Raport stiintific final

privind implementarea proiectului in perioada octombrie 2011 – septembrie 2016

Clinical and Biomathematical Modeling of Vascular Changes Following

Anti-Angiogenic Therapy in Advanced Colorectal Carcinoma

Activity report for October, 2011 – September 2016

Project Director: Dr. Gabriel Gruionu

ABSTRACT: Colorectal carcinoma (CRC) represents an important health burden, being the third leading cause of cancer death in the world. The cancer-stromal cell interaction contributes directly to tumor growth and metastasis by creating an imbalance of positive and negative growth factors and increased microvascular

density via angiogenesis. Recently, advances in chemotherapy and biological therapies targeting the angiogenic growth factors offered additional hope for treatment but the exact biological mechanisms are still

not clear. Therefore, the long-term goal of the proposed research is to gain improved understanding of

the mechanisms by which tumor microvascular networks (MVN) respond to chemotherapy and/or

anti-angiogenic therapy. To address this, the first objective is to map the MVN and cellular

components of normal colorectal tissue and CRC tumors before and after chemotherapy and/or anti-

angiogenic treatment in CRC patients . Changes in morphometric and hemodynamic parameters of MVN

will be observed with a novel combination of minimally invasive ultrasound and confocal imaging

techniques (CE-EUS and CLE) correlated with the type and dosage of therapy. The second objective is to

develop computer simulations of blood flow and structural adaptation of the MVN in CRC tumors .

The predictions of the model will be compared with the observed changes in the MVN structure following chemo- and anti-angiogenic treatment. The project will have a significant scientific and social impact leading to a better categorization and prediction of patient’s response to treatment before exposure to

chemotherapy or surgery.

Specific activity calendar:

Activity A 1.1 Set-up of a structured database and definition of the experimental models

A complex database was set up on a dedicated computer and back up to an external hard drive to include all

the identifying information (age, ID, location, sex), imaging procedure, biopsy location, diagnosis, treatment dosage and final evaluation. The details about each patient group is presented in the following sections and

the Materials and Methods of each paper. A1.2. Protocol based inclusion of patients (CE-EUS and CLE) and data sampling.

The patient samples were collected and analysed according to the following protocol.

M1-3 M4-6 M7-9 M10-11 M12-14 M15-17 M18-20 M21-23 M24-26 M27-29 M30-32 M33-35

A 3.1 Development of the mathematical model of

normal and untreated CNC MVN

A 4.2 Forecasting angiogenesis during and

after antiangiogenic treatment

A 1.1 Set-up of a structured database and

definition of the experimental models

A 1.2 Protocol-based inclusion of patients (CE-EUS & CLE), tissue sampling

A 2.1 Pathological and

immunohistochemical analysis of biopsy

samplesA 2.3 Mathematical model of the anti-angiogenic treated MVN

In the first year, over 60 patients were enrolled in the study (age 49-76 years). Every patient signed a

consent form before the beginning of the study. For CLE examination we used the dedicated system (EC-3870 CIFK, Pentax, Tokyo, Japan), which has a miniature confocal microscope integrated into the distal tip

of a conventional flexible endoscope. The endomicroscope uses a laser bean with an excitation wavelength of 488 nm and a maximum laser power output at the surface of the targeted tissue of ≤1mW. This results in optical sections of 475x475μm2 with a lateral resolution of 0.7 μm for a 7 μm thick slice (z-axis). CLE

imaging is performed on fresh biopsies of both normal mucosa and colorectal cancer tissue obtained during lower GI endoscopic procedures. The biopsies undergo a staining protocol, including incubation (1h, 37°C,

1:10 dilution) with Alexa-Fluor 488 labeled anti-CD31 antibodies. Scanning is performed with the biopsies on histology glass slides, placed in direct and gentle contact with the distal tip of the confocal laser endomicroscope. Consecutive images are captured and digitally stored on the system’s hard drive as grey-

scale images (250-300 for each biopsy sample) for later download and processing. The imaging procedures are backed by immunohistochemical studies of corresponding biopsies for evaluating tumor vascular

patterns and performing a thorough morphometric analysis.

