetaxel uptake in tumors (P ¼ 0.013). Finally, in a subgroup of patients who subsequently received

docetaxel therapy, relative high [11C]docetaxel uptake was related with improved tumor response.

Conclusions: Quantification of [11C]docetaxel kinetics in lung cancer was feasible in a clinical setting.

Variable [11C]docetaxel kinetics in tumors may reflect differential sensitivity to docetaxel therapy. Our

findings warrant further studies investigating the predictive value of [11C]docetaxel uptake and the effects

of comedication on [11C]docetaxel kinetics in tumors. Clin Cancer Res; 17(14); 4814–24. �2011 AACR.

Introduction

Docetaxel belongs to the family of taxanes, a class of drugsthat binds to microtubules and subsequently induces cell

cycle arrest and apoptosis (1). Docetaxel is widely used forsystemic therapy of several solid malignancies, includinglung cancer (2). However, clinical failure of docetaxel ther-apy remains a major problem, and often patients are sub-jected to therapy-related toxicity without gaining benefit. Asresponse to anticancer drugs is, at least in part, thought todepend on achieving sufficient drug levels in tumor tissue,assessment of docetaxel uptake in tumors in vivo may beuseful to understand treatment failure in patients.

To this end, docetaxel was labeled with the short-livedpositron emitting radionuclide carbon-11, resulting in[11C]docetaxel with an identical molecular structure asthe drug docetaxel itself (3, 4). Using [11C]docetaxel andpositron emission tomography (PET), microdosing studiescan be carried out to monitor pharmacokinetics and phar-macodynamics of docetaxel noninvasively in patients. In aprevious safety study, [11C]docetaxel showed high accu-mulation in liver (5, 6), whereas concentrations in the chestwere low (6). These biodistribution data indicate that[11C]docetaxel may be a suitable PET tracer for measuringdocetaxel kinetics in thoracic tumors.

Authors' Affiliations: 1Department of Nuclear Medicine & PET Research,2Department of Pulmonology, 3Department of Clinical Pharmacology &Pharmacy, VU University Medical Center, Amsterdam, The Netherlands;and 4Department of Pulmonology, St Antonius Hospital, Nieuwegein, TheNetherlands

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

This study was partly presented at the 2010 ASCO Annual Meeting,Chicago, Illinois, June 4–8, 2010, #2543; at the SNM Annual Meeting,Salt Lake City, Utah, June 5–9, 2010, #449; and at the 22nd EORTC-NCI-AACR symposium, Berlin, November 16–19, 2010, #576.

Corresponding Author: A.A.M. van der Veldt, VU University MedicalCenter, Department of Nuclear Medicine & PET Research, P.O. Box7057, 1007 MB Amsterdam, The Netherlands. Phone: þ 31 20 4444214; Fax: þ 31 20 444 3090; E-mail: [email protected]

doi: 10.1158/1078-0432.CCR-10-2933

�2011 American Association for Cancer Research.

ClinicalCancer

Research

Clin Cancer Res; 17(14) July 15, 20114814


Published OnlineFirst July 17, 2011; DOI:10.1158/1078-0432.CCR-10-2933

81

To assess whether a microdose [11C]docetaxel scan canbe used to predict response to docetaxel therapy, quanti-fication of [11C]docetaxel uptake in tumor tissue is needed.This, in turn, requires the development of a tracer kineticmodel, describing tumor [11C]docetaxel kinetics in relationto the time course in arterial plasma (delivery). Arterialblood sampling, however, is less suited for routine clinicalstudies. Dynamic PET scans of the chest provide the pos-sibility to noninvasively generate an image derived inputfunction (IDIF) based on the time course in, for example,the ascending aorta. As the accuracy of an ascending aortaIDIF depends on the biodistribution of a tracer, this pro-cedure needs to be validated also for [11C]docetaxel.Uptake of docetaxel in a tumor depends, at least in

part, on its delivery through the circulation, which maybe regulated by both drug exposure and tumor perfu-sion. Docetaxel exposure is reflected by clearance of[11C]docetaxel from blood. Tumor perfusion can be mea-sured using oxygen-15 labeled water ([15O]H2O), which isa freely diffusible PET tracer (7). Tumor size may also affectdocetaxel delivery, as central necrotic areas with reducedtumor perfusion may develop with increasing tumorsize (8).In addition, efflux pumpsmay affect the concentration of

radiolabeled drugs in tumors. Docetaxel is a substrate forthe efflux transporter ABCB1 (formerly known as P-glyco-protein or MDR1; ref. 9). In this respect, the glucocorticoiddexamethasone, which is given as standard premedicationto prevent several docetaxel-induced toxicities (10, 11), isof particular interest, because dexamethasone is a potentinducer of this efflux transporter (12). Accordingly, pre-medication with dexamethasone may affect docetaxelkinetics in tumors.The primary objective of the present study was to eval-

uate the feasibility of quantitative PET studies with[11C]docetaxel in patients with lung cancer. As mentionedabove, this required development of the optimal tracer

kinetic model for quantification of [11C]docetaxel kineticsin lung cancer patients and validation of the use of anoninvasive procedure to enable implementation in rou-tine clinical practice. The secondary objective was toexplore whether [11C]docetaxel kinetics were associatedwith tumor perfusion, tumor size, and administration ofpremedication with dexamethasone. Finally, as a limitednumber of patients were actually scheduled for docetaxeltherapy, a preliminary assessment of the relationshipbetween [11C]docetaxel uptake and response to docetaxeltherapy was possible.

Patients and Methods

PatientsThirty-four patients (23 males and 11 females; median

age 62 years; range 32–74 years) with advanced-stagecancer were prospectively enrolled prior to planned sys-temic therapy. Thirty-two patients were diagnosed withnon-small cell lung cancer and two with malignantmesothelioma. Criteria for enrollment in the study were18 years of age or older, a malignant lesion of at least1.5 cm in diameter within the chest, life expectancy of atleast 12 weeks, Karnofsky performance status scale >60%,thrombocyte count >100 � 109�L�1, and hemoglobin >6.0mmol�L�1. Exclusion criteria included previous treatmentwith taxanes, claustrophobia, pregnancy or lactation, metalimplants (e.g., pacemakers), use of coumarin derivatives orinhibitors of thrombocyte aggregation, use of inhibitors orsubstrates of the efflux transporter ABCB1, concurrenttreatment with experimental drugs, and participation ina clinical trial with any investigational drug within 30 daysprior to study entry. When patients were scheduled fordocetaxel therapy, computed tomography (CT) scans werecarried out at baseline and every cycle or every two cycles oftreatment to assess clinical response according to ResponseEvaluation Criteria in Solid Tumors (RECIST) version 1.1(13). The study was approved by the Medical Ethics ReviewCommittee of the VU University Medical Center. Prior toinclusion, each patient signed a protocol-specific informedconsent.

Synthesis of radiopharmaceuticals[15O]H2O and [11C]docetaxel were synthesized accord-

ing to Good Manufacturing Practice (GMP) standards asdescribed previously (3, 4, 14). Docetaxel was obtainedfrom Green PlantChem Company Ltd., which was used tosynthesize the precursor of [11C]docetaxel. [11C]docetaxelitself was produced with a decay-corrected overall radio-chemical yield of 10 � 1% prior to purification. Themedian specific activity at time of injection was 2.0GBq�mmol�1 (range: 1.0–37.3 GBq�mmol�1).

Scanning protocolStudies were conducted on a Gemini TF-64 PET-CT

scanner (Philips Medical Systems; ref. 15). This scannerhas an axial field of view of 18 cm, divided into 45contiguous planes. All patients underwent a dynamic

Translational Relevance

Docetaxel is an effective drug for the treatment ofpatients with several advanced malignancies includingbreast cancer, prostate cancer, and lung cancer. How-ever, a number of patients will not benefit from doc-etaxel therapy. Tumor resistance to docetaxel may beassociated with reduced drug concentrations in tumortissue. Positron emission tomography (PET) is a non-invasive technique that can be used to quantify kineticsof radiolabeled docetaxel ([11C]docetaxel) in tumors.The present study shows the feasibility and potentialclinical relevance of quantitative [11C]docetaxel PETstudies in patients with lung cancer. In the future,microdosing studies using [11C]docetaxel may be usedto predict benefit from docetaxel in individual patients.In addition, PET imaging with [11C]docetaxel may beuseful for evaluating effects of other drugs on docetaxeldelivery to tumors and to optimize drug scheduling.

Quantification of [11C]docetaxel Kinetics in Lung Cancer

www.aacrjournals.org Clin Cancer Res; 17(14) July 15, 2011 4815



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[11C]docetaxel PET–CT scan. Eight patients underwent asecond [11C]docetaxel scan to assess test–retest reproduci-bility of measurements. The second [11C]docetaxel scanwas carried out approximately 4 hours after the first.Twenty-eight patients underwent an additional PET scanusing [15O]H2O to measure tumor perfusion.

Patients were asked to fast from midnight before scan-ning. A light breakfast at 08.00 hours or a light lunch at12.00 hours, and water and tea were allowed until PETscanning. In the first 24 patients, dexamethasone (8 mgp.o.) was given to prevent potential allergic reactions. Asnone of these patients did experience any side-effects, theMedical Ethics Review Committee allowed dexamethasoneadministration to be discarded in subsequent patients.

All patients received two venous catheters, one for tracerinjection, the other for blood sampling. In addition, 17patients received an indwelling radial artery catheter forarterial blood sampling during the dynamic [11C]docetaxelscan. Patients were positioned supine on the scanner bedwith both tumor and aortic arch located inside the axialfield of view of the scanner. Elastic body-restraining ban-dages were used to minimize movement during scanning.

Following a 50 mAs low-dose CT scan for attenuationcorrection, a 10 minutes dynamic scan was started simul-taneously with an intravenous injection of 370 MBq[15O]H2O (5 mL at a rate of 0.8 mL�s�1), followed by a35mL saline flush (rate 2 mL�s�1). At least 20minutes afteradministration of [15O]H2O, which has a half-life of 2minutes, a 60-minute dynamic scan was started simulta-neously with an intravenous injection of [11C]docetaxel(median dose 335 MBq; range 133–385 MBq; dissolvedin a maximum volume of 12 mL saline, at a rate of0.8 mL�s�1), followed by 35 mL saline (rate 2 mL�s�1).

Data were normalized and all appropriate correctionswere applied for dead time, decay, randoms, scatter, andattenuation. Using the 3-dimensional row action maxi-mum likelihood reconstruction algorithm (3D RAMLA),[15O]H2O and [11C]docetaxel scans were reconstructedinto 26 (1 � 10, 8 � 5, 4 � 10, 2 � 15, 3 � 20, 2 �30, and 6 � 60 s) and 36 (1 � 10, 8 � 5, 4 � 10, 2 � 15, 3 �20, 2� 30, 6� 60, 4� 150, 4� 300, and 2� 600 s) frames,respectively.

Blood samplingIn the first 17 patients, arterial blood sampling was

carried out during [11C]docetaxel scanning.Using an onlinedetection system (16), arterial blood was withdrawn con-tinuously at a rate of 5 mL�min�1 during the first 5 minutesand 1.7 mL�min�1 thereafter. Twenty-nine minutes afterinjection, online sampling was discontinued to minimizethe total amount of blood to be taken. In addition, both10mL arterial and venous samples were collectedmanuallyat 2.5, 5, 10, 15, 20, 30, 40, and 60 minutes postinjection.Prior to each sample, 3–5 mL blood was discarded andthe line was flushed with 2 mL saline after each sample.Blood samples were analyzed for blood and plasma con-centrations and potential radiolabeled metabolites of[11C]docetaxel as described in the Supplementary Data.

Input functionsBlood sampler data of [11C]docetaxel were corrected for

delay relative to the time-activity curve of the ascendingaorta. The resulting delay-corrected sampler curve wascalibrated using the manually drawn arterial blood sam-ples. Plasma/whole blood ratios derived from the manualblood samples were fitted to a sigmoid function. Finally,the blood sampler input function (BSIF) was obtained bymultiplying the delay-corrected and calibrated samplercurve with this sigmoid function.

IDIFs were derived for both [15O]H2O and[11C]docetaxel scans. An IDIF of the ascending aorta hasbeen validated for several PET tracers including [15O]H2O(17) and it is considered to be a noninvasive alternative toarterial sampling. Hence, volumes of interest (VOI) of 1 cmdiameter were drawn over the ascending aorta in approxi-mately 10 consecutive image planes of the frame in whichthe first pass of the bolus was best visualized. Projection ofthese VOIs onto all image frames yielded the arterial time-activity curve CA(t). A similar approach was used for rightventricular cavity and pulmonary artery, thereby providinga time-activity curve for the pulmonary circulation CV(t)(17). For [11C]docetaxel, the plasma IDIF was obtained bymultiplying CA(t) with a sigmoid function describing theplasma/whole blood ratio over time. The correction forplasma/whole blood ratio was based on either arterial orvenous sampling.

Delineation of tumorsTumors were defined on the low-dose CT scans by an

experienced nuclear medicine physician (E.F.C.) who wasblinded to patients’ history and outcome. To this end, alllow-dose CT images were converted to ECAT 7 formatand tumor VOIs were drawn using the CAPP softwarepackage (CTI/Siemens). Finally, these VOIs were pro-jected onto the dynamic images of the corresponding[15O]H2O and [11C]docetaxel scans, thereby generat-ing tumor time-activity curves for [15O]H2O and[11C]docetaxel.

Analysis of tumor perfusionKinetic analysis of data was carried out using dedicated

programs written within the software environmentMatlab (The MathWorks Inc.). The standard single-tissuecompartment model was used to derive tumor perfusionfrom [15O]H2O kinetics, applying corrections for botharterial and pulmonary artery blood volume (18):

CTðtÞ ¼ ð1 � VA � V V Þ � F � CAðtÞ � e� F

VTt

þ VACAðtÞ þ V V CV ðtÞ

where CT(t) represents measured tissue [15O]H2O con-centration as function of time, F perfusion, VA arterialblood volume, VV pulmonary circulation blood volume,and VT the volume of distribution or partition coefficientof water.

Using nonlinear regression, tumor time-activity curveswere fitted to this single-tissue compartment model using

van der Veldt et al.

Clin Cancer Res; 17(14) July 15, 2011 Clinical Cancer Research4816



83

IDIF as arterial input function (17). The correction forpulmonary circulation blood volume was included, as itimproved the quality of the fits without affecting tumorperfusion values (17).

Analysis of [11C]docetaxel kinetics in tumorsTo develop a kinetic model and validate the use of a

noninvasive procedure for quantification of [11C]docetaxeldata, only lesions with a volume �4 cm3 were considered.The generated time-activity curves of arterial blood and

tumor tissue were entered into the analysis (Fig. 1). First,nonlinear regression analysis was applied to fit the tumortime-activity curves of [11C]docetaxel to a two-tissue rever-sible (4 rate constants) and a two-tissue irreversible (3 rateconstants) compartment model, both including a bloodvolume parameter and using the BSIF derived plasma inputfunction. Akaike and Schwarz criteria (19, 20) were used to

determine which model best described [11C]docetaxelkinetics in tumors.

The two-tissue compartment model (Fig. 1) describes thetotal tissue signal (CT) by the following equation:

CTðtÞ ¼ C1ðtÞ þ C2ðtÞ

where C1(t) and C2(t) are concentrations in 1st and 2ndcompartment, respectively. Kinetics in both compartmentsare given by the following differential equations:

dC1ðtÞdt

¼ K1CpðtÞ � ðk2 þ k3ÞC1ðtÞ þ k4C2ðtÞ

dC2ðtÞdt

¼ k3C1ðtÞ � k4C2ðtÞ

where CP is arterial plasma concentration, K1 the rateconstant for transport from plasma to tumor, k2 the rate

A

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rvesK

inetic m

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Figure 1. Compartmental modeling of dynamic [11C]docetaxel PET scans. A, arterial concentrations of [11C]docetaxel were obtained from arterial bloodsampling or an IDIF. For the latter, VOIs were drawn over the ascending aorta in a frame in which the first pass of the bolus was best visualized. In addition, atumor VOI was defined on the low-dose CT scan. Finally, aorta VOI and tumor VOI were projected onto the dynamic images of the corresponding[11C]docetaxel scan, thereby generating time-activity curves. B, time-activity curves of arterial blood and tumor tissue were entered into two-tissuecompartment modeling. To this end, either BSIF or IDIF was entered into the analysis as arterial input function. C, schematic diagram of a two-tissuecompartment model. The concentration (C) in the tumor consists of [11C]docetaxel in compartments 1 (C1) and 2 (C2), representing free and bound[11C]docetaxel, respectively. Kinetics of [11C]docetaxel in tumor tissue is regulated by input from plasma (CP) and four kinetic rate constants K1, k2, k3, and k4.K1 is the rate constant describing transport from plasma to tumor, k2 is the rate constant for clearance from tumor to plasma, and k3 and k4 are kineticrate constants describing exchange between the two tumor compartments. For the irreversible two-tissue compartment model k4 ¼ 0. VOI, volume ofinterest; BSIF, blood sampler derived input function; IDIF, image derived input function.





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constant for clearance from tumor to plasma, and k3 and k4kinetic rate constants describing exchange between 1st and2nd compartment.

For the irreversible two-tissue compartment model, k4 is0. In this case the net influx rate constant Ki can becalculated:

Ki ¼ K1 � k3k2 þ k3�

In case of irreversible uptake, both robustness and sim-plicity of the Ki estimation can be improved by using thePatlak method (21). The Patlak plot is a linearization of thecompartmental equations, and is given by:

CTðtÞCpðtÞ ¼ Ki �

Ð t0 CpðtÞ � dt

CpðtÞ þ V0;

where the intercept V0 represents the initial volume ofdistribution. Ki is now given by the slope of the linear partof the curve.

The schematic diagram in Supplementary Fig. S1 illus-trates the various steps that were carried out to develop asimplified procedure suitable for clinical implementation of[11C]docetaxel studies. After validation of a simplifiedkinetic analysis (i.e., Patlak analysis), use of IDIF was com-paredwithuseofBSIF.Next, theuseofdiscrete venous ratherthan arterial samples to correct IDIF for the time course ofthe plasma/whole blood ratio was investigated. Finally, theleast invasive procedure was used to determine test–retestvariability of [11C]docetaxel quantification in tumors.

[11C]docetaxel clearanceTo determine the effect of dexamethasone on blood

kinetics of [11C]docetaxel, the clearance of [11C]docetaxelwas calculated using the following equation:

Clearance ¼ DÐCpðtÞ � dt � BSA

where the injected does (D) of [11C]docetaxel is divided bythe integral of the plasma time-activity curve multiplied bythe body-surface area (BSA).

StatisticsStatistical analysis was carried out using SPSS software

(SPSS for Windows 16.0, SPSS, Inc.). Correlations wereexplored using the Spearman’s correlation coefficient. Levelof agreement was assessed using the intraclass correlationcoefficient with a 2-way randommodel and Bland–Altmananalysis (22). TheMann–Whitney test was used to comparebetween groups.

Results

[11C]docetaxel kinetics in bloodInitially, the plasma/whole blood ratio was >1, but it

rapidly decreased to values <1 from 15 minutes onward(Supplementary Fig. S2A). There was high correlationbetween plasma/whole blood ratios obtained from arterialand venous sampling (Spearman’s r ¼ 0.970; P < 0.001;n ¼ 169). In all patients, there was rapid systemic clearance

A B C10

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kBq.

mL–1

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40 60

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/CP

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ivity

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q.m

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Figure 2. A, PET image of[11C]docetaxel uptake at 10–60minutes post injection showing amediastinal metastasis withincreased [11C]docetaxel uptake(arrow). B, corresponding CTimage. C, PET-CT fusion image.D, representative time-activitycurve in the corresponding tumor.E, Patlak-plot of [11C]docetaxel inthe corresponding tumor. Ki, netinflux rate constant; CT, measuredPET activity in tumor; CP,measured plasma activity inarterial blood.





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of radioactivity from blood (Supplementary Fig. S2B). Thisprecluded reliable high performance liquid chromatogra-phy (HPLC) measurements of radiolabeled metabolites of[11C]docetaxel beyond 15 minutes after injection. Over thefirst 15 minutes, HPLC chromatograms did not reveal anyradiolabeled metabolites and no radioactivity was mea-sured in the solid-phase-extraction-rinsing fraction. Due tothis rapid clearance of [11C]docetaxel, calibration of theBSIF was not reliable at time points > 10 minutes afterinjection. Therefore, only the first 10 minutes of data wereused for further analysis.

