DEVELOPMENT AND CHARACTERIZATION OF A LIPOSOME

IMAGING AGENT

by

Jinzi Zheng

A thesis submitted in conformity with the requirements

for the degree of Doctor of Philosophy

Graduate Department of Medical Biophysics

University of Toronto

© Copyright by Jinzi Zheng (2009)

ii

Abstract

Development and Characterization of a Liposome Imaging Agent

Doctor of Philosophy, 2009

Jinzi Zheng

Department of Medical Biophysics

University of Toronto

Applied cancer research is heavily focused on the development of diagnostic tools

with high sensitivity and specificity that are able to accurately detect the presence and

anatomical location of neoplastic cells, as well as therapeutic strategies that are effective

at curing or controlling the disease while being minimally invasive and having negligible

side effects. Recently, much effort has been placed on the development of nanoparticles

as diagnostic imaging and therapeutic agents, and several of these nanoplatforms have

been successfully adopted in both the research and clinical arenas.

This thesis describes the development of a nanoparticulate liposome system for

use in a number of applications including multimodality imaging with computed

tomography (CT) and magnetic resonance (MR), longitudinal vascular imaging, image-

based biodistribution assessment, and CT detection of neoplastic and inflammatory

lesions. Extensive in vitro and in vivo characterization was performed to determine the

physico-chemical properties of the liposome agent, including its size, morphology,

stability and agent loading, as well as its pharmacokinetics, biodistribution, tumor

targeting and imaging performance. Emphasis was placed on the in vivo CT-based

quantification of liposome accumulation and clearance from healthy and tumor tissues in

iii

a VX2 carcinoma rabbit model, gaining insight not only on the spatial but also the

temporal biodistribution of the agent. The thesis concludes with a report that describes

the performance of liposomes and CT imaging to detect and localize tumor and

inflammatory lesions as compared to that of 18

F-fluorodeoxyglucose (FDG) – positron

emission tomography (PET). The outcome of the study suggests that liposome-CT could

be employed as a competitive method for whole body image-based disease detection and

localization.

Overall, this work demonstrated that this liposome agent along with quantitative

imaging systems and analysis tools, has the potential to positively impact cancer

treatment outcome through improved diagnosis and staging, as well as enable

personalization of treatment delivery via target delineation. However, in order to prove

clinical benefit, steps must be taken to advance this agent through the regulatory stages

and obtain approval for its use in humans. Ultimately, the clinical adoption of this

multifunctional agent may offer improvements for disease detection, spatial delineation

and therapy guidance.

iv

Acknowledgements

The successful completion of this thesis was made possible by various contributions from

a number of people. Their scientific contributions are acknowledged at the end of each

pertinent chapters of this thesis. Here I would like to recognize and thank individuals who

have contributed to my growth both as a person and as a scientist over the course of the

past five years:

- My supervisors Dr. David Jaffray and Dr. Christine Allen for their ongoing support

and encouragement, in addition to their scientific guidance and mentorship;

- My supervisory committee members Dr. Mark Henkelman, Dr. Sandy Pang and Dr.

Cynthia Menard for providing me with a fresh outlook on research problems and help

in finding potential solutions;

- Fellow labmates, past and present, for their company during many many lunches and

coffee breaks, for their constructive criticism during all of my practice talks, for the

fun times at conferences, and above all for their sincere and generous friendship;

- My boyfriend Patrick Blit for his patience during my late night experiments, his

willingness to provide feedback on many conference abstracts and scholarship

applications, as well as for his constant love and support throughout the highs and

lows of my graduate school journey;

- My parents for never doubting my capabilities and always pushing me to perform at

my very best.

v

Table of Contents

Chapter 1. Introduction................................................................................................. 1

1.1. Nanoparticles in Cancer Diagnosis and Treatment............................................. 2

1.2. Rationale for Spatio-Temporal Biodistribution Assessment .............................. 6

1.3. Imaging as a Non-invasive Method for Nanoparticle Biodistribution

Assessment...................................................................................................................... 8

1.4. Thesis Outline ................................................................................................... 11

Chapter 2. Multimodal Contrast Agent for Combined CT and MR Imaging

Applications ................................................................................................................... 14

2.1. Foreword ........................................................................................................... 15

2.2. Introduction....................................................................................................... 15

2.3. Materials and Methods...................................................................................... 19

2.4. Results............................................................................................................... 23

2.5. Discussion ......................................................................................................... 36

2.6. Acknowledgements........................................................................................... 40

Chapter 3. In Vivo Performance of a Liposomal Vascular Contrast Agent for CT and

MR-Based Image Guidance Applications ........................................................................ 41

3.1. Foreword ........................................................................................................... 42

3.2. Introduction....................................................................................................... 42

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3.3. Materials and Methods...................................................................................... 44

3.4. Results............................................................................................................... 50

3.5. Discussion ......................................................................................................... 61

3.6. Acknowledgements........................................................................................... 64

Chapter 4. Quantitative CT Imaging of the Spatial and Temporal Distribution of

Liposomes in a Rabbit Tumor Model ............................................................................... 65

4.1. Foreword ........................................................................................................... 66

4.2. Introduction....................................................................................................... 66

4.3. Experimental Section ........................................................................................ 68

4.4. Results............................................................................................................... 71

4.5. Discussion ......................................................................................................... 84

4.6. Acknowledgements........................................................................................... 88

Chapter 5. Liposome Contrast Agent for CT-based Detection and Localization of

Neoplastic and Inflammatory Lesions in Rabbits: Validation with FDG-PET and

Histology ................................................................................................................... 89

5.1. Foreword ........................................................................................................... 90

5.2. Introduction....................................................................................................... 90

5.3. Materials and Methods...................................................................................... 92

5.4. Results............................................................................................................... 98

5.5. Discussion ....................................................................................................... 109

vii

5.6. Acknowledgements......................................................................................... 112

Chapter 6. Summary and Future Directions ............................................................. 113

6.1. Summary......................................................................................................... 114

6.2. Future Directions ............................................................................................ 115

6.2.1. Technology Translation and Commercialization: Challenges and

Opportunities........................................................................................................... 116

6.2.2. Extension to a Modular Multimodality Imaging Platform ..................... 117

6.2.3. Additional Characterization of Liposome Transport and Distribution ... 121

References....................................................................................................................... 125

viii

List of Tables

Table 2.1 Size and loading characteristics of the dual-agent-containing liposome

formulation................................................................................................................ 25

Table 2.2 Relaxivity r1 and r2 values for the free gadoteridol, free iohexol and

gadoteridol, free iohexol and liposome encapsulated agents solutions. ................... 33

Table 3.1 Pharmacokinetic parameters for iohexol and gadoteridol when administered in

a liposome formulation to female Balb-C mice. . ..................................................... 53

Table 4.1 Liposome biodistribution expressed as %ID and as %ID/cm3 of organ/tissue. .

................................................................................................................................... 78

Table 4.2 List of the iodine concentration detection sensitivity using CT for organ and

tissues of known volumes. . ...................................................................................... 80

Table 5.1 List and classification of the neoplastic and inflammatory lesions detected

using CT and PET imaging, their volumes and maximum signal values. . .............. 99

ix

List of Figures

Figure 2.1 Schematic of the liposome-based contrast agent system................................ 18

Figure 2.2 Transmission electron micrograph of the negatively stained dual-agent

containing liposomes. ............................................................................................... 24

Figure 2.3 The in vitro release profile for iohexol and gadoteridol from liposomes

dialyzed under sink conditions against HBS at 4 °C and 37 °C ............................... 26

Figure 2.4 Size of the dual-agent-containing liposomes during dialysis under sink

conditions against HBS at 37 °C............................................................................... 27

Figure 2.5 In vitro imaging efficacy of the liposome-based contrast agent system in CT

and MR...................................................................................................................... 28

Figure 2.6 CT and MR signals as a function of increasing iodine and gadolinium

concentrations. .......................................................................................................... 30

Figure 2.7 1/T1 and 1/T2 relaxation rates as a function of gadolinium and iodine

concentrations. .......................................................................................................... 32

Figure 2.8 Illustration of the use of the liposome-based contrast agent in a healthy rabbit

model in CT and MR. ............................................................................................... 34

Figure 2.9 Relative percentage signal enhancement achieved in the aorta of the rabbit

measured from MR and CT images. ......................................................................... 35

Figure 3.1 Pharmacokinetics of free iohexol, free gadoteridol, liposomal iohexol and

liposomal gadoteridol in healthy female Balb-C mice.. ........................................... 52

Figure 3.2 Biodistribution of iohexol and gadoteridol when administered in a liposome

formulation to female Balb-C mice. ........................................................................ 55

x

Figure 3.3 CT and MR 3D maximum intensity projection images of a healthy New

Zealand White rabbit pre and post liposome administration. ................................... 56

Figure 3.4 Plots of the relative change in signal intensity pre- and post-administration of

the multimodal liposomal agent in CT and MR versus the measured plasma iodine

and gadolinium concentrations.. ............................................................................... 59

Figure 3.5 Summary of the hematological and biochemical evaluation of plasma samples

obtained from female Balb-C mice........................................................................... 60

Figure 4.1 Liposome biodistribution and kinetics in tumor-bearing rabbits assessed via

CT imaging. .............................................................................................................. 73

Figure 4.2 (a) Liposome biodistribution profiles in the various organs and tissues of

interest as measured using CT-based detection of the co-encapsulated iohexol and

gadoteridol. (b) Time-dependent tumor-to-muscle ratio of iodine concentration. ... 75

Figure 4.3 CT maximum intensity projections of a representative tumor-bearing rabbit

and of five segmented tumor volumes pre and post liposome injection................... 81

Figure 4.4 Tumor volume fraction occupied by liposomes and the change in tumor

volumes measured using CT in the five rabbits over 14 days. ................................. 83

Figure 5.1 Flow chart illustration of the experimental steps. .......................................... 97

Figure 5.2 Three cases of primary tumors detected by CT and PET, and confirmed by

histology.................................................................................................................. 103

Figure 5.3 Two cases of inflammatory lesions in the muscle detected by CT and PET,

and confirmed by histology.. .................................................................................. 104

Figure 5.4 CT and PET imaging signal intensities of neoplastic and inflammatory

lesions. .................................................................................................................... 106

xi

Figure 5.5 Kinetic profiles of liposome contrast agent accumulation and clearance in

tumor and inflammatory lesions. ............................................................................ 107

Figure 5.6 Incidental finding: malignant lymph nodes detected by FDG-PET ............ 108

Figure 6.1 Schematic representation of the modular multimodality liposome imaging

platform................................................................................................................... 120

xii

List of Abbreviations and Symbols

%ID Percent injected dose

ALP Alkaline phosphatase

ALT Alanine transaminase

AST Aspartate transaminase

AUC Area under the curve

CH Cholesterol

CIHR Canadian Institute of Health Research

CL Plasma clearance

CT Computed tomography

DCE-MR Dynamic contrast enhanced-MR

∆HU Change in Hounsfield unit

DLS Dynamic light scattering

∆meanHU Change in mean Hounsfield unit

DNA Deoxyribonucleic acid

DPPC 1,2-Dipalmitoyl-sn-Glycero-3-Phosphocholine

DSPE 1,2-Distearoyl-sn-Glycero-3-Phosphoethanolamine

DTPA Diethylene triamine pentaacetic acid

EPR Enhanced permeability and retention

FAZA Fluoroazomycin arabinoside

FDG Fluoro-2-deoxy-D-glucose

FMISO Fluoromisonidazole

xiii

FOV Field of view

GMP Good manufacturing practice

H&E Hematoxylin and eosin

HBS HEPES buffer solution

HBSS Hanks balanced salt solution

HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid

HPLC High performance liquid chromatography

HSPC Hydrogenated soya phosphatidylcholine

HU Hounsfield unit

ICP-AES Inductively coupled plasma atomic emission spectrometry

IR Inversion recovery

Kd Distribution rate constant

Ke Elimination rate constant

MHC Major histocompatibility complex

MIP Maximum intensity projection

MPS Monophagocytic system

MR Magnetic resonance

MRS Magnetic resonance spectroscopy

MWCO Molecular weight cut-off

PA Phosphatidic acid

pan-CK Pan-cytokeratin

PBS Phosphate buffered saline

PEG Poly-[ethylene glycol]

xiv

PET Positron emission tomography

PK Pharmacokinetics

PS Phosphatidylserine

PTA Phosphotungstic acid

R2 Coefficient of determination

r1 Longitudinal relaxivity

r2 Transverse relaxivity

RBC Red blood cells

RES Reticulo-endothelial system

ROI Region(s) of interest

SI Signal intensity

SPECT Single photon emission computed tomography

SUVmax Maximum standardized uptake value

t1/2 Half-life (vascular or physical)

t1/2α Distribution half-life

t1/2β Elimination half-life

TE Echo time

TEM Transmission electron microscopy

T1 Longitudinal relaxation rate constant

T2 Transverse relaxation rate constant

TI Inversion time

TLD Thermo luminescent dosimeter

TR Repetition time

xv

UHN University Health Network

USPIO Ultrasmall superparamagnetic iron oxide

UV Ultraviolet

Vd Volume of distribution

WBC White blood cells

1

Chapter 1. Introduction

2

This thesis reports on the development of a liposomal nanoparticle system that

supports non-invasive characterization of its in vivo biodistribution and kinetics by

volumetric imaging modalities such as computed tomography (CT) and magnetic resonance

(MR) imaging. Furthermore, its potential applications in cancer diagnosis and treatment are

also explored. Specifically, proof-of-principle studies were conducted to assess the

feasibility of its employment for multimodality imaging, blood pool/vascular imaging,

image-guided assessment of drug delivery, and cancer detection.

The following chapter outlines the rationale as well as provides literature background

to frame the context of the work described in this thesis.

1.1. Nanoparticles in Cancer Diagnosis and Treatment

The two main goals in applied cancer research are the development of 1) diagnostic

tools with high sensitivity and specificity that are able to accurately detect the presence and

anatomical location of neoplastic cells as well as characterize their abnormal nature; and 2)

therapeutic strategies that are effective at curing or controlling the disease, while being

minimally invasive and having negligible side effects. Recently, much effort has been placed

on the development of nanoparticles as diagnostic imaging and therapeutic agents, and

several of these nanoplatforms have achieved success in both the research and clinical arenas.

Overall, there are three rationales for employing nanoparticles instead of traditional small

molecules as a new class of agents that have the potential to lead to improved diagnosis and

treatment. First, the critical size of nanoparticles and their tunable surface characteristics

result in pharmacokinetics profiles that enable applications requiring longitudinal imaging

and sustained drug delivery. Second, their extended pharmacokinetics allow for increased

3

tumor tissue targeting resulting in greater target-to-background signal ratio in imaging

applications and enhanced therapeutic index when used as a treatment vector. Third, the high

payload of imaging and/or therapeutic agents that nanoparticles carry can be exploited for

amplification of imaging signal or therapeutic effect, especially when used in conjunction

with a lower sensitivity imaging system or a less cytotoxic drug, respectively.

The pharmacokinetics of a nanoparticle is determined by its size, charge, surface

modification and shape [1]. It is generally agreed that the hydrodynamic radius of a

nanoparticles should be at least 10 nm [2] (greater than the sieving coefficient of the renal

glomerular capillary wall for spherical particles) in order to avoid significant clearance via

renal excretion [3, 4] as well as distribution into the extracellular space through the

fenestrations in the vascular endothelial walls (up to 10 nm [5]) . In addition to the above

described passive size-dependent nanoparticle removal process, the body also has an active

nanoparticle opsonization process in place by the reticulo-endothelial system (RES) [6] also

termed mononuclear phagocytic system (MPS). The most commonly used strategy to

minimize opsonization is particle surface modification with poly-[ethylene glycol] (PEG) [7].

PEG is an inert and highly hydrophilic linear polymer chain. Its incorporation onto the

surface of nanoparticles provides good steric stabilization and prevents both self-aggregation

as well as protein binding [1]. As a result, nanoparticle destabilization due to protein

adhesion is minimized and its vascular circulation lifetime is increased. Sadzuka et al.

investigated the pharmacokinetics of drugs encapsulated in either non-PEGylated or

PEGylated liposomes. They observed a 6-fold increase in the area under the curve (AUC) of

the drug pharmacokinetics profile when it is formulated in the PEGylated liposomes

compared to the PEG-free liposome formulation and a 36-fold increase compared to the

4

AUC of the free drug [8]. The size of nanoparticles also plays an important role in their

accumulation in organs that make up the RES, namely liver and spleen. Liu et al. reported in

1992 on the biodistribution of liposomes of different sizes (30 – 450 nm) [9]. They measured

70% of the injected dose (%ID) of liposomes with a diameter less than 70 nm localized in the

liver. This can be explained by the size of the fenestrations in the endothelium of the liver

sinusoid (100 nm, [10]). In the spleen, Liu et al. found that liposomes with a diameter of 200

nm or less exhibited minimal uptake. However, as the particle size increased, the rate of

spleen accumulation also increased. The authors concluded that particles between 70 and 200

nm in diameter were optimal for avoidance of liver and spleen uptake. The particle surface

charge can further be modulated to minimize opsonization by phagocytic cells of the RES.

Levchenko et al. demonstrated that the presence of charged lipids in the liposome bilayer (in

the absence of PEG), especially the negatively charged phosphatidic acid (PA) and

phosphatidylserine (PS), strongly accelerated the clearance of liposomes from blood [11].

However, the liposome pharmacokinetics becomes more complex if it contains both PEG and

a charged phospholipid [11]. More recently, Geng et al. [12] reported that nanoparticle shape

can influence their pharmacokinetics and RES sequestration. Specifically, they demonstrated

that cylinder-shaped filomicelles were able to achieve blood circulation half-life as long as 5

days, about 10 times greater than their spherical counterparts. Their in vitro macrophage

studies revealed that these worm-shaped nanoparticles experience a strong drag force in the

presence of fluid flow which minimized macrophage engulfment [12]. However, the

feasibility of cylinder-like nanoparticles to carry large loads of imaging and/or therapeutic

agents has not yet been shown. As a result, currently available evidence support the

5

development of nanoparticles that are PEGylated, of approximately 100 nm in diameter and

have a neutral surface charge for applications requiring prolonged blood circulation lifetime.

Tumor targeting via the passive enhanced permeation and retention (EPR) effect, first

described by Matsumura and Maeda in 1986 [13], requires particles to have a prolonged

vascular residency time (i.e. maintain high plasma AUC for > 6 h in mice and rats [13-15]). It

has been agreed that the degree of macromolecule accumulation in tumors is directly

proportional to the blood AUC (or exposure) and inversely proportional to the rate of urinary

clearance [16-18]. Once the prerequisite of high exposure has been achieved, the transport of

macromolecules, such as nanoparticles, into tumor tissues is further affected by the tumor

vascular pore size (up to 400 nm, [19]). However, their subsequent intratumoral retention is a

function of the particle diffusivity in the tumor interstitial space [20], the speed of the tumor

venous return (usually slower than normal tissue [21, 22]), as well as the presence of a poor

lymphatic drainage system [21, 22]. Altogether, macromolecules and nanoparticles not only

preferentially accumulate in tumors via the enhanced vascular permeability, but they are also

preferentially retained there (for multiple hours to days). Conversely, low-molecular-weight

agents are distributed systemically following administration, rapidly cleared from the

circulating blood via renal clearance, and their tumor accumulation is only transient (on the

order of minutes). Their small size allows them to readily return to into the circulating blood

system following extravasation into the tumor interstitial space [15, 23]. The ability of the

EPR effect to significantly increase tumor accumulation versus healthy tissue distribution

results in increased target-to-background signal ratio during imaging and enhanced tumor-to-

healthy tissue therapeutic ratio during treatment. EPR is the hallmark of nanoparticle-based

delivery of diagnostic and therapeutic agents to tumors [18].

6

Once the tumor site is reached, different strategies have been developed for

selectively directing the nanoparticles to target specific cell populations and sub-cellular

compartments [24, 25]. These include the engineering of nanoparticles responsive to

different triggers that are either inherently present in the tumor microenvironment (i.e. pH

[26], matrix metalloproteinases [27]) or that can be induced externally (i.e. temperature [28,

29], light irradiation [30]). Molecularly targeted surface ligands can also be incorporated onto

the outer layer of the nanoparticles. These enable the retention of nanoparticles either on the

surface of the cells of interest or induce cellular uptake. Furthermore, appropriate surface

modifications also lead to successful targeting to intracellular compartments such as the

nucleus or the mitochondria [31-33].

The liposome system developed and employed in this thesis is a passive, sterically

stabilized particle that solely relies on the EPR effect to achieve tumor targeting. Extensive

characterization of the distribution patterns and kinetics of passive systems is necessary to

lay down the groundwork needed for future quantification aimed at assessing advantages of

the different active targeting strategies.

1.2. Rationale for Spatio-Temporal Biodistribution Assessment

The pharmacokinetics and biodistribution profile is often used as a surrogate to

evaluate the potential effectiveness of a new therapeutic or diagnostic agent. For example,

the blood concentration of a drug has often been correlated to its efficacy and toxicity [1]. As

a result, the agent should be designed to reach the desired therapeutic or diagnostic effect at

the lowest administration dose possible. The development process therefore aims to select the

7

formulation that yields the highest agent concentration at the desired target site (i.e. tumor)

and the lowest agent concentration elsewhere (i.e. healthy organs, background tissues).