During the second and third year, over 40 patients were enrolled in the study (age 49-76 years). We

used the same protocol for the CLE examination as before. The imaging procedures are backed by immunohistochemical studies of corresponding biopsies for evaluating tumor vascular patterns and

performing a thorough morphometric analysis. Compared to the previous article publishes in PLoS One, the new article introduced new morphometric parameters and demonstrated for the first time that tumor vessels are not actually more tortuous than the normal tissue vessels. The results were first presented at the United

European Gastroenterology Week (UEGW) international conference conference and published in the PLoS ONE journal (see conference reference [6] and manuscript abstract bellow [7]).

Evaluation of new morphometric parameters of neoangiogenesis in human colorectal cancer using

confocal laser microscopy (CLE) and targeted panendothelial markers

The tumor microcirculation is characterized by an abnormal vascular network with dilated, tortuous, and

saccular vessels. Therefore, imaging the tumor vasculature and determining its morphometric characteristics represent a critical goal for optimizing the cancer treatment that targets the blood vessels (i.e. antiangiogenesis therapy). The aim of this study was to evaluate new vascular morphometric parameters in

colorectal cancer, difficult to achieve through conventional immunohistochemistry, by using the confocal laser endomicroscopy method. Fresh biopsies from tumor and normal tissue were collected during

colonoscopy from five patients with T3 colorectal carcinoma without metastasis and were marked with fluorescently labeled anti-CD31 antibodies (Figure 1). A series of optical slices spanning 250 μm inside the tissue were immediately collected for each sample using a confocal laser endomicroscope. All

measurements were expressed as the mean ± standard error. The mean diameter of tumor vessels was significantly larger than the normal vessels (9.46±0.4 μm vs. 7.60±0.3 μm p=0.0166). The vessel density

was also significantly higher in the cancer vs. normal tissue samples (5541.05±262.81 vs.3755.79 ±194.96 vessels/mm3, p=0.0006). There results were confirmed by immunohistochemistry. In addition, the tortuosity

index and vessel lengths were not significantly different (1.06±0.016 and 28.78±3.27 μm in normal tissue, vs. 1.07±0.008 and 24.65±3.18 μm in tumor tissue respectively, p=0.4673 and p=0.7033). The

daughter/mother ratio (ratio of the sum of the squares of daughter vessel radia over the square of the mother vessel radius) was 1.11±0.09 in normal tissue, and 1.10±0.08 in tumor tissue (p=0.6497) (Table 1). The

confocal laser endomicroscopy is feasible for measuring more vascular parameters from fresh tumor biopsies than conventional immunohistochemistry alone. Provided new contrast agents will be clinically available, future in vivo use of CLE could lead to identification of novel biomarkers based on the

morphometric characteristics of tumor vasculature.

Figure 1. Ex-vivo CLE Vascular measurements of Vessel Length and Tortuosity Index. The Z projection of the image stack for normal (A) and tumor (B) microvasculature, apparently with more

tortuous branched vessels. The vessel length was measured using segmented line tool and reported in micrometres. The tortuosity index was calculated as the ratio of segmented and straight line lengths for both

normal (C) and malignant (D) human colorectal tissue. *The scale bar is 50 μm.

Morphometric

Parameters Normal Mucosa Colorectal Tumor P Value

Vessel Diameter

(μm) 7.60±0.3 9.46±0.4 0.0166

Vessel Density

(vessels/mm3) 3755.79 ±194.96 5541.05±262.81 0.0006

Vessel Length (μm) 28.78±3.27 24.65±3.18 0.7033

Tortuosity Index 1.06±0.02 1.07±0.01 0.4673

Daughter/Mother

Ratio 1.11±0.09 1.10±0.08 0.6497

Table 1. Average values of the morphometric parameters measured with CLE. The values are expressed as

the mean ± standard error.

CE-EUS study

We have enrolled 35 patients in the CE-EUS study and continue to analyze the data. A preliminary report was presented at the UEGW conference by Dr. Tatiana Cartana [1].

Title: Quantitative assessment of tumour perfusion of colorectal cancer patients by using

Contrast-enhanced endoscopic ultrasonography: a feasibility study. Introduction: Contrast enhanced endoscopic ultrasonography (CE-EUS) is a high resolution technique

enabling minimally invasive assessment of tumour perfusion. Despite recent technology advancements, the use of CE-EUS in the evaluation of colorectal cancer (CRC) has not been previously reported.