Quantification of [11C]docetaxel kinetics in tumors[11C]docetaxel accumulated in lung cancer lesions

(Fig. 2). Fig. 2D shows a representative time-activity curveof [11C]docetaxel in lung cancer. In the 17 patients whounderwent arterial blood sampling, a total of 15 lesionshad a volume �4 cm3. As a result, 15 lesions were eligiblefor validation of a simplified method for the analysis of[11C]docetaxel PET/CT scans. According to both Akaikeand Schwarz criteria, the irreversible two-tissue compart-ment model was the kinetic model of choice for 14 out of15 lesions.The irreversible behavior of [11C]docetaxel kinetics was

confirmed by Patlak plots, which became linear soonafter injection (Fig. 2E). The Patlak method showed themost robust values for Ki, whereas the individual micro-parameters K1, k2, and k3 showed relative large standarderrors, which are due to noise levels of tissue tracerkinetics.

Validation of a less invasive procedurePatlak andnonlinear regression analyses of [11C]docetaxel

data produced comparable Ki values (Spearman’s r ¼ 0.979;P < 0.001; Fig. 3A). Therefore, the more robust and fasterPatlak method was used in further analyses. Although Ki

valueswere lower for ascendingaortaderived IDIF than thosefor corresponding BSIF (Fig. 3B), correlation betweenboth sets of Ki values was high (Spearman’s r ¼ 0.946;P < 0.001). Use of venous and arterial samples to correctIDIF for plasma/whole blood ratios resulted in comparableKi values (Spearman’s r¼ 0.986; P < 0.001; Fig. 3C). Accord-ing to the Patlak method, the median Ki valueswere 0.011 mL�cm�3�min�1 (range, 0.003–0.024mL�cm�3�min�1), 0.008 mL�cm�3�min�1 (range, 0.003–0.019 mL�cm�3�min�1), and 0.008 mL�cm�3�min�1 (range,0.003–0.021 mL�cm�3�min�1) for BSIF, IDIF using arterialsamples and IDIF using venous samples, respectively.Finally, using IDIF (with plasma/whole blood correc-

tions based on venous samples) in the test–retest analysisshowed good reproducibility for Ki (Fig. 3D) with anintraclass correlation coefficient of 0.952 (95% confidenceinterval: 0.781–0.990), an absolute repeatability coefficientof 0.003 mL�cm�3�min�1 and a relative repeatability coef-ficient of 29%. These results indicate that an IDIF, togetherwith venous blood samples, could be used as a noninvasivearterial input function. Consequently, arterial samplingcould be discarded in the following patients. Finally,

venous samples were used to quantify tumor uptake of[11C]docetaxel in all 34 patients.

Correlation with tumor perfusionIn the 28 patients who underwent an additional PET scan

with [15O]H2O, a total of 27 lesions (20 primary tumorsand 7 metastases) with a size �4 cm3 could be defined onthe low-dose CT scan. In these lesions, tumor perfusion wasvariable with a median perfusion of 0.281 mL�cm�3�min�1

(range, 0.052–0.904 mL�cm�3�min�1). A significant asso-ciation between Ki of [

11C]docetaxel and tumor perfusionwas found (Spearman’s r ¼ 0.815; P < 0.001; Fig. 4).

Correlation with tumor sizeOverall, 32 lesions (22 primary tumors and 10 metas-

tases) could be identified on the corresponding low-doseCT scans. In these lesions, the Ki of [11C]docetaxel wasvariable (range, 0.0023–0.0229 mL�cm�3�min�1) with amedian Ki of 0.0092 mL�cm�3�min�1. Although the sizeof the lesions was highly variable (median size, 20 cm3;range, 5–485 cm3), therewas no association between tumor

A B

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Figure 3. Plots showing the essential results of the subsequent validationsteps indicated in Supplementary Fig. S1. A, Spearman's correlationbetween Patlak derived Ki and NLR derived Ki with plasma input functionobtained from BSIF. B, Spearman's correlation between IDIF derived Ki

and BSIF derived Ki; in both cases Ki was calculated using the Patlakmethod and arterial samples were used to correct the input function forchanging plasma/whole blood ratios. C, Spearman's correlation betweenPatlak derived Ki using venous samples and Patlak derived Ki using arterialsamples, where IDIF was corrected for changing plasma/whole bloodratios using either arterial samples or venous samples. D, Bland–Altmanplot of Patlak derived Ki test–retest data, where IDIF was corrected forchanging plasma/whole blood ratios using venous samples. Dotted linesrepresent �1.96 � SD values. Ki, net influx rate constant; NLR, nonlinearregression; r, Spearman's correlation coefficient; P, P-value; IDIF, imagederived input function; BSIF, blood sampler input function; art, arterialsamples; ven, venous samples; solid lines (A–C) represent linear fitsthrough the data points; mean Ki, mean Ki of test and retest scans;D Ki, absolute difference in Ki between test and retest scans.





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size and Ki of [11C]docetaxel (Spearman’s r ¼ �0.140;P ¼ 0.446) or tumor perfusion (Spearman’s r ¼ �0.139;P ¼ 0.491).

Effects of dexamethasone on [11C]docetaxel kineticsAs premedication with dexamethasone was required in

the first 24 patients and discontinued thereafter, it waspossible to investigate potential effects of dexamethasoneadministration on [11C]docetaxel kinetics in tumors (size�4 cm3). Dexamethasone treated patients had significantlylower Ki values (median Ki, 0.0072 mL�cm�3�min�1; range,0.0023–0.0208 mL�cm�3�min�1) than patients not pre-treated with dexamethasone (median Ki, 0.0118mL�cm�3�min�1; range, 0.0051–0.0229 mL�cm�3�min�1;Mann–Whitney, P ¼ 0.013; Fig. 5A).

Althoughtumorperfusionwas somewhat lower inpatientspretreated with dexamethasone (median perfusion, 0.265mL�cm�3�min�1; range, 0.052–0.725 mL�cm�3�min�1) ascompared with patients who were not pretreated with dex-amethasone (median perfusion, 0.396 mL�cm�3�min�1;range, 0.093–0.904 mL�cm�3�min�1), this difference didnot reach statistical significance (Mann–Whitney, P ¼0.093; Fig. 5B).However, whenKiwas normalized for tumorperfusion, therewasnodifferencebetweenpatientswhowerepretreated with dexamethasone and patients who were notpretreated (Mann–Whitney, P ¼ 0.297). When analyzedseparately, the association between Ki of [11C]docetaxeland tumor perfusion still persisted in both patients treated(Spearman’s r ¼ 0.785; P ¼ 0.001) and not treated(Spearman’s r ¼ 0.552; P ¼ 0.063) with dexamethasone.Furthermore, dexamethasone administration did not affect[11C]docetaxel clearance from plasma. The median plasmaclearance during the first 10 minutes of data was 8.24

mL�s�1�m�2 (range, 6.09–12.40 mL�s�1�m�2) and 8.27mL�s�1�m�2 (range, 6.32–9.44mL�s�1�m�2) in patientswithand without dexamethasone premedication, respectively(Mann–Whitney, P ¼ 0.724; Fig. 5C).

[11C]docetaxel kinetics and clinical outcomeSeven non-small cell lung cancer patients were scheduled

for docetaxel therapy following this PET study. Three ofthose were treated simultaneously with platinum-based agents. All patients received premedication with

0.03

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Figure 4.Net influx rate constant of [11C]docetaxel versus tumor perfusion.The solid line represents the linear least squares fit through the measureddata. Ki, net influx rate constant; F, tumor perfusion; r, Spearman'scorrelation coefficient; P, P-value.

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11C]docetaxel in tumors. B, Tumorperfusion. C, Plasma clearance of [11C]docetaxel. Ki, net influx rateconstant; F, tumor perfusion; n.s. not significant.





87

dexamethasone prior to PET scanning. When smallertumors were also included, a total of 12 lesions could beidentified in the field of view of the PET scan. In theselesions, the median tumor size was 3 cm3 (range, 1–334cm3) with a median [11C]docetaxel Ki of 0.0073mL�cm�3�min�1 (range, 0.0023–0.0228 mL�cm�3�min�1).In the first evaluation, the median change in the longestdiameter of these lesions was 4% (range, �6% to 100%).The Ki of [

11C]docetaxel was negatively associated with thechange in tumor size (Spearman’s r ¼ �0.803; P ¼ 0.002).Tumors with a Ki value > 0.0073 mL�cm�3�min�1 had asignificantly better response than tumors with a lower Ki

value (Mann–Whitney, P ¼ 0.007). Figure 6 shows anexample of a patient with stable disease and anotherpatient with progressive disease. The change in tumor sizewas not significantly affected by additional treatment withplatinum-based agents (Mann–Whitney, P ¼ 0.073).

Discussion

Docetaxel is an effective drug for the treatment ofpatients with several cancers, including non-small cell lungcancer (23, 24). However, tumor resistance to docetaxeltherapy remains a major challenge. Quantitative[11C]docetaxel PET studies may provide insight in kineticsof docetaxel in tumors and therefore contribute to appro-priate selection of cancer patients for docetaxel therapy.Using a state of the art validation approach, the presentstudy shows the feasibility and reproducibility of quanti-

tative PET studies with [11C]docetaxel in patients with lungcancer. Tumor kinetics of [11C]docetaxel were irreversibleand associated with tumor perfusion. Patients pretreatedwith dexamethasone showed significantly lower[11C]docetaxel uptake in tumors, whereas no differencein [11C]docetaxel clearance was measured in these patients.In the few patients who were subsequently treated withdocetaxel, [11C]docetaxel uptake in tumors seemed to beassociated with treatment outcome.

[11C]docetaxel showed fast kinetics, reflected by therapid clearance of radioactivity from blood. Consequently,only 10 minutes of blood data could be used, as inputfunctions were not reliable at later times. In addition, 10–15 minutes after injection already more than 50% of thetotal administered activity was located in the liver. Rapidclearance of [11C]docetaxel from blood and high[11C]docetaxel uptake in liver likely reflect extensive meta-bolism of docetaxel. Nevertheless, no radiolabeled meta-bolites of [11C]docetaxel were detected, obviating the needto correct the arterial input function for radiolabeled meta-bolites. In the liver microsomes, docetaxel is metabolizedmainly by the cytochrome P450 enzyme CYP3A4 (25).Hepatic transformation and subsequent biliary excretioninto feces is known to account for �80% of the eliminationof an administered therapeutic dose (26). In addition, activeeffluxbyABCB1 in intestine andbiliary systemrepresents analternative pathway of docetaxel elimination (27).

Ki of [11C]docetaxel in lung cancer was variable andhighly related to tumor perfusion, but not to tumor size.

Figure 6. Computed tomographyimages of 2 patients withmetastatic non-small cell lungcancer who were treated withdocetaxel. A–B, example of apatient with relatively high[11C]docetaxel uptake(Ki ¼ 0.0151 mL�cm�3�min�1) inrecurrent disease (arrow), whichshowed stable disease (B) ascompared with baseline (A). C–D,example of a patient with relativelylow [11C]docetaxel uptake(Ki ¼ 0.0050 mL�cm�3�min�1) inthe primary tumor (arrow), whichshowed rapid progression withincreased atelectasis within2 months (D) as compared withbaseline (C).

A B

C D





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Tumor perfusion also was variable, which may reflectinterindividual differences in tumor vasculature. The tumorvasculature itself may also limit [11C]docetaxel delivery totumors, as it is structurally and functionally abnormal,consisting of leaky and dilated vessels that result inincreased interstitial fluid pressure and reduced drug pene-tration (28). Limited drug penetration in tumors is animportant mechanism of tumor resistance to docetaxeltherapy. A previous study in tumor xenografts showed thatdocetaxel accumulation was limited to the first �100 mmaround a blood vessel, with little drug reaching a distanceof 100 to 150 mm (29). Although a larger tumor size mayresult in reduced perfusion in the central part, consequentlyleading to lower average perfusion values, no associationsbetween tumor size and [11C]docetaxel kinetics or tumorperfusion were found.

The high correlation between tumor perfusion and[11C]docetaxel uptake suggests that tumor uptake of[11C]docetaxel primarily depends on tumor perfusion.Consequently, administration of drugs that change tumorperfusion, e.g., antiangiogenic agents, may have signifi-cant effects on docetaxel delivery to tumors, possiblyaffecting its efficacy. The methodology developed here,measuring both perfusion and docetaxel kinetics, pro-vides a noninvasive means to investigate effects of anti-angiogenic drugs on both tumor perfusion and docetaxeldelivery. This, in turn, may lead to optimized schedulingof drugs, thereby enhancing antitumor efficacy of com-bination therapy.

Next to tumor perfusion, intracellular binding of[11C]docetaxel to tubulin may determine [11C]docetaxelkinetics in tumors. The taxane docetaxel acts by binding tothe beta-tubulin subunit of the microtubules, promotingtubulin assembly into microtubules, stabilizing them, andinhibiting depolymerization to free tubulin (2). Tumor cellscan alter the tubulin isotype, thereby reducing docetaxelbinding (30) with subsequent lower Ki values of[11C]docetaxel.

Apart from those parameters that regulate uptake of[11C]docetaxel in tumor tissue, efflux from tumor cellsmay be another determinant of [11C]docetaxel kinetics,especially because docetaxel is a substrate for the drug effluxtransporter ABCB1 (9). This efflux transporter is a memberof the ATP binding cassette family and may contribute tomultidrug resistance in tumors by actively eliminating drugsfrom cancer cells (31). The lowerKi values of [

11C]docetaxelmeasured in patients treated with the ABCB1 inducer dex-amethasone may reflect the importance of ABCB1 for[11C]docetaxel kinetics in tumors. In addition, antivasculareffects of dexamethasone may contribute to the lower Ki

values of [11C]docetaxel, because dexamethasone is knownto decrease total blood volume in tumors (32). The non-significant difference in perfusion-normalized Ki valuessuggests that reduced tumor perfusion may contribute tolower [11C]docetaxel uptake in dexamethasone pretreatedpatients. Although dexamethasone potentially increases[11C]docetaxel clearance by inducingboth intestinal ABCB1(12) and CYP3A4 activity (33), dexamethasone adminis-

tration was not associated with higher [11C]docetaxelplasma clearance. As calculated Ki values of [

11C]docetaxelwere corrected for the activity in plasma, the presentexplorative analysis suggests that dexamethasonemay affect[11C]docetaxel kinetics in tumors. To date, conflictingresults have been reported on the antitumor effects ofdexamethasone in addition to docetaxel (34, 35). Becausedexamethasone is administered routinely as premedicationfor docetaxel,more studies are required to further clarify theeffects of dexamethasone and its scheduling on perfusionand docetaxel kinetics in tumors.

PET using radiolabeled anticancer drugs may be valu-able for predicting outcome prior to start of treatmentand, as such, it may be an important tool for individua-lized treatment planning. Human PET studies with radi-olabeled anticancer drugs (36), including F-18 labeled5-fluorouracil ([18F]5-FU; ref 37 and 38) and tamoxifen([18F]fluorotamoxifen; ref. 39), have shown that hightumor concentrations of the radiolabeled drug were asso-ciated with improved tumor response. Although thepresent study was not designed to predict tumor responseto docetaxel therapy, the finding in the limitednumber of docetaxel-treated patients suggests that vari-able [11C]docetaxel kinetics in tumors may reflect differ-ential sensitivity to docetaxel therapy. Ideally, onlypatients scheduled for docetaxel treatment should havebeen selected for the present study. In the present valida-tion study, however, three cannulas including one forarterial sampling were required and therefore alsopatients scheduled for other therapies were included.The noninvasive approach developed in this study nowprovides a means to investigate the relationship between[11C]docetaxel uptake and response to docetaxel treat-ment in larger cohorts of lung cancer patients and inpatients with other tumors located in the thoracic regionsuch as locally advanced breast cancer. Although micro-dosing prevents patients from drug-induced toxicitiesassociated with therapeutic doses, it has potential limita-tions, as the kinetic behavior of tracer and therapeuticdoses differ. Therefore, further PET studies using[11C]docetaxel during docetaxel therapy are also neededto assess whether tumor kinetics are dose dependent.

In conclusion, full quantification of [11C]docetaxelkinetics in lung cancer patients using a noninvasivePET based approach is feasible. Tumor kinetics of[11C]docetaxel were highly variable and strongly relatedto tumor perfusion. In addition, uptake of [11C]docetaxelin tumors was reduced in patients pretreated with dexa-methasone. Variable [11C]docetaxel kinetics in tumors mayreflect differential sensitivity to docetaxel therapy. Thefindings of this study warrant further clinical studies inves-tigating the predictive value of initial [11C]docetaxel uptakeand the effects of comedication on docetaxel kinetics intumors.

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.





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Acknowledgments

The authors would like to thank Suzette van Balen, Amina Elouah-mani, Judith van Es, Robin Hemminga, Femke Jongsma, Rob Koopmans,Nghi Pham, Nasserah Sais, Annemiek Stiekema, and Jeroen Wilhelmusfor scanning the patients, Niki Hoetjes, Marc Huisman, Jurgen Mourik,and Floris van Velden for help with processing of the blood samples,Otto Hoekstra, Natasja Kok, Daniela Oprea-Lager, Ilona Pomstra, PieterRaijmakers, and Atie van Wijk for help with logistic planning and patientcare, Pieter Postmus and Hugo Rutten for recruiting patients, DennisBoersma for technical assistance, Ronald Boellaard for help with dataanalysis, Stefan de Haan and Sebastiaan Kleijn for assistance withthe Figures, Jonas Eriksson, Rob Klok, and Dennis Laan for the produc-tion of [11C]docetaxel, Gert Luurtsema, Marissa Rongen, and Kevin

Takkenkamp for the production of [15O]H2O and the analysis of theblood samples.

Grant Support

This studywas financially supported by VUmcCancer Center Amsterdam.The costs of publication of this article were defrayed in part by the

payment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely to indicatethis fact.

Received November 3, 2010; revised April 23, 2011; accepted May 16,2011; published OnlineFirst July 12, 2011.

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SUPPLEMENTARY METHODS

Analyses of blood samples

Blood samples were analyzed for blood and plasma concentrations and potential

radiolabeled metabolites of [11C]docetaxel. Whole blood (0.5 mL) was weighted in

duplicate and 0.05 mL 10% Triton X-100 solution was added. After centrifuging the

remaining whole blood (5 min; room temperature; 4000 rpm), plasma was harvested

and 0.5 mL plasma was weighted in duplicate, again adding 0.05 mL 10% Triton X-100

solution. A well-counter (Wallac 1480 Wizard, Perken Elmer, Zaventem, Belgium), cross-

calibrated against the PET scanner, was used to determine activity concentrations.

For metabolite analysis, a high performance liquid chromatography (HPLC) system, as

described previousl (1,2), was used. The HPLC column used was a Phenomenex Luna 5u

C18 100A 250 x 10.00 mm (Phenomenex, Torrance, CA, USA). Components for solid

phase extraction (SPE) columns (4.7 x 50 mm) were purchased from Jones

Chromatography (Hengood, England). tC18 specification silica stationary phase, used in

the SPE columns, was obtained from commercially available Sep-Pak® cartridges (Waters

Corporation, Milford, MA, USA). Harvested plasma was rinsed, using a Millipore GV filter

(Millipore, Molsheim, France). The HPLC loop was loaded with a plasma sample that was

eluted onto the SPE column, using a 0.01 M di-ammonium hydrogen phosphate solution

with a flow of 0.5 mL·min-1 for a period of 4 min. The flow was then gradually increased

to 3 mL·min-1 for a period of 30s and kept at 3 mL·min-1 for an additional 220s to rinse

polar plasma components from the SPE column. The phosphate fraction was collected

and weighted. Amounts of ~ 1.5 mL of this eluate were weighted and counted for

radioactivity, resulting in the polar metabolite fraction [counts per minute (CPM)·g-1] if

activity was measured. Trapped activity was then eluted from the SPE column with a

mixture of 65/35 acetonitril/ammoniumacetate 5mMol, pH 4.1 onto the HPLC column

with a flow of 1.8 mL·min-1 for a period of 20 min. The eluate was collected in fractions of

30s that were counted using a gamma counter to generate an HPLC plot. A weighted

aliquot of the plasma was also counted for calculating recovery.

References

1. Greuter HN, Van Ophemert PL, Luurtsema G, et al. Optimizing an online SPE-HPLC method for analysis of (R)-[11C]1-(2-chlorophenyl)-N-methyl-N-(1-methylpropyl)-3-isoquinolinecarboxamide [(R)-[11C]PK11195] and its metabolites in humans. Nucl Med Biol 2005;32:307-12.

2. Greuter HN, Van Ophemert PL, Luurtsema G, Franssen EJ, Boellaard R, Lammertsma AA. Validation of a multiwell {gamma}-counter for measuring high-pressure liquid chromatography metabolite profiles. J Nucl Med Technol 2004;32:28-32.

92

SUPPLEMENTARY FIGURES

Figure 1. Schematic diagram illustrating the various analyses that were performed to validate a

less invasive procedure for analysis of [11C]docetaxel kinetics in lung cancer patients.

TAC, time-activity curve; BSIF, blood sampler derived input function; IDIF, image derived

input function.