The temporal component of a biodistribution assessment is also important. In the

case of a diagnostic agent, the biodistribution kinetics defines the optimal imaging window

for obtaining information on a specific biological or physiological process. For example, in a

routine functional CT or dynamic contrast enhanced (DCE)-MR imaging session, it is

important to characterize the distribution and clearance kinetics of the agent in order to

accurately define the arterial and venous phases. If the imaging probe employed is involved

in an active biological process, such as fluorodeoxyglucose (FDG) in cellular metabolism or

ultra-small superparamagnetic iron oxide (USPIO) in macrophage phagocytosis, the

timelines of these processes must be defined in order to set the time gap between probe

administration and imaging (i.e. one hour for FDG-PET, and 24 hours for USPIO-MR). In

the case of a therapeutic agent, its pharmacokinetics and biodistribution influence its efficacy

and toxicity. For example, studies conducted in mice to compare the efficacy of liposome-

encapsulated doxorubicin versus free doxorubicin found a gain in the plasma AUC of at least

60-fold [34-37] and an increase of 14-fold in the peak tumor drug concentration for the

liposomal drug [35]. This resulted in an enhancement in treatment efficacy (i.e. 6-fold [38])

and a significant decrease in toxicity [34, 39]. Characterization of the temporal profile of the

biodistribution and clearance of the therapeutic agent of interest will better enable the setting

of appropriate dosing regimens.

8

1.3. Imaging as a Non-invasive Method for Nanoparticle Biodistribution Assessment

Traditional nanoparticle pharmacokinetics and biodistribution studies rely on plasma

and tissue sampling. The invasive nature of these procedures can change the biological

system under observation resulting in unreliable representation of the in vivo conditions.

Furthermore, animals often need to be sacrificed at each sampling time point in order to

either provide enough plasma or tissue for analysis or because their vital organs are removed

during the biodistribution assessment process. These limitations associated with traditional

pharmacokinetics and biodistribution studies can be overcome through the use of non-

invasive imaging techniques in conjunction with appropriate labeling of the nanoparticle of

interest. Image-based measurements, when successfully correlated with tissue agent

concentrations, can be used to collect meaningful data on the same animal over multiple time

points with minimum amount of perturbation to biological and physiological processes [40].

Therefore, not only animal-to-animal variations are avoided, but also the total number of

animals required for each study can be reduced [41]. Furthermore, thanks to the increasing

availability of small animal scanners, the imaging assays employed in the preclinical

environment can be more readily translated to the clinical setting.

To date, non-invasive nuclear imaging techniques such as PET and single photon

emission computed tomography (SPECT) have been extensively explored for

pharmacokinetics and biodistribution studies [42, 43]. PET isotopes have shown an

advantage over SPECT isotopes for radiolabeling of small molecules because atom

replacement is possible with positron emitters such as 11

C, 15

O, 13

N and 18

F in a compound

without modification of its pharmaceutical, biological or biochemical properties [44].

However, for long-circulating nanoparticulates such as liposomes, PET labeling is unsuitable

9

because the positron emitters often have much shorter physical half-lives (10 minutes for 13

N,

20.4 minutes for 11

C, 110 minutes for 18

F and 12.7 hours for 64

Cu) compared to the vascular

half-life of the nanoparticles (~ 55 hours for liposomal doxorubicin, Doxil

). As such, PET

tracer-labeled pharmaceutical carriers cannot be tracked over their full circulation-lifetime in

vivo and repeated imaging over multiple time points is greatly limited. Some SPECT

radiotracers have physical half-lives that are suitable for longitudinal carrier therapeutics

studies, such as 111

In with t1/2 of 67.9 hours. The presence of a metal chelating agent such as

diethylene triamine pentaacetic acid (DTPA) when labeling a macromolecular agent is also

less of a concern compared to its use for the labeling small molecules as it usually does not

significantly affect the pharmacokinetics and distribution of the macromolecule [45]. In

addition, advanced SPECT systems allow for collection of photons emitted at different

energy windows. This is very valuable for applications requiring simultaneous imaging of

multiple radiotracers (i.e. monitoring the biodistribution of multiple species of carriers

labeled with radionuclides of different and resolvable gamma energies). However, as the

radioactivity of the tracer decays, the imaging time need to be increased in order to maintain

the image quality and count statistics. Harrington et al. [46] conducted a clinical study

administering 111

In-DTPA-labeled liposomes to 17 patients with locally advanced cancers.

Serial whole body gamma camera images were acquired up to 7 days post-injection showing

liposome localization in the tumor lesions as well as in healthy tissues. The image quality of

the data set acquired at day-7 was significantly deteriorated due to both physical decay of

111In and biological clearance of liposomes. This report confirms that the performance of

SPECT over the course of a longitudinal biodistribution assessment is not constant. In

addition, just like PET, the use of SPECT imaging to map the colloidal carrier tissue

10

distribution is greatly limited by its inability to provide structural and anatomical

information. Recent development of integrated imaging systems such as PET/CT and

SPECT/CT has enabled acquisition and fusion of anatomy with the nuclear imaging data.

Furthermore, the development of PET/MR and SPECT/MR systems will likely provide an

even more fertile ground for innovations in the area of nuclear medicine-based monitoring of

biodistribution of long circulating nanoparticles.

More recently, MR has also been explored as a potential tool to image tissue

distribution of nanocarriers [47-49]. Viglianti et al. [50, 51] reported a particularly interesting

set of studies where MR was successfully used to visualize and quantify drug release from

temperature sensitive liposomes labeled with Mn2+

. Advantages of MR over other imaging

modalities (i.e. CT, PET and SPECT) include the absence of ionizing radiation and high soft-

tissue contrast. However, its sensitivity for measuring T1 and T2-shortening contrast agent

concentrations (i.e. 10-5

M for Mn2+

[51]) is about 105 to 10

7 times lower than SPECT (10

-10

M [52]) and PET (10-11

to 10-12

M [52]) , respectively. In addition, although a number of fast

mapping techniques have been described for quantification of T1 [53-55] and T2 [56], data

collection times are still generally lengthier and image resolution lower than that of

conventional qualitative MR acquisitions [57, 58].

The whole-body imaging techniques described above have the ability to quantify drug

tissue distribution non-invasively. Their resolution limitations make them inadequate for

providing information on the intracellular localization of the administered agents.

Microscopes with fluorescence detectors are currently the most widely used tool for

visualization of molecule distribution within a cell [59]. Because optical imaging techniques

lack depth penetration and are heavily affected by scattering effects, quantitative in vivo

11

imaging cannot be performed. Hence, if the administered drug and carrier were either

inherently fluorescent (i.e. doxorubicin) or labeled with a fluorescent probe, then by

collecting a small biopsy sample from the location of interest, the intracellular localization of

both the drug and carrier can be visualized using a confocal microscope. However, accurate

quantification of fluorescence is sometimes difficult even ex vivo due to optical property

changes. For example, doxorubicin fluorescence is partially quenched when the drug binds to

the deoxyribonucleic acid (DNA) [60].

The work conducted within this thesis is aimed at characterizing the whole body

biodistribution map and kinetics of liposomes using volumetric imaging modalities (CT and

MR). This liposome platform has been engineered to allow for future addition of modular

components that would support imaging in other modalities such as PET, SPECT and optical.

This modular multimodality approach will enable quantification of the whole body

distribution and cellular uptake of nanoparticles in vivo across a wide range of spatial

resolution and detection sensitivity scales through full exploitation of the respective strengths

of different imaging techniques.

1.4. Thesis Outline

A versatile multi-purpose contrast agent system is highly advantageous as it can

provide multi-parametric characterization of the disease following just one single injection.

This thesis describes the development and characterization of a novel liposome system with

exploration of a number of different applications in cancer. Chapter 2 [61] focuses on the

formulation and in vitro characterization of the loading, size, morphology, stability and

imaging properties of this liposome agent. It also illustrates the potential use of this system

12

for CT and MR dual-modality imaging during image-guided therapeutic procedures by

demonstrating that the signal enhancements in both imaging modalities are co-localized.

Chapter 3 [62] describes the pharmacokinetics and biodistribution of the liposome system in

healthy mice determined by evaluation using traditional blood sampling and whole organ

digestion methods. The pharmacokinetics profile obtained was fitted to a one-compartment

model and the volume of distribution of the liposomes was matched to that of the blood

volume of an average mouse. The vascular half-life of this liposome system was calculated to

be approximately 100-fold greater than that of a clinically available small molecule CT or

MR contrast agent. This showed feasibility to employ these liposomes as intravascular

contrast agents for longitudinal imaging applications. Chapter 4 [63] explores the suitability

of these imageable liposomes to be used in image-guided drug delivery. Volumetric CT

methods were used to measure the concentration of liposome carriers in the organs and

tissues of VX2-carcinoma bearing rabbits over a 14-day period. It is concluded that CT has

the ability to detect in vivo concentrations of iodine at sensitivity as high as 8 nmol/cm3

(equivalent to 1 µg/cm3) while maintaining the ability to identify boundaries of anatomical

structures at sub-millimeter resolution. Using this approach, heterogeneity in the intratumoral

distribution of the liposomes was visualized and their intratumoral volume of distribution

quantified in vivo. As a result, the combined use of iodinated liposomes and CT imaging

allows for monitoring of colloidal drug delivery and provides an opportunity for online

adjustment of therapeutic regimens and implementation of adaptive pharmaceutical delivery.

Chapter 5 investigates the ability of the liposome system developed within the framework of

this thesis to reach sites of tumor and inflammation. The performance of liposome-CT is then

compared to that of FDG-PET for whole-body detection of suspect lesions in a rabbit model

13

bearing both VX2-carcinoma and immune myositis. Comprehensive histopathology was also

conducted to confirm the abnormalities. Liposomes induced contrast enhancement in CT at

sites of tumor and inflammation. Interestingly, the mean accumulation of liposomes at the

inflammatory lesions, observed at five days post-administration, was significantly higher

than at found at the tumor sites (p < 0.0001). The partial volume adjusted maximum

standardized uptake values (SUVmax) measured from the FDG-PET data set did not yield

significant differences in FDG uptake between the two lesion types (p > 0.15). These

observations suggest that this liposome agent could play a potential role in increasing the

specificity of disease detection and localization. Finally, Chapter 6 discusses the challenges

and opportunities for its ready translation into the clinical setting (i.e. commercialization and

application for regulatory approval), potential modifications that would increase its

performance and versatility, as well as additional investigations needed to better define its

role in image-based characterization of tumor morphology and patho-physiology.

14

Chapter 2. Multimodal Contrast Agent for Combined CT and MR

Imaging Applications

15

2.1. Foreword

Innovations in nanoparticle design and construction open opportunities for

engineering of novel imaging agents that carry signal generating moieties for more than one

imaging modality – these are referred to as multimodal imaging agents. The following

chapter describes the development and characterization of a liposome-based CT and MR

contrast agent and it has been published as:

Zheng J, Perkins G, Kirilova A, Allen C, Jaffray DA. Multimodal Contrast Agent for

Combined Computed Tomography and Magnetic Resonance Imaging Applications.

Investigative Radiology, Volume 41, Number 3, Pages 339 – 348. March 2006.

It has been reproduced with permission from Lippincott Williams & Wilkins.

2.2. Introduction

In recent years there has been an increase in the use of multimodality imaging (i.e.

CT/PET, CT/SPECT, x-ray/MR) [64-71]. Since each medical imaging modality has unique

strengths and limitations, it is often through the compound use of multiple modalities that the

complete assessment of a patient is achieved. Interest in the area of multimodality imaging

has also been prompted by the realization that such techniques offer much more sophisticated

characterization of the morphology and physiology of tissues and organs, and that confidence

gained in the accurate correspondence or registration of different modalities greatly enhances

their value [72]. This improved value of imaging will ultimately allow for advances in

diagnosis and evaluation of disease, image-guided therapeutic interventions, and assessment

of treatment outcomes. The recent integration of CT and PET systems is a good example of

the advantages of the multimodal approach [64-66]. The CT-PET combination has

16

revolutionized the utilization of PET in diagnostic applications since it has been shown to

increase the specificity of PET-based assessment by accurately placing the diseased structure

within the body frame [73-75]. In the context of radiation therapy, there is a need to merge

CT and MR imaging - CT is employed for 3D volumetric radiation dose calculation and MR

is utilized for accurate delineation of the target and normal structures [76]. For example,

accurate delineation and targeting of the prostate gland in radiation therapy of prostate cancer

necessitates parallel use of CT and MR imaging [77]. Furthermore, CT technology in the

form of conventional and cone-beam systems is employed on a daily basis to guide the

delivery of radiation therapy on treatment machines [78, 79]. The development of a

multimodal CT and MR contrast agent with the ability to facilitate target delineation and

assist in the guidance of therapy has the potential to increase both the accuracy and the

precision of the delivery of radiation therapy.

Clinical imaging in all modalities requires that an adequate level of differential

contrast relative to noise be achieved in order to identify the structures or phenomena under

observation. Although imaging on CT and MR can be performed without the administration

of contrast agents there are numerous instances in both disease diagnosis and treatment, in

which procedures benefit from the improved contrast and dynamics that are added by the use

of these agents [80, 81]. In addition, if the multimodal agent’s localization in the body is

persistent enough, it can potentially become a relatively non-invasive alternative to fiducial

markers for image-guided radiotherapy procedures. Given these considerations, it is the

objective of these investigations to develop an agent to assist in the multimodal registration

process through the creation of spatially consistent image signals across CT, MR and cone-

beam CT for radiation therapy applications.

17

The present study proposes unilamellar liposomes as a delivery system (Figure 2.1)

for two commercially available contrast agents: Omnipaque

(iohexol, Nycomed Imaging

AS, Oslo, Norway), a CT agent, and ProHance

(gadoteridol, Bracco Diagnostics Inc.,

Princeton, NJ, USA), an MR agent. The objective of this study is to examine the feasibility of

such a multimodal system to effectively induce and maintain contrast enhancement in both

CT and MR. Specifically, the size, morphology and encapsulation efficiency of the

liposomes for both CT and MR agents are measured. The in vitro stability of the system and

in vitro release kinetic profiles of the encapsulated agents are determined. The relaxivity

characteristics and the in vitro CT and MR imaging properties of the system are investigated

in a phantom. In addition, a preliminary imaging-based assessment of the in vivo stability of

this multimodal contrast agent is conducted in a lupine model. These series of studies

represent the first step towards the development of a colloidal carrier-based multimodal

contrast agent for combined CT and MR imaging.

18

Figure 2.1 Schematic of the liposome-based contrast agent system (not drawn to scale).

19

2.3. Materials and Methods

Materials

The components of liposomes: 1,2-Dipalmitoyl-sn-Glycero-3-Phosphocholine

(DPPC, M.W. 734), Cholesterol (CH, M.W. 387) and 1,2-Distearoyl-sn-Glycero-3-

Phosphoethanolamine-N-[Poly(ethylene glycol)2000] (PEG2000DSPE, M.W. 2774) were

purchased from Northern Lipids Inc. (Vancouver, British Columbia, Canada). The CT

contrast agent, Omnipaque

was obtained from Nycomed Imaging AS, Oslo, Norway.

Omnipaque

(300 mg/mL of Iodine) contains iohexol (M.W. 821.14), an iodinated, water-

soluble, non-ionic monomeric contrast medium. The MR contrast agent used was ProHance

from Bracco Diagnostics Inc. (Princeton, NJ, USA). ProHance

(78.6 mg/mL of gadolinium)

contains gadoteridol (M.W. 558.7), a non-ionic gadolinium complex of 10-(2-hydroxy-

propyl)-1,4,7,10-tetraazacyclododecane-1,4,7-triacetic acid.

Preparation of liposome formulations

Lipid mixtures (200 mmol/L) of DPPC, cholesterol and PEG2000DSPE in 55:40:5

percent mole ratios were dissolved in ethanol at 70°C. The lipid-ethanol solution was then

hydrated at 70°C with Omnipaque

(300 mg/mL of iodine, 45%vol) and Prohance

(279.3

mg/mL of gadoteridol, 45%vol). The initial ethanol content was 10%vol. The resulting

multilamellar vesicles were then extruded [82, 83] at 70°C with a 10 mL LipexTM

Extruder

(Northern Lipids Inc., Vancouver, British Columbia, Canada). Specifically, the samples

were first extruded 5 times with two stacked polycarbonate membranes of 0.2 µm pore size

20

(Nucleopore

Track-Etch Membrane, Whatman Inc., Clifton, NJ, USA) and subsequently 5

times with two stacked polycarbonate membranes of 0.08 µm pore size.

Physico-chemical characterization of liposome formulations

Liposome size and morphology

The size of liposomes was measured by dynamic light scattering (DLS) at 25°C

using a DynaPro DLS (Protein Solutions, Charlottesville, VA, USA). Liposome

morphology was studied by transmission electron microscopy (TEM) with a Hitachi 7000

microscope operating at an acceleration voltage of 80 kV. The liposome sample was first

diluted in distilled water and then mixed with phosphotungstic acid (PTA) in a 1:1

volume ratio. The sample solutions were then deposited onto negatively charged copper

grids that had been pre-coated with carbon.

Evaluation of loading efficiency, in vitro stability and in vitro release kinetics

Following liposome preparation, the unencapsulated agent was removed by

membrane dialysis. Specifically, 1 mL of the liposome sample was placed in an 8000

molecular weight cut-off (MWCO) dialysis bag suspended in 250 mL of N-(2-

Hydroxyethyl)Piperazine-N'(Ethanesulfonic Acid) (HEPES) buffer saline (HBS) and left

to stir for 8 hours. The liposomes were then ruptured using a 10-fold volume excess of

ethanol in order to measure the concentration of encapsulated agents. The iodine

concentration was determined using a UV assay with detection at a wavelength of 245

nm (Heλios γ, Spectronic Unicam, MA, USA). The gadolinium concentration was

determined using an assay based on inductively coupled plasma atomic emission

21

spectrometry (ICP-AES Optima 3000DV, Perkin Elmer, MA, USA). The encapsulation

efficiency of the agents was calculated using the following equation:

100 npreparatio during addedagent ofamount

edencapsulatagent ofamount efficiencyion encapsulat % ⋅=

The in vitro release kinetic profile for both agents was assessed by the dialysis

method [84]. In short, 1 mL of the liposome sample was placed in a dialysis bag (MWCO

8000) suspended in 250 mL of HBS and incubated at 4°C or 37°C. At specific time

points, 5 mL of the dialysate was removed for measurement of the iodine and gadolinium

concentrations and 5 mL of fresh HBS was added in order to maintain constant volume.

The stability of the liposomes was assessed by measuring the size of liposomes at specific

time points during the incubation period.

In vitro CT and MR imaging

CT scanning was performed using a GE LightSpeed Plus 4-detector helical scanner

(General Electric Medical Systems, Milwaukee, WI, USA) with the following scan

parameters: 2.5 mm slice thickness, 120 kV, 300 mA and 15.2 x 15.2 cm field of view

(FOV). The mean attenuation in Hounsfield units (HU) was measured in each agent-

containing tube (1 cm in diameter) using circular regions of interest (ROI) of 7 mm2.

MR imaging was performed with a head coil in a 1.5 Tesla GE Signa TwinSpeed MR

scanner (General Electric Medical Systems, Milwaukee, WI, USA). Scans were produced

using a T1 weighted spin echo sequence with a repetition time (TR) of 450 ms, an echo time

(TE) of 9 ms, a slice thickness of 3 mm, a FOV of 19.9 x 19.9 cm and an image matrix of

256 x 192 pixels. The relative signal intensity was taken over an ROI of 7 mm2.

22

In vitro relaxometry

All in vitro relaxometry measurements were performed at 20°C on a 1.5 Tesla, 20-

cm-bore superconducting magnet (Nalorac Cryogenics Corp., Martinez, CA) controlled by

an SMIS spectroscopy console (SMIS, Surrey, UK). The T1 relaxation time data were

acquired using an inversion recovery (IR) sequence [85] with 35 inversion recovery time (TI)

values logarithmically spaced from 1 to 32000 ms. A 10 second delay was given between

each acquisition and the next inversion pulse. The T2 relaxation time data were acquired

using a CPMG sequence [85, 86] with TE/TR = 1/10000 ms. For every measurement 2000

even echoes were sampled with 8 averages. The effects of any residual transverse magnetiza-

tion following the off-resonance irradiation was removed by phase-cycling the π/2 pulse (-

x/x).

The T1 relaxation data were analyzed assuming mono-exponential behavior

(

⋅−⋅=

−1

0 21 T

t

eMS , where S is the signal observed, M0 is the magnetization at

equilibrium, t is time and T1 is the longitudinal relaxation time). All T2 decay data were

plotted to a one component T2 model with a Gaussian fit on a logarithmic time scale. The r1

and r2 values were calculated from linear regression analysis of 1/T1 and 1/T2 relaxation rates

versus gadolinium concentration.