Aims & Methods: Therefore the aim of our study was to evaluate tumour vascularity in CRC by using CE-EUS and time intensity curve analysis in correlation with pathology parameters of angiogenesis. We

included 35 patients with CRC that were examined by low mechanical index CE-EUS prior to any therapy, using 4.8 ml of Sonovue (Bracco, Italy) administered in bolus injection as contrast agent. Time intensity

curve (TIC) parameters were determined by offline analysis of recorded video sequences with specific software (Fig. 2). Immunohistochemical assessment of tumour vascularization included microvascular density calculation using CD31 and CD105 specific staining, which was available for 18 of the patients.

Figure 2. Offline video analysis - Image-Pro Plus (Media Cybernetics, Bethesda, SUA Results: Most tumours were well vascularized at CE-EUS examination, demonstrating either homogenous

uptake of the contrast agent or inhomogeneous enhancement, with stronger peripheral uptake and avascular areas towards the intestinal lumen. The mean values (± SD) for TIC parameters were: 10.08 ± 3.85 s for

arrival time (AT), 24.03 ± 10.94 s for time to peak (TTP), 41.43

± 19.24 a.u. for peak intensity (PI) and 5477.45 ± 2922.68 a.u.*s for the area under the curve (AUC) (Table 1). An inverse

correlation was noted between AT and CD31 MVD, but without reaching statistical significance (Spearman r = -0.55, p= 0.1328) and also between TIC parameters Imax and AUC and lymph

nodes involvement (r = -0.439, p = 0.0683).

TIC Parameter Mean value ± SD Min - Max

AT (s) 10.08 ± 3.85 4.17 - 16.67

TTP (s) 24.03 ± 10.94 9.33 - 56.17

PI (a.u.) 41.43 ± 19.24 10.1 - 80.1

AUC (a.u.*s) 5477.45 ± 2922.68 830.1 - 11735

Table 1. TIC parameters. a.u. - arbitrary units; AT - arrival time;TTP - time to peak; PI - peak intensity (Imax ); AUC - area under the curve

Conclusions: CE-EUS using low mechanical index examination and TIC analysis is feasible for the assessment of intratumoral perfusion in colorectal cancer. Further studies on larger groups of patients are

necessary to improve the examination technique and define its role in the evaluation of CRC patients.

By the forth year, over 57 patients were enrolled in the study (age 49-76 years). The consent forms that every patient has to sign before the beginning of the study were attached to the previous report. Compared to

the previous 2012 article published in PLoS One, the new article also published in 2014 in PLoS One introduced new morphometric parameters and demonstrated for the first time that tumor vessels are not

actually more tortuous than the normal tissue vessels (see abstract below) [5]. Evaluation of New Morphometric Parameters of Neoangiogenesis in Human Colorectal Cancer Using

Confocal Laser Endomicroscopy (CLE) and Targeted Panendothelial Markers

Abstract The tumor microcirculation is characterized by an abnormal vascular network with dilated, tortuous, and saccular vessels. Therefore, imaging the tumor vasculature and determining its morphometric characteristics

represent a critical goal for optimizing the cancer treatment that targets the blood vessels (i.e. antiangiogenesis therapy). The aim of this study was to evaluate new vascular morphometric parameters in

colorectal cancer, difficult to achieve through conventional immunohistochemistry, by using the confocal laser endomicroscopy method. Fresh biopsies from tumor and normal tissue were collected during colonoscopy from five patients with T3 colorectal carcinoma without metastasis and were marked with

fluorescently labeled anti-CD31 antibodies. A series of optical slices spanning 250 μm inside the tissue were immediately collected for each sample using a confocal laser endomicroscope. All measurements were

expressed as the mean ± standard error. The mean diameter of tumor vessels was significantly larger than the normal vessels (9.46±0.4 μm vs. 7.60±0.3 μm p=0.0166). The vessel density was also significantly higher in the cancer vs. normal tissue samples (5541.05±262.81 vs.3755.79 ±194.96 vessels/mm3,

p=0.0006). There results were confirmed by immunohistochemistry. In addition, the tortuosity index and vessel lengths were not significantly different (1.06±0.016 and 28.78±3.27 μm in normal tissue, vs.

1.07±0.008 and 24.65±3.18 μm in tumor tissue respectively, p=0.4673 and p=0.7033). The daughter/mother ratio (ratio of the sum of the squares of daughter vessel radia over the square of the mother vessel radius) was 1.11±0.09 in normal tissue, and 1.10±0.08 in tumor tissue (p=0.6497). The confocal laser

endomicroscopy is feasible for measuring more vascular parameters from fresh tumor biopsies than conventional immunohistochemistry alone. Provided new contrast agents will be clinically available, future

in vivo use of CLE could lead to identification of novel biomarkers based on the morphometric characteristics of tumor vasculature.