Figure 2.

(A) Mean (o) ± SD (vertical error bars) of arterial plasma/whole blood ratios as function of time for

seventeen patients. The solid line represents the best fit of these ratios to a sigmoid function.

(B) Mean whole blood and plasma time-activity curves of seventeen patients.

P/W ratio, plasma/whole blood ratio; normalized activity, activity concentration normalized to the

area under the curve of the corresponding whole blood curve.

Tumor TAC + aorta TAC + venous samples

Less

inv

asive

Tumor TAC + aorta TAC + arterial samples

Tumor TAC + online sampling


IDIF corrected using venous samples

IDIF corrected using arterial samples

Simplified kinetic model with BSIF

Data input

Optimal kinetic model with BSIF

Method

Reproducibility

Tumor TAC + aorta TAC + venous samples

Less

inv

asive

Tumor TAC + aorta TAC + arterial samples






Data input


Method

Reproducibility




Data input


Method

Reproducibility

0 20 40 600

1

2

Time (min)

P/W

ratio

0 10 20 300

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Time (min)

Nor

mal

ized

activ

ity

A B Whole bloodPlasma

0 20 40 600

1

2

Time (min)

P/W

ratio

0 10 20 300

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Time (min)

Nor

mal

ized

activ

ity

A B Whole bloodPlasma

93

Chapter 8

Rapid decrease in delivery of chemotherapy to tumors after anti-VEGF therapy: implications

for scheduling of anti-angiogenic drugs

Astrid A.M. van der Veldt, Mark Lubberink, Idris Bahce, Maudy Walraven, Michiel P. de Boer, Henri N.J.M. Greuter, N. Harry Hendrikse, Jonas Eriksson,

Albert D. Windhorst, Pieter E. Postmus, Henk M. Verheul, Erik H. Serné, Adriaan A. Lammertsma, Egbert F. Smit

Cancer Cell 2012;21:82-91.

Cancer Cell

Article

Rapid Decrease in Delivery of Chemotherapyto Tumors after Anti-VEGF Therapy: Implicationsfor Scheduling of Anti-Angiogenic DrugsAstrid A.M. Van der Veldt,1,* Mark Lubberink,1,6 Idris Bahce,2 Maudy Walraven,3 Michiel P. de Boer,4

Henri N.J.M. Greuter,1 N. Harry Hendrikse,1,5 Jonas Eriksson,1 Albert D. Windhorst,1 Pieter E. Postmus,2

Henk M. Verheul,3 Erik H. Serne,4 Adriaan A. Lammertsma,1 and Egbert F. Smit21Department of Nuclear Medicine and PET Research2Department of Pulmonology3Department of Medical Oncology4Department of Internal Medicine5Department of Clinical Pharmacology and PharmacyVU University Medical Center, 1007 MB Amsterdam, The Netherlands6PET Centre, Uppsala University Hospital, 751 85 Uppsala, Sweden

*Correspondence: [email protected]

DOI 10.1016/j.ccr.2011.11.023

SUMMARY

Current strategies combining anti-angiogenic drugs with chemotherapy provide clinical benefit in cancerpatients. It is assumed that anti-angiogenic drugs, such as bevacizumab, transiently normalize abnormaltumor vasculature and contribute to improved delivery of subsequent chemotherapy. To investigate thisconcept, a study was performed in non-small cell lung cancer (NSCLC) patients using positron emissiontomography (PET) and radiolabeled docetaxel ([11C]docetaxel). In NSCLC, bevacizumab reduced bothperfusion and net influx rate of [11C]docetaxel within 5 hr. These effects persisted after 4 days. The clinicalrelevance of these findings is notable, as there was no evidence for a substantial improvement in drugdelivery to tumors. These findings highlight the importance of drug scheduling and advocate further studiesto optimize scheduling of anti-angiogenic drugs.

INTRODUCTION

Angiogenesis is a critical component for growth and metastatic

spread of tumors (Hanahan and Weinberg, 2000; Carmeliet,

2000). Vascular endothelial growth factor (VEGF), which is over-

expressed in many human malignancies, is a key regulator of

tumor angiogenesis, inducing proliferation, differentiation, and

migration of endothelial cells (Ferrara et al., 2003). Consequently,

numerous drugs have been developed to target the signaling

pathways of VEGF and its receptors (VEGFR; Ferrara andKerbel,

2005).

Bevacizumab is a humanized monoclonal antibody that

targets circulating VEGF and subsequently prevents binding of

VEGF to its receptors (Ferrara et al., 2004). Except for metastatic

renal cell cancer (Yang et al., 2003), clinical efficacy of single-

agent bevacizumab treatment has been very limited in the

majority of advanced malignancies (Reese et al., 2001; Cobleigh

et al., 2003). Combined with chemotherapy, however, additional

value was shown in colorectal (Hurwitz et al., 2004), breast (Miller

et al., 2007), and non-small cell lung cancer (NSCLC; Sandler

et al., 2006).

In the past years, the normalization theory proposed by Jain

(2001) has gained widespread acceptance for explaining

additional antitumor effects of inhibitors of VEGF signaling,

when combined with cytotoxic drugs. It is hypothesized that

anti-angiogenic drugs normalize structurally and functionally

abnormal tumor vasculature, thereby reducing interstitial fluid

pressure, improving drug penetration, and subsequently

Significance

Optimal scheduling of anti-angiogenic drugs is important for improving efficacy of combination therapy in patients withadvanced-stage cancer. In this study, effects of the anti-angiogenic drug bevacizumab on delivery of chemotherapy tonon-small cell lung cancer (NSCLC) were investigated using positron emission tomography and 11C-labeled docetaxel.Bevacizumab induced a rapid and significant reduction in delivery of chemotherapy to tumors in NSCLC patients. The studyprovides a framework for investigating effects of anti-angiogenic drugs on drug delivery to tumors in vivo. In addition, it high-lights the importance of drug scheduling and advocates further studies to optimize scheduling of anti-angiogenic drugs.

82 Cancer Cell 21, 82–91, January 17, 2012 ª2012 Elsevier Inc.

121

enhancing efficacy of cytotoxic drugs. Exploration of the

normalization window may be crucial for optimizing drug

scheduling in order to improve clinical efficacy. To date,

however, no clinical studies have been reported on the effects

of anti-angiogenic agents on drug delivery in cancer patients.

Positron emission tomography (PET) is a noninvasive imaging

technique that can be used to monitor drug pharmacokinetics

and pharmacodynamics in vivo by radiolabeling drugs of interest

with short-lived positron emitting radionuclides (Gambhir, 2002).

Previously, the cytotoxic drug docetaxel, a taxane targeting the

microtubular network, has been radiolabeled with the radionu-

clide C-11 ([11C]docetaxel; van Tilburg et al., 2004), enabling

in vivo quantification of docetaxel kinetics in lung cancer (Van

der Veldt et al., 2011). In the latter study, feasibility of noninvasive

PET measurements using radiolabeled water ([15O]H2O) and

[11C]docetaxel was demonstrated and uptake of [11C]docetaxel

in lung tumors was found to be associated with tumor perfusion,

measured using [15O]H2O.

The purpose of the present study was to investigate the

effects of anti-angiogenic drugs on tumor perfusion and

[11C]docetaxel delivery in patients with advanced-stage NSCLC

using PET. To this end, bevacizumab was selected, as it is the

most selective inhibitor of VEGF signaling among currently

approved anti-angiogenic drugs. It was hypothesized that

bevacizumab improves drug delivery by normalizing tumor

vasculature, which should be reflected by a more homogeneous

distribution of perfusion and [11C]docetaxel delivery. A

secondary objective of this study was to investigate (systemic)

effects of bevacizumab on (1) circulating VEGF levels in plasma;

(2) cardiovascular parameters, including blood pressure,

cardiac output, and microcirculation in muscle and skin; (3)

systemic exposure of [11C]docetaxel; and (4) perfusion and

[11C]docetaxel uptake in normal tissues. For the latter, the

thyroid gland and the vertebral body were selected. The thyroid

gland is known to be highly sensitive to VEGF inhibition (Kamba

et al., 2006), whereas the vertebral body may reflect effects of

bevacizumab on [11C]docetaxel uptake in bone marrow.

Figure 1. Tumor Measurements in 10 NSCLC

Patients at Baseline and after Administration of

Bevacizumab

Horizontal bars represent median values.

(A) Perfusion (F).

(B) Volume of distribution of water (VT).

(C) F/VT.

(D) Net rate of influx (Ki) of [11C]docetaxel.

*p value < 0.05; **p value < 0.01.

RESULTS

Bevacizumab Induces Rapid Reductionin Tumor PerfusionTo investigate the effect of anti-VEGF therapy

on tumor perfusion (F), PET scans using

[15O]H2O, which is a freely diffusible tracer

(Hoekstra et al., 2002; Wilson et al., 1992),

were performed at baseline and 2 hr, 5 hr, and

4 days after bevacizumab administration. Five

hours after bevacizumab administration, there

was a significant reduction in tumor perfusion, which persisted

until day 4 (Figures 1A and 2A). In three out of eight patients,

tumor perfusion already decreased 2 hr after the end of bevaci-

zumab infusion. Accordingly, tumor perfusion showed median

percentage changes of 8% (range �39 to +15%; N = 9; p value =

0.889), �20% (range, �39 to �7%; N = 8; p value = 0.012),

and �38% (range, �55 to �4%; N = 10; p value = 0.005) at

2 hr, 5 hr, and 4 days after bevacizumab administration, respec-

tively. In addition, the volume of distribution of water (VT),

a measure of the (viable) fraction of tissue that is able to

exchange [15O]H2O, was decreased at 4 days after bevacizumab

administration (Figure 1B), with a median percentage change

of �7% (range, �52 to +2%; N = 10; p value = 0.022). Individu-

ally, eight out of ten patients showed a reduction in volume of

distribution of water. Although both perfusion and volume of

distribution of water showed an overall decrease, the reduction

in perfusion was more severe, as illustrated by a significant

decrease in the ratio of tumor perfusion over volume of distribu-

tion (F/VT; (Figure 1C). Collectively, these findings indicate that

the decrease in tumor perfusion is not due to a reduction in

tumor tissue, which was confirmed by an unchanged tumor

volume on subsequent computed tomography (CT) scans.

Bevacizumab Decreases the Net Influx Rate of[11C]docetaxel in TumorsTo determine whether delivery of chemotherapy is affected by

bevacizumab, PET scans using [11C]docetaxel were performed

at baseline and 5 hr and 4 days after bevacizumab administra-

tion. Kinetics of [11C]docetaxel in tumor tissue are irreversible

and can be quantified using Patlak graphical analysis, providing

the net influx rate constant (Ki) of [11C]docetaxel in tumor

tissue (Patlak et al., 1983; Van der Veldt et al., 2011). Prior

to bevacizumab infusion, tumors showed a variable Ki of

[11C]docetaxel (median Ki, 0.0132 ml$cm�3$min�1; range,

0.0054–0.0247 ml$cm�3$min�1; N = 10). After administration of

bevacizumab, median Ki of [11C]docetaxel significantly

decreased (Figures 1D and 2B), resulting in amedian percentage

Cancer Cell

Effects of Bevacizumab on Delivery of Chemotherapy

Cancer Cell 21, 82–91, January 17, 2012 ª2012 Elsevier Inc. 83

122

change of �22% (range, �51 to �4%; N = 9; p value = 0.008)

and �34% (range, �61 to �16%; N = 10; p value = 0.005) at

5 hr and 4 days, respectively. In line with the decrease in

the volume of distribution of water, the distribution volume of

[11C]docetaxel, which can be obtained from the Patlak plot,

also showed a decline on day 4 with a median percentage

change of �14% (range, �24 to + 20%; N = 10; p value =

0.052). Before administration of bevacizumab, [11C]docetaxel Ki

was associated with tumor perfusion (Spearman’s r = 0.626;

N = 10; p value = 0.053). As two patients had one missing scan

(either [11C]docetaxel PET or [15O]H2O PET), this correlation

could not be evaluated at 5 hr. At 4 days, the correlation between

[11C]docetaxel Ki and perfusion showed a slight decrease

(Spearman’s r 0.564; N = 10; p value = 0.090).

Tumor Heterogeneity of [11C]docetaxel UptakeIs Not Affected by BevacizumabAs it is assumed that normalization of tumor vasculature results

in a more homogenous distribution of perfusion and drug

delivery, spatial distributions of tumor perfusion, volume of

distribution of water, and [11C]docetaxel Ki were analyzed on

a voxel-by-voxel basis using histogram analysis. For the Ki of

[11C]docetaxel, only the median kurtosis of the histograms

showed a trend toward an increase from 2.60 at baseline to

3.11 (N = 9; p value = 0.051) and 2.97 (N = 10; p value = 0.059)

at 5 hr and 4 days, respectively, whereas standard deviation

and kurtosis of the other histograms (F and VT) did not change.

When histogram analysis was applied to separately analyze

tumor center and rim, larger tumors showed lower perfusion

and lower values of [11C]docetaxel Ki in the center than in the

rim. When all primary tumors were analyzed, median baseline

values, however, were not significantly different (N = 10; p value =

0.739 and 0.579, respectively). At 5 hr and 4 days after bevacizu-

mab administration, mean, median, minimum, and maximum

values of tumor perfusion and [11C]docetaxel Ki showed the

same degree of reduction (p value < 0.05) in the whole tumor,

as in the center and the rim separately. In addition, the volume

of distribution of water showed a significant decrease in both

center and rim at 4 days (N = 10; p value < 0.05). Standard devi-

ation and kurtosis of all histograms (F, VT, and [11C]docetaxel Ki)

did not change in the center and the rim, except for a decreased

standard deviation of perfusion in the center at 5 hr (N = 8;

p value = 0.028). Furthermore, changes in perfusion, volume of

distribution of water, and [11C]docetaxel Ki were not associated

with baseline tumor volumes. Collectively, these results indicate

that bevacizumab induces an overall decrease in perfusion,

volume of distribution of water, and [11C]docetaxel Ki in tumors

without significantly affecting tumor heterogeneity.

Decrease in [11C]docetaxel Delivery to Tumors IsAccompanied by Rapid Reduction in Circulating VEGFPlasma levels of circulating VEGF were measured to evaluate

whether the rapid decrease in [11C]docetaxel Ki in tumors was

supported by a rapid decrease in free VEGF. As VEGF is mainly

transported by platelets (Verheul et al., 1997), circulating VEGF

was assessed in both platelet-poor and platelet-rich plasma.

At 3 hr, administration of bevacizumab resulted in a significant

decrease in circulating VEGF in platelet-rich plasma (N = 7;

p value = 0.018; Figure 3). In the majority of patients, free

VEGF in plasma was completely neutralized within 3 hr and

seemed to recover in part after 4 days. Comparable changes

in VEGF levels were measured in platelet-poor plasma.

A Reduction in [11C]docetaxel Delivery to Tumors Is NotAssociated with Cardiovascular ParametersBecause arterial hypertension and cardiotoxicity are commonly

reported side effects associated with inhibitors of VEGF/

VEGFR-2 signaling (Chen and Cleck, 2009), it was investigated

whether the rapid decrease in tumor perfusion and [11C]doce-

taxel Ki was accompanied by early onset cardiovascular

changes. A single infusion of bevacizumab did not affect systolic

and diastolic blood pressure during the first 4 days (Figures 4A

and 4B). Median cardiac output as derived from first pass

dynamic [15O]H2O PET scans (Knaapen et al., 2008), however,

showed a trend toward a reduction at day 4 (from 6.9 l$min�1

to 6.0 l$min�1; N = 9; p value = 0.051; Figure 4C). As inhibitors

of VEGF/VEGFR-2 signaling may induce so-called rarefaction

(Mourad et al., 2008), that is, a reduction in the number of arteri-

oles or capillaries within vascular beds of various tissues (e.g.,

muscle and skin), muscle perfusion in the erector spinae, as

well as capillary density in the skin, were measured. Muscle

perfusion was obtained from the [15O]H2O images, whereas nail-

fold capillaries in the dorsal skin of the third finger were examined

using a capillary microscope (Serne et al., 2001). Perfusion in the

erector spinae muscle and capillary density in the skin did not

change during the first 4 days after administration of

Figure 2. PET-CT Images of a 51-Year-Old Woman

with Metastatic Non-Small Cell Lung Cancer

(A) Parametric perfusion images obtained at baseline

and at 5 hr and 4 days after bevacizumab administration.

In the whole tumor, the mean perfusion changed from

0.875ml$cm�3$min�1 at baseline to 0.765ml$cm�3$min�1

at 5 hr and 0.535 ml$cm�3$min�1 at 4 days.

(B) Patlak images of [11C]docetaxel uptake obtained at

baseline and at 5 hr and 4 days after bevacizumab

administration. In the whole tumor, the mean Ki of

[11C]docetaxel changed from 0.0205 ml$cm�3$min�1 at

baseline to 0.0193 ml$cm�3$min�1 at 5 hr and

0.0127 ml$cm�3$min�1 at 4 days.

F, perfusion; Ki, net influx rate constant.

Cancer Cell



123

bevacizumab (Figures 4D, 4E, and 4F). Of note, [11C]docetaxel Ki

in muscle tissue (median Ki, 0.0072 ml$cm�3$min�1; range,

0.0029–0.0104 ml$cm�3$min�1) was lower than that in tumor

tissue (N = 10; p value = 0.002). The Ki of [11C]docetaxel in

muscle tissue was neither associated with perfusion nor affected

by bevacizumab.

Bevacizumab Increases Systemic Exposureof [11C]docetaxelTo investigate whether decreased [11C]docetaxel Ki in tumor

tissue was associated with a change in systemic exposure of

[11C]docetaxel, plasma clearance of [11C]docetaxel was deter-

mined. Four days after bevacizumab administration, plasma

clearance of [11C]docetaxel was significantly decreased (N = 10;

p value = 0.037), as reflected by a shift to the right of the plasma

curves (Figure 5). Consequently, bevacizumab increased thedura-

tionof [11C]docetaxel exposurebya reduction inplasmaclearance.

However, this increased systemic exposure of [11C]docetaxel did

not result in increased [11C]docetaxelaccumulation in tumor tissue,

as the retention index of [11C]docetaxel still decreased after

bevacizumabadministration (from0.0155ml$cm�3$min�1atbase-

line to 0.0109 ml$cm�3$min�1 at day 4; N = 10; p value = 0.005).

Bevacizumab Decreases Thyroid PerfusionBecause normal vessels of the thyroid gland are known for their

extensive capillary regression after anti-VEGF therapy (Kamba

et al., 2006), thyroid perfusion was also determined using para-

metric perfusion images. In four out of ten patients, the primary

tumorwas located in the upper lobes, enabling adequate analysis

of thyroid perfusion at baseline and day 4. Four days after beva-

cizumab administration, median perfusion in the thyroid gland

showed a decrease (from 1.316 ml$cm�3$min�1 at baseline to

0.585 ml$cm�3$min�1 at day 4; p value = 0.068), whereas the

volume of distribution of water did not change (p value = 0.273).

[11C]docetaxel Uptake in Bone Marrow Is Not Affectedby BevacizumabAs [11C]docetaxel shows high uptake in bone marrow (Van der

Veldt et al., 2010b) and anti-VEGF therapy can block rapid

induction of viable circulating endothelial progenitor cells from

bone marrow and can inhibit taxane-induced bone marrow

colonization in tumors (Shaked et al., 2008), the effects of beva-

cizumab on [11C]docetaxel uptake in bone marrow was also

evaluated. To this end, perfusion and [11C]docetaxel Ki were

determined in the vertebral body. Perfusion values were signifi-

cantly lower in the vertebral body than in tumors (N = 10; p value=

0.003), whereas Ki values of [11C]docetaxel were significantly

higher than those in tumors (N = 10; p value < 0.001; Figure 6).

In contrast to tumor tissue, there was no association between

[11C]docetaxel Ki and perfusion in the vertebral body (Spear-

man’s r = �0.285; N = 10; p value = 0.425). Perfusion and

[11C]docetaxel Ki did not change after bevacizumab administra-

tion (Figure 6).

DISCUSSION

Current strategies combining anti-angiogenic therapy with cyto-

toxic agents have shown proven efficacy in cancer patients,

including those with advanced-stage NSCLC (Sandler et al.,

2006). Pretreatment with anti-angiogenic drugs may transiently

normalize abnormal tumor vasculature (Batchelor et al., 2007)

and thereby contribute to improved delivery of subsequent

chemotherapy, enhancing efficacy (Jain, 2005). Investigating

this process of vasculature normalization in vivo is a major

challenge, which is mainly restricted to imaging studies.