In vivo CT and MR imaging

The in vivo imaging study was performed under a protocol approved by the Animal

Care and Use Committee of the University Health Network. A New Zealand white rabbit

(male, 3.5 kg) was anaesthetized with an intramuscular injection of 40 mg/kg of ketamine

23

and 5 mg/mL of xylazine. 2% isoflurane vapor was given by inhalation throughout the study.

10 mL of the liposome-based contrast agent solution (36 mg/kg of iodine and 12 mg/kg of

gadolinium) was injected into the marginal ear vein catheter at a rate of 1 mL/second. Pre-

and post-contrast injection images of the rabbit were acquired in both imaging modalities. 15,

60, 120, 180 minutes and 24, 72 and 168 hours following the contrast agent injection, the

rabbit was imaged in CT (120kV, 200mA, FOV = 22.0 x 22.0 cm, slice thickness = 1.25 mm

and image matrix of 512 x 512) and then moved to the MR scanner at 30, 90, 150, 200

minutes and 24, 72 and 168 hours post-contrast to acquire images in MR (3D FSPGR

sequence with a TR of 8.5 ms, a TE of 4.1 ms, a slice thickness of 3.0 mm with an overlap of

1.5 mm, an FOV of 22.0 x 22.0 cm and an image matrix of 256 x 256).

The signal intensity in MR and the mean attenuation values (HU) in CT were

measured over a circular ROI of 4 mm2. The cross-sectional images were exported from a

review station (Merge eFilm, Milwaukee, WI, USA). The same window and level was used

for the pre and post-contrast images.

2.4. Results

Physico-chemical characterization of liposome formulation

The prepared liposome formulation resulted in vesicles having a spherical

morphology (Figure 2.2) and a mean diameter of 74.4 ± 3.3 nm. Table 2.1 summarizes the

agent loading properties of the liposome formulation. The average loading efficiency (n=8)

achieved for iohexol was 19.6 ± 2.8 % (26.5 ± 3.8 mg/mL iodine loaded, approximately

2.4x104 iohexol molecules per liposome), which represents an agent to lipid ratio of

approximately 0.2:1 (wt:wt). The average loading efficiency (n=8) attained for gadoteridol

24

was 18.6 ± 4.4 % (6.6 ± 1.5 mg/mL gadolinium loaded, approximately 1.4x104 gadoteridol

molecules encapsulated in one liposome), which represents an agent to lipid ratio of

approximately 0.05:1 (wt:wt).

Figure 2.2 Transmission electron micrograph of the negatively stained dual-agent

containing liposomes at (a) 40,000 magnification and (b) 80,000 magnification.

25

Diameter

(nm)

Iodine

added

(mg/mL)

Iodine

loaded

(mg/mL)

Iodine

loading

efficiency

(%)

Gadolinium

added

(mg/mL)

Gadolinium

loaded

(mg/mL)

Gadolinium

loading

efficiency (%)

74.4 ± 3.3 135 26.5 ± 3.8 19.6 ± 2.8 35.5 6.6 ± 1.5 18.6 ± 4.4

Table 2.1 Size and loading characteristics of the dual-agent-containing liposome

formulation (n = 8). The liposomes are composed of DPPC/cholesterol/DSPE-PEG (55/40/5/

mole ratio). Data represent the mean ± standard deviation.

Figure 2.3 includes the in vitro release profile for both agents under sink conditions in

physiological buffer at 4ºC (Figure 2.3a) and 37ºC (Figure 2.3b). As shown, following the

15-day incubation period at 4°C, 8.7 ± 1.5 % and 6.6 ± 4.5 % of the encapsulated iodine and

gadolinium were released, respectively, and at 37°C, 9.1 ± 2.5 % and 7.5 ± 1.4 % of the

encapsulated iodine and gadolinium were released, respectively. The liposomes were also

sized periodically during the incubation period in order to assess their stability under sink

conditions in HBS at 37ºC. As seen in Figure 2.4 the liposome size remains constant

throughout the incubation period.

In vitro imaging

Visual contrast enhancement was observed in CT and MR when the liposome-based

contrast agent was imaged in vitro at varying concentrations (Figures 2.5a and 2.5b). Figure

2.6a illustrates the measured CT attenuation of the liposome encapsulated contrast agents, the

unencapsulated iohexol, the unencapsulated gadoteridol and the mixture of unencapsulated

26

(a)

(b)

Figure 2.3 The in vitro release profile for iohexol and gadoteridol from

DPPC/cholesterol/DSPE-PEG (55/40/5 mole ratio) liposomes dialyzed under sink conditions

(250-fold volume excess) against HBS (a) at 4 °C and (b) at 37 °C (n = 4). Data are

represented as the mean ± standard deviation.

27

iohexol and gadoteridol. Attenuation values varied linearly with concentration for all contrast

agent solutions. Linear regression analysis revealed an attenuation of 38.5 ± 0.5 HU/(mg of

gadolinium) in 1 mL of HBS for the unencapsulated gadoteridol (r=0.99), 29.0 ± 0.4 HU/(mg

of iodine) in 1mL of HBS for the unencapsulated iohexol (r=0.99), 37.8 ± 0.5 HU/(mg of

iodine and 0.2 mg of gadolinium) in 1 mL of HBS for the mixture of unencapsulated iohexol

and gadoteridol (r=0.99), and 36.3 ± 0.5 HU/(mg of iodine and 0.2 mg

of gadolinium) in 1

mL of HBS for the liposome formulation (r=0.99). The slightly lower attenuation values

observed for the liposome encapsulated iohexol and gadoteridol compared to free iohexol

and gadoteridol are due to the presence of lipids, which, with respect to water, have lower CT

attenuation values.

Figure 2.4 Size of the dual-agent-containing liposomes during dialysis under sink conditions

(250-fold volume excess) against HBS at 37 °C (n = 3). Data are represented as the mean ±

standard deviation.

28

(a) (b)

Figure 2.5 In vitro imaging efficacy of the liposome-based contrast agent system (a) in CT

(2.5 mm slice thickness, 120 kV, 300 mA and 15.2 cm2 FOV) and (b) in MR (450 ms TR, 9

ms TE, 3 mm slice thickness, 19.9 cm2 FOV and 256 x 192 image matrix). Data are

represented as the mean ± standard deviation.

Figure 2.6b illustrates the MR relative signal profile as a function of gadolinium or

iodine concentration. It is known that the relationship between gadolinium concentration and

relative signal intensity in MR becomes markedly non-linear at high concentrations of

gadolinium [87-89]. Furthermore, negative enhancement occurs in MR when the gadolinium

concentration reaches high enough levels to cause significant T2 shortening, which in turn

results in signal loss [90-93]. The plots in Figure 2.6b for liposome encapsulated gadoteridol

and iohexol, free gadoteridol and iohexol, liposome-encapsulated gadoteridol and free

29

gadoteridol all exhibit non-linear characteristics. The free iohexol plot confirms that iodine in

the concentration range of 0 to 17 mmol/L shows signal intensity levels comparable to those

achieved by water. The average differential signal intensity (SI) in MR for free iohexol

samples was 1.8 ± 7.1 SI relative to water. The unencapsulated gadoteridol samples reached

peak differential signal intensities (> 600 SI with respect to water) in the gadolinium

concentration range of 1 to 9 mmol/L. This is in accordance with previous findings [89, 92].

A slight decrease in the mean signal intensity was observed when free gadoteridol was mixed

with iohexol. This finding is consistent with previous reports on the capability of iodinated

contrast agents to diminish the signal enhancing effects of gadolinium [94-96]. Encapsulation

of gadoteridol in liposomes (in the presence and absence of iohexol) was found to cause a

right shift in the differential signal intensity profile (peak signal intensities in MR achieved

with gadolinium concentration ranging from 5 to 18 mmol/L). Encapsulation of gadoteridol

in the interior of liposomes diminishes MR signal at lower gadolinium concentrations (< 5

mmol/L) due to limited bulk water access which decreases 1/T1 values [97]. At higher

gadolinium concentrations (> 5 mmol/L), however, encapsulation of gadoteridol significantly

dampens the T2 relaxation effect allowing high signal levels to be maintained over a much

broader gadolinium concentration range in MR.

30

(a)

(b)

Figure 2.6 (a) CT (2.5 mm slice thickness, 120 kV, 300 mA and 15.2 cm2 FOV) attenuation

in HU as a function of contrast agent concentration in mmol/L. Although gadolinium has CT

attenuation properties, iodine provides more effective CT enhancement. (b) Differential

signal intensity (with respect to water) in MR (450 ms TR, 9 ms TE, 3 mm slice thickness,

19.9 cm2 FOV and 256 x 192 image matrix) as a function of increasing gadolinium and

iodine concentrations. Symbols represent liposome-encapsulated gadoteridol and iohexol (■),

liposome-encapsulated gadoteridol (●), free iohexol and gadoteridol (▲), free gadoteridol

(●) and free iohexol (▼). Data are represented as the mean ± standard deviation.

31

In vitro relaxometry

For the relaxometry measurements, T1 (Figure 2.7a) and T2 (Figure 2.7b) rates were

observed to be linear and concentration dependent for both the liposome encapsulated and

the unencapsulated contrast agents. The r1 and r2 values of unencapsulated gadoteridol were

5.1 and 6.2 s-1

mmol-1

L, respectively. The r1 and r2 values for gadoteridol in the presence of

iohexol were 6.4 and 7.8 s-1

mmol-1

L, respectively, and the r1 and r2 values for the liposome

encapsulated agents were 1.2 and 1.5 s-1

mmol-1

L. The r1 and r2 values for iohexol were found

to be 0.0 s-1

mmol-1

L. Therefore, the encapsulation of the paramagnetic agent gadoteridol in

liposomes (in the presence of iohexol) significantly reduces both the 1/T1 and 1/T2 relaxivity

values, in accordance with Figure 2.6b, as well as previously published data [97].

In vivo imaging

Preliminary in vivo imaging shows visual contrast enhancement in the heart (Figure

2.8) and major blood vessels in both CT and MR up to 72 hours (3 days) following

administration of the liposome-based multimodal contrast agent. Figure 2.9 illustrates the

maintained measurable signal enhancement found in the blood (measured in the aorta) for the

two imaging modalities. Specifically, the signal intensities in MR were increased by over

200% after the administration of the multimodal contrast agent for 72 hours and then

decreased to signal intensities that were approximately twice as high as the pre-contrast

injection values 7 days post administration. In CT, a 60% increase in HU was achieved and

maintained for 3 hours following administration of the agent and a 35% increase in HU was

detectable at 72 hours post-contrast injection. No measurable increase in HU was found 7

days post-contrast injection. The prolonged enhancement achieved in the blood pool in both

32

imaging modalities demonstrates that the liposome carriers are able to circulate and reside in

the blood while retaining the co-encapsulated small molecular weight agents.

(a)

(b)

Figure 2.7 (a) 1/T1 relaxation rate and (b) 1/T2 relaxation rate as a function of gadolinium

(Gd) and iodine (I) concentration obtained at 20°C with a 1.5T, 20-cm-bore superconducting

magnet controlled by an SMIS spectroscopy console. Encapsulation of gadoteridol greatly

reduces both the r1 and r2 of the gadolinium atoms. Symbols represent free gadoteridol (■),

free iohexol and gadoteridol (●), free iohexol (▲) and liposome encapsulated agents (▼).

The r1 and r2 values for all four solutions are listed in Table 2.2. Data are represented as the

mean ± standard deviation.

33

r1 (s-1

mmol-1

L) r2 (s-1

mmol-1

L)

Free gadoteridol 5.14 ± 0.06 6.21 ± 0.08

Free gadoteridol and iohexol (1:29 mole ratio of Gd to I) 6.38 ± 0.16 7.83 ± 0.20

Free iohexol (x-axis = [I] in mmol/L) 0.00 ± 0.00 0.01 ± 0.01

Liposome encapsulated agents 1.23 ± 0.02 1.46 ± 0.02

Table 2.2 Relaxivity r1 and r2 values for the free gadoteridol, free iohexol and gadoteridol,

free iohexol and liposome encapsulated agents solutions plotted in Figures 2.7a and 2.7b.

Data are represented as the mean ± standard deviation.

34

Figure 2.8 Illustration (not quantitative) of the use of the liposome-based contrast agent (single administration of 36 mg/kg of iodine

and 12 mg/kg of gadolinium co-encapsulated in liposomes) in a 3.5 kg white New Zealand rabbit in CT and MR. CT (120 kV,

200mA) and MR (3D FSPGR sequence, TR/TE=8.5/4.1) axial images at the level of the rabbit heart were obtained before and after

contrast agent injection (15, 60, 120, 180 minutes and 24, 72, 168 hours post-contrast in CT and 30, 90, 150, 200 minutes and 24, 72,

168 hours post-contrast in MR). The same window and level were used for pre- and post-contrast injection images. Note the visual

contrast enhancement obtained and maintained in the heart in both imaging modalities.

35

Figure 2.9 Relative percentage signal enhancement achieved in the aorta of the rabbit measured

from MR and CT images using circular regions of interest. In MR, a relative signal intensity

increase of 1930.3 ± 188.1 was measured 30 minutes post-contrast injection and a relative signal

intensity increase of 1028.5 ± 169.3 was measured 7 days post-contrast injection. In CT, a

relative HU increase of 39.2 ± 8.9 was measured 15 minutes post-contrast injection and no

measurable HU increase was found 7 days post-injection. Data are represented as the mean ±

standard deviation.

36

2.5. Discussion

Rational design of a multimodal contrast agent is a complex endeavour in that

different underlying physical mechanisms are responsible for contrast generation across

imaging modalities. In the case of CT, agents containing elements with high atomic number,

such as iodine, are able to increase the differential x-ray attenuation between different soft

tissues and organs. Whereas, MR contrast agents made up of paramagnetic metals, such as

gadolinium, are able to deliver signals by increasing surrounding tissue relaxivity.

Furthermore, the differences in intrinsic sensitivity and resolution between the two imaging

modalities create a requirement for substantially different concentrations of each reporter

moiety in order to achieve adequate signal intensity1. For example, in a clinical context, MR

is sensitive to gadolinium concentrations between 1-10 µg/mL, while CT requires at least 1

mg/mL of iodine for detection [80]. A multimodal contrast agent with efficacy in CT and MR

must, therefore, accommodate this 100-fold differential in sensitivity and minimize any

agent-related signal interferences across different imaging modalities.

To date, although a multitude of contrast agents are commercially available for single

modality imaging, few attempts have been made to develop contrast agents that can be used

across multiple imaging modalities [100-105]. The lack of development in this area is likely

due to challenges presented by the fact that the distinct imaging modalities have distinct

sensitivities for different contrast agents [80]. A simple approach for realizing a multimodal

contrast agent for CT and MR has been to exploit commercially available extracellular

1 It is important to note that the different physical processes involved in the generation of CT and MR signals

contribute to the difference in detection sensitivity for their respective contrast agents (i.e. iodine and

gadolinium). For example, for a CT scanner operating at 120 kVp and 200 mA, the photon fluence measured at

50 cm away from the x-ray source is in the order of 108 to 10

9 photons/mm

2 [98]. This means that an iodine

atom (of ~ 10-8

mm2 in surface area) has a probability of interacting with only 1 to 10 x-ray photons over the

entire exposure time. Conversely in MR, a gadolinium chelate can interact with approximately 106 water

protons in one second [99].

37

gadolinium-based contrast agents for enhancement in both of these modalities. In this case,

the properties of gadolinium that allow for use in both CT and MR include its relatively high

atomic number and paramagnetic characteristics [100-104]. However, due to their low

molecular weight, these agents only remain in the vascular system for a short period of time,

exhibit rapid dynamic distribution changes in different organs and are excreted quickly. The

use of these agents for cross-modality imaging would therefore require both multiple

administrations and fast imaging sequences. Also, the low gadolinium payload per molecule,

relative to conventional iodinated contrast agents, would necessitate the administration of

higher doses for adequate CT enhancement which may have implications in terms of both

cost and toxicity [100-104]. Furthermore, the short in vivo residence time of these agents

would impose limitations on the size of the anatomic region that could be imaged optimally

and would exclude them from being used in image-guidance applications due to their

inability to provide prolonged contrast enhancement over the entire course of treatment [81].

An approach to effectively deliver the required amount of contrast in each imaging modality

and to prolong the presence of the agents in vivo is to employ particulate carriers such as

liposomes. Specifically, liposome-based systems have been evaluated for either

encapsulating [106-122] or chelating [123-127] single CT or MR contrast agents.

In this study liposomes were selected as the system of choice for delivery of CT and

MR contrast agents at appropriate concentrations. The strategy of co-encapsulating two

agents in a liposome was pursued for the following reasons: (i) guarantee of consistent

transport and distribution of both agents; (ii) liposomes have well understood and

characterized physical and biological properties, and formulations based on this technology,

such as Doxil

(Ortho Biotech Products, L.P., Bridgewater, NJ, USA), DaunoXome

(Gilead

38

Sciences, Inc., Foster City, CA, USA) and Nyotran

(Aronex Pharmaceuticals, Inc., The

Woodlands, TX, USA), have received regulatory approval for clinical use; (iii) both the CT

and MR contrast agents selected for encapsulation have been widely used in clinical

applications; (iv) encapsulation of iohexol in liposomes does not affect the CT attenuation

capability of this agent; therefore, as long as a sufficient quantity of iodine is loaded into the

interior of the liposomes adequate signal enhancement is expected; and (v) although

gadolinium relaxation is greatly dependent on the amount of water that the gadolinium atoms

can access when encapsulated, the permeability of the liposome membrane can be easily

adjusted by varying the lipid composition and cholesterol content [128-130]. In the present

study, the liposomes were prepared from DPPC, cholesterol and PEG2000DSPE (55:40:5

percent mole ratios). A high cholesterol content (> 40%) was used in order to produce fluid

membranes with a high degree of mechanical stability [128, 131]. The fluidity of the

membrane will allow for adequate interaction between the encapsulated gadolinium atoms

and the external aqueous environment. Cholesterol-rich liposomes (> 40%) have also been

shown to be less subject to protein binding when compared to cholesterol-poor (< 20%)

liposomes [132, 133]. Furthermore, cholesterol-rich liposomes formed primarily from DPPC

are known to be more resistant to the destabilizing effects of serum proteins and have

reduced uptake by the monophagocytic system (MPS), when compared to DPPC-based

cholesterol-poor formulations [133-135]. The addition of PEG onto the liposome surface is

aimed to increase its in vivo circulation lifetime [136, 137]. The presence of PEG will also

improve the MR imaging performance since it has been found that liposomes containing

5%mol of PEG can achieve up to two times higher r1 relaxivity values in solution relative to

conventional (non-PEGylated) liposomes. This increase in the r1 relaxivity values for the

39

PEGylated liposome solution has been attributed to the presence of PEG-associated water

protons in the vicinity of the liposome membrane [138]. The present formulation was

prepared using the high-pressure extrusion method [82, 83] and was comprised of spherical

vesicles (Figure 2.2) of ~ 74 nm in diameter. This vesicle size was chosen because small

unilamellar liposomes of less than 100 nm in diameter have been found to have prolonged in

vivo circulation lifetimes [130].

The ideal system for delivery of long circulating contrast agents will have minimal

agent release in vivo. A stable formulation with slow release profiles for both agents will

allow for prolonged imaging studies and repeated scans in CT and MR. It is known that

extracellular agents with small molecular weights such as iohexol and gadoteridol have a

much faster clearance profile in vivo compared to colloidal carriers such as liposomes [81].

Therefore, as the encapsulated agents are released from the liposomes, the signal

enhancement will diminish in both CT and MR at a rate that is proportional to that of agent

release and clearance. In this way, the slow agent release profiles (< 9% of each agent

released over 15 days, Figure 2.3) and stability (liposome size remained unchanged over 15

days, Figure 2.4) achieved in vitro for the current liposome formulation has translated into

prolonged signal enhancement in vivo in both imaging modalities (Figures 2.8 and 2.9).

These studies only include a preliminary evaluation of this system thus a more detailed

analysis of the in vivo performance of this agent is a topic of ongoing investigation [139].

The loading characteristics of the current system (Table 2.1) represent roughly 10%

of the iodine and gadolinium concentrations found in the commercially available

preparations (i.e. Omnipaque

and Prohance

). However, agents encapsulated in a colloidal

delivery system of 74 nm in diameter will have ~1/3 of the volume of distribution in vivo

40

compared to small extracellular agents since the latter will readily cross the fenestrations in

the epithelial lining of the blood vessels and enter the interstitium following an intravenous

injection [140, 141]. Consequently, directions for future investigations are aimed at achieving

higher agent loading levels (~3x) in order to minimize the injection volume required. In

addition, there is interest in modifying the surface of the liposomes in order to actively target

the vehicles for delivery of agents to specific sites for functional and molecular imaging

applications.

This proof of principle study has demonstrated the feasibility of engineering a stable

liposome-based system that can be used for CT and MR imaging. This system leverages

existing clinical knowledge and experience since it employs contrast agents and colloidal

carrier technology that are currently approved for use in humans. However, it is necessary to

analyze the impact of the liposome formulation on the pharmacokinetics and biodistribution

of the agents. These studies, as well as further analysis of the imaging efficacy of the current

formulation are underway. Successful optimization of this system may allow for an

accelerated development and approval timeline for clinical evaluation. In general, research

into the development of multimodal contrast agents has the potential to lead to solutions for

the combined challenge of disease detection, treatment design and therapy guidance.