More recently, we have identified new markers which are more specific to tumor endothelium than the traditional markers. We use CD105 to identify the vessels which are new and specific to tumors vs. the host

vessels. The results of the preliminary study were presented by Dr. Ciocalteu at the UEGW 2014 conference in Vienna, Austria. [10]

Feasibility Study for the Evaluation of Morphopatological Pattern of Neoangiogenesis in Human

Colorectal Cancer using Confocal Laser Endomicroscopy and Targeted Anti- CD105 Antibodies.

Introduction: Confocal Laser Endomicroscopy (CLE) is an imaging technique for gastrointestinal endoscopy providing in vivo microscopy at subcellular resolution. An important question in validating

tumor angiogenesis is what proportion of the tumor vascular network is represented by pre-existing parent tissue vessels or newly formed vessels. CD105 (endoglin) represents a proliferation-associated endothelial

cell adhesion molecule. In contrast to pan-endothelial markers, such as CD31, CD105 is preferentially expressed in activated endothelial cells that participate in neovascularization.

Aims & Methods: The aim of the study was to evaluate neoangiogenesis and vessel density in colorectal cancer patients by using two fluorescently labeled antibodies on fresh biopsy samples imaged with CLE. We

evaluated CD105 and CD31 expression from samples of five patients with primary colon adenocarcinoma, using a dedicated endomicroscopy system (EC-3870 CIFK, Pentax, Japan). Image J (National Institutes of Health, USA) software was used to obtain the Z projection of the confocal serial images from each biopsy

sample previously combined into stacks. Vascular density and vessel diameters were measured within two 50x475 mm rectangular regions of interest centered in the middle of each image in the horizontal and

vertical direction. The results were averaged over all the patients and were expressed as the mean± standard error.

Results: The use of CD105-antibody was found to be suitable for the detection of blood vessels only in

colorectal cancer. Whereas anti-CD31 antibodies stained blood vessels in both normal and pathologic colon equally, CD 105 expression was observed primarily in malignant lesions, with little or no expression in the vessels of the normal mucosa (252.63±195.6 vessels/mm3 in only two patients). We could measure the

average diameter of anti-CD105 antibodies stained vessels of 11.22±0.8 μm in tumor tissue, counting 2812.61±147.3 vessels/mm3. When using anti-CD31 antibodies, the average diameter of vessels in the

normal sample was 6.22±0.3 μm and the vessel density was 3199.98±478.5 vessels/mm3, while in the tumor sample we obtained an average diameter of 10.38 ± 0.4 μm and a vessel density of 4816.81± 620.7vessels/ mm3. Thus, there were more vessels stained with CD31 than by CD105 (p<0.05). The results were also

confirmed by immunohistochemistry.

Conclusion: Specific imaging and quantification of tumor microvessels is feasible using CLE examination and CD 105 immunostaining of samples. CD 105 is a more specific marker for tumour angiogenesis, as compared to commonly used panendothelial markers. The combination of CD 105 staining with CLE

analysis could provide a more reliable evaluation of the angiogenetic status of patients with colorectal cancer.

CE-EUS study

We have enrolled 57 patients with colorectal tumors in the CE-EUS study and continue to analyze the data.

For the examination we use a Pentax radial EUS endoscope (EG-3670URK, Pentax, Hamburg, Germany) coupled to a Hitachi Preirus ultrasound system (Hitachi Medical Corp, Tokyo, Japan) with integrated low mechanical index contrast enhanced examination mode. During the procedure we initially describe tumor

and lymph node characteristics (echogenicity, echostructure, size, tumor extent into the bowel wall and surrounding structures) for TNM classification, followed by contrast-enhanced examination with bolus

administration of the contrast agent (Sonovue 4.8 ml, Bracco, Italy). 60 seconds video sequences are saved and stored in .avi format on the internal hard-drive of the ultrasound system for later offline analysis. For time-intensity curve analysis we use a dedicated software tool (VueBox™, Bracco) which requires prior

conversion of the recorded films into DICOM format. A preliminary report on the quantitative analysis of tumor perfusion by using time-intensity curve analysis was presented during Digestive Diseases Week 2014,

Chicago, Illinois by Dr. Tatiana Cartana [11]. Title: Low Mechanical Index Contrast-Enhanced Endoscopic Ultrasound for Quantitative Assessment

of Tumour Perfusion in Colorectal Cancer Patients: Preliminary Study

INTRODUCTION: Contrast enhanced ultrasound is an already established and valuable imaging technique with increasing clinical applications. Furthermore contrast enhanced endoscopic ultrasound (CE-EUS) benefits from a higher imaging resolution that enables minimally invasive assessment of tumour perfusion.