Whereas conventional imaging studies, such as CT and mag-

netic resonance imaging, have concentrated on changes in

tumor perfusion, the present concept of PET imaging using a

radiolabeled drug to study drug delivery in patients after anti-

VEGF therapy has not been reported yet. The humanized mono-

clonal antibody bevacizumab induced an overall decrease in

both perfusion and Ki of [11C]docetaxel in tumor tissue within

a few hours after bevacizumab administration, a decrease

that persisted for at least four days. These findings represent

physiological changes in tumors, as measured changes were

beyond the known test-retest variability (van der Veldt et al.,

2010a and 2011). The large range of changes in perfusion and

[11C]docetaxel uptake is most likely due to interpatient differ-

ences in tumor response to bevacizumab and partly due to

differences in interval between end of bevacizumab infusion

and PET scans. Nevertheless, the results indicate a decrease

in perfusion and [11C]docetaxel uptake in tumor tissue of all

patients. Based on these data, it can be concluded that anti-

VEGF therapy is not able to improve drug delivery to tumors

but rather has the opposite effect.

Results of the present study are at variance with those ob-

tained by Willett et al. (2004), where improved drug delivery in

rectal cancer was postulated partly based on human imaging

studies. Tumor perfusion, as determined by dynamic contrast-

enhanced CT scanning decreased, whereas the standardized

uptake value of 20-deoxy-20-[18F]fluoro-D-glucose ([18F]FDG)

remained unchanged at 12 days after bevacizumab administra-

tion. However, kinetics of [18F]FDG are fundamentally different

from those of anticancer drugs, as [18F]FDG reflects glucose

metabolism. In the present study, however, the decrease in

standard deviation of tumor perfusion in the center of the

tumor at 5 hr and the increase in kurtosis of [11C]docetaxel

histograms may reflect a more homogenous distribution as

Figure 3. Platelet-rich Plasma Levels of VEGF in Seven IndividualPatients at Baseline and after Administration of Bevacizumab

Vascular endothelial growth factor levels were corrected for platelet count and

are expressed in pg$ml�1 per 200,000 platelets$ml�1. Horizontal bars represent

median values.

*p value < 0.05.

Cancer Cell



124

a result of certain normalization of tumor vasculature. Neverthe-

less, these possible changes in tumor heterogeneity did not

result in improved drug delivery, as bevacizumab infusion

caused a rapid and overall reduction in [11C]docetaxel Ki in

tumors. In addition, drug uptake may be further impaired by

development of tumor necrosis, associated with extensive

vascular damage, which usually develops after anti-VEGF

therapy. Although it is not possible to define necrotic areas on

low-dose CT, development of necrotic areas was possibly re-

flected by a reduction in the distribution volume of water after

4 days, despite an unchanged total tumor volume on low-dose

CT.

Apart from tumor parameters, systemic effects after admin-

istration of bevacizumab were evaluated. The rapid changes

in tumor perfusion and [11C]docetaxel Ki were associated with

an immediate reduction in plasma levels of VEGF, indicating

an immediate inhibition of VEGF signaling in the whole body.

This rapid neutralization of circulating VEGF also induced a

decrease in perfusion of the thyroid gland, whereas perfusion

and [11C]docetaxel Ki in the vertebral body and muscle tissue

were not affected. In addition, Ki values of [11C]docetaxel in the

vertebral body and muscle tissue were essentially different

from that in tumor tissue and were not related to perfusion in

these normal tissues. These findings imply that tumor tissue

shows a difference in sensitivity to VEGF inhibition (Kamba

et al., 2006) and in drug delivery as compared with normal

tissues. Among the cardiovascular parameters, only cardiac

output showed a decrease at day 4, whereas blood pressure

and capillary density did not change during the first 4 days after

Figure 4. Cardiovascular Variables in Ten NSCLC

Patients at Baseline and after Administration of

Bevacizumab


(A) Systolic blood pressure (SBP).

(B) Diastolic blood pressure (DBP).

(C) Cardiac output.

(D) Perfusion (F) in muscle tissue.

(E) Nailfold capillary density.

(F) Nailfold capillary density during venous occlusion (VO).

bevacizumab infusion. These findings indicate

that the rapid and significant changes in

perfusion and [11C]docetaxel Ki in tumors are

not caused by immediate development of

hypertension, microvascular rarefaction, or a

rapid reduction in cardiac output. Conse-

quently, it can be concluded that the decrease

in perfusion and [11C]docetaxel Ki in tumors

can be attributed to rapid inhibition of VEGF

signaling in tumors. As the decrease in perfu-

sion and [11C]docetaxel uptake in tumors is

probably too rapid to be solely ascribed to

inhibition of tumor angiogenesis, vasoconstric-

tive effects of anti-angiogenic drugs on tumor

vessels, particularly those from the host,

should be considered as a potential underlying

mechanism. In this regard, inhibition of endo-

thelial nitric oxide synthesis by VEGF inhibitors

may be an important factor (Dhaun and Webb, 2010; Syrigos

et al., 2011; Ng et al., 2007). Although plasma clearance of

[11C]docetaxel decreased slightly after bevacizumab administra-

tion, signifying prolonged duration of [11C]docetaxel exposure,

this decrease in clearance appeared to be too limited to result

in an overall increase in [11C]docetaxel uptake, that is, retention

index, by tumors.

Bevacizumab was selected to investigate the effects of anti-

angiogenic agents, as it is the most selective inhibitor of VEGF

signaling among presently approved anti-angiogenic drugs,

and it does not have multiple targets like most tyrosine kinase

inhibitors. In addition, the long terminal half-life of 17–21 days

(Ferrara et al., 2004) enables sequential measurements after

a single administration of bevacizumab. The study was conduct-

ed in patients with advanced-stage NSCLC, as noninvasive

PET-CT measurements using [15O]H2O and [11C]docetaxel

were previously found to be feasible in this patient group (Van

der Veldt et al., 2011). As a result, [11C]docetaxel measurements

could be repeated in individual patients who acted as their own

control. Although both docetaxel and bevacizumab are active

agents for the treatment of advanced lung cancer (Sandler

et al., 2006; Kudoh et al., 2006), single-agent bevacizumab is

not considered effective for the treatment of NSCLC patients.

Consequently, ethically it was not acceptable to prolong the

study with PET measurements at later time points. In addition,

the localization of the lung tumors did not enable invasive

measurements of interstitial fluid pressure (Curti et al., 1993) or

sequential biopsies for additional histopathological analyses.

Furthermore, use of tracer amounts of docetaxel (microdoses)

Cancer Cell



125

may be a potential limitation of the present study, as it is conceiv-

able that the effects of bevacizumab on [11C]docetaxel delivery

in tumors may not hold true for pharmacological drug concentra-

tions. However, use of repeated therapeutic doses mixed with

the radiolabeled drug, instead of microdoses, will obscure

bevacizumab-induced effects, as cytotoxic drugs themselves

also affect both tumor perfusion (Dunnwald et al., 2008) and

interstitial fluid pressure (Griffon-Etienne et al., 1999) and may

modulate the specific targets of the drug under study (Shalli

et al., 2005). In a separate study, in which [11C]docetaxel was

given at tracer concentrations and during infusion of a thera-

peutic dose, albeit was possible to predict tumor uptake of

(therapeutic) docetaxel from the tumor kinetics of (tracer)

[11C]docetaxel (data not shown), indicating that the present

bevacizumab-induced decrease in [11C]docetaxel uptake in

tumors is likely to represent changes in tumor uptake of thera-

peutic doses of docetaxel.

The results of the present study pose a number of important

issues relevant to anti-angiogenic drugs administered in combi-

nation with other anticancer drugs. In human tumors, bevacizu-

mab induced a rapid decrease in perfusion and [11C]docetaxel

uptake. It is conceivable that other inhibitors of the VEGF

signaling pathways may produce similar effects. In addition, it

is likely that these effectsmay persist during continued treatment

with these drugs. Therefore, administration of anti-angiogenic

drugs can be considered after administration of the other anti-

cancer agents, as the immediate decrease in tumor perfusion

should decrease clearance of drugs from tumors. Hence,

preclinical studies are warranted to investigate this concept for

scheduling of anticancer drugs. To improve scheduling of

combination therapy, other potential mechanisms need to be

investigated to understand the synergistic effects with anti-

angiogenic drugs. In this regard, it is important to explore the

effects of anti-angiogenic drugs on proliferative activity of tumor

cells (Ortholan et al., 2010) and their environment, such as

mobilization of bone marrow-derived circulating endothelial

progenitor cells (Shaked et al., 2008) and acute release of

cytokines from the tumor microenvironment (Gilbert and He-

mann, 2010).

The results of the present study may explain why several

clinical trials have failed to show the additional value of anti-

angiogenic drugs in specific populations of cancer patients.

Clearly, more clinical studies are needed to assess whether

administration schedules affect response and outcome of com-

bination strategies. To this end, the optimal design to prove

clinical relevance of drug scheduling would be a randomized

controlled trial in which cancer patients are randomized to

different administration schedules.

In conclusion, the results of this human study indicate a rapid

and significant reduction in perfusion and [11C]docetaxel uptake

in NSCLC after administration of bevacizumab. The clinical rele-

vance of these findings is notable, as the present study did not

provide evidence for a substantial improvement in drug delivery

to tumors but rather showed the opposite effect. These findings

highlight the importance of drug scheduling and advocate further

studies to optimize scheduling of anti-angiogenic drugs.

EXPERIMENTAL PROCEDURES

Patient Selection

Between October 2009 and September 2010, ten patients (six men and four

women; median age 58 years; range, 47–70 years) with advanced-stage

NSCLC were prospectively enrolled. Patients participated in this study prior

to their scheduled therapy. The study was approved by the Medical Ethics

Review Committee of the VU University Medical Center, Amsterdam. All

patients signed a protocol-specific informed consent form prior to study

enrollment.

Inclusion criteria were the following: age R18 years; a malignant lesion

R1.5 cm in diameter within the chest; life expectancy of at least 12 weeks;

Eastern Cooperative OncologyGroup performance status <3;R4weeks since

any prior surgery or radiotherapy; no previous acute toxicities (>1) in accor-

dance with Common Terminology Criteria for Adverse Events v3.0 (CTCAE);

adequate organ function [hemoglobin R6.0 mmol∙l�1; absolute neutrophil

countR1.53 109/l; absolute platelet count >1003 109/l; total serum bilirubin

%1.5 upper limit of normal (ULN); aspartate aminotransferase and alanine

aminotransferase%2.5 x ULN (in case of liver metastases% 5 x ULN); alkaline

phosphatase%2.5 x ULN; serum creatinine%1.5 ULN or creatinine clearance

R60 ml∙min�1; normal serum calcium; urine dipstick for proteinuria <2+]; and

use of effective contraception.

Exclusion criteria were the following: squamous lung cancer; history of R

grade 2 hemoptysis; cavitary lesion; tumor invading major blood vessels;

newly diagnosed and untreated central nervous system metastases; any

unstable systemic disease (including but not limited to clinically significant

cardiovascular disease and uncontrolled hypertension); major surgery or

significant traumatic injury <28 days before study entry; prior treatment with

taxanes or bevacizumab; concurrent treatment with other anticancer agents

or experimental drugs; use of inhibitors or substrates of the efflux transporter

ABCB1; serious nonhealing wound or ulcer; a history of documented hemor-

rhagic diathesis or coagulopathy; therapeutic anticoagulation; regular use of

aspirin (>325 mg per day); planned radiotherapy or major surgery; pregnancy

or lactation; metal implants (e.g., pacemakers); and claustrophobia.

Study Design

Patients received a single infusion of bevacizumab (15 mg$kg�1, infused over

90 min). In the week prior to this infusion, patients underwent a dynamic PET-

CT study with both [15O]H2O and [11C]docetaxel. At 5 hr and 4 days after infu-

sion of bevacizumab, the PET-CT protocol was repeated. In addition, 2 hr after

infusion of bevacizumab, patients underwent an additional dynamic PET-CT

scan with [15O]H2O. Sequential scans were possible because of the short

half-lives of oxygen-15 and carbon-11, which are 2.0 and 20.3 min, respec-

tively. Initially, the last time point for PET measurements was set at day 7.

However, recruitment of patients seemed difficult, as patients were not willing

Figure 5. Plasma Clearance of [11C]docetaxel at

Baseline and after Administration of Bevacizumab

(A) Example of plasma activity curves of [11C]docetaxel in

a patient at baseline and after 5 hr and 4 days following

bevacizumab administration. Plasma activity curves are

divided by injected dose (ID).

(B) Plasma clearance of [11C]docetaxel in 10 NSCLC

patients at baseline and after administration of bev-

acizumab.


*p values < 0.05.

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126

to postpone their planned chemotherapy for more than a few days. Hence, the

protocol was amended and the last time point was set at day 4. Adverse events

were graded in accordance with CTCAE v3.0. After the last PET-CT study,

patients started with their scheduled therapy. In accordance with the guide-

lines of the Medical Ethics Review Committee of the VU University Medical

Center, the total radiation burden of the study was estimated at <10 mSv.

As efficacy was not an endpoint of the present study, response evaluation

and data collection for survival were not performed.

Synthesis of Radiopharmaceuticals

The radiosyntheses of [15O]H2O and [11C]docetaxel were performed in accor-

dance with good manufacturing practice (GMP) standards (Jackson et al.,

1993; van Tilburg et al., 2004 and 2008). Docetaxel, obtained from Green

PlantChem Company (Hangzhou, China), was chemically modified and used

as precursor in the synthesis of [11C]docetaxel. 11C-labeled docetaxel was ob-

tained with an isolated decay-corrected radiochemical yield of 10 ± 2% and

a radiochemical purity of >98%. [11C]docetaxel has an identical molecular

structure as the drug docetaxel. The identity of [11C]docetaxel was confirmed

by comparison of retention times on high-performance liquid chromatography

with authentic docetaxel.

Scanning Protocol

Imaging studies were performed on a state-of-the-art three-dimensional (3D)

PET-CT scanner (Gemini TF-64, Philips Medical Systems, Best, The Nether-

lands; Surti et al., 2007). This scanner has an axial field of view of 18 cm,

divided into 45 contiguous planes. All patients underwent PET-CT scans

with [15O]H2O and [11C]docetaxel at baseline and at day 4. Nine patients

underwent a [15O]H2O PET-CT scan at 2 hr and eight patients underwent

combined [15O]H2O and [11C]docetaxel PET-CT scans at 5 hr, whereas one

patient underwent a single [11C]docetaxel PET-CT scan at 5 hr. The median

times from the end of the bevacizumab infusion to the first, second, and third

scan sessions were 1.9 hr (range, 1.4–2.3 hr), 5.6 hr (range, 4.9–8.6 hr), and

4 days (range, 3–5 days). Sudden technical difficulties, clinical problems,

and logistic issues were the reasons for missing scans and different time

intervals.

Until 3 hr prior to scanning, food and drinks were allowed. On the day of

a PET study, patients were asked to consume similar meals prior to scanning.

All patients received two venous catheters, one for tracer injection and the

other for blood sampling. Patients were positioned supine on the scanner

bed, with both tumor and aortic arch located inside the axial field of view of

the scanner. Elastic body-restraining bandages were used to minimize move-

ment during scanning.

A 10 min dynamic scan was started simultaneously with an intravenous

injection of 370 MBq [15O]H2O (5 ml at a rate of 0.8 ml$s�1, followed by

a 35 ml saline flush at a rate of 2 ml$s�1). Thereafter, a 50 mAs low-dose CT

scan was performed for attenuation correction purposes. At least 20 min after

administration of [15O]H2O, a 60min dynamic scan was started simultaneously

with an intravenous injection of [11C]docetaxel (dissolved in a maximum

volume of 12 ml saline, infused at a rate of 0.8 ml$s�1, and followed by a 35 ml

saline flush at a rate of 2 ml$s�1). The median injected dose of [11C]docetaxel

was 344 MBq (range, 122–388 MBq) with a median specific activity of 3.2

GBq$mmol�1 (range; 1.0–25.8 GBq$mmol�1). During PET scanning, blood

pressure was monitored with a Dinamap (Dash 4000, GE Medical Systems

Information Technologies, Inc., Milwaukee, Wisconsin).

Figure 6. Perfusion and [11C]docetaxel Uptake in

the Vertebral Body, which Represents Bone

Marrow, in Ten Individual Patients at Baseline

and after Administration of Bevacizumab


(A) Perfusion (F).

(B) Net rate of influx (Ki) of [11C]docetaxel.

Data were normalized and all appropriate corrections

for dead time, decay, randoms, scatter, and attenuation

were applied. Using the 3D row actionmaximum likelihood

reconstruction algorithm, [15O]H2O and [11C]docetaxel

scans were reconstructed into 26 (1x10, 8x5, 4x10, 2x15, 3x20, 2x30, and

6x60 s) and 36 (1x10, 8x5, 4x10, 2x15, 3x20, 2x30, 6x60, 4x150, 4x300, and

2x600 s) frames, respectively.

Blood Sampling

Sequential blood samples were collected in ACD vacutainers (8.5 ml, Becton

Dickinson, Heidelberg, Germany; Cat. No. 364606) at baseline, and at 3 hr

and 4 days after the end of the bevacizumab infusion. Prior to each sample,

3 ml–5 ml blood was discarded and the line was flushed with 2 ml saline after

each sample. After collection, the blood samples were centrifuged immedi-

ately to obtain platelet-rich plasma (15 min; 20C; 156 x g; N = 7 patients).

Platelet-rich plasma was further centrifuged to obtain platelet-poor plasma

(15 min; 20C; 330 x g; N = 3 patients). Thereafter, plasma was stored at

�20C until analysis. Concentrations of VEGF (pg∙ml�1) were assessed in

duplicate using a Quantikine enzyme-linked immunosorbent assay (ELISA)

kit (R&DSystems,Minneapolis, Minnesota). Vascular endothelial growth factor

concentrations in platelet-rich plasma were corrected for platelet count and

were expressed in pg$ml�1 per 200,000 platelets$ml�1.

After intravenous injection of [11C]docetaxel, 10 ml discrete venous samples

were collected manually at 2.5, 5, 10, 15, 20, 30, 40, and 60 min post-injection.

Blood samples were analyzed for radioactivity concentrations in blood and

plasma. Whole blood (0.5 ml) was weighted in duplicate and 0.05 ml 10%

Triton X-100 solution was added. After centrifuging the remaining whole blood

(5 min; room temperature; 4000 rpm), plasma was harvested and 0.5 ml

plasma was weighted in duplicate, again adding 0.05 ml 10% Triton X-100

solution. A well-counter, cross-calibrated against the PET scanner, was

used to determine activity concentrations. Samples were not analyzed for

radiolabeledmetabolites, as these were not detected previously (Van der Veldt

et al., 2011).

Input Functions

Kinetic analyses of data were performed using dedicated programs written

within the software environment Matlab (The MathWorks Inc., Natick, Massa-

chusetts). The ascending aorta in the [15O]H2O and [11C]docetaxel images

was used to generate noninvasive image-derived input functions (IDIF), as

validated previously (van der Veldt et al., 2010a and 2011). Volumes of

interest (VOI) of 1 cm diameter were drawn over the ascending aorta in

approximately ten consecutive image planes of the frame in which the first

pass of the bolus was best visualized. Projection of these VOIs onto all image

frames yielded the arterial time-activity curve (TAC) CA(t). A similar approach

was used for the pulmonary artery in approximately five consecutive planes,

thereby providing a TAC for the pulmonary circulation CV(t) (van der Veldt

et al., 2010a). The [11C]docetaxel plasma IDIF was obtained by multiplying

CA(t) with a sigmoid function (Gunn et al., 1998), which was obtained by

fitting the plasma/whole blood ratios derived from the venous samples. As

the rapid [11C]docetaxel clearance precludes reliable input functions at later

time points, the generation of input functions of [11C]docetaxel was limited to

the first 10 min of data (Van der Veldt et al., 2011).

Analysis of Perfusion and [11C]docetaxel Kinetics in Tumors

Scans were anonymized and randomly presented to an experienced observer

(I.B.) who was blinded to patients’ history and outcome. To delineate compa-

rable tumor VOIs, this observer analyzed all scans from one patient in the same

session. Low-dose CT images were converted to ECAT 7 format. Thereafter,

Cancer Cell



127

primary tumors were delineated on low-dose CT images using the CAPP

software package (CTI/Siemens, Knoxville, Tennessee). Next, VOIs were

projected onto the dynamic images of the corresponding [15O]H2O and

[11C]docetaxel scans, thereby generating tumor TACs for [15O]H2O and

[11C]docetaxel, respectively.

The standard single-tissue compartment model was used to derive tumor

perfusion from [15O]H2O kinetics (Hermansen et al., 1998; van der Veldt

et al., 2010a). Using nonlinear regression, [15O]H2O tumor TACs were fitted

to the single-tissue compartment model using IDIF as arterial input function

(van der Veldt et al., 2010a). The correction for pulmonary circulation blood

volume was included, as it improves the quality of the fits without affecting

tumor perfusion values. Using this approach, the absolute test-retest vari-

ability of tumor perfusion is 0.03 ml$cm�3$min�1 (van der Veldt et al., 2010a).