2.6. Acknowledgements

The authors would like to acknowledge Dr. Tom Purdie for operation of the CT

scanner, Dr. Greg Stanisz for use of the SMIS spectroscopy console and T2 data analysis

software, Ewa Odrobina for assistance in relaxivity data collection, Jubo Liu for TEM image

acquisition and Sandra Lafrance for animal care.

41

Chapter 3. In Vivo Performance of a Liposomal Vascular Contrast Agent

for CT and MR-Based Image Guidance Applications

42

3.1. Foreword

The previous chapter described the feasibility of employing a nanoparticle liposome

system to stably co-encapsulate two distinct imaging agents and provide signal enhancement

in both imaging modalities. This chapter investigates the in vivo performance of this

multimodality liposome system, including its ability to remain confined within blood vessels

in healthy animals, its increased vascular circulation life-time compared to administrations of

un-encapsulated agents, and the range of intravascular iodine and gadolinium concentration

that are quantifiable non-invasively using CT and MR, respectively, and validated by

chemical analysis methods through plasma sampling. The overall goal is to demonstrate the

utility of this liposome agent for vascular imaging and longitudinal image-guidance

applications. The following chapter has been published as:

Zheng J, Liu, J, Dunne M, Jaffray DA, Allen C. In Vivo Performance of a Liposomal

Vascular Contrast Agent for CT and MR-Based Image Guidance Applications.

Pharmaceutical Research, Volume 24, Number 6, Pages 1193 – 1201. June 2007.

It has been reproduced with kind permission from Springer Science + Business Media.

3.2. Introduction

There has been a tremendous growth in the use of non-invasive imaging techniques

for characterization of biological processes, diagnosis of disease and guidance of

interventions or treatment. Examples of image guided interventions include x-ray, MR and

ultrasound-guided surgical procedures [142-145], as well as cone-beam CT-based guidance

of radiation therapy delivery [78, 79]. Although different imaging techniques are able to

43

detect inherent contrast in biological systems, conventional diagnostic agents have been

employed to enhance soft tissue contrast [146, 147]. However, these are typically low

molecular weight molecules and their rapid clearance creates the need for multiple

administrations (i.e. angiography). The development of a long circulating contrast agent

would offer benefits for guiding interventions in which multiple injections are not feasible or

the imaging procedure requires more persistent signal enhancement. Specifically, in radiation

therapy, volumetric CT and MR data sets are first acquired and registered for the purpose of

radiation dose calculation and target definition [76], and cone-beam CT is then used to guide

the delivery of radiation at each treatment session [78, 79]. In this application, the contrast

agent is required to provide prolonged signal enhancement for planning (CT and MR), as

well as visibility during the process of cone-beam CT acquisition. Thus, an agent with an in

vivo lifetime of several days or even weeks would be ideal.

A viable strategy to achieve prolonged signal enhancement in vivo is to employ

colloidal vehicles to carry conventional contrast agents. Indeed, nano-sized contrast agents

have been engineered using liposomes [61, 106, 108, 148-154], lipid and polymeric micelles

[155-159], nanoparticles [160-165], dendrimers [166-169] and proteins [170, 171] as carrier

systems. In a few cases, these systems have been designed to provide simultaneous contrast

enhancement in multiple modalities [61, 105, 150, 172, 173]. However, none of the colloidal

systems reported to date have been demonstrated to provide satisfactory and simultaneous

signal enhancement in CT and MR. Also, the limited in vivo stability and circulation lifetime

of these systems prevent their use throughout both the planning and delivery of radiation

therapy.

44

In a previous report, our group summarized the development and in vitro

characterization of a dual modality contrast agent for imaging in CT and MR [61]. The agent

consists of liposomes co-encapsulating iohexol, an iodine-based conventional CT agent, and

gadoteridol, a gadolinium-based conventional MR agent within their internal aqueous

compartment. The liposome-based system exhibited high stability in vitro, with less than

10% of the total amount of the encapsulated agents (i.e. iohexol and gadoteridol) released

over a 14-day period in physiological buffer at 37°C. The present study is aimed at

investigating the in vivo pharmacokinetics and imaging characteristics of this dual modality

agent. Specifically, the in vivo stability was evaluated by measuring the pharmacokinetics

and biodistribution of the liposome encapsulated CT and MR agents in Balb-C mice

following intravenous (i.v.) administration. Studies evaluating the in vivo imaging efficacy

were conducted in New Zealand White rabbits using clinical CT and MR scanners. In

addition, the signal increases measured in a region of interest in the rabbit aorta in the two

imaging modalities were correlated with the actual iodine and gadolinium concentrations

detected in plasma samples in order to investigate the potential of using this agent for

quantitative imaging applications.

3.3. Materials and Methods

Materials

1,2-Dipalmitoyl-sn-Glycero-3-Phosphocholine (DPPC, M.W. 734), and 1,2-

Distearoyl-sn-Glycero-3-Phosphoethanolamine-N-[Poly(ethylene glycol)2000] (DSPE -

PEG2000, M.W. 2774) were purchased from Genzyme Pharmaceuticals (Cambridge, MA,

USA). Cholesterol (CH, M.W. 387) was purchased from Northern Lipids Inc. (Vancouver,

45

British Columbia, Canada). The CT contrast agent Omnipaque

(Nycomed Imaging AS,

Oslo, Norway) has an iodine concentration of 300 mg/mL and consists of the non-ionic,

iodinated molecule iohexol (N , N ´-Bis(2,3-dihydroxypropyl)-5-[N-(2,3-dihydroxypropyl)-

acetamido]-2,4,6-triiodo-isophthalamide, M.W. 821.14, 3 iodine atoms per molecule)

dissolved in an aqueous solution with tromethamine and edentate calcium disodium. The MR

contrast agent ProHance

(Bracco Diagnostics Inc., Princeton, NJ, USA) has a gadolinium

concentration of 78.6 mg/mL and consists of the non-ionic, gadolinium complex gadoteridol

(10-(2-hydroxy-propyl)-1,4,7,10-tetraazacyclododecane-1,4,7-triacetic acid, M.W. 558.7, 1

gadolinium atom per complex) dissolved in an aqueous solution with calteridol calcium and

tromethamine.

Preparation and characterization of liposome formulations

Liposomes composed of DPPC, cholesterol and PEG2000DSPE in 55:40:5 percent

mole ratios were prepared according to a method described in detail elsewhere [61]. Briefly,

100 mmol/L of the lipid mixture was first dissolved in an initial ethanol volume

corresponding to 10% of the desired final sample volume. Omnipaque

and Prohance

were

then added to the lipid mixture at a volume ratio of 4:1 and left to hydrate at 75°C for at least

4 hours. The resulting multilamellar vesicles were then sized to 70-85 nm in diameter using

high pressure extrusion (10 extrusion cycles) at 70°C with a 10 mL LipexTM

Extruder

(Northern Lipids Inc., Vancouver, British Columbia, Canada). The un-encapsulated iohexol

and gadoteridol molecules were removed by membrane dialysis (8,000 molecular weight cut-

off) for 8 hours against 250-fold excess volume of N-(2-hydroxyethyl)piperazine-

N'(ethanesulfonic acid) (HEPES) buffer saline (HBS). The size of the liposomes was

46

measured by dynamic light scattering (DLS) analysis of dilute solutions using a DynaPro

DLS instrument (Protein Solutions, Charlottesville, VA, USA) at 25°C. The final

concentration of iohexol was determined using a UV assay with detection at a wavelength of

245 nm (Heλios γ, Spectronic Unicam, MA, USA). The final concentration of gadoteridol

was determined using an assay based on inductively coupled plasma atomic emission

spectrometry (ICP-AES Optima 3000DV, Perkin Elmer, MA, USA) [61].

Pharmacokinetics and biodistribution studies

The pharmacokinetics and biodistribution studies were performed under protocols

approved by the University Health Network Animal Care and Use Committee. Female Balb-

C mice (8-12 weeks, 18-23 g) were administered slow bolus tail vein injections of 150 µL of

the contrast agent. Each mouse received 650 mg/kg of iohexol (equivalent to 300 mg/kg

iodine) and 60 mg/kg gadoteridol (equivalent to 17 mg/kg of gadolinium) either as a mixture

of free agents diluted in HBS or co-encapsulated in liposomes. The animals were

anaesthetized with 2% isoflurane and a terminal blood volume (0.5-1.0 mL) was drawn by

cardiac puncture at 5, 15, 30 minutes and 1, 2 and 3 hours following the administration of the

free agent mixture, and at 5 minutes, 1, 8, 24, 48, 72, 96, 120, 144 and 168 hours following

administration of the liposome formulation. The animals were then sacrificed by cervical

dislocation and their heart, liver, kidneys and spleen were harvested. Each organ was

thoroughly washed in phosphate buffer saline (PBS, pH = 7.4) and then frozen at -80°C.

The plasma was isolated by centrifugation of the blood samples at 3000 g for 10

minutes. Iohexol and gadoteridol were extracted from the plasma and tissue samples using

10% perchloric acid (4-fold excess volume). Plasma and tissue concentrations of iohexol

47

were determined using a high performance liquid chromatography instrument (HPLC,

PerkinElmer Series 200) equipped with a C18 Xterra reverse-phase column with ρ-

aminobenzoic acid as the internal standard. The mobile phase for plasma samples was 90%

methanol and 10% 100mM acetic acid buffer at a pH of 4.10. The mobile phase for tissue

samples was composed of 92% methanol and 8% 100mM acetic acid buffer at a pH of 4.10.

The flow rate was 0.9 mL/min and UV detection was performed at 245 nm to measure the

concentration of iohexol. The plasma and tissue concentrations of gadoteridol were

determined using ICP-AES [61].

The data obtained from the pharmacokinetics study was used to determine the main

pharmacokinetic parameters for iohexol and gadoteridol when administered as free agents or

agents encapsulated within liposomes. For the free agents, a two-compartment model was

used to determine the distribution constant (Kd or α) and the elimination constant (Ke or β).

The distribution half-life (t1/2α ) was then calculated using the equation: t1/2α = ln(2)/Kd, while

the elimination half-life (t1/2β) was calculated using the equation: t1/2β = ln(2)/Ke. For the

liposome-encapsulated agents, the Ke value was determined by fitting the plasma

concentration versus time curve (each data point represents the mean of three distinct

animals) with a one-compartment model. The vascular circulation half-life (t1/2) was then

calculated using the following equation: t1/2 = ln(2)/Ke. The area under the plasma

concentration versus time curve (AUC) was calculated using the trapezoid rule. The plasma

clearance CL and the volume of distribution Vd were determined using Equations 3.1 and 3.2,

respectively, as shown below.

BodyWeightAUC

DoseCL

⋅= (Equation 3.1)

48

e

dK

CLV = (Equation 3.2)

Due to the inadequate resolution of the clinical CT and 1.5 T MR (and head coil) systems for

imaging mouse vasculature, a larger animal model (rabbit) was employed for the following

imaging studies.

CT and MR imaging of animal subjects

The in vivo imaging study was performed under a protocol approved by the

University Health Network Animal Care and Use Committee. Healthy female New Zealand

White rabbits (2.5-3 kg) were anaesthetized with an intramuscular injection of either a

ketamine and xylazine mixture or acepromazine. A slow bolus injection (0.5 mL/second) of

20 mL of the liposomal contrast agent formulation was then administered to the marginal ear

vein catheter. Each rabbit received 730 mg/kg iohexol (equivalent to 340 mg/kg of iodine)

and 69 mg/kg gadoteridol (equivalent to 19 mg/kg of gadolinium) co-encapsulated within the

liposomes. 2% isoflurane vapor was given by inhalation throughout the study. Images of the

rabbits were acquired pre and post-administration of the liposome formulation in CT (GE

Discovery ST, General Electric Medical Systems, Milwaukee, WI, USA) and MR (GE Signa

TwinSpeed MR scanner, General Electric Medical Systems, Milwaukee, WI, USA). The

rabbits were CT scanned (120 kVp, 200 mA, a voxel size of 0.43 x 0.43 x 0.625 mm3, and a

FOV of 220 x 220 x 400 mm3) at 10 and 60 minutes as well as 24, 48, 72, 96, 120 and 168

hours following administration of the liposome formulation. The rabbits were MR scanned

(3D FSPGR sequence with a TR of 9.8 ms, a TE of 4.3 ms, a flip angle of 15°, a voxel size of

0.86 x 0.86 x 1.5 mm3 over a FOV of 220 x 220 x 228 mm

3, and an image matrix of 256 x

256) at 30 and 90 minutes as well as 24, 48, 72, 96, 120 and 168 hours post-administration of

49

the formulation. The mean attenuation values in Hounsfield units (HU) in CT and the relative

signal intensities (SI) in MR were measured in the aorta with circular regions of interest of

over a cross sectional area of ~ 9 mm2 in a single axial image. For visualization purposes,

3D maximum intensity projection (MIP) images were generated using eFilm Workstation

(Merge eFilm, Milwaukee, WI, USA). The same window and level were used for the pre and

post-contrast images. In addition, for the correlation study, 1.5 mL of blood was collected

from the ear vein of the same rabbits at the following time points: 5 minutes, 24, 48, 72, 96,

120 and 168 hours.

Acute toxicity studies and corresponding statistical analysis

Female Balb-C mice (8-12 weeks, 18-20 g) were randomly divided into three groups

as follows: mice receiving no formulation, mice receiving empty liposomes (530 mg/kg of

lipid); mice receiving iohexol (650 mg/kg, equivalent to 300 mg/kg iodine) and gadoteridol

(53 mg/kg, equivalent to 15 mg/kg gadolinium) co-encapsulated within liposomes (530

mg/kg lipid). Seven days later blood samples (0.5-1mL) were drawn by cardiac puncture and

sent to Vita-Tech (Markham, Ontario, Canada) for haematological and biochemical analysis.

The analysis included determination of number of white and red blood cells (WBC and

RBC), platelets, and measurement of hematocrit, hemoglobin, serum creatinine, alkaline

phosphatase (ALP), alanine transaminase (ALT) and aspartate transaminase (AST)

concentrations. Statistical comparisons of the acute toxicity values were performed using the

student t-test [174]. Computations were performed in Microsoft Excel. P-values greater than

0.05 were considered to be statistically insignificant.

50

3.4. Results

Preparation and characterization of the multimodal liposome formulation

The preparation, physico-chemical characterization and in vitro optimization of this

multimodal liposome formulation have been described in detail elsewhere [61]. The average

diameter of the liposomes in each preparation, as measured by DLS, was found to range

between 70-85 nm. Each formulation contained an iodine to lipid weight ratio of 1:1.8 and

gadolinium to lipid weight ratio of 1:35.7. The iodine to gadolinium ratio employed in this

formulation was selected from consideration of in vitro imaging studies in phantoms, which

evaluated the sensitivity of each imaging modality to detect the presence of contrast material

within the formulation [61].

Pharmacokinetics and biodistribution studies in healthy mice

The pharmacokinetics and organ distribution profiles of the co-encapsulated contrast

agents, iohexol and gadoteridol, were evaluated in healthy female Balb-C mice as a means to

assess the in vivo stability of this liposome formulation. Figure 3.1 includes the 7-day

pharmacokinetics profiles for iohexol and gadoteridol, following i.v. administration in the

DPPC/CHOL/PEG2000DSPE liposomes, as well as the 3-hour pharmacokinetics profiles for

free iohexol and gadoteridol. The pharmacokinetics profiles for the agents encapsulated in

liposomes were fit using a one-compartment model and the main pharmacokinetics

parameters were calculated as listed in Table 3.1. The circulation half-lives for the agents

were found to be 18.4 ± 2.4 hours for liposome encapsulated iohexol and 18.1 ± 5.1 hours for

liposome encapsulated gadoteridol. The pharmacokinetics profiles for the free agents were fit

using a two-compartment model. The distribution (α phase) half-life for free iohexol was

51

12.3 ± 0.5 minutes and for free gadoteridol it was 7.6 ± 0.9 minutes, while the elimination (β

phase) half-lives were 3.0 ± 0.9 hours for free iohexol and 3.0 ± 1.3 hours for free

gadoteridol. The values obtained for the half-lives of the free agents are in agreement with

previously published results [175, 176]. The extended and similar circulation half-lives

obtained for iohexol and gadoteridol when administered in this liposome formulation suggest

that these agents remain co-encapsulated within the formulation in vivo.

Figure 3.2 includes biodistribution profiles for the liposome-encapsulated agents in

the heart, liver, kidney and spleen over a 7-day period. Similar distribution and clearance

behavior were seen in the heart and liver for iohexol and gadoteridol. While an enhanced

elimination of iohexol was observed in the kidney and the spleen compared to gadoteridol.

In vivo CT and MR imaging in healthy rabbits

Imaging studies were performed on rabbits with a clinical CT scanner and a clinical

MR scanner with a head coil. As shown in Figure 3.3, the same rabbit was imaged

sequentially in CT and MR for a period of 7 days at selected time points both prior to and

following administration of the liposome formulation. The clear post-contrast visualization of

the rabbit heart, liver and spleen, as well as the transient visualization of the kidneys, is in

agreement with the presence of the liposomal iohexol and gadoteridol detected in the same

organs in mice (Figure 3.2).

At each time point a 1 mL sample of blood was also collected from the rabbit and the

plasma concentrations of agents present were quantified using HPLC and ICP-AES analysis.

A region of interest of 2 mm in diameter in the rabbit aorta was identified and the signal

52

0 25 50 75 100 125 150 175 2000.01

0.1

1

10

100

1000

10000

Time (h)

Pla

sm

a a

ge

nt

co

nce

ntr

atio

n

(µg

/mL

)

0.0 0.5 1.0 1.5 2.0 2.5 3.01

10

100

1000

10000

Time (h)

Pla

sm

a a

gen

t co

ncen

tratio

n

(µg/m

L)

changes were measured in CT and MR and compared to the concentration values for iodine

and gadolinium as determined by analysis of the plasma samples.

Figure 3.1 Pharmacokinetics of free iohexol (�), free gadoteridol (�), liposomal iohexol

(�) and liposomal gadoteridol (�) in healthy female Balb-C mice (n=3). The 2-week-old

mice (18-23 g) were i.v. administered free iohexol and free gadoteridol diluted in HBS or

liposome encapsulated iohexol and gadoteridol containing 650 mg/kg of iohexol (equivalent

to 300 mg/kg iodine) and 60 mg/kg gadoteridol (equivalent to 17 mg/kg of gadolinium).

Plasma was sampled at the indicated time points and analyzed using HPLC for iohexol and

ICP-AES for gadoteridol. Data are represented as the mean ± standard deviation.

53

Iohexol Gadoteridol

Ke 0.0377 0.0383

r2 0.975 0.980

t1/2 (h) 18.4 18.1

AUC (µµµµg*h/mL) 5910000 582000

CL (mL/h/g) 0.00219 0.00206

Vd (mL/g) 0.0580 0.0538

Table 3.1 Pharmacokinetic parameters for iohexol and gadoteridol when administered in a

liposome formulation to female Balb-C mice. Abbreviations: Ke is the elimination constant;

r2 is the coefficient of determination for this fit (every point used for the fit is the mean value

obtained from 3 distinct animals); t1/2 is the vascular circulation half-life; AUC is the area

under the concentration versus time curve in plasma; CL is the total plasma clearance and Vd

is the volume of distribution per unit mass.

54

(a)

0 25 50 75 100 125 150 175 2001

10

100

1000

10000

µg

ag

en

t /

g h

eart

Time (h)

(b)

0 25 50 75 100 125 150 175 2001

10

100

1000

10000

Time (h)

µg

ag

en

t /

g liv

er

55

(c)

0 25 50 75 100 125 150 175 2001

10

100

1000

10000

Time (h)

µg a

ge

nt

/ g

kid

ne

y

(d)

0 25 50 75 100 125 150 175 2001

10

100

1000

10000

Time (h)

µg

ag

en

t /

g s

ple

en

Figure 3.2 Biodistribution of iohexol (�) and gadoteridol (�) when administered in a

liposome formulation to female Balb-C mice. The animals were sacrificed at specific times

and a) heart, b) liver, c) kidneys, d) spleen samples were analyzed to determine levels of

iohexol and gadoteridol. Each data point represents the mean of three distinct animals ±

standard deviation.

56

Figure 3.3 Three-dimensional maximum intensity projection images (anterior view) of a healthy New Zealand White rabbit (3kg)

obtained in CT (120 kV, 200mA) and MR (3D FSPGR sequence, TR/TE=9.8/4.3) prior to and following i.v. administration (as

indicated) of the liposome formulation of iohexol and gadoteridol. The same window and level were used for pre- and post-injection

images. Note the visual contrast changes in the heart (H), aorta (A), vena cava (V), carotid artery (C), kidney (K) and spleen (S).

57

The percent signal increases in CT and MR were calculated using equations 3 and 4.