Despite recent technology advancements, the use of CE-EUS in the evaluation of colorectal cancer (CRC) has not been previously reported.

AIMS & METHODS: Therefore the aim of our study was to evaluate tumour vascularity in CRC by using CE-EUS and to describe time intensity curve parameters for these tumors in relation to different clinical and

pathological features. We prospectively included 40 patients with CRC that were examined by low mechanical index (0.2) CE-EUS prior to any therapy, using as a contrast agent 4.8 ml of Sonovue (Bracco, Italy) administered in bolus injection. Offline analysis of the recorded video sequences was performed with

specific software (VueBox™, Bracco) and several parameters were determined based on time intensity curves (TIC), including peak enhancement (PE), rise time (RT), mean transit time (mTT), time to peak

(TTP) and area under the curve (AUC).

RESULTS: CE-EUS examination showed that most of the tumours were well vascularized, with either

homogenous uptake of the contrast agent or inhomogeneous enhancement resulting from stronger peripheral

uptake and avascular areas towards the intestinal lumen, with the latter pattern most frequently seen in advanced tumors (T3, T4). Only 6 (15%) of the colorectal tumors were hypoenhancing. The mean values (±

SE) for TIC parameters were: 51.93 ± 20.46 a.u. for PE, 7.49 ± 1.18 s for RT, 76.52 ± 22.39 s for mTT, 9.76 ± 1.30 s for TTP and 889.39 ± 466.94 a.u.*s for the area under the curve (AUC).

CONCLUSION: The assessment of intratumoral perfusion in colorectal cancer is possible with low mechanical index CE-EUS examination and TIC analysis. In the future this imaging method could be used

to predict the response to targeted antiangiogenic therapies or to follow-up intratumoral drug distribution, based on further investigation and validation on larger groups of patients which will improve the

examination technique and define its actual role in the evaluation of CRC patients.

Up to date, over 60 patients were enrolled in the study (age 49-76 years). The consent forms that every

patient has to sign before the beginning of the study were attached to the previous report.

For CLE examination we use the dedicated system (EC-3870 CIFK, Pentax, Tokyo, Japan), which has a miniature confocal microscope integrated into the distal tip of a conventional flexible endoscope. The endomicroscope uses a laser bean with an excitation wavelength of 488 nm and a maximum laser power

output at the surface of the targeted tissue of ≤1mW. This results in optical sections of 475x475μm2 with a lateral resolution of 0.7 μm for a 7 μm thick slice (z-axis). CLE imaging is performed on fresh biopsies of

both normal mucosa and colorectal cancer tissue obtained during lower GI endoscopic procedures. The biopsies undergo a staining protocol, including incubation (1h, 37°C, 1:10 dilution) with Alexa-Fluor 488 labeled anti-CD31 antibodies. Scanning is performed with the biopsies on histology glass slides, placed in

direct and gentle contact with the distal tip of the confocal laser endomicroscope. Consecutive images are captured and digitally stored on the system’s hard drive as grey-scale images (250-300 for each biopsy sample) for later download and processing.

A2.1. Pathological and immunohistological analysis of biopsies. All patient biopsies were analysed for diagnostic purposes. The samples were fixed in neutral buffered

formalin and were further processed for paraffin inclusion. Aside from ensuring the pathological diagnostic, slides from the paraffin blocks underwent an antigen retrieval procedure and were immunostained for CD31.

A species specific polymeric HRP secondary antibody was used to amplify the reaction, and the signal was finally visualised using a specific precipitating HRP substrate (DAB, 3,3'-Diaminobenzidine). After image acquisition under a light microscope, the microvessel density (MVD) was assessed based on direct counting

on areas with the highest vascular populations, according to the classically hotspot method. Furthermore total vascular areas were also calculated on the captured images using a stylus design tablet in order to

obtain a fine delimitation of the signal and vascular lumens. After area-normalisation, both parameters were compared with CLE measurements.