The kinetics of [11C]docetaxel in tumors was described by a two-tissue irre-

versible compartment model, linearized using the Patlak method (Patlak et al.,

1983). When applying the Patlak method to the first 10 min of dynamic PET

data with the starting time at 2 min, the Ki of [11C]docetaxel has an absolute

test-retest variability of 0.003 ml$cm�3$min�1 (van der Veldt et al., 2011). In

addition, the retention index of [11C]docetaxel in tumor tissue was calculated

by dividing the measured radioactivity concentration at 10 min post-injection

by the integral of the plasma curve up to this time.

To analyze heterogeneity of tumor perfusion at the voxel level, parametric

perfusion images were generated (van der Veldt et al., 2010a). Hence, IDIFs

and a basis function implementation of the standard single-tissue compart-

ment model were applied (Boellaard et al., 2005; Lodge et al., 2000; Watabe

et al., 2005). Fifty logarithmically spaced, precomputed basis functions with

F/VT values, ranging from 0.1 to 2.0 min�1 were used and parametric perfusion

images were postsmoothed with a Gaussian filter of 10 mm full width at half

maximum. Then, VOIs previously defined on the low-dose CT scans were

projected onto the parametric perfusion images. Next, voxel intensity histo-

grams were generated for the whole VOI, its center and its rim. A voxel was

considered to be part of the rim if at least one of the voxels in its 3D six-con-

nected neighborhood was outside the defined VOI. In accordance with this

method, the median baseline volume of the whole tumor VOI was 13.3 cm3

(range, 1.7–278.5 cm3) with center and rim accounting for median volumes

of 2.5 cm3 (range, 0.1–183.8 cm3) and 9.1 cm3 (range, 1.5–81.3 cm3),

respectively. Similarly, voxel intensity histograms were generated for the Ki

of [11C]docetaxel, applying the Patlak method on a voxel basis. The voxel

intensity histograms were used to characterize tumor heterogeneity of

perfusion and [11C]docetaxel uptake, analyzing the following parameters:

percentage of voxels, mean value, standard deviation, median value, minimal

value, maximal value, kurtosis, and skewness of the distribution. More homog-

enous distributions are characterized by lower standard deviations and higher

kurtosis (more peaked distribution) of corresponding histograms.

Cardiac Output

Using dynamic [15O]H2O PET data, the cardiac output can be estimated by the

following equation (Knaapen et al., 2008):

Cardiac output=ID

Z t

0

CV$dt

; (1)

where the injected radioactivity (ID) of [15O]H2O is divided by the area under

the curve of the blood activity in the pulmonary artery (CV) multiplied by the

duration of the first pass of the bolus. The TAC of the pulmonary artery was

fitted with a linear upslope and followed by an exponential downslope, which

was extrapolated to remove contamination of recirculating radioactivity.

Microcirculation in the Skin

In eight patients, microcirculation in the skin was investigated. At baseline,

3 hr and 4 days, nailfold capillaries in the dorsal skin of the third finger were

visualized using a capillary microscope (Serne et al., 2001). Capillary density

was defined as the number of erythrocyte-perfused capillaries$mm�2. First,

baseline capillary density was recorded for 2 min. Thereafter, venous

occlusion was applied to expose a maximal number of perfused capillaries.

To this end, a digital cuff was inflated to 60 mmHg for 60 s. Recordings

were presented randomly and in a blind fashion to an experienced investigator

(M.P.d.B.), who counted number of capillaries off-line from a videotape. Using

the same visual fields as used during baseline measurements, peak capillary

density during venous congestion was counted in the 60 s recordings. Day-

to-day variation of baseline capillary density and peak capillary density during

venous congestion were 2.3% ± 1.8% (Serne et al., 2002) and 9.5 ± 7.1%

(Serne et al., 2001), respectively.

Muscle Perfusion

On the low-dose CT scans, VOIs (diameter, 1 cm) were drawn over the erector

spinae muscle in five consecutive image planes. Projection of these muscle

VOIs onto the dynamic images of the corresponding [15O]H2O scan yielded

a muscle TAC for [15O]H2O. The standard single-tissue compartment model

was used to derive muscle perfusion (Hermansen et al., 1998) but without

correction for pulmonary circulation blood volume:

CTðtÞ= ð1 � VAÞ$F$CAðtÞ5e� F

VTt+VA CAðtÞ; (2)

where CT(t) is the total measured tissue signal in tumor as function of time, F is

perfusion, VA is arterial blood volume, and VT is the volume of distribution

or partition coefficient of water. To evaluate [11C]docetaxel kinetics in

normal tissue, muscle VOIs were also projected onto the corresponding

[11C]docetaxel image and those TACs were analyzed using the Patlak method

(Patlak et al., 1983).

[11C]docetaxel Clearance

To determine influence of bevacizumab on blood kinetics of [11C]docetaxel,

clearance of [11C]docetaxel was calculated using the following equation:

Clearance=IDR

CPðtÞ$dt$BSA; (3)

where the injected dose (ID) of [11C]docetaxel is divided by the integral of the

plasma (CP) TAC multiplied by the body surface area.

Thyroid Perfusion

In those cases in which the thyroid gland was in the field of view, additional

parametric perfusion images were generated, using 50 precomputed basis

functions with F/VT values, ranging from 0.1 to 15 min�1 and postsmoothing

with a Gaussian filter of 10 mm in full width at half maximum. Then, the thyroid

gland could be delineated on parametric perfusion images applying a semi-

automatic threshold technique (50% of the maximum voxel value with correc-

tion for local background; van der Veldt et al., 2010a). Thereafter, these VOIs

were projected onto the dynamic [15O]H2O images. Again, the standard

single-tissue compartment model (Equation 2) was applied to calculate

perfusion.

Perfusion and [11C]docetaxel Kinetics in Bone Marrow

Perfusion and [11C]docetaxel uptake were determined in the vertebral body,

representing active bone marrow. From the level of the main carina to ten

image planes downwards, VOIs (diameter, 1.5 cm) were defined in the verte-

bral body on low-dose CT scans. These VOIs were projected onto dynamic

images of the [15O]H2O and [11C]docetaxel scans, generating corresponding

TACs.

Equation 2 was applied to calculate vertebral body perfusion, whereas the

Patlak method (Patlak et al., 1983) was applied to determine [11C]docetaxel

uptake.

Statistics

Statistical analysis was performed using SPSS software (SPSS for Windows

16.0, SPSS, Inc., Chicago, IL). Correlations were explored using the Spear-

man’s correlation coefficient. The Mann-Whitney test was used to compare

between groups. The Wilcoxon signed-rank test was used to compare

variables at 2 hr, 3 hr, 5 hr, and 4 days after bevacizumab administration

with baseline values. A two-tailed probability value of p value < 0.05 was

considered significant.

ACKNOWLEDGMENTS

The authors would like to thank all patients who participated in this study.

In addition, the authors would like to thank Suzette van Balen, Amina

Cancer Cell



128

Elouahmani, Judith van Es, Robin Hemminga, Femke Jongsma, Nghi Pham,

Nasserah Sais, and Jeroen Wilhelmus for scanning the patients, Emile

Comans, Otto Hoekstra, Daniela Oprea-Lager, Pieter Raijmakers, Nafees

Rizvi, Natasja Kok, Ilona Pomstra, Atie van Wijk, Sabri Duzenli, Martijn

Groenendijk, Esther Nossent, Arifa Pa�si�c, Suzy Samii, Serge van Wolferen,

and Jennifer Benit for help with logistical planning and patient care, Ronald

Boellaard, Dennis Boersma, Marc Huisman, Arthur van Lingen, and Maqsood

Yaqub for technical assistance; Peter van de Ven for statistical advice; Bart

Kuenen for help with the design of the study; Martien Mooijer, Anneloes

Rijnders, and Dennis Laan for production of [11C]docetaxel; Henk Dekker for

help with the analyses of VEGF levels; and Marissa Rongen, Robert Schuit,

and Kevin Takkenkamp for the production of [15O]H2O and the analysis of

blood samples. This work was supported by a grant of the Cancer Center

Amsterdam. This study was presented in part at the 2011 ASCO Annual

Meeting, Chicago, IL, June 3–7, 2011, #3059; and at the 14th World Confer-

ence on Lung Cancer, Amsterdam, The Netherlands, July 3–7, 2011, #O18.02.

Received: July 23, 2011

Revised: November 2, 2011

Accepted: November 29, 2011

Published: January 17, 2012

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Chapter 9

Summary

Positron emission tomography (PET) is an imaging technique that may be useful for

individualized treatment planning in cancer patients. For that purpose, radiolabeling

anticancer drugs with positron emitters is promising, as these may then be used to

monitor drug pharmacokinetics and pharmacodynamics in patients non-invasively. In this

thesis, validation and clinical implementation of a newly radiolabeled anticancer drug,

carbon-11 labeled docetaxel ([11C]docetaxel), in patients with lung cancer were

presented.

In Chapter 1, principles of PET and applications of several PET tracers in oncology were

introduced. In addition, development of the novel PET tracer [11C]docetaxel and its

validation in lung cancer patients was described.

In Chapter 2, the role of PET and radiolabeled anticancer drugs in predicting tumor

resistance was reviewed. In this chapter, the focus was on resistance pathways that may

impede drug delivery to tumors and how PET can help to reveal these pathways.

Mechanisms of drug resistance that were discussed included factors that may affect

distribution of drugs within the body, bioavailability of drugs in the circulation, as well as

transport of drugs to tumors. Within that framework, radiolabeled anticancer drugs that

have been developed, together with their stage of clinical implementation, were

reviewed. It was concluded that use of radiolabeled anticancer drugs (e.g. [18F]paclitaxel

and [18F]fluorouracil) provides a unique means for personalized treatment planning and

drug development. In this chapter, it was also argued that combining these specific PET

tracers with other less specific ones, such as tracers for blood flow (e.g. [15O]H2O) and

efflux transporters (e.g. [11C]verapamil), may provide additional information on drug

resistance mechanisms. Finally, it was mentioned that radiolabeled anticancer agents

may be valuable for evaluating optimal timing of combination therapies.

As tumor perfusion may influence the delivery of radiolabeled drugs to tumors, the

validity and reproducibility of dynamic [15O]H2O PET/CT scans for measuring tumor

perfusion were assessed in Chapter 3. In addition, quantitative accuracy of parametric

perfusion images was validated. To that end, eleven patients with non–small cell lung

cancer (NSCLC) underwent two dynamic [15O]H2O PET scans on the same day. This

validation study showed that the use of image derived input functions (IDIFs) obtained

from the ascending aorta was an accurate alternative for arterial blood sampling when

quantifying tumor perfusion. In addition, it was shown that image quality obtained with a

clinical PET/CT scanner enabled generation of accurate parametric perfusion images.

Volumes of interest (VOIs) delineated on low-dose computed tomography (LD-CT) scans

had the highest reproducibility and changes of more than 16% in tumor perfusion were

likely to represent treatment effects.

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Chapters 4 to 7 described a series of steps that were followed in order to validate the

use of [11C]docetaxel in clinical PET studies.

In Chapter 4, the biodistribution of [11C]docetaxel was determined in healthy male rats

at 5, 15, 30 and 60 minutes after injection. This preclinical study showed the highest

[11C]docetaxel uptake in spleen, followed by urine, lungs and liver, whereas brain and

testes showed the lowest uptake. Within less than 5 minutes, [11C]docetaxel essentially

had cleared from blood and plasma. This preclinical study was needed to obtain an initial

estimate of the expected radiation dose in humans, which in turn was required for

obtaining ethics permission to conduct human studies.

In Chapter 5, biodistribution and actual human radiation dosimetry of [11C]docetaxel

were determined in seven patients with solid tumors using whole body PET/CT scans.

Gall bladder and liver showed high [11C]docetaxel uptake, whilst uptake in brain and

normal lung was low. In the liver, the percentage injected dose at 1 hour was 47 ± 9%.

[11C]docetaxel was rapidly cleared from plasma and no radiolabeled metabolites were

detected. [11C]docetaxel uptake in tumors was moderate and highly variable between

tumors. The effective dose of [11C]docetaxel ·MBq-1. In contrast to the

previous study in rats, [11C]docetaxel showed low uptake in human lungs. Therefore, it

was concluded that [11C]docetaxel may be a promising tracer for tumors in the thoracic

region.

In Chapter 6, the feasibility of quantitative [11C]docetaxel scans in lung cancer patients

was evaluated. In addition, it was investigated whether [11C]docetaxel kinetics were

associated with tumor perfusion, tumor size, or dexamethasone administration. In this

study, 34 lung cancer patients underwent dynamic PET-CT using [11C]docetaxel and

[15O]H2O. The first 24 patients were premedicated with dexamethasone. For

quantification of [11C]docetaxel kinetics, the optimal tracer kinetic model was developed.

Tumor kinetics of [11C]docetaxel were irreversible and could be quantified using the

Patlak method. Furthermore, it was shown that reproducible quantification of

[11C]docetaxel kinetics in tumors was possible using an IDIF. In tumors, the net rate of

influx (Ki) of [11C]docetaxel was variable and strongly related to tumor perfusion, but not

to tumor size. In addition, patients pre-treated with dexamethasone, a potent inducer of

the efflux transporter ABCB1, showed lower [11C]docetaxel uptake in tumors. In a

subgroup of patients who subsequently received docetaxel therapy, relative high

[11C]docetaxel uptake was related with improved tumor response. Accordingly, it was

concluded that quantification of [11C]docetaxel kinetics in lung cancer was feasible in a

clinical setting and that the observed variation in [11C]docetaxel kinetics between tumors

may reflect differential sensitivity to docetaxel therapy.

As pharmacokinetics of [11C]docetaxel at tracer doses may be different from those at

therapeutic doses, the microdosing concept was validated for [11C]docetaxel in Chapter

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7. The research question to be addressed was whether a PET study using a tracer dose of

[11C]docetaxel could predict tumor uptake of unlabeled (cold) docetaxel during a

therapeutic infusion. For this purpose, docetaxel-naïve lung cancer patients underwent

two [11C]docetaxel PET scans, one after a bolus injection of a tracer dose [11C]docetaxel

and another during a combined infusion of a tracer dose [11C]docetaxel and a therapeutic

dose of docetaxel (75 mg·m-2). Compartmental and spectral analyses were used to

quantify [11C]docetaxel tumor kinetics. In addition, [11C]docetaxel PET measurements

were used to estimate the area under the curve (AUCTumor) of cold docetaxel in tumors.

[11C]docetaxel Ki in tumors was comparable during microdosing and therapeutic scans.

[11C]docetaxel AUCTumor during the therapeutic scan could be predicted reliably using an

impulse response function derived from the microdosing scan together with the plasma

curve of [11C]docetaxel during the therapeutic scan. At 90 minutes, the accumulated

amount of cold docetaxel in tumors was < 1% of the total infused dose of docetaxel.

[11C]docetaxel Ki derived from the microdosing scan correlated with AUCTumor of cold

docetaxel during the therapeutic scan and with tumor response to docetaxel therapy.

Based on these results, it was concluded that microdosing data of [11C]docetaxel PET can

indeed be used to predict tumor uptake of cold docetaxel during chemotherapy. The

study in this chapter provides a framework for investigating the PET microdosing concept

for radiolabeled anticancer drugs in patients.

In Chapter 8, the effects of the anti-angiogenic drug bevacizumab on tumor perfusion

and [11C]docetaxel uptake in non-small cell lung cancer (NSCLC) was investigated.

Bevacizumab is a humanized monoclonal antibody that targets circulating vascular

endothelial growth factor (VEGF) and subsequently prevents binding of VEGF to its

receptors. It is assumed that anti-angiogenic drugs, such as bevacizumab, transiently

normalize the abnormal tumor vasculature and contribute to improved delivery of

subsequent chemotherapy. To investigate this concept, a study was performed in NSCLC

patients using PET and [11C]docetaxel. In NSCLC, bevacizumab reduced both perfusion

and [11C]docetaxel Ki within 5 hours. These effects persisted after 4 days and were not

associated with significant changes in tumor heterogeneity of [11C]docetaxel uptake.

Reduction in [11C]docetaxel delivery to tumors was accompanied by rapid reduction in

circulating levels of VEGF, but not with changes in cardiovascular parameters such as

blood pressure, cardiac output and capillary density in the skin. The clinical relevance of

these findings is notable, as there was no evidence for substantial improvement in drug

delivery to tumors after administration of bevacizumab. This study highlights the

importance of drug scheduling and advocates further studies to optimize scheduling of

anti-angiogenic drugs.

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Chapter 10

Discussion and future perspectives

PET scans using radiolabeled anticancer drugs

As mentioned in Chapter 2, numerous anticancer drugs have been radiolabeled with

positron emitters. Since publication of Chapter 2 in 2008, more anticancer drugs have

been developed as tracers for positron emission tomography (PET) including

[11C]erlotinib (1-3) and [11C]sorafenib (4). There appears to be a discrepancy, however,

between the number of radiolabeled anticancer drugs that have been developed and the

relatively small number of clinical studies applying these PET tracers in patients. This

discrepancy may be due to several potential caveats on the path from development to

clinical implementation of a new PET tracer, which is very complex and is challenging due

to technical, logistical, financial, and/or patient related issues. First of all, a complex and

expensive research infrastructure is required (Figure 1): a cyclotron for production of

positron emitters, an on-site good manufacturing practice (GMP) laboratory for synthesis

of the tracer, a PET/CT scanner for acquisition of the images, an on-line blood sampler in

case of arterial blood sampling, an on-site laboratory for measurements of radioactivity

concentrations and radioactive metabolites in blood, and dedicated computers and

software to analyze and quantify the PET data acquired (5).

Figure 1. Overview of facilities and highly qualified personnel required for development and clinical

implementation of a radiolabeled anticancer drug. Required personnel for a specific facility are

listed next to the corresponding facility.

141

Second, in addition to the facilities mentioned above, also highly qualified personnel is

required: a cyclotron operator, a chemist who synthesizes the PET tracer, a

radiopharmacist who is responsible for quality control of the tracer production, a

technologist for acquiring the PET images, a (nuclear medicine) physician who is

responsible for the medical condition of the patient as well as for arterial blood sampling,

a chemist for analyzing blood samples during PET scanning, and a physicist responsible

for acquisition protocols and data analyses. The short half-lives of most PET tracers

require that the facilities and personnel mentioned above are located and working in the

same building at very close proximity. Third, apart from the requirement of adequate

facilities and personnel, patient related issues may arise. The biodistribution of a

radiolabeled drug may limit its use to specific tumor types. High background uptake of a

radiolabeled drug in e.g. the liver will make it inadequate for uptake measurements in

tumors located in the liver. In addition, patients should be willing and physically able to

undergo PET scans as well as arterial blood sampling. Fourth, clinical implementation of a

novel PET tracer may be hampered by technical problems associated with the

characteristics of a specific PET tracer, such as challenging tracer synthesis, rapid

metabolism in vivo resulting in rapid ingrowth of radiolabeled metabolites, high non-

specific binding or poor reproducibility of the uptake parameter of interest. Fifth, from

the above, it will be clear that the development of radiolabeled anticancer drugs is very

expensive and time-consuming (6,7). Because of the complexity and high costs of PET

scans using radiolabeled anticancer drugs, validation studies usually are performed in a

limited number of patients. Therefore, the design of these studies should be as optimal

as possible in order to obtain all relevant PET data. In this regard, the need for optimal

acquisition of PET data should not be underestimated, as data can be acquired only once,

whereas they can be (re)analyzed as often as needed.

[15O]H2O PET/CT for measurement of tumor perfusion

As tumor perfusion can be an important factor for the delivery of radiolabeled anticancer

drugs to tumors, application of the established flow tracer [15O]H2O using a PET/CT

scanner was validated in patients with lung tumors (Chapter 3). The short-half life of

oxygen-15, which is 2.03 minutes, enables sequential PET scans using both [15O]H2O and

a radiolabeled anticancer drug. However, the short-half life of oxygen-15 requires the

presence of a nearby cyclotron. Apart from the potential application in combination with

radiolabeled drugs, [15O]H2O PET/CT scans are increasingly used to assess response of

the tumor vasculature to anti-angiogenic therapy (8-13). For example, in non-small cell

lung cancer (NSCLC) patients treated with bevacizumab and erlotinib, a reduction in

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tumor perfusion of more than 20% after three weeks was associated with improved

progression-free survival (10).