( )100

HU

HUHUHU

o

o

t

tt

increase ⋅−

=% (Equation 3)

( )100

SI

SISISI

o

o

t

tt

increase ⋅−

=% (Equation 4)

Figure 3.4 includes a plot of the signal changes in CT and MR versus the measured value of

the concentration of each respective agent in plasma. A linear correlation (r2=0.997) was

obtained for the %HUincrease measured in CT and the concentration of iodine in the plasma

(Ciodine). In contrast, an exponential relationship was obtained for the %SIincrease measured in

MR and the plasma concentrations of gadolinium (Cgadolinium). This is a result of the

established non-linear relationship between MR signal intensity and gadolinium

concentration [177]. The successful correlation of the signal changes measured using the

imaging systems and the actual concentration of contrast agents detected in the biological

samples indicates that this liposome formulation may be suitable for quantitative imaging

applications, as well as non-invasive and quantitative CT and MR tracking of these nano-

sized vehicles in vivo.

Preliminary evaluation of acute toxicity

Figure 3.5 summarizes the results obtained from the hematological and biochemical

analysis of plasma samples obtained one week following administration of both empty

liposomes and the liposome formulation of the CT and MR contrast agents. As shown, there

were no statistically significant changes (for p=0.05) in the levels of red and white blood

cells, hemoglobin, hematocrit, serum creatinine, and various liver enzymes (ALP, ALT and

AST), 7 days following administration of the multimodal liposomes in comparison to

58

animals receiving no treatment or those that received the empty liposomes. This analysis

provides a preliminary indication of the lack of toxicity and biocompatibility of this

formulation.

(a)

0 300 600 900 1200 1500 1800 2100

0

50

100

150

200

250

300

350

400

%HUincrease

= 0.183*Ciodine

- 9.65

R2=0.997

Ciodine

(µµµµg/mL)

HU

in

cre

ase (

%)

(b)

0 50 100 150 200 250

0

50

100

150

200

250

300

%SIincrease

= a*(1 - e-b*C

gadolinium)

a = 326.2 + 31.8

b = 0.102 + 0.002

Cgadolinium

(µµµµg/mL)

SI in

cre

ase (

%)

59

(c)

0 300 600 900 1200 1500 1800 2100

0

50

100

150

200

250

300

350

400

Ciodine

or Cgadolinium

(µµµµg/mL)

Sig

nal in

cre

ase (

%)

% HUincrease

in CT vs. Ciodine

% SIincrease

in MR vs. Cgadolinium

Figure 3.4 Plots of the relative change in signal intensity pre- and post-administration of the

multimodal liposomal agent (a) in CT versus the measured plasma iodine concentration, (b)

in MR versus the measured plasma gadolinium concentration. The %HUincrease in CT was

measured using circular regions of interest of 2 mm in diameter in the rabbit aorta and the

plasma concentrations of iodine were determined by HPLC (�). The %SIincrease in MR was

measured using circular regions of interest of 2 mm in diameter in the rabbit aorta and the

plasma concentration of gadolinium was determined by ICP-AES (�). (c) The two plots are

combined in a single graph to illustrate the differential response of each modality to different

concentrations of the respective contrast agent.

60

WB

C (

x10e9/L

)

RB

C (

x10e9/L

)

Hem

og

lob

in (

g/L

)

Hem

ato

cri

t (%

)

Pla

tele

ts (

x10e9/L

)

Seru

m C

reati

nin

e (

um

ol/L

)

AL

P (

U/L

)

AL

T (

U/L

)

AS

T (

U/L

)

0

200

400

600

800

1000

1200

No-injection

Empty liposomes (day 7)

Iohexol and gadoteridol loaded liposomes (day 7)

Figure 3.5 Summary of the hematological and biochemical evaluation of plasma samples

obtained from female Balb-C mice (n=3) seven days following (1) no treatment, (2)

administration of empty liposomes, or (3) administration of liposomes containing both

iohexol and gadoteridol. Abbreviations: white blood cell (WBC), red blood cell (RBC),

alkaline phosphatase (ALP), alanine transaminase (ALT) and aspartate transaminase (AST).

Data are represented as the mean ± standard deviation. For all parameters, the differences

between the 3 groups are found to be statistically insignificant using the student t-test (all p-

values were greater than 0.05).

61

3.5. Discussion

The in vivo stability of this liposome formulation was confirmed by evaluation of the

pharmacokinetics (PK) and biodistribution of the co-encapsulated agents, iohexol and

gadoteridol, in healthy mice at various time points following intravenous administration. As

shown in Table 3.1, the circulation half-lives for iohexol and gadoteridol were 18.4 ± 2.4

hours and 18.1 ± 5.1 hours, respectively, when administered in this liposome formulation.

When the free agents were administered at the same dose, the distribution (α phase) half-life

for the free iohexol was 12.3 ± 0.5 minutes and 7.6 ± 0.9 minutes for the free gadoteridol;

while, the elimination (β phase) half-lives were 3.0 ± 0.9 hours for free iohexol and 3.0 ± 1.3

hours for free gadoteridol. Thus, formulation of these agents in the

DPPC/CHOL/PEG2000DSPE liposomes significantly increases their circulation half-lives.

Though efforts were not put forward to distinguish between the encapsulated and released

iohexol or gadoteridol, the similar behavior of iohexol and gadoteridol in terms of

accumulation and clearance as detected in the blood, heart and liver strongly suggests that

these agents are still co-encapsulated within the internal aqueous volume of the liposomes at

the time of measurement. However, iohexol shows an enhanced elimination in both the

kidney and the spleen compared to gadoteridol. This may be attributed to the different

mechanisms associated with the clearance and metabolism of the individual contrast agents

in the kidneys [178, 179] and the spleen. Studies have shown that following intravenous

administration approximately 95% of the free agents are cleared though the glomerular

filtration process in the kidneys [175, 180]. Consequently no study has yet been conducted to

investigate the clearance and metabolism of iohexol and gadoteridol in the spleen. The

alteration in the biodistribution of these agents due to administration in the liposome

62

formulation has now prompted a separate study to investigate the clearance of these agents

from the spleen.

The contrast enhancement seen in CT and MR, as shown in Figure 3.3, is due to the

increased iodine and gadolinium content in the visually enhanced locations. Unlike

radionuclide and optical imaging which employ radionuclide tracers and optical labels, CT

and MR contrast agents such as iohexol and gadoteridol do not decay or bleach over time.

Hence CT and MR are two imaging methods suitable for multi-session longitudinal studies,

especially those requiring long imaging sequences. One of the advantages of this dual CT

and MR contrast agent system is that the in vivo agent concentrations may be monitored over

a wider range. Figure 3.4 shows the ability of MR to estimate in vivo gadolinium

concentrations ranging from 10 µg/mL to 200 µg/mL, while CT can estimate iodine

concentrations from 100 µg/mL to 2000 µg/mL. The lower detection limit presented here

corresponds to the iodine or gadolinium concentration needed to generate a signal differential

in CT or MR that is greater than the highest noise level. The two imaging modalities may,

therefore, detect in vivo liposome concentrations that are one thousand fold lower (~ 1011

liposomes/mL) than the original formulation administered (~ 1014

liposomes/mL). In this

way, the dual liposome-based CT and MR contrast agent allows for measurement over a

broader concentration range, and also takes advantage of the strengths of each imaging

modality. For example, CT provides contrast of the bony structures with high spatial and

temporal resolution, while MR allows for better visualization of the soft tissues [76, 77, 181].

The colloidal size of this multimodal liposomal agent makes it a good intravascular

agent (Figure 3.3) that may be able to provide reliable estimation of vascular volume.

Currently available small molecular weight contrast agents exhibit two-compartment

63

pharmacokinetics, quickly leaking from the blood vessels into the tissue interstitium. Thus,

they require complex physiological modeling as well as fast imaging sequences in order to

measure their first pass enhancement in studies involving deconvolution of blood vessel

permeability and vascular volume in angiogenic tumors [182-184]. The successful

development of this liposomal agent with prolonged intravascular residence time may be of

assistance in obtaining more accurate perfusion and permeability measurements in healthy

and diseased tissues, as well as information on physiological processes that occur over a

longer time course.

Following characterization of the in vivo stability and behavior of this liposome-based

system it also became evident that this system may be used as a tool to address unanswered

questions that remain surrounding the in vivo fate of passively and actively targeted

nanocarriers. The clear advantages to the use of imaging methods, over conventional whole

organ digestion methods, to map liposome distribution in vivo is the non-invasive nature of

this approach and the ability to also obtain sub-organ or sub-tissue distribution patterns up to

the spatial resolution limit of the imaging system. Specifically in this study, the voxel size

achieved was 0.43 x 0.43 x 0.625 mm3 in CT and 0.86 x 0.86 x 1.5 mm

3 in MR. Potential

applications of this CT and MR system include non-invasive assessment of tumor

accumulation and distribution of passively and actively targeted liposomes in pre-clinical and

clinical settings, development of correlations between tumor penetration of liposomes and the

state of tumor vasculature [185]. In addition, this multimodal liposome system may be used

to assess the performance or behavior of liposomes following administration of different

therapies (i.e. anti-angiogenic therapies, radiotherapy and/or chemotherapy), which may

ultimately aid in the optimization of the sequence and dosing of combined therapies.

64

3.6. Acknowledgements

This work is funded in-part by a CIHR Operating Grant and a CIHR Proof of

Principle Grant to D.A. Jaffray and C. Allen, the Premier’s Research Excellence Award, the

Fidani Chair in Radiation Physics and the Grange Advanced Simulation Initiative. J. Zheng

is grateful for the Excellence in Radiation Research for the 21st Century Training Fellowship

and the Mitchell Scholarship. The authors would like to thank the UHN animal care staff for

their assistance.

65

Chapter 4. Quantitative CT Imaging of the Spatial and Temporal

Distribution of Liposomes in a Rabbit Tumor Model

66

4.1. Foreword

The previous two chapters demonstrated the stability of the liposome system in vitro

and in vivo. This chapter explores the use of volumetric regions of interests in CT to measure

the changes in iodine concentrations in normal and diseased tissues over time. The sensitivity

(i.e. of minimum amount of detectable iodine) of this method was assessed as a function of

the size of the volume of analysis. The method was then applied to non-invasively

characterize the biodistribution and kinetics of liposomes in a VX2 carcinoma rabbit model

over a 14-day period. The sub-millimeter spatial resolution of CT allowed for visualization of

the heterogeneity of contrast enhancement within tumors, allowing quantification of the

intratumoral volume of distribution of liposomes over time. The following chapter has been

published as:

Zheng J, Jaffray DA, Allen C. Quantitative CT Imaging of the Spatial and Temporal

Distribution of Liposomes in a Rabbit Tumor Model. Molecular Pharmaceutics,

Volume 6, Number 2, Pages 571-580. March 2009.

It has been reproduced with permission from the American Chemical Society. Copyright

2009 American Chemical Society.

4.2. Introduction

Characterization of the pharmacokinetics and biodistribution of novel imaging and

therapeutic agents is critical for understanding their potential performance and effectiveness

in vivo [186-189]. In recent years, developments in imaging techniques have provided new

tools for non-invasive visualization of the spatial and temporal distribution of these agents

through labeling with fluorescent, radioactive, radioopaque or paramagnetic molecules and

67

assessment using optical, single photon computed tomography (SPECT), positron emission

tomography (PET), CT and magnetic resonance imaging (MRI), respectively [190-195]. The

non-invasive nature of image-based assessments allows for repeated in vivo and in situ data

acquisition from the same subject over multiple time points, thereby reducing the required

number of animals while increasing the accuracy of measurements. Furthermore, if a high

resolution imaging technique is employed, the intra-organ and tissue distribution of the agent

can be resolved. As a result, imaging has become utilized increasingly for biodistribution

investigations; however, appropriate extraction of quantitative data from images still remains

a challenge.

Nano-sized lipid nanoparticles such as liposomes have been widely employed as

delivery vehicles for a range of molecules such as drugs and contrast agents. Their size and

surface properties have proven to be critical for passive accumulation in tumors and sites of

inflammation through the enhanced permeation and retention (EPR) effect [21, 196-198].

Their in vivo distribution has been assessed by numerous research groups in a variety of

healthy and disease-bearing animal models as well as in patients using both traditional tissue

extraction [199, 200] and nuclear imaging techniques [46, 201]. SPECT imaging techniques

rely on radioisotope labeling of liposomes. As a result, the imaging time window is limited

by the physical half-life of gamma photon emitting isotopes such as 99m

Tc (t1/2 = 6 h) or In111

(t1/2 = 67 h), and increased image acquisition time is necessary to compensate for

radioisotope decay. CT contrast agents such as iodine and barium are non-radioactive, have

high atomic numbers and provide high x-ray attenuation. The employment of a CT-based

assessment is therefore suitable for investigations involving long-circulating nanoparticle

systems, as well as for monitoring slow physiological processes such as the passive

68

accumulation of nano-carriers in tumors via the EPR phenomenon. Furthermore, volumetric

CT imaging allows for extremely fast data acquisition in sub-millimeter isotropic voxels.

When combined with 3D image analysis tools, volumetric quantification of signal profiles

within an organ or tissue of interest is possible. This enables the performance of whole body

mass balance calculations and quantification of intra-organ heterogeneity. In addition, CT is

currently the fastest and most widespread whole body volumetric imaging modality, which

makes it very attractive for high throughput biodistribution investigations.

The goal of the current research is to longitudinally quantify the presence of iohexol

and gadoteridol-containing liposomes in the various body compartment volumes, as well as

to visualize the heterogeneity of liposome distribution within a tumor using volumetric high-

resolution CT imaging.

4.3. Experimental Section

Materials

The lipid components of the liposome bilayer 1,2-Dipalmitoyl-sn-Glycero-3-

Phosphocholine (DPPC, M.W. 734) and 1,2-Distearoyl-sn-Glycero-3-Phosphoethanolamine-

N-[Poly(ethylene glycol)2000] (PEG2000DSPE, M.W. 2774) were purchased from Genzyme

Pharmaceuticals (Cambridge, MA, USA); cholesterol (CH, M.W. 387) was purchased from

Northern Lipids Inc. (Vancouver, British Columbia, Canada). The CT contrast agent

Omnipaque

(Nycomed Imaging AS, Oslo, Norway) has an iodine concentration of 300

mg/mL and consists of the non-ionic, iodinated molecule iohexol (N, N'-Bis(2,3-

dihydroxypropyl)-5-[N-(2,3-dihydroxypropyl)-acetamido]-2,4,6-triiodo-isophthalamide,

M.W. 821.14, 3 iodine atoms per molecule) dissolved in an aqueous solution with

69

tromethamine and edentate calcium disodium. The non-ionic, gadolinium complex

gadoteridol (10-(2-hydroxy-propyl)-1,4,7,10-tetraazacyclododecane-1,4,7-triacetic acid,

M.W. 558.7, 1 gadolinium atom per complex, ProHance

by Bracco Diagnostics Inc.,

Princeton, NJ, USA) dissolved in an aqueous solution with calteridol calcium and

tromethamine (gadolinium concentration of 78.6 mg/mL) was also encapsulated in the

liposomes.

Preparation and Characterization of Liposome Formulations

The liposome composition (DPPC, cholesterol and PEG2000DSPE in 55:40:5 percent

mole ratios) and preparation method were described in detail in previous publications [61,

62]. The mean diameter of the final liposome sample was measured by dynamic light

scattering (DLS) analysis of dilute solutions using a DynaPro DLS instrument (Protein

Solutions, Charlottesville, VA, USA) at 25°C. The final concentration of iohexol was

determined using a UV assay with detection at a wavelength of 245 nm (Cary 50 UV/VIS

Spectrophotometer, Varian Inc, CA, USA). The final concentration of gadoteridol was

determined using an assay based on inductively coupled plasma atomic emission

spectrometry (ICP-AES Optima 3000DV, Perkin Elmer, MA, USA).

CT Imaging of Tumor Bearing Rabbits

The following in vivo imaging study was performed under a protocol approved by the

University Health Network Animal Care and Use Committee. Five healthy male New

Zealand White rabbits (2.8-3.2 kg) were inoculated with approximately 400 µL of VX2

carcinoma cells which were obtained from two propagation rabbits. The tumour cells were

70

injected intramuscularly into the animals’ left lateral quadriceps. The contrast-enhanced

imaging studies were performed seven to ten days after the tumour inoculation procedure.

Specifically, each rabbit was intubated and kept under anaesthesia with a mixture of

isoflurane and oxygen via inhalation throughout each imaging session. A slow bolus

injection (0.5 mL/second) of approximately 15 mL of the liposomal contrast agent

formulation was then administered via the marginal ear vein catheter. Each rabbit received

595 mg/kg of iohexol (equivalent to 276 mg/kg of iodine, corresponding to approximately

half of the iodine dose/body weight typically administered to patients in a bolus form) and 40

mg/kg gadoteridol (equivalent to 11 mg/kg of gadolinium) co-encapsulated within liposomes

of 80.2 ± 3.4 nm in diameter and 6.2 ± 4.3 % in polydispersity. CT Images (GE Discovery

ST, General Electric Medical Systems, Milwaukee, WI, USA) of the rabbits were acquired

pre and post-administration of the liposome formulation at 30 minutes as well as 1, 2, 3, 5, 7,

10 and 14 days following administration of the liposome formulation using the following

imaging parameters: 80 kVp, 200 mA, a voxel size of 0.43 x 0.43 x 0.625 mm3, and a FOV

of 220 x 220 x 400 mm3. The nominal x-ray dose for one whole body scan estimated by the

scanner’s CT dose index is 15 mGy. In addition, urine and feces samples were collected on a

daily basis and analysed for iodine content using neutron activation analysis (Becquerel

Laboratories, ON, Canada) for assessment of liposome clearance route(s) and kinetics.

Volumetric Analysis of the CT Data Sets

Semi-automated contouring using MicroView v2.2 allowed for generation of three-

dimensional volumes of interest consisting of the left and right kidneys, spleen, liver, tumor

and the contra lateral muscle. The mean HU value for a given organ or tissue was calculated

71

by averaging the signal of all voxels within the contoured volume. A voxel number versus

CT signal profile was also generated for each volume at each imaging time point. All profiles

were fit to a Gaussian curve with R2 values greater than 0.90. The sigma of the signal profiles

is a compounded result of the heterogeneity of the biological system and uncertainty in the

measurement method. For the bulk volume analysis, an assumption was made that the organs

and tissues of interest were homogeneous. The uncertainty in the measurement method was

obtained by CT imaging a large water phantom and measuring the standard deviation of the

signal within volumes of similar size as the organs and tissues of analysis (ranging from 0.2

to 40.9 cm3). The Welch’s t-test was used to calculate the degree of significance between the

CT signals within the same organ over the different time points. The difference between the

mean Hounsfield unit (HU) measured at time t post-liposome injection and the mean HU

measured pre-liposome administration at time t=0 (Equation 4.1).

0=−=∆ tt meanHUmeanHUmeanHU (Equation 4.1)

4.4. Results

Liposome Accumulation and Clearance Kinetics in Organs and Tissues of Interest

An axial image representing each organ and tissue of interest is shown in Figure 4.1a.

In Figure 4.1b, the organ volumes that were contoured and analyzed are illustrated in yellow

with respect to their locations within the rabbit body. The liposome accumulation and

clearance kinetics profiles in each organ (left and right kidneys, liver, spleen and tumor) of

each of the five animals are shown in Figure 4.1c as ∆meanHU (Equation 4.1).

In all volumes of interest and in all five animals, a sharp increase in the mean HU

value was seen immediately following the administration of the liposome agent (30 minutes

72

post-injection) as a result of the systemic distribution of liposomes in the blood stream.

While the mean signal intensities measured in the healthy organs (kidneys, liver and spleen)

decreased over time, significant contrast enhancement of the tumor volume is not observed

until 24 hours post-injection, and it is sustained up to 10 days following a single

administration of the liposomes (Figure 4.2a). As a control, analysis was also performed on

the muscle volume located on the contra-lateral thigh. The highest tumor-to-muscle iodine

concentration ratio of 11.9 ± 6.0 was detected at 7 days post-injection (Figure 4.2b).

However, the highest liposome accumulation (915 µg/cm3 of iodine) at the tumor site

occurred at 48 h following administration. The linear relationship between differential CT

attenuation values and iodine concentration was determined in a separate phantom study. It

was measured that every 1 mg/mL of iodine and 0.05 mg/mL of gadolinium encapsulated in

liposomes provided a differential signal increase of 38.04 ± 0.64 HU in CT when operated at

80 kVp and 200 mA. The coefficient of determination R2 for the linear regression was 0.996.

73

Figure 4.1 Visual illustration of (a) axial CT slices of the rabbit kidneys, liver, spleen and

tumor acquired at 48 h post-injection. These images are acquired at sub-millimeter resolution

and they demonstrate potential for quantification of intra-organ heterogeneity. In this

particular study, bulk organ analysis was performed on (b) the contoured organ/tissue

volumes (in yellow). (c) The differential mean HU measured in each volume of interest (with

respect to the pre-injection data set) at selected time points. Each profile represents the values

obtained for a given rabbit over 14 days.