Four out of the twenty patients of these patients were imaged with laser confocal endomicroscopy and included in the feasibility study that was presented as an oral talk at the 2011 United European

Gastroenterology Week (UEGW) international conference, in Stockholm and granted the National Scholar Award [1], and as a poster at the Cajal International Symposium [2]. The extensive feasibility study was published in the PLoS ONE journal, an ISI open access publication with the impact factor of 4.09 points (see

abstract bellow) [3]. The data from the remaining (and future) patients which are imaged by contrast ultrasound endoscopy are currently processed and analysed for publication in a similar or better ISI journal.

Some of the results were included in a literature review article accepted for publication in an ISI journal 2.775 impact factor [4].

PLoS ONE manuscript title: Confocal Laser Endomicroscopy for the Morphometric Evaluation of

Microvessels in Human Colorectal Cancer Using Targeted Anti-CD31 Antibodies Abstract:

Introduction: Numerous anti-angiogenic agents are currently developed to limit tumor growth and metastasis. While these drugs offer hope for cancer patients, their transient effect on tumor vasculature is

difficult to assess in clinical settings. Confocal laser endomicroscopy (CLE) is a novel endoscopic imaging technology that enables histological examination of the gastrointestinal mucosa. The aim of the present

study was to evaluate the feasibility of using CLE to image the vascular network in fresh biopsies of human colorectal tissue. For this purpose we have imaged normal and malignant biopsy tissue samples and compared the vascular network parameters obtained with CLE with established histopathology techniques.

Materials & Methods: Fresh non-fixed biopsy samples of both normal and malignant colorectal mucosa

were stained with fluorescently labeled anti-CD31 antibodies and imaged by CLE using a dedicated endomicroscopy system. Corresponding biopsy samples underwent immunohistochemical staining for CD31, assessing the microvessel density (MVD) and vascular areas for comparison with CLE data, which

were measured offline using specific software.

Results: The vessels were imaged by CLE in both normal and tumor samples. The average diameter of normal vessels was 8.5±0.9 μm whereas in tumor samples it was 13.5±0.7 μm (p=0.0049). Vascular density was 188.7±24.9 vessels/mm2 in the normal tissue vs. 242.4±16.1 vessels/mm2 in the colorectal cancer

samples (p=0.1201). In the immunohistochemistry samples, the MVD was 211.2±42.9/mm2 and 351.3±39.6/mm2 for normal and malignant mucosa, respectively. The vascular area was 2.9±0.5% of total

tissue area for the normal mucosa and 8.5±2.1% for primary colorectal cancer tissue. Conclusion: Selective imaging of blood vessels with CLE is feasible in normal and tumor colorectal tissue

by using fluorescently labeled antibodies targeted against an endothelial marker. The method could be translated into the clinical setting for monitoring of anti-angiogenic therapy.

The patho-imuno-histological analysis was performed for every patient in parallel with other imaging techniques. All patient biopsies were analysed for diagnostic purposes. The samples were fixed in neutral

buffered formalin and were further processed for paraffin inclusion. Aside from ensuring the pathological diagnostic, slides from the paraffin blocks underwent an antigen retrieval procedure and were

immunostained for CD31 and CD105. A species specific polymeric HRP secondary antibody was used to amplify the reaction, and the signal was finally visualised using a specific precipitating HRP substrate (DAB, 3,3'-Diaminobenzidine). After image acquisition under a light microscope, the microvessel density

(MVD) was assessed based on direct counting of areas with the highest vascular populations, according to the classically hotspot method. Furthermore total vascular areas were also calculated on the captured images

using a stylus design tablet in order to obtain a fine delimitation of the signal and vascular lumens. After area-normalisation, both parameters were compared with CLE and EUS measurements. The results are included in the individual studies for each imaging method.

The patho-imuno-histological analysis was performed using new methods adapted for fresh biopsies.

Surgical specimens (or biopsy for one of the patients) were fixed in 4% neutral buffered formalin and processed for routine paraffin embedding and sectioning as 4 µm-thick sections. From each block, a slide was stained with hematoxylin- eosin for clinical diagnosis, and the next serial sections were utilized for

immunohistochemistry to visualize the CD31 antigen. Briefly, after microwaving in citrate buffer (pH=6), as an antigen retrieval method, the sections were cooled to room temperature and incubated for 30 minutes in

1% hydrogen peroxide in order to quench endogenous peroxidase. In order to block the unspecific antigenic sites, the specimens were blocked for 30 minutes in 2% skim milk (Bio-rad, München, Germany), and the first antibody was incubated over-night at 4°C (anti-CD31, mouse anti-human, IgG1, clone JC70A, Dako,