Biodistribution and radiation dosimetry of [11C]docetaxel

Administration of [11C]docetaxel appeared to be safe in humans with an effective dose of

4.7 μSv·MBq-1 (Chapter 5). In 2011, Kurdziel et al. (14) evaluated the biodistribution

and dosimetry of [18F]paclitaxel in healthy volunteers and newly diagnosed breast cancer

patients. Like docetaxel, paclitaxel belongs to the family of taxanes (15). In the clinical

treatment of cancer patients, the taxanes docetaxel and paclitaxel are often compared,

as these drugs have similar mechanisms of action (16). Despite similarity in chemical

structures, their metabolism is very distinct. Docetaxel metabolism is similar across

species, whereas paclitaxel metabolism is very species dependent. For both drugs,

hepatobiliary excretion is the main pathway of elimination and a major fraction of the

dose is excreted in feces. As paclitaxel was radiolabeled with fluorine-18, which has a

half-life of 109.8 minutes, the authors were able to perform whole-body PET/CT scans for

three hours after injection of [18F]paclitaxel. Because of the longer half-life of fluorine-18,

however, the effective dose of [18F]paclitaxel (28.8 μSv·MBq-1) was significantly higher

than that of [11C]docetaxel. In accordance with the biodistribution of [11C]docetaxel

(Chapter 5), [18F]paclitaxel showed high uptake in the gastrointestinal tract. Successive

whole body PET scans showed that both [11C]docetaxel and [18F]paclitaxel accumulate in

the liver and are subsequently excreted into the bile and ultimately into the intestine

(Figure 2). The shorter half-life of [11C]docetaxel resulted in lower radiation dosimetry

estimates in organs, but this prohibited measurements at three hours after injection. As

a result, it was not possible to determine biological clearance of [11C]docetaxel at later

time points. Therefore, further clearance of [11C]docetaxel was estimated according to

physical decay after the last whole-body PET scan. Consequently, the radiation dosimetry

of [11C]docetaxel may be somewhat underestimated in the gall bladder as well as the

intestine.

Biodistribution studies have demonstrated that both [11C]docetaxel and [18F]paclitaxel

show low uptake in brain [Chapter 5; (14)]. The brain is protected by the blood-brain

barrier, which prevents toxins from accumulating in brain tissue. In the blood-brain

barrier, the efflux transporter ABCB1 (formerly known as P-glycoprotein or MDR1) is

expressed (17,18). As both docetaxel and paclitaxel are well-characterized substrates of

this efflux transporter (19,20), these drugs essentially cannot penetrate the brain and

often show failure in tumors and metastases in the brain (21,22).

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Figure 2. Four successive [11C]docetaxel whole body PET scans showing that [11C]docetaxel

accumulates in liver, subsequently is excreted into bile and ultimately into intestine. Because of

high [11C]docetaxel uptake in the liver, the present projection could not visualize the high uptake of

[11C]docetaxel in the gall bladder (Chapter 5).

As a result, several inhibitors of ABCB1, such as cyclosporin A and tariquidar, are under

investigation in order to improve the uptake of ABCB1 substrates in the brain (23,24).

Remarkably, increased uptake of [11C]docetaxel was observed in the pituitary gland

(Figure 3). This increase can be explained by the fact that the posterior pituitary gland is

not protected by the blood brain barrier. Therefore, it is conceivable that other anticancer

drugs will show accumulation in the pituitary gland as well (14). Although acute side-

effects of chemotherapy on the pituitary gland, e.g. hypophysitis, are not commonly

reported for most anticancer drugs, chemotherapy may have late effects. Koppelmans et

al (25) have reported that breast cancer survivors, previously treated with chemo-

therapy, are more likely to develop pituitary adenomas than subjects without a history of

cancer and chemotherapy treatment. They suggested that the development of pituitary

adenomas may be related to an early postmenopausal status. However, the hypophyseal

accumulation of [11C]docetaxel indicates that anticancer drugs can accumulate in

pituitary tissue, suggesting that chemotherapy may also affect the pituitary gland.

Therefore, further studies are warranted to investigate the (late) effects of chemotherapy

on the pituitary gland. Furthermore, the biodistribution of [11C]docetaxel provided

information on the background uptake of the tracer in normal organs, thereby identifying

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Figure 3. Transverse (left), coronal (middle) and sagittal (right) PET images showing low

[11C]docetaxel in the brain, but increased uptake in the pituitary gland (arrows).

tumor types that can be monitored using [11C]docetaxel PET. High [11C]docetaxel uptake

in liver and intestine makes it unlikely that the tracer can be applied for imaging of the

abdominal region. In addition, relatively high [11C]docetaxel uptake in the vertebral body

makes it also unlikely that [11C]docetaxel is useful for imaging bone metastases.

Unfortunately, these findings exclude the use of [11C]docetaxel PET in patients with

hormone refractory metastatic prostate cancer, as these patients frequently present with

metastatic sites in paraaortic lymph nodes, pelvic lymph nodes and spine, in particular in

the lumbar level of the spine (26). As 90% of patients with hormone refractory

metastatic prostate cancer have bone metastases (26), high penetration of

[11C]docetaxel in the vertebral body may partially explain the efficacy of docetaxel in this

patient population (27). However, this hypothesis remains to be proven. Although

[11C]docetaxel is not suitable for imaging of tumors in the abdomen, low [11C]docetaxel

uptake in the thoracic region makes [11C]docetaxel an interesting tracer for tumors

located in the thoracic region, including breast cancer and lung cancer.

The estimated effective dose in humans extrapolated from rat studies was comparable to

the measured dose in humans (5.4 vs. 4.7 μSv·MBq-1). However, the results of the

preliminary biodistribution study in healthy male rats (Chapter 4) differed from the

[11C]docetaxel results in humans (Chapter 5), as the animal study showed relatively high

[11C]docetaxel uptake in lungs. In addition, the rat study was not able to predict high

uptake of [11C]docetaxel in the gall bladder, as rats do not have a gall bladder. In the rat

study, [11C]docetaxel was administered through a tail vein injection, followed by post

mortem examinations of internal organs (Chapter 4; Figure 4). Such sacrifice

experiments are time-consuming and require the sacrifice of many animals at multiple

time points to determine pharmacodynamics and pharmacokinetics of the tracer.

145

Alternatively, small animal imaging offers the possibility of studying kinetics of a

radiolabeled anticancer drug in mice and rats in vivo (28-30). Using dedicated small

animal systems, a spatial resolution of ~ 2 mm can be achieved (31). The main challenge

of small animal imaging studies, however, is the measurement of a metabolite corrected

plasma input function, as extensive blood sampling is not possible in small animals. In

case of larger animals, a clinical scanner can also be used (32). In particular, animal

studies in monkeys will provide biodistribution results that are more comparable to those

in humans (14,33).

Research in animals has always been a vital step in the development of novel PET

tracers. Prior to studies in humans, a biodistribution study is usually performed in

animals to exclude high tracer uptake in organs that are highly sensitive to radiation

exposure, such as the thyroid gland. In addition, animal studies are carried out to

estimate the radiation dose in humans. As a result, medical ethics committees commonly

require animal studies prior to administration of the radiolabeled drug in humans.

Figure 4. Biodistribution of [11C]docetaxel in healthy male rats.

(A) PET scan showing the biodistribution of [11C]docetaxel in a male rat. The PET image was

obtained using a High Resolution Research Tomograph (HRRT) with a spatial resolution of about

2.5 mm. Red indicates the highest [11C]docetaxel uptake.

(B) Standardized uptake values of [11C]docetaxel in organs as obtained from sacrifice experiments.

Standardized uptake values were calculated as the ratio of tissue radioactivity concentration and

injected dose normalized for body weight.

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However, in case of positron emitters with a short half-life such as carbon-11 (20.3

minutes), a different approach may be more appropriate. These short half-lives are

associated with a low and predictable radiation dose. Therefore, for these short-lived

tracers, animal studies could be omitted. Such an approach may help to reduce the

number of animal experiments, may prevent incorrect interpretation due to animal-

human differences and may speed up the development of radiolabeled anticancer drugs.

Quantification of [11C]docetaxel kinetics in tumors

Since whole body PET scans do not provide data for absolute quantification of

[11C]docetaxel kinetics in tumors, dynamic PET scans were performed (see Chapter 1).

For only a few radiolabeled anticancer drugs, tumor kinetics in humans have been

quantified previously using dynamic scanning [Chapter 6; (34-37)]. Quantitative

measurements of [11C]docetaxel revealed rapid, but rather low irreversible uptake of

[11C]docetaxel in tumors (Chapter 6). This relatively low [11C]docetaxel uptake in tumors

was in line with the results obtained from the biodistribution study in patients (Chapter

5). Despite its longer half-life, low irreversible tumor uptake has also been reported for

the other radiolabeled taxane, [18F]paclitaxel (14). The relatively low tumor uptake of

these radiolabeled taxanes may be explained by the rapid clearance of the two tracers

from blood [Chapters 5 & 6; (14)]. Whereas radiolabeled metabolites have been detected

for [18F]paclitaxel (33), no radiolabeled metabolites were seen for [11C]docetaxel

(Chapters 5 & 6), making quantification of [11C]docetaxel kinetics less complex. In

addition, the short half-life of [11C]docetaxel enables sequential measurements on the

same day.

Because of its low uptake in tumors, [11C]docetaxel PET is not suitable for detection of

tumors. Nevertheless, monitoring tumor kinetics of [11C]docetaxel may be useful for

other purposes. First, [11C]docetaxel PET, when combined with [15O]H2O PET, provides

insight into the relation between tumor perfusion and [11C]docetaxel kinetics. In Chapters

6 and 7, it was demonstrated that tumor perfusion is an important factor for delivery of

both [11C]docetaxel and therapeutic doses of docetaxel to tumors. As a result, tumor

perfusion may be predictive of tumor response to docetaxel therapy. These findings

advocate further studies investigating the predictive value of tumor perfusion for tumor

response to chemotherapy, at least in case of taxanes. Second, [11C]docetaxel kinetics

may provide insight into ABCB1 dependent drug efflux and could be predictive of tumor

uptake of other ABCB1 substrates, as overexpression of ABCB1 is found in many drug

resistant tumors (38). Third, effects of other (anticancer) drugs on delivery of

[11C]docetaxel can be evaluated. In this regard, not only anti-angiogenic drugs (Chapter

147

8), but also inhibitors of ABCB1 are of interest [Chapter 6, (39,40)]. In addition,

inhibitors of ABCB1 may decrease the rapid clearance of [11C]docetaxel from blood

(41,42), as ABCB1 is also extensively expressed in intestine and the biliary system (43),

and may contribute to [11C]docetaxel elimination (44). Finally, [11C]docetaxel tumor

kinetics may be useful for prediction of tumor response to docetaxel therapy, as

preliminary results showed that the variable uptake of [11C]docetaxel in lung cancer

tissue was associated with response to docetaxel treatment (Chapters 6 & 7). Larger

studies are warranted to confirm the predictive value of [11C]docetaxel uptake in tumors.

Concept of [11C]docetaxel microdosing

In a PET microdosing study, usually less than 1% of the pharmacological dose of a drug

is administered (45). As a result, kinetics of tracer doses may be different from those of

therapeutic doses (46). Previously, other PET studies have shown that a therapeutic dose

can significantly affect uptake of radiolabeled anticancer drugs in normal organs as well

as in tumors (36,37,47,48). Therefore, the effects of a pharmacological dose on the

kinetics of a microdose need to be evaluated for each radiolabeled anticancer drug

separately. In Chapter 7, the kinetic behavior of [11C]docetaxel in tumors was monitored

after a regular bolus injection of [11C]docetaxel as well as during an infusion of a

therapeutic dose of docetaxel. Results showed that [11C]docetaxel PET can be used to

predict uptake of therapeutic doses of docetaxel in tumors.

However, implementation of studies evaluating the PET microdosing concept can be

difficult as, compared with other PET studies, additional issues need to be addressed.

First, recruitment of patients willing to participate in such studies can be challenging.

Receiving their first chemotherapy while lying in a PET scanner can be a more stressful

event, as patients will have less contact with family and/or friends for (emotional)

support during chemotherapy infusion. Second, infusion of chemotherapy, in particular

the first infusion of taxanes, may be associated with acute allergic reactions, including

anaphylactic shock in rare cases. This potential risk for severe allergic reactions requires

close monitoring of the patient during PET scanning, which needs to be discontinued

immediately in case of suspicion of an allergic reaction. Third, the proposed study design

is not applicable for oral anticancer drugs, which are usually administered on a daily

basis. For these oral drugs, PET scanning with the radiolabeled anticancer drug

(microdose) may be repeated during treatment with the oral drug. Then, the optimal

time-point for PET scanning needs to be defined on the basis of pharmacokinetics of the

oral anticancer drug under study (46). Only a small amount of administered docetaxel

appears to accumulate in tumors. In Chapter 7, it was demonstrated that less than 1% of

148

the total infused dose of docetaxel accumulated in tumors. These findings indicate that

there is an urgent need for strategies that selectively enhance drug delivery to tumors.

Ultrasound triggering may be useful for this purpose, as it enables localized delivery of

drug-loaded microbubbles to tumors (49). In addition, optimal scheduling of combined

treatment strategies may improve the delivery of drugs to tumors, thereby enhancing

treatment efficacy. In addition, also direct effects of other (anticancer) drugs on

metabolism as well as drug delivery to tumors need to be investigated.

Effects of bevacizumab on [11C]docetaxel delivery to tumors

Using PET and a radiolabeled anticancer drug, it is possible to evaluate the (direct)

effects of other anticancer drugs on tumor kinetics of the radiolabeled drug. In this

regard, the effect of anti-angiogenic drugs is of special interest. Anti-angiogenic therapy

might affect the abnormal tumor vasculature in three different ways: (i) no effect at all,

(ii) excessive destruction of tumor vasculature and reduction in perfusion leading to

increased hypoxia and necrosis, (iii) or after pruning of some abnormal vessels the

structure of remaining tumor vessels may become more normal, resulting in increased

perfusion and drug delivery (50). As previously described by Jain (50), anti-angiogenic

drugs may normalize the structurally and functionally abnormal tumor vasculature,

thereby enhancing efficacy of cytotoxic drugs. Based on results of previous studies by

Jain (50,51), the next step (Chapter 8) was to investigate effects of the anti-angiogenic

drug bevacizumab on tumor uptake of [11C]docetaxel in NSCLC patients. Bevacizumab, a

monoclonal antibody that targets circulating vascular endothelial growth factor (VEGF),

appeared to reduce both perfusion and net influx rate of [11C]docetaxel within 5 hours.

These rapid effects persisted after 4 days. In line with the results of Chapter 8, a 20%

decline in fluorine-18 labeled 5-fluorouracil ([18F]5-FU) uptake was also measured in

human colorectal cancer at 24 hours after administration of bevacizumab (52). Currently,

only a few clinical studies have investigated the (early) effects of anti-angiogenic drugs

on perfusion and drug delivery in tumors. However, the results of these studies seem

conflicting (52-55), indicating that more studies are warranted to elucidate the effects of

anti-angiogenic therapy on delivery of anticancer drugs to tumors.

Animal studies may be instrumental in elucidating the mechanism by which the observed

effects could be explained. However, measuring drug uptake after anti-angiogenic

therapy in an animal model will face other limitations, such as the artificial characteristics

of a xenograft tumor model and the different effects of anti-angiogenic drugs on animal

physiology as compared to human physiology, probably resulting in different time related

effects. In addition, a clinical study in patients enables to measure effects of the anti-

149

angiogenic drug bevacizumab on the human system, including the cardiovascular

system, whereas a patient derived xenograft model in animals will not be affected by

systemic effects of bevacizumab on the animal physiology, since bevacizumab targets

human VEGF only. Animal studies may, however, be useful for investigating whether

administration of a (cytotoxic) anticancer drug prior to an anti-angiogenic drug results in

decreased clearance of the cytotoxic anticancer drug in tumors.

The results presented in Chapter 8 highlight the importance of drug scheduling for the

treatment of cancer patients. However, the impact of drug scheduling on the antitumor

efficacy usually is not investigated. With regard to drug scheduling, studies have only

shown that frequent administration of cytotoxic drugs at low doses, known as

'metronomic' chemotherapy, can increase anti-angiogenic activity of drugs (56,57). No

clinical studies have investigated the relation between the sequence of combination

schedules consisting of anti-angiogenic drugs and the efficacy in cancer patients.

Therefore, future studies should be focused on optimal scheduling of anti-angiogenic

drugs in order to improve the efficacy of combination therapy.

Future perspectives of [11C]docetaxel PET

Although, at present, [11C]docetaxel PET cannot be used on a large scale because of its

complexity and high costs, it is a promising technique for several investigations. PET

studies using both [11C]docetaxel and tracers that can show in vivo functionality of

multidrug resistance (MDR) transporters (e.g. (R)-[11C]verapamil) may provide more

insight into the role of MDR transporters in [11C]docetaxel uptake by tumors (Chapter 2).

Furthermore, effects of other (anticancer) drugs, including anti-angiogenic drugs and

inhibitors of ABCB1, on delivery of [11C]docetaxel to tumors can be explored. In

particular, [11C]docetaxel PET may help to define the optimal design of large clinical

trials to investigate the effects of drug scheduling on efficacy in cancer patients. In

addition, [11C]docetaxel PET may be useful to predict response to docetaxel therapy and

select patients for docetaxel-containing treatment strategies, thereby contributing to a

more personalized treatment planning in individual cancer patients. For these purposes,

a less complex scan protocol would be useful. In future studies, the duration of an

[11C]docetaxel PET scan could be reduced from 60 to 10 minutes, as only the first 10

minutes of the data can be used for quantification. Finally, therapeutic [11C]docetaxel

PET scans may be simplified. Assuming that plasma kinetics of [11C]docetaxel are

comparable during microdosing and therapeutic scans, plasma kinetics of [11C]docetaxel

during therapeutic infusion can be modeled by convolution of a measured bolus plasma

curve. Applying this method, preliminary data suggest that [11C]docetaxel plasma curves

150

during therapeutic infusion can be predicted on the basis of the plasma curve from the

microdosing study (Figure 5). As a result, tumor uptake of [11C]docetaxel and cold

docetaxel could be solely predicted from the [11C]docetaxel microdosing scan. Further

studies are warranted to validate this simplified concept for [11C]docetaxel and other

radiolabeled drugs.

Figure 5. Measured plasma activity concentration during therapy (open circles) as predicted (solid

line) by convolution of a measured bolus plasma curve with a modeled infusion curve (dashed line;

constant infusion reaching the patient between 10 and 70 min after start of the infusion pump,

dispersed with a mono-exponential dispersion function with a time constant of 10 min).

Conclusions

PET using radiolabeled anticancer drugs is a promising method for better guided

treatment planning in individual cancer patients. However, the development and clinical

implementation of a new radiolabeled anticancer drug is very complex and can be

challenging. In the present thesis, the novel PET tracer [11C]docetaxel was validated for

use in lung cancer patients. Human PET studies showed that [11C]docetaxel may be a

useful tracer for tumors located in the thoracic region, including breast cancer and lung

cancer. Subsequently, quantitative PET data showed irreversible kinetics of

Time after start infusion of [11C]docetaxel & therapeutic docetaxel

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ity c

once

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tion

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·mL-1

)

Time after start infusion of [11C]docetaxel & therapeutic docetaxel

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)

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[11C]docetaxel in lung tumors. In addition, PET scans using [11C]docetaxel demonstrated

that less than 1% of the therapeutic dose of docetaxel accumulated in lung tumors and

that [11C]docetaxel delivery to tumors was significantly decreased by prior administration

of the anti-angiogenic drug bevacizumab. The [11C]docetaxel PET studies presented in

this thesis provide a framework for clinical validation of the PET microdosing concept of

other radiolabeled anticancer drugs as well as for investigating effects of anti-angiogenic

drugs on drug delivery to tumors in vivo.

152

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Nederlandse samenvatting

De afgelopen jaren heeft de ontwikkeling van vele nieuwe geneesmiddelen de

behandelmogelijkheden voor patiënten met kanker aanzienlijk uitgebreid. Het grote aantal

beschikbare middelen heeft de behandeling van patiënten met kanker echter niet

vereenvoudigd. Anti-kanker middelen zijn namelijk niet effectief in een substantieel aantal

patiënten. Daarnaast gaat een behandeling met anti-kanker middelen vaak gepaard met vele

en vaak ook ernstige bijwerkingen. Daarom is er behoefte aan een techniek die kan aangeven

welke patiënten baat hebben bij een bepaalde behandeling en welke patiënten niet. Positron

emissie tomografie (PET) is een beeldvormende techniek die mogelijk waardevol is om een

geïndividualiseerd behandelplan voor patiënten met kanker op te stellen. Daartoe wordt een

tracer dosis (speurdosis) van een anti-kanker middel gelabeld (gemerkt) met een positron

emitter, zodat een anti-kanker middel met de PET scanner zichtbaar gemaakt kan worden in

het lichaam. Dergelijke radioactief gelabelde anti-kanker middelen kunnen zo worden gebruikt

om de farmacokinetiek en farmacodynamiek van geneesmiddelen niet invasief (d.w.z. via

beeldvorming) in patiënten te vervolgen. In dit proefschrift worden de validatie en

implementatie van een nieuw radioactief gelabeld anti-kanker middel, [11C]docetaxel, in

patiënten met longcarcinoom gepresenteerd.