74

(a)

0 50 100 150 200 250 300 350

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Iodin

e c

once

ntr

atio

n (

µg

/cm

3 tis

su

e)

Time (h)

Blood

Left Kidney

Right Kidney

Spleen

Liver

Tumor

Muscle

75

(b)

0 50 100 150 200 250 300 350

0

2

4

6

8

10

12

14

16

18

20

Tu

mor

to M

uscle

Io

din

e C

on

cen

tra

tion

Ra

tio

Time (h)

Figure 4.2 (a) Liposome biodistribution profiles in the various organs and tissues of interest

as measured using CT-based detection of the co-encapsulated iohexol and gadoteridol. The

encapsulated iodine to gadolinium weight ratio is 20 to 1. At day 14, the blood, spleen, tumor

and muscle showed statistically significant accumulation of liposomes (p < 0.001), while the

mean signal measured in the kidneys and the liver were not statistically significant compared

to the mean signal of the same organs pre-liposome administration. (b) Time-dependent

tumor-to-muscle ratio of iodine concentration. The highest ratio occurs at 7 days post-

liposome injection, which coincides with the highest liposome accumulation detected in the

tumor. Each data point represents the mean ± standard deviation for five animals.

76

Time-Dependent Biodistribution as a Function of Injected Dose

Conventional biodistribution studies and nuclear medicine imaging techniques report

the amount of drug or agent extracted or the total radioactivity measured from a given organ

or tissue, respectively, as a percentage of the injected dose (%ID) and as percentage of the

injected dose per weight (%ID/g or %ID/kg) of the organ or tissue of interest. This data is

measured from the CT data set using an anatomically accurate volumetric organ-based

analysis technique. Table 4.1 displays the percentage of injected iodine per organ and the

percentage of injected iodine per volume (cm3) of tissue for blood, kidneys, liver, spleen and

tumor. Our findings are in agreement with a study performed by Harrington et al. [46] in

cancer patients who had been administered 111

In-DTPA labeled Doxil®

liposomes and

imaged with SPECT. It is important to note that there are physiological differences between

rabbits and human. The lipid composition of the liposomes employed for this study (DPPC :

cholesterol : PEG2000DSPE at 55:40:5 mol%) is fairly similar to the Doxil®

liposome

formulation (HSPC : cholesterol : PEG2000DSPE at 56:39:5 mol%). Previously, our group has

shown that the biodistribution profile of this liposome formulation in healthy mice matched

the profiles reported by other groups who used either Doxil®

liposomes or other liposome

formulations that closely matched the composition of Doxil®

[62, 202]. Table 4.1 shows that

the %ID of iodine measured in the rabbits’ vascular compartment using CT is 89.8 ± 19.5%

at 30 minutes post-injection and decreases to 51.4 ± 4.2% at 48 hours and then to 10.9 ±

3.3% at day 10. In comparison, Harrington et al. reported that 95.0 ± 11.8% of the %ID of

111In (i.e.

111In-Doxil

) remained in patients’ blood 30 minutes post-liposome administration,

55.5 ± 9.3% at 48 hours and 4.9 ± 5.1% at day 10. The blood pharmacokinetics profile from

each rabbit was fitted to a one-compartment model and the mean vascular half-life t1/2 was

77

calculated to be 63.6 ± 5.8 h. The R2 values indicative of the goodness of fit ranged between

0.90 and 0.97 across the study population.

In addition, the liposome accumulation in each rabbit kidney was measured to be

between 1.9 ± 0.5% (0.5 h) and 0.1 ± 0.1% (240 h), in agreement with the values reported by

Harrington et al. of 1.6 ± 0.8% (0.5 h) and 0.7 ± 0.4% (240 h) in patients. As well, the tumor

accumulation in rabbits was measured to be 0.9 ± 0.3% in this study at 72 hours post-

injection, which falls within the range of 0.3 - 2.6 %ID reported for patients having different

types of tumor burden and treated with Doxil®

liposomes. However, the %ID of liposomes

measured in the rabbit liver and spleen, was about four times lower than the values reported

by Harrington et al. in patients. In fact, a greater degree of cumulative excretion via the

urinary route was observed in the current study (27.0 ± 15.7 %ID) compared to the 18.3 ± 6.9

%ID reported by Harrington et al. over the first 4 days post-injection. Stool samples collected

from all five animals over the entire study period revealed a cumulative 7.3 ± 9.8 %ID of

iodine excreted at day 4 and a cumulative 12.6 ± 15.1 %ID excreted at day 14. Overall, with

the combination of the CT volume analysis method for blood, kidneys, liver, spleen and

tumor, and iodine detection in urine and feces, it was possible to account for 100.8 ± 22.0%

of the total injected dose of iodine at 30 minutes post liposome administration, 80.8 ± 12.2%

of the total injected dose at 72 h post-injection, and 58.5 ± 9.4% of the total injected dose at

14 days post-administration. The remaining amount of iodine may be non-specifically

distributed in other body compartments that were not included in this analysis such as the

skin, muscle, fat or the interstitial fluid space.

78

Blood Kidneys Liver Spleen Tumor Urine Feces

Time (h) % ID

0.5 89.8 ± 19.5% 3.9 ± 0.6% 5.9 ± 2.7% 0.8 ± 0.5% 0.4 ± 0.1% -* -*

24 59.3 ± 4.7% 1.7 ± 0.4% 3.9 ± 0.9% 1.0 ± 0.4% 0.7 ± 0.1% 18.8 ± 14.3% 1.3 ± 1.7%

48 51.4 ± 4.2% 1.3 ± 0.4% 4.4 ± 1.0% 1.0 ± 0.4% 0.9 ± 0.3% 22.9 ± 16.2% 4.2 ± 6.0%

72 44.2 ± 5.9% 1.0 ± 0.4% 4.3 ± 2.8% 0.7 ± 0.3% 0.9 ± 0.3% 24.2 ± 16.9% 5.5 ± 7.5%

120 33.1 ± 4.8% 0.8 ± 0.3% 3.0 ± 2.2% 0.5 ± 0.2% 1.1 ± 0.3% 29.4 ± 14.8% 8.5 ± 10.7%

168 21.1 ± 4.5% 0.5 ± 0.3% 2.2 ± 1.5% 0.3 ± 0.2% 1.1 ± 0.3%

35.3 ± 14.9% 10.3 ± 12.7%

240 10.9 ± 3.3% 0.3 ± 0.2% 1.2 ± 0.8% 0.2 ± 0.1% 1.0 ± 0.3% 39.5 ± 13.9% 11.8 ± 14.3%

336 2.1 ± 1.4% -** -** 0.1 ± 0.0% 0.6 ± 0.3% 43.1 ± 12.3% 12.6 ± 15.1%

Time (h) % ID / cm3

0.5 0.42 ± 0.04% 0.20 ± 0.08% 0.14 ± 0.05% 0.24 ± 0.10% 0.05 ± 0.05%

24 0.29 ± 0.06% 0.09 ± 0.02% 0.10 ± 0.03% 0.25 ± 0.08% 0.09 ± 0.02%

48 0.25 ± 0.06% 0.07 ± 0.02% 0.11 ± 0.03% 0.26 ± 0.07% 0.11 ± 0.01%

72 0.22 ± 0.06% 0.06 ± 0.02% 0.10 ± 0.04% 0.21 ± 0.06% 0.11 ± 0.01%

120 0.16 ± 0.05% 0.05 ± 0.02% 0.07 ± 0.03% 0.16 ± 0.04% 0.11 ± 0.01%

168 0.11 ± 0.04% 0.03 ± 0.02% 0.05 ± 0.02% 0.10 ± 0.03% 0.10 ± 0.01%

240 0.06 ± 0.03% 0.02 ± 0.02% 0.04 ± 0.01% 0.08 ± 0.02% 0.08 ± 0.02%

336 0.01 ± 0.01% -** -** 0.03 ± 0.01% 0.04 ± 0.02%

Table 4.1 Liposome biodistribution expressed as %ID and as %ID/cm3 of organ/tissue. The

volume of the organs and tissues of interest were measured using the CT data set with the exception

of the blood compartment. The blood volume for each animal was calculated as the injected dose

divided by the y-intercept of the mono-exponential fit from the blood iodine concentration vs. time

profile. The estimation rather than measurement of blood volume increases the uncertainty

associated with the %ID and as %ID/cm3 values for blood pool. The high variance in the blood

iodine content at 30 minutes post-injection is likely due to inaccuracies associated with the timing

of the imaging session. The values for urine and feces are cumulative. Each table entry represents

the mean ± standard deviation for five animals.

* No urine or stool output.

** Iodine concentration in this organ for this time point was below the detection limit.

79

Sensitivity of CT in Detecting the Tissue Concentrations of Iodine-Labeled Liposomes

CT imaging was performed on all animals pre and post contrast administration at

selected time points. As stated in the methods, volumes of interest were generated from semi-

automatic contours. The voxel number versus CT signal profiles generated were then

Gaussian fitted with R2

greater than 0.95 for kidneys, liver, spleen and tumor and with R2

greater than 0.90 for blood. The Welch’s t-test was used between each pair of pre and post-

injection volume sets to determine whether their signal profiles were statistically different (p

< 0.001). The critical t value of 3.291 was then used to calculate the minimum differential

HU needed for a given pre and post-injection data set pair to be determined to be statistically

different. These values were then converted into µg/cm3 of iodine concentration representing

the minimum amount of iodine that CT is able to detect in the different organs (Table 4.2). It

is worth noting that all voxels within the liver, kidneys, spleen and tumor were used in the

analysis in order to maximize statistical power. However, it was not possible to contour all

voxels occupied by blood. As a result, the sensitivity in detecting iodine concentrations in

blood can be improved by increasing the volume of analysis. In this case, due to the high

iodine content circulating in the bloodstream, even at day 14, the blood iodine concentration

(76.6 ± 39.5 µg/cm3) was above the limit of detection of the current method (11.4 µg/cm

3).

Classification of Heterogeneity in the Intratumoral Distribution of Liposomes

Once it had been established that the iodine detection sensitivity in the tumor is 1.8

µg/cm3 (equivalent to a differential mean HU increase of 0.11 ∆HU) for this particular study,

it was possible to calculate and visualize the percentage of tumor volume that was occupied

by iodinated liposomes. Figure 4.3 provides visual illustration of the accumulation and

80

clearance of the iodinated liposomes from the tumors of the five rabbits over the 14-day

period. It may be noted that although the percentage of tumor volume occupancy by the

liposomes is fairly consistent across the five data sets, the spatial distribution patterns differ

significantly from animal to animal. The graph in Figure 4.4a shows the time dependent

volume of distribution of liposomes in tumor as the fraction of the total tumor volume

occupied. The percent occupancy peaked at 72 ± 5% 48 h post-injection.

Mean Sampling Volume

(cm3)

Minimum Mean ∆HU for

Significance (p < 0.001)

Iodine Detection

Sensitivity (µg/cm3)

Blood 0.2 0.68 11.4

Kidney 9.0 0.10 1.6

Liver 40.9 0.05 0.8

Spleen 3.1 0.17 2.9

Tumor 11.4 0.11 1.8

Table 4.2 List of the mean organ and tissue sampling volume used for this study during the

analysis of the CT data sets. For a given body compartment of a set mean volume, the

minimum mean differential HU (∆HU) needed to detect statistically significant amounts of

iodine was calculated using the Welch’s t-test.

81

Figure 4.3 (a)* Anterior views of 3D CT maximum intensity projections (MIP) of a

representative VX2 carcinoma bearing male New Zealand White rabbit (3 kg) at 30 minutes,

82

24 and 48 hours post liposome administration. The arrows indicate the site of the tumor and

the EPR effect is visualized through the gradual opacification of the tumor area resulting

from the accumulation of the iohexol and gadoteridol containing liposomes. (b) The five

quadrants represent data acquired from five distinct animals, with each quadrant displaying

3D maximum intensity projections of the segmented tumor volumes pre and up to 14-days

post liposome injection. Note that although the percent volume of distribution (Vd) of

liposomes in the tumor at the different time points is relatively similar, the intratumoral

spatial distribution pattern greatly differs from animal to animal. In addition, the tumor

growth process can also be monitored, visualized and effectively measured using CT (see

Figure 4.4b).

* Adapted from Zheng et al. [203] to illustrate the anatomical location of the segmented

tumor volumes

83

(a)

0 50 100 150 200 250 300 350

0.0

0.1

0.2

0.3

0.4

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Rabbit 1

Rabbit 2

Rabbit 3

Rabbit 4

Rabbit 5

Tu

mo

r V

olu

me

(m

m3

)

Time (h)

Figure 4.4 (a) Representation of the tumor volume fraction occupied by liposomes over 14

days. Voxels with values greater than or equal to the µ + 2σ of the pre-injection tumor CT

signal were considered contrast enhanced. Each data point represents the mean ± standard

deviation for five animals. (b) Changes in tumor volume measured using CT in the five

rabbits over 14 days.

84

4.5. Discussion

Recent developments in image-guided drug delivery are prompted by the belief that

an increased understanding of the biodistribution of drug carriers in individual patients will

lead to improvements in personalized treatment design and delivery. Advances in nano-sized

drug carriers have enabled improved delivery of anticancer drugs to the tumor site, by

exploitation of the EPR phenomenon, while minimizing their non-specific distribution to

healthy organs and tissues. EPR describes the mechanism by which macromolecules or

nanoparticles are retained within healthy vasculature due to their colloidal size, but are able

to accumulate in tumors due to the leakiness of the abnormal vasculature and lack of

effective lymphatic drainage at these sites, in comparison to normal tissue [21, 196-198]. The

addition of an imageable component to a drug carrier, in combination with the employment

of volumetric imaging techniques, enables non-invasive visualization and quantification of

the effectiveness of tumor targeting and sparing of healthy tissue. The successful translation

of image-guided drug delivery to the clinical setting would permit timely adjustments of

treatment regimens on a per patient basis and ultimately enable implementation of

personalized medicines.

In the current study, iohexol and gadoteridol were co-encapsulated within liposomes

to enable CT and MR imaging of the nanoparticle biodistribution following administration.

The physico-chemical characteristics and stability of this formulation have been described in

detail elsewhere [61]. We also previously reported the pharmacokinetics profiles of iohexol

and gadoteridol as free agents and liposome-encapsulated agents [62] to demonstrate the

prolonged imaging window of the contrast agent encapsulated liposomes. Similar to other

small molecules, un-encapsulated iohexol and gadoteridol exhibit rapid distribution and

85

clearance upon administration. Liposome encapsulation of the small molecular weight agents

changed their profiles from biphasic to monophasic. In healthy Balb-C mice, the calculated

tα1/2 was 12.3 ± 0.5 minutes for iohexol and 7.6 ± 0.9 minutes for gadoteridol, the elimination

(β phase) half-lives were 3.0 ± 0.9 hours for iohexol and 3.0 ± 1.3 hours for gadoteridol;

whereas the vascular half-lives were 18.4 ± 2.4 and 18.1 ± 5.1 hours for iohexol and

gadoteridol, respectively, when co-encapsulated in liposomes [62]. As a result, it is

reasonable to attribute the longitudinal signal increases observed in the blood and tissue

compartments to the presence of the encapsulated agents.

Once it is established that the images are indeed reporting the biodistribution of the

nanoparticulate carriers, there remains a significant challenge in using imaging techniques to

assess the in vivo performance of drug delivery systems. This challenge lies in the accurate

extraction of quantitative data from the images. Firstly, it must be ensured that the given

signal change measured in a given voxel corresponds to a consistent change in the

concentration of the nanocarrier in the same volume. When using imaging modalities such as

MR and CT, in which signal changes can occur as a result of endogenous changes in tissue

properties, the benefit of having anatomical information comes with the challenge of

extracting signal changes that are solely generated by the presence of contrast agents. For

example, when conducting longitudinal studies lasting days to weeks in a tumor-bearing

animal, the tumor morphology and physiology can change. The signal generation process of

an anatomic MR data set relies on the tissue T1 and T2 relaxation parameters, which are

known to be very sensitive to changes in tumor tissue properties such as local water

concentration [204]. The sensitivity to these parameters, which have made MR so powerful

for soft tissue and tumor characterization, increases the challenge of quantifying relaxivity

86

changes that are exclusively caused by shifts in the contrast agent concentration. The

underlying signal generation process in CT is dependent on the x-ray attenuation profile of a

tissue, which during disease progression undergoes a more gradual modification process than

its relaxation properties. As a result, although the liposomes employed for this investigation

co-encapsulate iohexol and gadoteridol and can be imaged using both CT and MR, CT was

relied on exclusively for quantification.

The second requirement for quantification of imaging data, in the case of a

longitudinal study, is high confidence in defining corresponding volumes of interest for

analysis across image sets acquired at different times. Although a voxel-based time-course

analysis was not pursued here, both rigid and deformable image registration techniques have

shown success, within a reasonable error range, in the identification of voxels across

longitudinal data sets in organs and tissues that do not undergo significant anatomic changes

over the course of the imaging study [205, 206]. However, these algorithms cannot be

applied to tissues that significantly change either due to disease progression or treatment. For

example, during this particular study (2 weeks), the rabbit tumor volumes tripled in size

(Figure 4.4b). Due to the low confidence in accurately identifying the same set of

intratumoral voxels over time, a decision was made to measure the mean signal changes over

all voxels that make up the bulk tumor volume and classify groups of intratumoral voxels

according to their HU values rather than their spatial distribution (Figure 4.4a).

Lastly, accurate quantification of the in vivo nanocarrier biodistribution is best

achieved with a 3D analysis method. In situations when the nanocarrier is uniformly

distributed, 2D region of interest (ROI) analysis may be preferred due to its simplicity and

speed, and the mean signal value obtained is representative of the entire volume of interest.

87

However, the nanocarrier distribution patterns are often heterogeneous or unknown, the

employment of 2D ROIs for image analysis is vulnerable to variations in 2D ROI placement.

In this study, 3D ROI-based analysis was used on all organs and tissues of interest, whether

or not they were known to be homogeneous or heterogeneous, in order to provide unbiased

and observer-independent measurements that reflected the signal intensities of all voxels

within the volumes of interest over all time points. The variance in the signal distributions

provides insight on the heterogeneity of the organ/tissue under investigation. These

heterogeneities include variance in anatomy, physiology and differential uptake and

clearance of the contrast agent. The use of CT is attractive in monitoring these

heterogeneities longitudinally due to its geometric accuracy. An additional advantage in

using this 3D whole organ/tissue volume-based analysis is that it increased the number of

voxels that were sampled for each measurement. As a result, a higher statistical confidence

was achieved when comparing the differences among the signal profiles measured in the

same organ or tissue over time, allowing us to confidently report much lower iodine

concentrations (i.e. 0.8 µg/cm3 for the liver, Table 4.2) compared to those published by other

research groups that have employed 2D ROI analysis techniques [106, 151, 207]. This also

demonstrates that there is an opportunity to decrease imaging dose while still satisfying the

necessary level of iodine detection.

In conclusion, the feasibility and effectiveness of quantitative CT-based

measurements of the pharmacokinetics and biodistribution of a nanocarrier in vivo have been

demonstrated. Longitudinal imaging was performed up to 14 days post-liposome

administration. The vascular half-life of 63.6 ± 5.8 h for the liposomes enabled high

accumulation at the tumor sites (915 µg of iodine /cm3 of tumor tissue at 48 h post-injection)

88

through exploitation of the EPR effect. Furthermore, although the intratumoral distribution of

liposomes was highly heterogeneous and variable from animal to animal, the vehicle

occupied the majority (72 ± 5%) of the total tumor volume at 48 h post-injection in the five

rabbits. These observations support ongoing efforts in our research laboratory to develop

robust metrics for spatial classification of the heterogeneous intratumoral distribution

patterns of nanocarriers. These, in conjunction with molecular imaging tracers that report the

different properties of the tumor micro-environment (i.e. FAZA-PET, FMISO-PET), will

become a powerful tool set to elucidate the ability of drug carriers to deliver therapeutic

agents to various intratumoral regions that have distinct sensitivities to treatment. In addition,

increased employment of non-invasive, quantitative image-guided pharmacokinetics and

biodistribution assessments in the development and pre-clinical testing of novel nanocarriers

has the potential to greatly facilitate their clinical translation. Conversely, the adoption of

imageable nanotherapeutics in the clinical setting, along with quantitative imaging systems

and analysis tools, will positively impact therapy outcome through personalization of

treatment delivery.

4.6. Acknowledgements

This work is funded in-part by CIHR and OICR research grants, the Fidani Chair in

Radiation Physics and the Grange Advanced Simulation Initiative. Jinzi Zheng is grateful for

the CIHR Canada Graduate Scholarship. The authors would like to thank Dr. Ivan Yeung for

providing the VX2 tumor model, Dr. Sandy Pang for helpful comments and discussions with

regards to pharmacokinetics modeling and the University Health Network animal care staff

for their technical services.

89

Chapter 5. iposome Contrast Agent for CT-based Detection and

Localization of Neoplastic and Inflammatory Lesions in Rabbits:

Validation with FDG-PET and Histology

90

5.1. Foreword

The localization, biodistribution and kinetics of liposomes to healthy and tumor

tissues were quantified using CT in a rabbit model in the previous chapter. Over the course of

the study reported in the previous chapter, it was observed that additional lesions (away from

the primary tumor site) were enhancing on CT following liposome agent administration. The

goal of this chapter is to characterize the CT contrast enhancing lesions (primary or

otherwise) with FDG-PET and histology, and assess the performance of liposome-CT to

detect these abnormalities with respect to established methods (FDG-PET and histology).

The following chapter is currently being considered for publication by Radiology:

Zheng J, Allen C, Serra S, Vines D, Charron M, Jaffray DA. Liposome Contrast

Agent for CT-based Detection and Localization of Neoplastic and Inflammatory

Lesions in Rabbits: Validation with FDG-PET and Histology.

Submitted to Radiology on September 1, 2009 (submission number RAD-09-1635, under

review).

5.2. Introduction

Non-invasive imaging techniques play an integral role in whole body screening of

neoplastic and inflammatory lesions. Earlier detection, diagnosis and accurate staging will

increase the efficacy of disease management [208]. Approaches to implement this include the

development of high sensitivity and high resolution imaging devices (i.e. PET, MR and CT),

and the engineering of novel agents that enhance the contrast of disease lesions through

physiological or biological targeting.

91

Sites of tumor and inflammation are both characterized by enhanced vascular

permeability [209]. The unique size and particle surface characteristics of colloidal agents,

such as PEGylated liposomes, allow them to be retained in healthy blood vessels, circulate

for a prolonged period of time in vivo through avoidance of uptake by the monophagocytic

system (MPS), also known as the reticulo-endothelial system (RES), and preferentially

extravasate at sites of enhanced vascular permeability. Specifically, it has been reported that

liposomes in the 70 to 200 nm size range are optimal for minimizing liver and spleen

accumulation, the two main organs that make up the MPS [9]. As a result, liposomes have

been explored for both imaging and therapeutic delivery to both sites of tumor and

inflammation [210, 211].

Innovations in nanoparticle-based contrast agent development will also have

important implications for research and development of novel chemotherapeutic and anti-

inflammatory drug delivery carriers. For example, nano-sized liposomes have been widely

employed as a colloidal carrier for a variety of anti-tumor drugs: liposomal doxorubicin,

Doxil®

(Johnson & Johnson, Langhorne, PA, USA), being the most clinically successful

nanosystem [212]. The ability to non-invasively quantify the concentration of liposomes at

tumor sites and to non-invasively map their intratumoral distribution with respect to

functional and physiological parameters of the tumor microenvironment have the potential to

bring greater insight to the rational development of colloidal therapeutic agents.

The recent development of a combined liposome-based CT and MR agent and the

characterization of its stability [61], pharmacokinetics and biodistribution [62], as well as

imaging performance in both healthy [62] and tumor-bearing animals [63] have been

reported. In addition, the tumor accumulation and clearance kinetics of this liposome agent

92

were quantified, which allowed for definition of the optimal tumor imaging window

following an intravenous administration [63]. This study assesses the ability of the same

liposome agent, together with CT imaging, to localize both tumor and inflammatory sites in a

rabbit model with VX2-carcinoma and immune myositis. Finally, the sensitivity of the

liposome-CT detection of abnormal lesions is compared to that of FDG-PET. As well,

comprehensive histopathological information is reported for tissue samples.

5.3. Materials and Methods

Animal Model of Tumor and Inflammatory Lesions. All experiments were

performed under an approved animal care and use protocol (University Health Network).

Nine healthy male New Zealand White rabbits (Charles River, Wilmington, MA, USA)

weighing 2.7 ± 0.3 kg were inoculated with 400 µL of a cell suspension (approximately 107

cells per ml) which was obtained from three VX2-carcinoma-bearing propagation rabbits

[213-216]. Specifically, the donor rabbits were sacrificed with a lethal dose (160 mg/kg) of

intravenously administered sodium pentobarbital solution (Euthanyl; Bimeda®-MTC Animal

Health Inc., Cambridge, Ontario, Canada). Their tumors were excised and placed in Hanks

Balanced Salt Solution (HBSS, Sigma-Aldrich, Oakville, Ontario, Canada). In a sterile

laminar down-flow air system, the tumor was then washed twice with sterile HBSS and the

viable portion of the tumor was cut into small fragments (2 x 3 mm). The final cell

suspension was obtained by pushing the tumor fragments through a 70 µm cell strainer in the

presence of HBSS. The cell suspension was then loaded into syringes and injected

intramuscularly into the animals’ left lateral quadriceps. No attempt was made to isolate the

VX2 carcinoma cells from the stromal cells that were part of the donor tumors. This injection

93

resulted in the formation of primary tumors in all nine rabbits. In addition, inflammatory

lesions were identified in the skeletal muscles of six of the nine recipient animals and these

were classified as non-infectious immune myositis by two human pathologists (S. S. and S.

A., Toronto General Hospital, Toronto, Ontario, Canada) with extensive animal histology

experience. The mechanism for this focal inflammatory lesion formation is unknown.

However, they exclusively occur in tumor-bearing rabbits and their origin may be associated

with the exposure to the stromal component of donor tumor.

Discussion with a team of veterinary pathologists (P. T. and team, Ontario Veterinary

College, University of Guelph, Guelph, Ontario, Canada) confirmed the nature of the

inflammatory lesions (i.e. nonsuppurative myositis and necrosis) and a hypothesis pertaining

to their pathogenesis was formulated. Specifically, the spontaneous formation of the myositis

lesions may be explained via simple host rejection of the tumor with activation of various

clonal populations of T lymphocytes as well as dendritic cells and macrophages. The donor

tumor cocktail administered to the recipient animals contained immune cells expressing

different major histocompatibility complex (MHC) antigens from the donor rabbit. This led

to the activation of host (recipient) T cells and dendritic cells, as well as initiation of the

nonsuppurative inflammation and eventual necrosis seen around the primary tumors 13 days

post-inoculation. In addition, this intense inflammation also caused fragmentation of

myofibers and led the activated clonal populations of host T cells as well as macrophages to

be directed against epitopes on muscle proteins. Finally, some of these inflammatory cells

may “escape” the original site of inflammation in some animals, and set up similar muscle-

directed inflammation elsewhere in the body, similar to an autoimmune reaction. Regardless

94

of the process, these inflammatory lesions were employed as a model of inflammation in

assessing the performance of the liposome agent.

Liposome-CT and FDG-PET Imaging. As in a previously published method [61],

80 nm liposome CT contrast agent co-encapsulating iohexol (Omnipaque®

, GE Healthcare,

USA) and gadoteridol (Prohance®

, Bracco Diagnostic Inc., Princeton, NJ, USA) was

prepared and characterized. This liposome agent stably retains the co-encapsulated agents

and exhibits a long vascular half-life on the order of 60 hours in VX2-carcinoma bearing

rabbits [63]. For this study, the liposome agent was administered intravenously to the rabbits

once tumor lesions were established (seven days post inoculation). The rabbits were first

induced using a nose cone with a mixture of isoflurane and oxygen via inhalation, and then

intubated and maintained under the same inhalant anaesthesia. A slow bolus injection (0.5

mL/second) of 15 mL of the liposomal contrast agent formulation was administered through

the marginal ear vein catheter. Each rabbit received 400 ± 80 mg/kg of iohexol (equivalent to

185 ± 37 mg/kg of iodine, corresponding to approximately one third of the iodine dose/body

weight typically administered to patients in a bolus form) and 25 ± 4 mg/kg gadoteridol

(equivalent to 7 ± 1 mg/kg of gadolinium) co-encapsulated within the liposomes. The

PET/CT imaging session (GE Discovery ST PET/CT, General Electric Medical Systems,

Milwaukee, WI, USA) took place twelve days after the tumor inoculation procedure, five

days post liposome contrast administration and one hour post 18

F-FDG injection (30.3 ± 5.1

MBq/kg via the marginal ear vein). The five-day delay was selected based on a previous

kinetic study [63] which determined the maximum tumor-to-muscle CT signal ratio was

achieved between days five and seven post liposome administration. Per conventional FDG-

PET imaging protocol, the rabbits were fasted for 18 hours prior to the imaging session, and

95

the blood glucose level for each rabbit was measured immediately before FDG

administration using a glucometer (Ascensia®

Contour®

, Bayer HealthCare LLC,

Mishawaka, IN, USA). The mean blood glucose level for the nine rabbits was within the

normal range (4.0 ± 1.4 mmol/L). During the one-hour waiting time between the FDG

injection and the PET/CT imaging, the rabbits were kept under anaesthesia with the

isoflurane and oxygen mixture delivered via inhalation. Two sets of CT images (high and

low resolution) were acquired at 80 kVp and 200 mA. One lower resolution CT data set (0.98

x 0.98 x 3.3 mm3 voxel size) was acquired immediately before the PET scan (2D acquisition

mode, four bed positions, four minutes of imaging time per bed position and three slice

overlap) and was used for attenuation correction of the PET data set (reconstructed at 0.98 x

0.98 x 3.3 mm3 voxels size). In the CT data set used for PET attenuation correction, the

tumor/inflammation voxel with the highest iodine contrast accumulation measured 298 HU.

According to a published phantom study [217], this level of CT attenuation value would only

induce a 7% bias relative to 0 HU in the PET emission data when compared to the 68

Ge-

derived correction. Therefore no adjustment was performed to compensate for the presence

of iodine in the PET attenuation correction. The higher resolution CT data set (voxel size of

0.39 x 0.39 x 0.63 mm3) used for image analysis was acquired immediately following the

PET acquisition. Figure 5.1 illustrates the experimental timeline in a flow diagram.

Abnormal Lesion Collection and Histopathological Examination. Approximately

18-20 hours post PET/CT imaging, the rabbits were sacrificed with a lethal dose (160 mg/kg)

of intravenously administered sodium pentobarbital solution. Based on the CT data sets,

needles were inserted into the carcasses to mark the rough anatomical location of the

abnormal lesions. The carcasses with needles were then CT scanned and the locations of the

96

lesions with respect to the needle fiducials were measured. Once identified, the lesions were

dissected by a certified veterinarian (University Health Network Animal Research Centre)

and immediately fixed in approximately 20 times volume excess of 10% formalin. Serial

sectioning and staining with hematoxylin-eosin (H&E) and pan-cytokeratin (pan-CK, marker

for VX2 carcinoma cells in muscle, as they are of epithelial origin) were performed by the

Pathology Research Program at the Toronto General Hospital (Toronto, Ontario, Canada).

The tissue slides were scanned at 20X magnification (0.5 µm/pixel) with ScanScope XT

(Aperio Technologies Inc., Vista, CA, USA). The histopathological examination was

performed by a pathologist (S. S.) and confirmed by a second pathologist (S. A.).

Image Analysis. Lesions were contoured in 3D on the full resolution CT data set

using a threshold-based contouring method (Microview v2.2, GE Healthcare). The signal

threshold was 3σ greater than the mean HU of a muscle volume in the contra-lateral side.

The resulting contours were visually inspected and manually adjusted to exclude bone and

assure tumor inclusion. The registration of the lower resolution CT and PET data set was

performed using the MIPAV software (CIT, NIH, Bethesda, USA). PET-based assessment of

the disease burden was performed by an experienced nuclear medicine physician (M. C.)

using the Xeleris visualization station (GE Medical Systems, Milwaukee, WI, USA). The

suspect lesions were first identified on the maximum intensity projection of the PET data,

and then the triangulation tool was used to verify the lesion on the coronal PET image. To

minimize potential bias caused by the presence of the CT agent, the low resolution CT data

set was provided and the window and level on the CT data set was preset such that any

liposome contrast uptake was imperceptible. Due to the small size of some lesions, partial

volume correction was applied to the PET data set [218]. Specifically, the partial volume

97

effect correction was calculated from a separate phantom study (results not shown) where 12

spheres of volumes ranging between 0.18 cm3 and 26.52 cm

3 were filled with the same

concentration of radioactivity relative to a uniform background (sphere to background ratio

of 4:1) and imaged on the same scanner using the same 2D acquisition protocol.

Figure 5.1 Flow chart illustration of the experimental steps.

VX2 carcinoma inoculation at the left lateral quadriceps (n=9)

Liposome contrast administration

(185 ± 37 mg/kg of iodine)

FDG injection (30.3 ± 5.1 MBq/kg)

7 days

5 days

1 hour

PET/CT imaging

18-20 hours

Tissue collection

98

5.4. Results

Tumor Detection. As summarized in Table 5.1, both liposome-CT and FDG-PET

independently detected the presence of neoplastic lesions, which were histologically

confirmed to be malignant, in the lateral upper left thighs of all nine rabbits (sites of tumor

inoculation). These primary tumors consisted of medium sized cells with scant cytoplasm

and round to oval nuclei arranged in glandular structure and/or in solid sheets. Focal

inflammation mainly characterized by lymphocytes in variable proportion was present mostly

at the periphery of the lesion. Necrosis was present in all lesions. The VX2 neoplastic cell

population within all of the primary tumor lesions were immuno-reactive for pan-cytokeratin.

Figure 5.2 illustrates three primary tumors of different sizes. Due to the highly heterogeneous

nature of this tumor model, the difference in volume (measured from the CT data set) of the

primary lesions ranged from as small as 0.07 cm3 to as large as 7.01 cm

3 (i.e. 100-fold

difference).

Inflammatory Lesion Detection. In addition to the primary tumors, 25 abnormal

lesions were detected in six of the nine rabbits (from the three different tumor inoculations)

from the PET/CT imaging study. Thirteen out of the 25 lesions were collected from the

animals under CT-guidance and sent for histopathological examination. The remaining

lesions were not collected because of their inaccessibility due to their anatomical location. As

outlined in Table 5.1, all 7 FDG-PET positive muscle lesions were also seen as abnormal on

the CT data set. Six out of these seven lesions were dissected and classified as inflammatory

by the pathologists. Figure 5.3 illustrates examples of one inflammatory lesion in the lower

lumbar muscle region and another one in the arm. Of the remaining 18 liposome-CT

enhanced muscle lesions, 7 were resected and classified as inflammatory by the pathologists.

99

Volume Range

(mm3)

Mean Volume

(mm3)

Lesions Detected by

FDG-PET

(SUVmax Range)

Lesions Detected by

Liposome-CT

(HUmax Range)

Primary tumors (histology confirmed) 70.1 – 7007.7 3513.7 ± 2763.5 9 (1.5-10.9) 9 (173-596)

Inflammatory lesions (with histology) 13.5 – 2732.1 737.3 ± 814.9 6 (2.7-7.1) 13 (254-493)

Inflammatory lesions (no histology) 28.8 – 503.5 107.6 ± 134.5 1 (3.5) 12 (208-498)

Table 5.1 List and classification of the neoplastic and inflammatory lesions detected using CT and PET imaging, their volumes and

maximum signal values. Note that all volumes and HUmax values reported here were measured using the full resolution liposome-CT

data set (voxel size of 0.39 x 0.39 x 0.63 mm3).

100

In general, the inflammatory masses were embedded deep within the muscles of the

upper thigh (always superior to the primary tumor and sometimes on the contralateral side),

the lower lumbar muscles and the arm muscle. Microscopically, these intramuscular lesions

showed irregular margins and consisted of multifocal conspicuous inflammation, infiltrating

within the endomysium. The inflammatory infiltrate included numerous histocytes, giant

cells, scattered lymphocytes and rare plasma cells. Degenerating muscle fibers and focal

calcifications were also present. All of the inflammatory lesions were negative for pan-

cytokeratin, in contrast to the primary tumors which were pan-cytokeratin positive. The

pathologists concluded that these inflammatory lesions appear to be non-infectious, and

likely a form of immune myositis.

Comparison of Liposome-CT Accumulation and FDG-PET Uptake. In this pilot

study, liposome-CT and FDG-PET were both able to detect all of the nine primary tumor

lesions. The difference in the performance of the two imaging techniques to identify

inflammatory lesions was not necessarily a function of tumor size. Specifically, liposome-CT

had a higher sensitivity for detecting muscle inflammations (25 lesions vs. 7 lesions detected

by FDG-PET), with volumes ranging between 0.01 cm3 and 2.73 cm

3. The lesions that were

also detected by FDG-PET ranged in volume between 0.05 cm3 and 1.04 cm

3. While the

lower spatial resolution may be the major contributor for PET’s inability to detect the eight

lesions that were less than 0.05 cm3 in volume; the remaining ten lesions that were not

detected by PET ranged between 0.06 cm3 and 2.73 cm

3. For the latter cases, their proximity

to high FDG uptake structures combined with an overall lower FDG uptake may be

contributing factors for missed abnormality identification. An attempt was made to determine

whether it is possible to discriminate between the two types of abnormalities (tumor and

101

inflammation) based on imaging signal alone. Figure 5.4a illustrates that five days post-

administration, the degree of liposome accumulation may allow for potential differentiation

of neoplastic from inflammatory lesions. In general, VX2 tumors exhibit less CT contrast

enhancement compared to inflammatory lesions. The mean of the ratios of HUmean measured

in the tumor over the HUmean measured in the blood (aorta) obtained from 14 distinct VX2-

tumor bearing rabbits (nine rabbits from this study + five additional rabbits from a separate

study) was 0.85 ± 0.11. Conversely, the mean of the ratios of HUmean measured in the

inflammatory sites (25 lesions from the 9 rabbits from this study + 8 lesions from the 5

additional rabbits) over the HUmean measured in the blood obtained from the rabbits

employed in this study was 1.31 ± 0.25. Results from Welch’s t test confirmed that the

HUmean value from the CT data set obtained 5-days post-liposome administration can be used

to differentiate between neoplastic and inflammatory lesions (p < 0.0001). Although the

average size of tumor lesions (5.97 ± 4.52 cm3) was much greater than the average size of the

inflammation lesions (0.40 ± 0.60 cm3), there is no clear correlation between liposome

uptake and lesion size (Figure 5.4b). Figure 5.4c depicts the range of partial volume

adjusted SUVmax values for the two lesion types calculated from the FDG-PET data set. The

mean adjusted SUVmax for the nine tumor lesions and eleven inflammatory lesions were 4.9 ±

2.0 and 5.3 ± 2.3, respectively. Welch’s t test concluded that there is no significant difference

in the adjusted SUVmax values obtained from these two lesion types (p > 0.15). A CT study

on a separate group of four rabbits (different from the nine employed for this CT/PET

investigation) was conducted to investigate the difference in liposome accumulation and

clearance kinetics from tumors and inflammatory lesions. Figure 5.5 reports the results from

the kinetic study and it illustrates that not only the inflammatory lesions exhibit higher CT

102

contrast enhancement over time, but also the greatest difference between the mean CT signal

measured in tumor and inflammatory sites occurred at 5 days post liposome administration. It

is also interesting to note that there was insufficient contrast uptake at the sites of

inflammation in the first 48 hours post injection.

Incidental Findings. A total of two lymph nodes (0.10 cm3 and 0.12 cm

3 in volume)

were classified as malignant from the FDG-PET results (Figure 5.6a and 5.6b). However,

neither was contrast enhanced in the CT data set. One of these two lymph nodes was

successfully collected and was determined to be unequivocal nodal metastasis (pan-

cytokeratin positive) by the pathologists. In a separate case (not from this series of animals,

Figure 5.6c), a VX2 carcinoma-bearing rabbit was administered the same liposome agent and

imaged with CT for five days post-injection and sacrificed. An enlarged para-aortic lymph

node (long axis measures 1.5 cm) at the lower lumbar muscle level and of abnormal

morphology was collected, confirmed to be malignant and in this case was also not contrast-

enhanced in CT. Although publications have reported liposome accumulation in malignant

lymph nodes following interstitial administrations [124], the above findings suggest that this

liposome formulation does not significantly accumulate in lymph nodes that have been

invaded by tumor cells following intravenous administration. However, due to the low

numbers of animals, no definitive conclusion can be made. A suspect liver lesion (no

histology available) of 1.15 cm3

in volume was also detected by FDG-PET (SUVmax = 4.6).

The same lesion was shown as a hypo-intense region in the liposome-CT data set. This is

consistent with the imaging morphology of hypovascular liver tumors detected with a

contrast-enhanced CT protocol [219]. Lastly, three suspect bone lesions were identified in the

FDG-PET data set with SUVmax values ranging between 1.7 and 2.2. No histology samples

103

are available to confirm the nature of these three lesions, and the liposome-CT data set does

not show an elevated contrast uptake pattern in these regions.

Figure 5.2 Three cases of primary tumors detected by CT and PET, and confirmed by

histology (pan-CK positive). The volumes of the lesions depicted are 7007 mm3, 299 mm

3

and 70 mm3 for cases A, B and C, respectively.

104

Figure 5.3 Two cases of inflammatory lesions in the muscle detected by CT and PET, and

confirmed by histology (pan-CK negative). The volumes of the lesions depicted are 2732

mm3 and 173 mm

3 for cases A and B, respectively. Lesion A was located in the right lower

lumbar muscle and lesion B was located in the left arm.

105

(a)

25%

75%

50%

25%

75%

50%

Tumor Inflammation

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

Le

sio

n t

o b

loo

d H

Um

ea

n r

atio

(b)

0 2 4 6 8 10 12 14 16 18 20

0.50

0.75

1.00

1.25

1.50

1.75

2.00

2.25

Inflammation

Tumor

Le

sio

n to

blo

od

HU

me

an r

atio

Lesion size (cm3)

106

(c)

25%

75%

50%25%

75%

50%

Tumor Inflammation

0

2

4

6

8

10

12

Ad

juste

d S

UV

ma

x

Figure 5.4 Imaging signal intensities of neoplastic and inflammatory lesions: a) ratio of

mean HU measured in an entire lesion over that measured in the blood from the liposome-CT

data set; b) difference in the normalized CT signals between the tumor and inflammatory

sites is independent of lesion size; and c) partial volume effect adjusted SUVmax measured in

the FDG-PET data set for the two lesion types. The upper, middle and lower bounds of the

boxes indicate the 75th

, 50th

and 25th

percentile, and the dash inside each box marks the mean

value of each sample population. Note that 5 additional VX2-carcinoma bearing rabbits with

8 inflammatory lesions from a separate study were included in the CT data set (a).