In Hoofdstuk 1 zijn de principes van PET en de toepassingen van verscheidene PET tracers

voor de oncologie geïntroduceerd. Daarnaast werden de ontwikkeling en validatie van de

nieuwe PET tracer [11C]docetaxel in patiënten met longcarcinoom besproken.

In Hoofdstuk 2 is beschreven hoe PET scans en radioactief gelabelde anti-kanker middelen

resistentie in tumoren kunnen voorspellen. In dit hoofdstuk werd besproken hoe PET gebruikt

kan worden om resistentiemechanismen te onderzoeken. Tot de mechanismen die bijdragen

aan resistentie voor geneesmiddelen behoren de verdeling van geneesmiddelen in het lichaam,

de beschikbaarheid van geneesmiddelen in de circulatie en het transport van geneesmiddelen

naar tumoren. In dat kader werden de reeds gelabelde anti-kanker middelen en hun huidige

klinische toepassing besproken. Er werd geconcludeerd dat het gebruik van gelabelde anti-

kanker middelen (bijvoorbeeld [18F]paclitaxel and [18F]fluorouracil) een unieke techniek is om

de behandeling van patiënten met kanker te individualiseren. Daarnaast kan het radioactief

labelen van anti-kanker middelen een rol spelen bij de ontwikkeling van nieuwe

geneesmiddelen. In dit hoofdstuk werd ook besproken dat het combineren van deze specifieke

PET tracers met andere minder specifieke tracers, zoals tracers voor doorbloeding

(bijvoorbeeld radioactief gelabeld water; [15O]H2O) en efflux transporters (bijvoorbeeld

[11C]verapamil), aanvullende informatie kunnen verschaffen over de mechanismen die

betrokken zijn bij de resistentie tegen anti-kanker middelen. Tenslotte werd in dit hoofdstuk

besproken dat gelabelde anti-kanker middelen nuttig zouden kunnen zijn om het optimale

tijdstip van toediening voor combinatietherapie te bepalen.

In Hoofdstuk 3 werd de reproduceerbaarheid van dynamische [15O]H2O PET/CT scans

onderzocht. Met deze PET scans kan de doorbloeding (ook wel perfusie genoemd) in tumoren

worden gemeten. Dit is van belang, aangezien de tumorperfusie het transport van gelabelde

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anti-kanker middelen naar tumoren mogelijk kan beïnvloeden. Daarnaast werd in dit hoofdstuk

de kwantitatieve nauwkeurigheid van de parametrische perfusiebeelden van de [15O]H2O PET

scans gevalideerd. Daartoe ondergingen elf patiënten met een niet-kleincellig longcarcinoom

twee dynamische [15O]H2O PET scans op dezelfde dag. Deze validatiestudie toonde aan dat

voor het kwantificeren van tumorperfusie de zogenaamde image derived input function (IDIF)

een accuraat alternatief is voor arteriële bloedafnames. Een IDIF is gebaseerd op de afbeelding

van de aorta ascendens in de PET scan en is daarom een niet-invasieve methode om de

arteriële input te meten. Daarnaast werd in dit hoofdstuk aangetoond dat de verkregen

beeldkwaliteit van de klinische PET/CT scanner het mogelijk maakt om goede parametrische

perfusiebeelden te genereren. Volumes of interest (VOIs) die werden ingetekend op

computertomografie scans hadden de hoogste reproduceerbaarheid. Op basis van de

reproduceerbaarheid werd geconcludeerd dat veranderingen van meer dan 16% in

tumorperfusie beschouwd mogen worden als een effect van een behandeling.

Hoofdstukken 4 tot en met 7 zijn gewijd aan de achtereenvolgende stappen die werden

genomen om de nieuwe tracer [11C]docetaxel in klinische PET-studies te gebruiken en te

valideren.

In Hoofdstuk 4 werd de biodistributie van [11C]docetaxel in gezonde mannetjesratten bepaald

op 5, 15, 30 en 60 minuten na injectie. Deze preklinische studie toonde aan dat [11C]docetaxel

de hoogste opname heeft in achtereenvolgens de milt, de urine, de longen en de lever. In de

hersenen en de testes werd daarentegen een zeer lage [11C]docetaxel opname gemeten.

Binnen minder dan 5 minuten was [11C]docetaxel bijna volledig geklaard uit zowel het bloed

als het plasma. Deze preklinische studie was vereist voor de medische ethische commissie,

zodat de verwachte stralingsbelasting voor mensen kon worden geschat.

In Hoofstuk 5 werden met whole body PET/CT scans de biodistributie en de dosimetrie van

[11C]docetaxel bepaald in seven patiënten met solide tumoren. In de galblaas en de lever

werden hoge [11C]docetaxel concentraties gemeten, terwijl de accumulatie in de hersenen en

normaal longweefsel laag was. Al na 1 uur bevond bijna de helft, namelijk 47 ± 9%, van de

geïnjecteerde dosis zich in de lever. [11C]docetaxel werd snel geklaard uit het plasma en er

werden geen radioactief gelabelde metabolieten gedetecteerd in het perifere bloed. De opname

van [11C]docetaxel in tumoren was beperkt en zeer variabel tussen de verschillende tumoren.

Op basis van de resultaten van deze studie werd de effectieve dosis van [11C]docetaxel

berekend op 4.7 Sv·MBq-1. In tegenstelling tot de eerdere studie in ratten, was de opname

van [11C]docetaxel in de longen laag. Op basis van de studie in patiënten werd geconcludeerd

dat [11C]docetaxel een veelbelovende PET tracer zou kunnen zijn voor tumoren in de thoracale

regio.

In Hoofdstuk 6 werd onderzocht in hoeverre het gebruik van kwantitatieve [11C]docetaxel

scans haalbaar is in patiënten met longcarcinoom. Daarnaast werd onderzocht of de kinetiek

van [11C]docetaxel geassocieerd was met de perfusie en de grootte van tumoren. Tevens werd

onderzocht of de inname van dexamethason, een middel dat in de klinische praktijk als

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premedicatie voor docetaxel wordt gegeven, de opname van [11C]docetaxel in tumoren zou

. In deze studie ondergingen 34 patiënten met longcarcinoom dynamische

PET-CT scans met [11C]docetaxel en [15O]H2O. De eerste 24 patiënten kregen voorafgaand aan

de PET scans dexamethason toegediend. Om de kinetiek van [11C]docetaxel te kwantificeren

werd eerst het optimale kinetische model ontwikkeld. De kinetiek van [11C]docetaxel in

tumoren bleek irreversibel en kon goed worden gekwantificeerd met de zogenaamde Patlak

methode. Verder werd vastgesteld dat het gebruik van een IDIF resulteerde in een goede

reproduceerbaarheid van de metingen in tumoren. De netto influx (Ki) van [11C]docetaxel in

tumoren bleek variabel en was sterk gerelateerd aan de perfusie, maar niet aan de grootte van

tumoren. Daarnaast hadden patiënten die waren voorbehandeld met dexamethason, een

middel dat de efflux transporter ABCB1 activeert, een lagere [11C]docetaxel opname in

tumoren. Een subgroep van de patiënten werd ook behandeld met docetaxel. In deze subgroep

leek een relatief hoge [11C]docetaxel opname in de tumor gerelateerd aan een betere respons

van de tumor op docetaxel. In dit hoofdstuk werd geconcludeerd dat het kwantificeren van de

kinetiek van [11C]docetaxel in longcarcinoom goed haalbaar is in de klinische setting. Verder

zou de inter-tumorale variatie in opname van [11C]docetaxel een verschillende gevoeligheid

voor een behandeling met docetaxel kunnen weerspiegelen.

Aangezien de farmacokinetiek van een tracer dosis [11C]docetaxel verschillend zou kunnen zijn

van een therapeutische dosis docetaxel, werd in Hoofdstuk 7 het zogenaamde concept van

microdosering gevalideerd voor [11C]docetaxel. In dit hoofdstuk werd uitgezocht of het

mogelijk is om met een tracerdosering van [11C]docetaxel de opname van ongelabeld (koud)

docetaxel in tumoren te voorspellen tijdens een infusie met een therapeutische dosis

docetaxel. Daartoe ondergingen patiënten met longcarcinoom, die niet eerder waren

behandeld met docetaxel, twee PET scans: één na een bolus injectie met een tracerdosering

van [11C]docetaxel en een andere tijdens een gecombineerde infusie van de tracerdosering van

[11C]docetaxel met een therapeutische dosis van docetaxel (75 mg·m-2). Compartimenten- en

spectraal-analyses werden gebruikt om de kinetiek van [11C]docetaxel in tumoren te

kwantificeren. Daarnaast werd de area under the curve (AUCTumor; oppervlakte onder de curve)

van koud docetaxel in tumoren geschat. Tijdens de tracer (microdosis) scan en de

therapeutische scan was de Ki van [11C]docetaxel in tumoren vergelijkbaar. Door gebruik te

maken van een zogenaamde impulse response function, die was gebaseerd op de metingen

tijdens de tracer (microdosis) scan en de [11C]docetaxel plasmacurve tijdens de therapeutische

scan, was het mogelijk om de AUCTumor van [11C]docetaxel gedurende de therapeutische scan

betrouwbaar te schatten. Na 90 minuten was de geaccumuleerde hoeveelheid koud docetaxel

in tumoren < 1% van de totale toegediende therapeutische dosis. De Ki van [11C]docetaxel van

de microdosering scan correleerde zowel met de AUCTumor van koud docetaxel tijdens de

therapeutische scan als met de respons van de tumor op de behandeling met docetaxel. Op

basis van deze resultaten werd geconcludeerd dat de data van de microdosering scan

inderdaad gebruikt kunnen worden om de opname van koud docetaxel in tumoren te

voorspellen gedurende de chemotherapie. De studie in dit hoofdstuk verstrekt een kader

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waarin het concept van microdosering met niet invasieve PET scans voor andere radioactief

gelabelde anti-kanker middelen in patiënten onderzocht kan worden.

In Hoofdstuk 8 werden de effecten van de angiogeneseremmer (vaatremmer) bevacizumab

onderzocht op de perfusie en opname van [11C]docetaxel in longtumoren. Bevacizumab is een

humaan monoklonaal antilichaam dat gericht is tegen de circulerende vasculaire endotheliale

groeifactor (VEGF) en zo voorkomt dat VEGF kan binden aan de VEGF receptor. Verondersteld

wordt dat angiogeneseremmers, zoals bevacizumab, tijdelijk het abnormale tumorvaatstelsel

normaliseren en zo bijdragen aan een verbeterd transport van de daarna gegeven

chemotherapie. Om dit concept te onderzoeken werd er een PET-studie verricht bij patiënten

met een niet-kleincellig longcarcinoom. Al binnen vijf uur na toediening van bevacizumab

namen zowel de perfusie als de opname van [11C]docetaxel significant af. Deze effecten waren

na vier dagen ook nog steeds duidelijk aanwezig en waren niet geassocieerd met significante

veranderingen in de heterogeniteit van [11C]docetaxel opname in tumoren. De verminderde

opname van [11C]docetaxel ging samen met een snelle afname in de hoeveelheid circulerend

VEGF in het bloed. Deze veranderingen waren echter niet geassocieerd met systemische

veranderingen in cardiovasculaire parameters, zoals bloeddruk, hart-minuutvolume en

capillaire dichtheid in de huid. De klinische relevantie van deze bevindingen is belangrijk,

aangezien er geen aanwijzingen zijn gevonden dat bevacizumab het transport van

chemotherapie naar tumoren verbetert. Het is belangrijk dat toekomstig onderzoek zich richt

op het bepalen van de optimale tijdstippen voor de toediening van angiogeneseremmers, zodat

deze middelen zo effectief mogelijk kunnen worden ingezet voor de behandeling van patiënten

met een maligniteit.

Concluderend is het gebruik van radioactief gelabelde anti-kanker middelen een veelbelovende

techniek om een meer specifieke behandeling voor individuele patiënten met kanker te

realiseren. In dit proefschrift werd de nieuwe PET tracer [11C]docetaxel gevalideerd in

patiënten met longcarcinoom. PET studies in patiënten lieten zien dat [11C]docetaxel mogelijk

een nuttige tracer is voor tumoren in de thoracale regio, zoals mammacarcinoom en

longcarcinoom. De opname van [11C]docetaxel in longtumoren was goed te meten. Er werd

geschat dat uiteindelijk minder dan 1% van de toegediende therapeutische dosis van docetaxel

in tumoren accumuleert. Daarnaast daalde de opname van [11C]docetaxel in tumoren wanneer

de angiogeneseremmer bevacizumab werd toegediend. De studies met [11C]docetaxel in dit

proefschrift bieden een goed raamwerk voor de klinische validatie van andere gelabelde anti-

kanker middelen. Op basis van de resultaten in Hoofdstuk 8 kan verder worden geconcludeerd

dat de effecten van angiogeneseremmers op het transport van chemotherapie naar tumoren

verder onderzocht dienen te worden.

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Dankwoord

DANKWOORD

Dit proefschrift is tot stand gekomen met de hulp en inspanning van vele mensen. Hierbij

wil ik iedereen bedanken voor alle hulp en betrokkenheid in de afgelopen jaren. Een

aantal personen wil ik graag in het bijzonder bedanken en ik hoop dat ik daarbij niemand

zal vergeten.

Allereerst wil ik de patiënten bedanken die hebben deelgenomen aan dit onderzoek. In

voor hen moeilijke tijden waren zij bereid om belangeloos deel te nemen aan de

intensieve studies bestaande uit uitgebreide PET scans en extra bloedafnames.

Verder wil ik mijn promotoren en co-promotoren bedanken. Prof. dr. A.A. Lammertsma,

beste Adriaan, hartelijk dank voor de mogelijkheden die je me hebt geboden om dit

klinische onderzoek met [11C]docetaxel uit te voeren. Jouw precisie en kennis over PET

modeling zijn niet te evenaren. Ik heb veel van je geleerd. Prof. dr. E.F. Smit, beste

Egbert, bedankt voor de goede samenwerking en je hulp bij het klinische aspect van de

studies. Ik heb veel geleerd van je slimme en nuchtere benadering van vraagstukken.

Dr. ir. M. Lubberink, beste Mark, bedankt voor je onmisbare hulp en begeleiding bij de

complexe studies. Alles in deze studies was nieuw en vaak zat het tegen. Toch lukte het

je keer op keer weer om een mooi Matlab programma te schrijven, zodat de data toch

geanalyseerd konden worden. Dr. N.H. Hendrikse, beste Harry, hartelijk dank voor je

betrokkenheid als ziekenhuisapotheker en co-promotor bij dit project.

Leden van de leescommissie, prof. dr. J.A. Gietema, dr. A.M. Dingemans, dr. ir. J.J.M van

der Hoeven, prof. dr. H.M.W. Verheul en prof. dr. G.A.M.S. van Dongen wil ik bedanken

voor de tijd die ze hebben genomen om dit proefschrift te beoordelen. Dear prof. dr. M.

Bergström, thank you very much for your willingness to evaluate my thesis.

Van de ontwikkeling en productie van een nieuwe PET tracer tot de toediening aan

patiënten en de analyse van de data zijn vele disciplines betrokken. Ik wil alle

medewerkers van de afdeling Nucleaire Geneeskunde & PET Research bedanken voor hun

bijdrage.

De medewerkers van het radionuclidencentrum (RNC) wil ik bedanken voor de productie

van [11C]docetaxel. Bert Windhorst en Jonas Eriksson, veel dank voor jullie hulp bij de

synthese van [11C]docetaxel. In het bijzonder wil ik Martien Mooijer, Anneloes Rijnders

en Dennis Laan bedanken voor hun inspanningen bij de productie van deze complexe

tracer. Wanneer de synthese tegenviel, waren jullie bereid om ’s avonds opnieuw

169

[11C]docetaxel te maken. Ik ben jullie daar dankbaar voor. Erika van Tilburg, hartelijk

dank voor alle jaren voorwerk waarin het je is gelukt om docetaxel te labelen. Ab Geldof,

beste Ab, bedankt voor je hulp en gezelligheid op het lab.

Suzette van Balen, Amina Elouahmani, Esther Bakker, Judith van Es, Robin Hemminga,

Femke Jongsma, Rob Koopmans, Nghi Pham, Nasserah Sais, Annemiek Stiekema en

Jeroen Wilhelmus, veel dank voor jullie grote inspanningen bij het scannen van de

patiënten. Tevens wil ik jullie bedanken voor de vele gezellige momenten in de

koffiekamer.

Henri Greuter, Gert Luurtsema, Marissa Rongen, Robert Schuit en Kevin Takkenkamp,

hartelijk dank voor de analyse van de grote hoeveelheden samples. Henri, bedankt voor

je betrokkenheid en enorme inzet bij de validatie van de samples. Ik ben onder de indruk

van je mooie Excel bestanden.

Alle nucleair geneeskundigen van de afdeling Nucleaire Geneeskunde & PET Research,

veel dank voor jullie ‘extra handen’ als het nodig was. Emile Comans, bedankt dat je met

je ongekende enthousiasme altijd klaarstond om te helpen. Annelies van Schie, bedankt

voor je hulp bij het chemotherapieprotocol van hoofdstuk 7. Pieter Raijmakers, dank voor

je betrokkenheid en inspirerende gesprekken over studies. Otto Hoekstra, bedankt voor

de mogelijkheden en de vrijheid die je me op de afdeling hebt gegeven om de

[11C]docetaxel studies uit te voeren. Daniela Oprea-Lager, Sandra Srbljin en Nafees

Rizvi, veel dank voor jullie betrokkenheid en de vele gezellige momenten.

De fysici van de afdeling Nucleaire Geneeskunde & PET Research en de medewerkers van

de afdeling Fysica en Medische Technologie (FMT): Ronald Boellaard, Dennis Boersma,

Marc Huisman, Arthur van Lingen, Floris van Velden en Maqsood Yaqub, bedankt voor

jullie technische ondersteuning. Arthur van Lingen, bedankt voor de gezellige momenten

en al je hulp bij het optimaliseren van de logistiek rondom de PET scans.

Amanda Kroonenberg, dank voor je hulp bij de volle agenda’s en niet te vergeten de

gezellige kopjes thee. Jaap van der Kuij, dank voor je hulp als ik weer eens aanklopte

met de bekende formuliertjes.

Medewerkers van de afdeling Longziekten, bedankt voor het mogelijk maken van de

studies. Prof. dr. P.E. Postmus en Idris Bahce, hartelijk dank voor de prettige

samenwerking. Atie van Wijk, veel dank voor je hulp bij de vele aspecten van de studies.

Je hebt me enorm geholpen. Natasja Kok, Ilona Pomstra, Sabri Duzenli, Martijn

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alle verpleegkundigen en

voedingsassistenten van de afdeling Longziekten, hartelijk dank voor jullie hulp bij de

uitvoering van de studies.

De afdeling Vasculaire Geneeskunde: Erik Serné en Michiel de Boer, bedankt voor de

vruchtbare samenwerking welke heeft geleid tot een kruisbestuiving tussen twee

proefschriften.

De afdeling Geneeskundige Oncologie: Henk Verheul, Maudy Walraven en Henk Dekker,

hartelijk dank voor de goede samenwerking en het mogelijk maken van de VEGF

metingen.

Bart Kuenen, bedankt voor de inspirerende gesprekken. Jaren geleden stond je aan de

‘wieg’ van de studie in hoofdstuk 8. Veel dank voor je steun en enthousiasme destijds om

deze studie op te zetten.

Judith Herder, Hugo Rutten en Ilse Vermeltfoort, veel dank voor jullie inzet om patiënten

van Nieuwegein tot Roosendaal te includeren voor de studies.

Ron Mathijssen en Walter Loos, bedankt voor de prettige en stimulerende samenwerking.

Dank voor het meten van de spiegels van koud docetaxel in Rotterdam.

Kamergenoten en collega-onderzoekers van de afdeling Nucleaire Geneeskunde & PET

Research: Christel Admiraal, Daniëlle Assema, Idris Bahce, Weena Chen, Ghislaine

Mulder, Virginie Frings, Femke Froklage, Larissa van Golen, Hans Harms, Cemile Karga,

Joop de Langen, Joline Lind, Patricia McCarthy, Luuk Rijzewijk, Nelleke Tolboom en Yeun

Ying Wong, dank voor jullie interesse, discussies en gezelligheid. Naast vele van jullie

heb ik vele dagen PET scans zitten intekenen. Dankzij jullie aanwezigheid was het

intekenen een stuk leuker!

Decaan, prof. dr. W. Stalman, dank voor de mogelijkheid die u mij hebt geboden om

beide promoties af te ronden en te verdedigen. Hartelijk dank voor uw hulp bij de

tijdsplanning van de promoties.