107

0 50 100 150 200 250 300 350

0

25

50

75

100

125

150

175

200

Lesio

n H

Um

ea

n

Time (h)

Tumor (n=4)

Inflammation (n=8)

Figure 5.5 Kinetic profiles of liposome contrast agent accumulation and clearance in tumor

and inflammatory lesions. The measurements were performed on four male New Zealand

White rabbits each bearing a primary VX2 carcinoma tumor in their upper left thigh and each

exhibiting between one to three inflammatory lesions in the lower lumbar muscle area. There

are no data points before 48 hours post liposome injection for the inflammatory lesions

because there was insufficient contrast enhancement to identify the lesion from surrounding

muscle.

108

(a)

(b)

(c)

Figure 5.6 a) and b) Two examples of FDG-PET positive lymph nodes (5 mm and 6 mm) that were not detected using liposome-CT; c)

a malignant lymph node excised from an animal from a separate study. The node (15 mm) was not contrast-enhanced in CT.

109

5.5. Discussion

The goal of this investigation was to demonstrate the ability of a newly developed

liposomal CT agent to localize in both tumor and inflammatory sites via the well-described

enhanced permeation and retention (EPR) effect [18]. Although liposomes have been

extensively reported to deliver drugs and radionuclide imaging agents to these sites [220,

221], this is the first time that CT-based assessment of liposome accumulation in both

neoplastic and inflammatory lesions is shown. Furthermore, no studies have sought to

compare the performance of an EPR targeting nanoscale contrast agent with that of FDG-

PET.

Image-based differentiation of malignant tumor and inflammatory lesions has proven

to be challenging due to physiological similarities present in these two types of

abnormalities. For example, both tumor and inflammation are generally characterized by

increased vascular permeability, metabolic activity and presence of immune cells such as

macrophages. As a result, in this study, it was not unexpected that both types of lesions were

detected by liposome-CT and FDG-PET. However, it is important to note that liposomes and

FDG target abnormal lesions through two very distinct bio-physiological processes. The

liposomes employed in this study were spherical particles of roughly 80 nm in diameter [61].

Due to their size, they are retained within the endothelial walls of normal vasculature, but are

able to leak into the interstitial space of tissues through the highly permeable vessels that

characterize both VX2 tumors and inflammatory sites. Furthermore, the slow venous return

and poor lymphatic drainage system found at tumor sites, as well as uptake by tumor and

inflammation associated macrophages significantly slows down their clearance [15, 23, 222].

The combination of these factors results in a preferential accumulation and retention of

110

liposomes at tumor sites. On the other hand, FDG has a molecular weight of 181.3 Daltons. It

is approximately 104 times smaller than a single CT liposome employed in this particular

study. Because its size matches that of a small molecule agent, it is subject to fast renal

clearance and does not localize at sites of tumor and inflammation via the EPR effect.

However, its retention within cells of high metabolic activity (i.e. neoplastic cells with high

proliferation rate and activated macrophages) allows it to be used effectively for tumor and

inflammation imaging [223-225]. Reports from a number of research groups have

demonstrated that dynamic imaging of liposomes [226] and FDG [225, 227-229] at tumor

and inflammatory sites allows for successful classification of the two lesion types. In this

investigation, only one imaging time point was used to differentiate tumor from

inflammation. For the particular tumor and inflammation model employed in this study,

liposomes demonstrated a statistically significant difference in their mean accumulation

relative to blood at the two sites, while FDG did not.

It is interesting to note that studies that have investigated the microdistribution of

liposomes and FDG in neoplastic lesions have concluded that both agents also localized in

the non-tumor component of the tumor tissue. Specifically, Kubota et al. reported in their

micro-autoradiography study that the macrophage layer surrounding tumor necrosis, the

young granular tissue with capillary vessels, fibroblasts and macrophages surrounding the

tumor mass, as well as the necrotic area with macrophages all showed higher grain count

than in the tumor cells themselves [230]. However, in human and animal tumors,

macrophages usually constitute 20-30% of the cellular tumor mass, therefore it is reasonable

to conclude that most of the radioactivity of 18

F-FDG in tumors originates from viable tumor

cells [229, 230]. Therefore, it is not surprising that inflamed tissues also exhibit high FDG

111

uptake. Kaim et al. reported in their autoradiographic quantification of 18

F-FDG uptake in

experimental soft-tissue abscesses in rats that the FDG uptake clearly coincided with the

presence of macrophages, and that no substantial increase in FDG uptake was detected within

the fibroblast-enriched granulation tissue [231]. Conversely, a study investigating the micro-

distribution of liposomes within C-26 colon carcinoma tumors reported that although the

gold-labeled liposomes were seen to be predominantly scattered in the extracellular space

between tumor cells, they also localized in areas surrounding blood vessels, as well as in the

endosomes and secondary lysosomes of tumor-associated macrophages [232]. Similarly, in a

rat model of focal infection, Laverman et al. found liposomes in the vicinity of blood vessels

and some present in endothelial cells, as well as significant localization within macrophages

[222]. Therefore, it could be hypothesized that the difference measured in this study between

the mean HU of tumor and inflammatory lesions was a function of both microvessel density

and macrophage presence. The difference in the liposome uptake kinetics at the sites of

tumor and inflammation (Figure 5.5) seem to indicate that it is the interaction between

liposome and macrophages that play a greater role in modulating its accumulation in

inflammatory lesions. The tumor kinetics curve peaks at 48 hours (two days) post liposome

administration (indicating that EPR occurs during this earlier time window), while the

inflammation kinetics curve peaks at 120 hours (five days) post injection (indicating that a

process different from EPR dominates this later time window). Current efforts are in place to

quantify the microvessel and macrophage density from the histology obtained for each lesion

in order to confirm the hypothesis.

In summary, results from this investigation demonstrated that increased contrast of

neoplastic and inflammatory lesions in CT is achieved with the administration of a liposomal

112

nano-agent. Its differential accumulation at sites of tumor and inflammation, as well as its

higher sensitivity in the detection of soft-tissue inflammatory lesions compared to FDG-PET,

suggest that, if approved for human use, liposomes could play a role in CT-based disease

screening and image-guided biopsy.

5.6. Acknowledgements

This work is funded in-part by CIHR and OICR research grants and the Fidani Chair

in Radiation Physics. Jinzi Zheng is grateful for the CIHR Banting and Best Canada

Graduate Scholarship. The authors would like to thank Dr. Anguo Zhong and Dr. Margarete

Akens for performing the VX2 tumor propagation, Dr. Alyssa Goldstein and Sandra Lafrance

for assistance during tissue collection, Dr. Harald Keller for providing the PET phantom data

used for partial volume correction, and Dr. Sylvia Asa and Dr. Patricia Turner for their

contribution to the histopathology component.

113

Chapter 6. Summary and Future Directions

114

6.1. Summary

A nano-sized liposome formulation was developed over the course of this thesis with

the ability to stably carry multiple imaging moieties. Extensive in vitro and in vivo

characterization was performed to explore the feasibility and utility of employing this nano-

system for a number of applications including multimodality CT and MR imaging (chapter

2), longitudinal vascular imaging (chapter 3), CT-based assessment of liposome

biodistribution and kinetics (chapter 4), and CT detection of tumor and inflammatory lesions

(chapter 5). The three main innovations of this thesis are: 1) development of the first

colloidal dual CT and MR imaging agent; 2) employment of CT as a quantitative and non-

invasive method for longitudinal evaluation of the biodistribution and kinetics of a

nanoparticulate agent; and 3) demonstration that the use of the liposome agent in conjunction

with CT imaging has superior performance, compared to FDG-PET, in the detection of

abnormalities of inflammatory origin as well as differentiation of these lesions from those of

neoplastic origin.

The work conducted within this thesis is highly inter-disciplinary. It took advantage

of the arguably most well characterized pharmaceutical carrier, the liposome, optimized a

formulation that can stably co-encapsulate multiple hydrophilic contrast agents and explored

its use in different imaging applications. The liposome literature goes back to the 1960s,

when it was first used as a model for studying biological membranes [233], then it was

recognized to be a promising carrier for pharmaceutical drugs and imaging agents. In medical

imaging, extensive investigations were first performed in nuclear medicine to assess its

suitability both as a radiopharmaceutical delivery system (i.e. by Caride et al. in 1976 [234])

and as an imaging agent [235]. The versatility of liposomes allowed for extension of their

115

employment in other imaging modalities such as CT (first preclinical report by Havron et al.

in 1981 [236] and first human study published by Leander et al. in 1998 [112]), MR (Magin

and et. reported the use of paramagnetic liposomes in mice in 1986 [237]), ultrasound (Unger

et al. described the feasibility of nitrogen-filled liposomes for vascular imaging in 1992

[238]) and optical imaging. The concept of using liposomes to co-load multiple imaging

moieties for cross-modality imaging emerged at around 2005 and 2006 with publications

reporting successful engineering of systems suitable for dual MR and optical imaging

(Mulder et al. in December 2005 [239]), MR and CT imaging (Zheng et al. in March 2006

[61]), and MR and SPECT imaging (Zielhuis et al in December 2006 [240]). Although

Chapter 2 of this thesis constituted one of the pioneer reports of multimodality imaging using

liposomes, other research groups have investigated other nano-systems, such as nanoparticles

[105, 241-243], nanocrystals [244], lipo-proteins [245] and dendrimers [246] for the same

purpose. It is likely that while a wide range of different nanosystems will remain to be used

in preclinical research applications, the first nanosystem that will achieve clinical approval

for use in humans will be explored for employment across different applications that benefit

from the use of multimodality imaging.

6.2. Future Directions

There are three broad directions in which further investigation can be pursued: 1)

comprehensive toxicity and efficacy studies to be conducted in appropriate animal models in

compliance with the regulatory approval application process in parallel with the selection of

a suitable commercialization partner; 2) continued innovation in the agent development side

to add functionality to the existing liposome platform (i.e. imaging capability beyond CT and

116

MR, specific cell targeting, ability to respond to triggers); and 3) employment of this

nano-system to further increase understanding of liposome transport, distribution and disease

localization, especially how these are modulated by the patho-physiology of the biological

system under investigation.

6.2.1. Technology Translation and Commercialization: Challenges and

Opportunities

The CT and MR liposome contrast agent developed within the framework of this

thesis demonstrated high stability in vitro and in vivo, no significant toxicity, and it

showed potential to benefit a number of imaging applications. Additional studies (results

not reported in this thesis) investigated its storage shelf-life and found that the liposomes

in a physiological buffer solution can be stored for at least one month at both room

temperature and 4°C without statistically significant leakage of the encapsulated agents

or change in the mean liposome size and size distribution. Furthermore, it was feasible to

scale-up the liposome contrast agent production from 20 mL per batch to 200 mL per

batch through the use of a large-scale LipexTM

high-pressure extruder (Northern Lipids

Inc., Burnaby, BC, Canada) without increasing the production time and at the same time

maintaining the same physico-chemical characteristics of the liposome solution reported

in this thesis.

In order to further the commercialization and technology translation efforts, the

current liposome contrast agent production procedure must be adapted to comply with the

Good Manufacturing Practice (GMP) standards. As final stage sterilization techniques,

such as irradiation, heat, high pressure and filtration are not suitable for liposomes, a

117

GMP production facility must be constructed to include a clean room where the entire

liposome preparation process will take place using sterile materials and production

instruments.

Initial discussion with the Canadian regulatory agency, Health Canada, has

indicated that further toxicity, clearance and metabolism studies should be conducted in

two animal models (one rodent and one non) in order to obtain comprehensive

information on the safety profile of this new agent. Furthermore, at least one clinical

application needs to be identified, with the support from clinicians, in order to allow for

patient population and clinical endpoint selection during the efficacy assessment stage of

the clinical trials.

It is challenging for an academic group to gather resources and expertise for the

translation and commercialization of a medical technology. Joint efforts with the UHN

business development office have led to successful funding applications through both

governmental and non-governmental sources to support these activities through task

outsourcing to pharmaceutical safety evaluation companies and regulatory approval

consultants. If regulatory approval for use of this liposome agent is achieved, this

research thesis will become a true example of successful translation from bench to

bedside.

6.2.2. Extension to a Modular Multimodality Imaging Platform

In routine clinical practice, specific imaging modalities are employed at different

stages of disease diagnosis and treatment. For example, combinations of anatomical and

functional imaging techniques such as CT, MR, PET, SPECT and US are often utilized

118

for disease diagnosis, staging and treatment planning. X-ray, MR, US and optical

imaging systems are also found in the treatment room to guide the delivery of various

interventions such as surgery, radiotherapy and radiofrequency ablation with the aim of

improving the accuracy of these procedures [78, 79, 247-251]. The benefit of combining

the different imaging modality is that they can provide complementary information on the

anatomy, physiology and function of the biological system under investigation. However,

because they rely on different signal generating mechanisms, it is sometimes difficult to

identify common structures for spatial reference. Accurate definition of the anatomical

location and boundary of the biological target is essential for therapy planning and

delivery. As a result, it would be extremely advantageous if signal generating agents

having the same pharmacokinetics, biodistribution and disease targeting ability are

available and their co-localization across imaging modalities would increase the

confidence in identification of disease and its boundary. A viable strategy is to engineer a

nanoplatform-based approach, which ensures that the biological performance of the nano-

agent remains constant while slight inert modifications can be made to custom match the

signal generating moiety load to the imaging modality or modalities of choice.

Liposomes are highly versatile colloidal particles that allow for encapsulation of

hydrophilic molecules within their aqueous core, the incorporation of hydrophobic

molecules within their lipid bilayer and insertion of additional lipid groups within their

bilayer that can either conjugate molecules or metal chelators [220]. In parallel with the

development of the dual-molecule co-encapsulation strategy described in this thesis, our

research team also explored the lipid exchange technique. Specifically, the incorporation

of lipid groups into the pre-formed liposome bilayer was optimized. These lipid groups

119

are either directly conjugated to an optical dye (i.e. Cy 5.5) or attached to a metal chelator

that binds to either a positron or single photon emitter (i.e. 64

Cu or 111

In), as well as

incorporate an active targeting ligand on the distal end of the PEG group to modulate the

distribution of liposomes to specific cell populations. Figure 6.1 shows the schematic

representation of the modular liposome multimodality imaging platform currently under

development. The resulting platform is aimed at providing persistent and co-localized

signal enhancements across multiple imaging systems (CT, MR, PET, SPECT and

optical). It has the potential to seamlessly bridge wide ranges of spatial, temporal and

sensitivity scales and to be employed throughout a variety of clinical scenarios (i.e.

diagnostic, pre-operative, intra-operative and follow-up imaging). Furthermore, strategies

to activate or deactivate different components of the liposome system following either

endogenous biological queues (i.e. temperature, pH, matrix metalloproteinase levels) or

external triggers (i.e. irradiation, hyperthermia, magnetic field) can be explored to

engineer a “smart” modular multimodality imaging platform.

120

Figure 6.1 Schematic representation of the modular multimodality liposome imaging platform. The aqueous core of the liposome can

be used to cargo hydrophilic small molecule therapeutic and imaging agents. Physical attachment of polymers such as DTPA, DOTA

and HYNIC onto phosphatidylethanolamine (PE) lipids allows for chelation of PET and SPECT metal radioisotopes. Optical imaging

probes and active targeting ligands can be either directly conjugated onto the PE lipid or the distal end of the PEG chain, or be

incorporated into the liposome system through strepavidin and biotin binding.

121

6.2.3. Additional Characterization of Liposome Transport and Distribution

The successful development of a modular multimodality imaging platform will allow

for comprehensive probing of the complexity of tumors. For example, Chapters 4 and 5 of

the present thesis demonstrated that CT is advantageous for high-resolution disease detection

and characterization. The voxel size of the clinical CT scanner (Discovery ST, GE

Healthcare, USA) employed throughout the rabbit imaging studies reported in this thesis was

390 x 390 x 630 µm3. Recent developments in the area of preclinical imaging resulted in

commercially available microCT systems with the ability to perform in vivo imaging with an

isotropic voxel size of approximately 15 µm in mice (Inveon microCT, Siemens Preclinical

Solutions, USA). As a result, it is now feasible to image the micro-distribution of imaging

agents, such as the liposome agent developed here, in tumors in vivo longitudinally. To date,

ex vivo imaging techniques such as autoradiography and confocal/multiphoton microscopy

have been routinely employed to quantify the distribution of radio- and optically-labelled

agents in tissue sections at tens of microns and sub-micron resolutions, respectively [252,

253] . The benefits of volumetric in vivo assessment of agent micro-distributions are clear.

Not only does it allow for mapping of the distribution of the agent of interest in a live

biological system without the deformations that often occur during the preparation of tissue

sections [254], but it also enables multiple measurements to be performed on the same

animal over time, permitting the evaluation of kinetic changes in the micro-distribution

pattern.

When performing serial high-resolution microCT imaging, the amount of radiation

dose delivered to an animal, especially small size rodents such as mice, should be considered.

Publications that investigated the effect of serial microCT radiation dose to animals have

122

found that there was no effect on tumor growth, mouse survival or ability to form metastasis

[255, 256]. Daibes Figueroa et al. reported in their thermo luminescent dosimeter (TLD)

assessment of mouse dosimetry an absorbed dose of 76 ± 5 mGy for one full rotation (360°)

of microCT scan (MicroCAT IITM

, Siemens Preclinical Solutions, USA) at 80 kVp and 54

mA with 0.5 mm of aluminum filtration [257]. This is equivalent to approximately 1/5 of the

whole body absorbed dose delivered to a 20 g mouse with the administration of one of the

longer lived SPECT isotope 111

In (360 mGy, assuming no biological washout [258]). These

dose considerations makes it feasible to design serial high-resolution microCT imaging

studies.

An attractive application of high-resolution imaging is for comparison of the micro-

distribution and kinetics of passively and actively targeted agents in tumors. To date, many

investigations have been carried out to assess the value of ligand-directed nanoparticle

delivery to tumors. Increased therapeutic efficacy has been often associated with the

employment of an actively targeted agent. However, no consensus has been reached with

respect to the underlying mechanisms that resulted in the improved therapeutic ratio. Several

groups suggest that the presence of an actively targeted ligand on the surface of nanoparticles

does not alter its tumor localization, but rather increases the intracellular uptake of the

nanocomplex [259, 260]. Other reports indicate that the actively targeted nanoparticles do

have an enhanced accumulation at tumor sites [261-265]. The multi-factorial nature of this

comparative investigation makes it difficult to draw straight-forward conclusions [266].

Longitudinal quantitative high-resolution microCT monitoring of the spatial and temporal

distribution of targeted and non-targeted nanoparticles within murine tumors at isotropic

resolutions of 15 µm is an attractive method that can potentially help elucidate the

123

mechanisms of tumor accumulation and distribution of different actively targeted

nanosystems. Furthermore, if the nanosystem is co-labelled with a CT agent and a near

infrared optical dye, and it is imaged with a microCT and an in situ confocal imaging probe

(i.e. Leica FCM1000), it is possible to assess both the intratumoral localization and the tumor

cell uptake of this nanosystem.

The study conducted in Chapter 5 illustrated that although both liposomes and FDG

significantly accumulate and are retained in neoplastic lesions, they do so according to very

different underlying biological and physiological processes. Much research has focused on

using imaging agents, also known as imaging biomarkers, to spatially map different

environments within a tumor (i.e. viable, necrotic and hypoxic areas [267]), it would be

interesting to query the effect of the diverse tumor micro-environment on the distribution and

uptake of imaging and therapeutic agents, in particular macromolecular agents such as

liposomes. The well-known EPR effect describes the differential accumulation and retention

of macromolecules at healthy and tumor tissues resulted from the difference in physiology

(i.e. increased vessel permeability and decreased lymphatic drainage found at tumor sites). It

is also generally accepted that parameters that define the tumor micro-environment, such as

regional micro-vessel density, blood flow, degree of oxygenation, pH and interstitial fluid

pressure, can influence the distribution of both imaging and therapeutic agents [268]. In fact,

functional imaging techniques such as functional CT and DCE-MR rely on these local

changes to derive information in order to classify the different tumor voxels. The

employment of macromolecular agents, especially groups of agents of different but well-

defined molecular weight and size, with high-resolution imaging modalities such as CT and

MR, has the potential to further elucidate the interplay of the different tumor micro-

124

environmental parameters described above. Furthermore, when used in conjunction with

other molecular imaging methods (i.e. FAZA-PET for hypoxia imaging), biological mapping

of abnormal lesions and high-resolution classification of the tumor micro-environment can be

achieved. This will have important implications for cancer staging, treatment planning,

delivery guidance, as well as therapy follow-up.

125

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