Prof. dr. P.C. Huijgens, beste Peter, bedankt voor je wijze raad.

Prof. dr. M.H.H. Kramer en prof. dr. S.A. Danner van de afdeling Interne Geneeskunde,

hartelijk dank voor de mogelijkheden en de vrijheid die jullie mij hebben gegeven om me

op het wetenschappelijk onderzoek te kunnen richten.

171

Opleiders en stafleden van de afdeling Interne Geneeskunde in het VUmc, dank voor de

stimulerende omgeving en prettige sfeer waarin ik word opgeleid. De afdelingen

Longziekten en Maag-, Darm-, en Leverziekten wil ik ook bedanken voor de leerzame en

leuke stages het afgelopen jaar. Collegae AIOS van de afdeling Interne Geneeskunde,

dank voor de plezierige samenwerking en jullie interesse in mijn onderzoek. Van de

polikliniek wil ik zowel de supervisoren, Erik Serné, Frans Claessen en Prabath

Nanayakkara als de andere AIOS bedanken voor hun interesse en steun tijdens de

laatste fase van mijn promoties.

Guusje Bertholet, veel dank voor de mooie illustraties. Ik heb het als zeer prettig ervaren

om met je samen te werken.

Collega-onderzoekers van de afdeling cardiologie: Wessel Brouwer, Stefan de Haan,

Gerjan de Roest, Lourens Robbers, Jeroen Slikkerveer en LiNa Wu, dank voor de

gezelligheid en de vele gezellige maaltijden in (en buiten) het personeelsrestaurant.

Johan Karreman, veel dank voor je gastvrijheid en hulp op 4D.

Lotty Hooft, lieve Lotty, ooit begon ik als student samen met jou op het lab. Ik heb veel

van je geleerd, maar het was ook altijd heel gezellig: van kleuringen op het lab tot een

reisje naar Japan. Bedankt voor de leuke momenten samen.

Wieteke Direcks en Natalie Proost, lieve Wieteke en Natalie, veel dank voor jullie

vriendschap en gezellige momenten.

op 3A-18

gehad. Dank voor de mooie tijd en de vele koffietjes. Veel succes met jullie nu al mooie

carrière. Lieve Hester en Michiel, veel geluk in jullie nieuwe huis, samen met jullie kleine

jongen.

Vrienden uit Antwerpen: lieve Ingeborg en Gijs, ook al ging ik naar Amsterdam en bleven

jullie in ‘het zuiden’, ik ben jullie niet vergeten! Bedankt voor jullie vriendschap.

Lieve Corinne en Dorota, dank voor jullie vriendschap en gezellige avondjes samen eten.

Corinne, je bent een zonnetje, want altijd lukt het je om iedereen op te vrolijken.

Mijn studievrienden en onderzoekmaatjes: Tji-Joong Gan en Louis Handoko, bedankt

voor de vele gezellige en inspirerende momenten. We hebben alle drie voor een ander

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specialisme gekozen, maar longziekten, cardiologie, en interne geneeskunde hebben vele

raakvlakken…

Lieve Louise, dank voor je vriendschap. Ik vind het jammer dat je voorgoed naar Parijs

bent verhuisd, maar dat mag de pret niet drukken. Ik kom snel weer naar Parijs.

Jessica Oudhof, lieve Jessica, in de tweede klas van het gymnasium, tijdens de repetities

Grieks, werden we vriendinnen en dat zijn we tot de dag van vandaag gebleven. Bedankt

daarvoor!

Irene Klaassen, lieve, Irene, meer dan 15 jaar geleden ontmoetten we elkaar op

zeilkamp in Friesland en jaren later studeerden we samen in Amsterdam. Veel dank voor

je vriendschap en steun in moeilijke tijden.

Lieve Irene en Corinne, bedankt dat jullie op deze bijzondere dag naast mij willen staan!

Families Kleijn en Mijnhout: lieve Mieke, Ruud, Irma, Ramón, Mikkie, Noah en Moos, veel

dank voor jullie interesse en gezelligheid in de afgelopen jaren.

Lieve Han en Aad, veel dank voor jullie steun en belangstelling.

Mijn lieve zus, Michaela, ik ben heel trots op je en ik wens je veel succes met je plannen

in Afrika.

Lieve papa, veel dank voor je belangstelling en de mogelijkheden die je me hebt geboden

om te studeren. Lieve mama, jouw steun en onvoorwaardelijke liefde zijn nog steeds

voelbaar. Helaas heb je niet meer kunnen meemaken wat ik na mijn studie geneeskunde

ben gaan doen. Hopelijk kun je ergens op een wolk toch nog meegenieten.

Allerliefste Sebastiaan, gedurende mijn hele promotie stond je aan mijn zijde. Dankzij

jouw steun en liefde waren tegenslagen veel minder zwaar. Soms hebben we weinig tijd

voor elkaar gehad, maar daar gaat nu verandering in komen. Ik hou veel van je!

173

Curriculum vitae

CURRICULUM VITAE

Astrid Aplonia Maria van der Veldt was born on March 14th 1979 in Rotterdam, the

Netherlands. After graduating from secondary school (gymnasium, Christelijk Lyceum

Almelo) in 1997, she studied medicine at the University of Antwerp in Belgium. In 1999,

she was allowed to study medicine in the Netherlands and she started her study at the

VU University in Amsterdam. During her study, she participated in the ‘VUmc Honours

Programme’. In addition, she worked as a student assistant on the research project

entitled ‘FDG PET in detecting recurrent cervical cancer’ at the Department of Nuclear

Medicine & PET Research of the VU University Medical Center under supervision of dr.

C.F.M. Molthoff and prof. dr. O.S. Hoekstra. In February 2006, she graduated from

medical school with honors. From 2006 to 2007, she worked as a research fellow at the

Department of Medical Oncology of the VU University Medical Center. In this period, she

investigated the clinical and pharmacodynamic aspects of sunitinib for advanced renal

cell cancer under supervision of prof. dr. E. Boven, prof. dr. J.B.A.G. Haanen, and dr.

A.J.M. van den Eertwegh. For this research project, she also worked at the Department

of Medical Oncology of The Netherlands Cancer Institute, Antoni van Leeuwenhoek

Hospital, Amsterdam, the Netherlands. In 2007, she started her PhD project on

[11C]docetaxel in lung cancer at the Department of Nuclear Medicine & PET Research of

the VU University Medical Center under supervision of prof. dr. A.A. Lammertsma, prof.

dr. E.F. Smit, dr. ir. M. Lubberink, and dr. N.H. Hendrikse. In this period, she continued

her previous research on sunitinib for advanced renal cell cancer. For her research

projects, she received several awards including the Merit Award of the American Society

of Clinical Oncology and the Chris Meijer Award of the CCA/V-ICI. In January 2011, she

started her specialization in Internal Medicine at the Department of Internal Medicine of

the VU University Medical Center, headed by prof. dr. M.H.H. Kramer. The research

projects performed at the Departments of Medical Oncology and Nuclear Medicine & PET

Research have resulted in a double dissertation consisting of two different theses entitled

‘Sunitinib for advanced renal cell cancer – clinical and pharmacodynamic aspects’ and

‘Towards personalized treatment planning of chemotherapy: [11C]docetaxel PET studies

in lung cancer patients’, respectively. In the future, Astrid hopes to combine patient care

with scientific research.

177

Publications

PUBLICATIONS

1. Hooft L, Van der Veldt AA, Van Diest PJ, Hoekstra OS, Berkhof J, Teule GJ, Molthoff CF.

[18F]fluorodeoxyglucose uptake in recurrent thyroid cancer is related to hexokinase i

expression in the primary tumor. J Clin Endocrinol Metab 2005;90:328-34.

2. Van der Veldt AA, Hooft L, Van Diest PJ, Berkhof J, Buist MR, Comans EF, Hoekstra OS,

Molthoff CF. Microvessel density and p53 in detecting cervical cancer by FDG PET in cases of

suspected recurrence. Eur J Nucl Med Mol Imaging 2006;33:1408-16.

3. Van der Veldt AA, Hadithi M, Paul MA, Van den Berg FG, Mulder CJ, Craanen ME. An unusual

cause of hematemesis: Goiter. World J Gastroenterol 2006;12:5412-5.

4. Van der Veldt AA, Kleijn SA, Pernet PJ, Oostra RJ, Jansweijer MC. Unilateral partial absence of

the fallopian tube in Williams syndrome: a new feature? Clin Dysmorphol 2007;16:195-6.

5. Van der Veldt AA, Van den Eertwegh AJ, Boven E. Adverse effects of the tyrosine-kinase

inhibitor sunitinib, a new drug for the treatment of advanced renal-cell cancer. Ned Tijdschr

Geneeskd 2007;151:1142-7.

6. Hooft L, Van der Veldt AA, Hoekstra OS, Boers M, Molthoff CF, Van Diest PJ. Hexokinase III,

cyclin A and galectin-3 are overexpressed in malignant follicular thyroid nodules. Clin

Endocrinol 2008;68:252-7.

7. Van der Veldt AA, Van den Eertwegh AJ, Hoekman K, Barkhof F, Boven E. Reversible cognitive

disorders after sunitinib for advanced renal cell cancer in patients with preexisting

arteriosclerotic leukoencephalopathy. Ann Oncol 2007;18:1747-50.

8. Nanayakkara PW, Van der Veldt AA, Simsek S, Smulders YM, Rauwerda JA. Verapamil-induced

erythermalgia. Neth J Med 2007;65:349-51.

9. Van der Veldt AA, Lammertsma AA, Hendrikse NH. [11C]Docetaxel and positron emission

tomography for noninvasive measurements of docetaxel kinetics. Clin Cancer Res 2007;

13:7522.

10. Helgason HH, Mallo HA, Droogendijk H, Haanen JG, Van der Veldt AA, Van den Eertwegh AJ,

Boven E. Brain metastases in patients with renal cell cancer receiving new targeted treatment.

J Clin Oncol 2008;26:152-4.

11. Van der Veldt AA, Meijerink MR, Van den Eertwegh AJ, Bex A, De Gast G, Haanen JB, Boven E.

Sunitinib for treatment of advanced renal cell cancer: primary tumor response. Clin Cancer

Res 2008;14:2431-6.

181

12. Van der Veldt AA, Boven E, Helgason HH, Van Wouwe M, Berkhof J, De Gast G, Mallo H, Tillier

CN, Van den Eertwegh AJ, Haanen JB. Predictive factors for severe toxicity of sunitinib in

unselected patients with advanced renal cell cancer. Br J Cancer 2008; 99:259-65.

13. Van der Veldt AA, Van Wouwe M, Van den Eertwegh AJ, Van Moorselaar RJ, Van Geijn HP.

Metastatic renal cell cancer in a 20-year-old pregnant woman. Urology 2008;72:775.

14. Hendrikse NH, Luurtsema G, Van der Veldt AA, Lubberink M. Positron emission tomography for

modeling pathophysiological processes in vivo. Curr Opin Drug Discov Devel 2008;11:717-25.

15. Van Cruijsen H, Van der Veldt AA, Vroling L, Oosterhoff D, Broxterman HJ, Scheper RJ,

Giaccone G, Haanen JB, Van den Eertwegh AJ, Boven E, Hoekman K, De Gruijl TD. Sunitinib-

induced myeloid lineage redistribution in renal cell cancer patients: CD1c+ dendritic cell

frequency predicts progression-free survival. Clin Cancer Res 2008; 14:5884-5892.

16. Van der Veldt AA, Luurtsema G, Lubberink M, Lammertsma AA, Hendrikse NH. Individualized

treatment planning in oncology: role of PET and radiolabelled anticancer drugs in predicting

tumour resistance. Curr Pharm Des 2008;14:2914-31.

17. Van der Veldt AA, Buist MR, Van Baal MW, Comans EF, Hoekstra OS, Molthoff CF. Clarifying the

diagnosis of clinically suspicious recurrent cervical cancer: impact of 18F-FDG PET. J Nucl Med

2008;49:1936-43.

18. Bex A, Van der Veldt AA, Blank C, Van den Eertwegh AJ, Boven E, Horenblas S, Haanen JB.

Neoadjuvant sunitinib for surgically complex advanced renal cell cancer of doubtful

resectability: initial experience with downsizing to reconsider cytoreductive surgery. World J

Urol 2009;27:533-9.

19. Van der Veldt AA, Boven E, Vroling L, Broxterman HJ, Van den Eertwegh AJ, Haanen JB.

Sunitinib-induced hemoglobin changes are related to the dosing schedule. J Clin Oncol

2009;27:1339-40.

20. Vroling L, Van der Veldt AA, De Haas RR, Haanen JB, Schuurhuis GJ, Kuik DJ, Van Cruijsen H,

Verheul HM, Van den Eertwegh AJ, Hoekman K, Boven E, Van Hinsbergh VW, Broxterman HJ.

Increased numbers of small circulating endothelial cells in renal cell cancer patients treated

with sunitinib. Angiogenesis 2009;12:69-79.

21. Van Cruijsen H, Van der Veldt AA, Hoekman K. Tyrosine kinase inhibitors of VEGF receptors:

clinical issues and remaining questions. Front Biosci 2009;14:2248-2268.

182

22. Van der Veldt AA, Kleijn SA, Nanayakkara PW. Silicone breast implants and anaplastic large T-

cell lymphoma. JAMA 2009;301:1227.

23. Van der Veldt AA, Boven E, Bex A. Re: Response of the primary tumor to neoadjuvant

sunitinib in patients with advanced renal cell carcinoma. AA Thomas, BI Rini, BR Lane, J

Garcia, R Dreicer, E A Klein, AC Novick and SC Campbell. J Urol 2009;181:518-523.

24. Van Erp NP, Eechoute K, Van der Veldt AA, Haanen JB, Reyners AK, Mathijssen RH, Boven E,

Van der Straaten T, Baak-Pablo R, Wessels JA, Guchelaar HJ, Gelderblom H. Pharmacogenetic

pathway analysis for determination of sunitinib-induced toxicity. J Clin Oncol 2009;27:4406-

12.

25. Van der Veldt AA, De Boer MP, Boven E, Eringa EC, Van den Eertwegh AJ, Van Hinsbergh VW,

Smulders YM, Serné EH. Reduction in skin microvascular density and changes in vessel

morphology in patients treated with sunitinib. Anticancer Drugs 2010;21:439-46.

26. Van der Veldt AA, Comans EF, Thunnissen FB, Hendrikse NH, Smit EF, Van der Hoeven JJ. Re:

Sarcoid-like reaction to malignancy on whole-body integrated 18F-FDG PET/CT: prevalence

and disease pattern. Clin Radiol 2010;65:94-6.

27. Bex A, Van der Veldt AA, Blank C, Meijerink MR, Boven E, Haanen JB. Progression of a caval

vein thrombus in two patients with primary renal cell carcinoma on pretreatment with

sunitinib. Acta Oncol 2010;49:520-3.

28. Van der Veldt AA, Meijerink MR, Van den Eertwegh AJ, Haanen JB, Boven E. Choi response

criteria for early prediction of clinical outcome in patients with metastatic renal cell cancer

treated with sunitinib. Br J Cancer 2010;102:803-9.

29. Bex A, Van der Veldt AA, Boven E, Haanen JB. Re: Surgical resection of renal cell carcinoma

after targeted therapy. AA Thomas, BI Rini, AJ Stephenson, JA Garcia, A Fergany, V

Krishnamurthi, AC Novick, IS Gill, EA Klein, M Zhou and SC Campbell. J Urol 2010;183:1646-

7.

30. Van Schaik AM, Kleijn SA, Van der Veldt AA, Van Tilburg W. Te veel dokters kiezen de dood.

Medisch Contact 2010;25:1218-1220.

31. Van der Veldt AA, Hendrikse NH, Smit EF, Mooijer MP, Rijnders AY, Gerritsen WR, Van der

Hoeven JJ, Windhorst AD, Lammertsma AA, Lubberink M. Biodistribution and radiation

dosimetry of (11)C-labelled docetaxel in cancer patients. Eur J Nucl Med Mol Imaging

2010;37:1950-8.

183

32. De Boer MP, Van der Veldt AA, Lankheet NA, Wijnstok NJ, Van den Eertwegh AJ, Boven E,

Serné EH. Sunitinib-induced reduction in skin microvascular density is a reversible

phenomenon. Ann Oncol 2010;21:1923-4.

33. Van der Veldt AA, Meijerink MR, Van den Eertwegh AJ, Boven E. Targeted therapies in renal

cell cancer: recent developments in imaging. Target Oncol 2010;5:95-112.

34. Van Erp NP, Mathijssen RH, Van der Veldt AA, Haanen JB, Reyners AK, Eechoute K, Boven E,

Wessels JA, Guchelaar HJ, Gelderblom H. Myelosuppression by sunitinib is flt-3 genotype

dependent. Br J Cancer 2010;103:757-8.

35. Meijerink MR, Van Waesberghe JH, Van Schaik C, Boven E, Van der Veldt AA, Van den Tol P,

Meijer S, Van Kuijk C. Perfusion CT and US of colorectal cancer liver metastases: a correlative

study of two dynamic imaging modalities. Ultrasound Med & Biol 2010;36;1626-36.

36. Kleijn S, Van der Veldt A. An entirely subcutaneous implantable cardioverter–defibrillator.

N Engl J Med 2010;363:1577.

37. Van der Veldt AA, Hendrikse NH, Harms HJ, Comans EF, Postmus PE, Smit EF, Lammertsma AA,

Lubberink M. Quantitative parametric perfusion images using 15O-labeled water and a clinical

PET/CT scanner: test-retest variability in lung cancer. J Nucl Med 2010;51:1684-90.

38. Van der Veldt AA, E Boven. Responsmeting bij patiënten met niercelcarcinoom tijdens

behandeling met angiogeneseremmers. Angiogenese Journaal 2010.

39. Van der Veldt AA, Haanen JB, Van den Eertwegh AJ, Boven E. Targeted therapy for renal cell

cancer: current perspectives. Discov Med 2010;10:394-405.

40. Van der Veldt AA, Eechoute K, Gelderblom H, Gietema J, Guchelaar HJ, Van Erp NP, Van den

Eertwegh AJ, Haanen JB, Mathijssen RH, Wessels JA. Genetic polymorphisms associated with a

prolonged progression-free survival in patients with metastatic renal cell cancer treated with

sunitinib. Clin Cancer Res 2011;17:620-9.

41. Van der Veldt AA, Kleijn SA. Advances in pancreatic neuroendocrine tumor treatment. N Engl J

Med 2011;364:1873.

42. Boven E, Meijerink MR, Vroling L, Van der Veldt AA. Surrogate markers of anti-angiogenic

therapies. Chapter in: Angiogenesis and therapeutic targets in cancer, 2011.

43. Van der Veldt AA, Lubberink M, Lammertsma AA, Smit EF. Comment on Cho et al.: Usefulness

of FDG PET/CT in determining benign from malignant endobronchial obstruction. Eur Radiol

2011;21:2148-9.

184

44. Van der Veldt AA, Lubberink M, Greuter HN, Comans EF, Herder GJ, Yaqub M, Schuit RC, Van

Lingen A, Rizvi SN, Mooijer MP, Rijnders AY, Windhorst AD, Smit EF, Hendrikse NH,

Lammertsma AA. Absolute quantification of [11C]docetaxel kinetics in lung cancer patients

using positron emission tomography. Clin Cancer Res 2011;17:4814-24.

45. Van der Veldt AA, Vroling L, De Haas RR, Koolwijk P, Van den Eertwegh AJ, Haanen JB, Van

Hinsbergh VW, Broxterman HJ, Boven E. Sunitinib-induced changes in circulating endothelial

cell-related proteins in patients with metastatic renal cell cancer. Int J Cancer 2011.

46. Van der Veldt AA, Lubberink M, Bahce I, Walraven M, De Boer MP, Greuter HN, Hendrikse NH,

Eriksson J, Windhorst AD, Postmus PE, Verheul HM, Serne EH, Lammertsma AA, Smit, EF.

Rapid decrease in delivery of chemotherapy to tumors after anti-VEGF therapy: implications

for scheduling of anti-angiogenic drugs. Cancer Cell 2012;21:82-91.

47. Vermaat JS, Gerritse FL, Van der Veldt AA, Roessingh WM, Niers TM, Oosting SF, Sleijfer S,

Roodhart JM, Beijnen JH, Schellens JH, Gietema JA, Boven E, Richel DJ, Haanen JB, Voest EE.

-free and overall

survival in metastatic renal cell cancer patients. Eur Urol 2012.

48. Van der Veldt AA, Smit EF. Bevacizumab in neoadjuvant treatment for breast cancer. N Engl J

Med 2012;366:1637.

185

Documents

Towards personalized treatment planning of chemotherapy: [ … 1 - 10... · not. Positron emission tomography (PET) is an imaging technique that may be useful for personalized treatment