Glostrup, Denmark, diluted as 1:100 in PBS with 1% BSA). The next day, the slides were washed, the fluorescence signal amplified using a peroxidase-conjugated polymeric system (EnVision Dako, Redox,

Bucharest, Romania), and then detected with 3,3′-diaminobenzidine – DAB (Dako). All washing steps were done in 1x PBS buffer. The final slides were evaluated using a Nikon Eclipse 55i microscope (Nikon, Tokyo, Japan) coupled to a 5 Mp color CCD camera (Nikon) and an image-analysis station (Image ProPlus

AMS software, Media Cybernetics, Bethesda, Maryland, USA). Four images from the highest vascular density areas were captured under the same illumination conditions and with a 40x objective for each case,

and archived as uncompressed TIFF images. A stylus-design pen was utilized to draw the outlines of the

vessels (as visualized by the DAB staining) in the Image ProPlus software package. All these regions of interest (ROIs) were pseudo-colored in black and measured automatically as total vascular areas and total

vascular numbers per 40x area, after which the results were normalized for 1 mm2 areas. All final measurements utilized the mean values for all the images captured from each case and histopathological

profile. We continued the analysis of the biopsies using new and improved techniques for detecting tumor

vasculature. We have identified new markers which are more specific to tumor endothelium than the traditional markers. We use CD105 to identify the vessels which are new and specific to tumors vs. the host

vessels. Experimental Protocol

Subjects

Tissue specimens from ten patients between the ages of 45–70 years old, with histologically proven rectal

cancer, undergoing surgical resection at the Department of Surgery from Emergency County Hospital of Craiova, were collected during colonoscopy. The patient population contained stage II-III (according to AJCC staging system) rectal adenocarcinomas without metastatic spread and it is part of a cohort described

before. Fresh tissues from these patients were immediately processed for both CLE and immunohistochemistry assessment. The study was conducted according to the Code of Ethics of the World

Medical Association (Declaration of Helsinki, 1964, as revised in 2004) and approved by the local Ethics Committee. All the patients included read and accepted the written informed consent prior to study entry.

Confocal laser endomicroscopy

The biopsy samples obtained from standard colonoscopy (CFQ160ZL, Olympus,Tokyo, Japan) were processed following a standardized protocol. During the endoscopic procedure, for every patient, several

biopsies were taken from tumor, avoiding the ulcerated areas as much as possible, as well as from macroscopically normal surrounding tissue samples. The biopsies were immersed immediately in 10% neutral buffered formalin for histopathological analysis, as well as in saline solution for the ex-vivo

immunohistochemical processing. Samples from saline solution were thoroughly washed and incubated for one hour in the dark, at 37°C, with Alexa-Fluor 488-labeled anti-CD31 (PECAM) antibody (mouse anti-

human IgG1, Exbio, Prague, Czech Republic) or respectively FITC-labeled anti-CD105/Endoglin antibody (mouse anti-human IgG2a, Exbio), diluted as 1:15 and 1:5 in saline with 1% bovine serum albumin (BSA, Sigma-Aldrich, Munich, Germany). Afterwards, the excess antibodies were washed away in saline and the

samples were immediately visualized in confocal laser endomicroscopy imaging to assess the microvascularization ex vivo up to a maximum depth of 250 µm. Confocal laser endomicroscopy images

were acquired using Pentax EC-3870 CIFK, Tokyo, Japan, a dedicated endomicroscopy system with an excitation wavelength of 488 nm and with a maximum laser power output of ≤1 mW at the surface of the tissue.

To assess both endothelial markers more accurately, we used the color overlay function in the ImageJ image processing software (National Institutes of Health, USA). This software was used to obtain the Z projection

of the confocal serial images from each biopsy sample previously combined into stacks. Thus, on the acquired images, Z-stacks and 3D reconstruction was performed, then the vascular density and the vessel diameters were measured within two 50x475 μm rectangular regions of interest centered in the middle of

each image in the horizontal and vertical direction.

The results of the study were published by our group in the World Journal of Gastrointestinal Oncology in 2015: “Tumor neoangiogenesis detection by confocal laser endomicroscopy and anti-CD105 antibody: Pilot study” [12].

Abstract

Aim: To evaluate neoangiogenesis in patients with colon cancer by two fluorescently labeled antibodies on fresh biopsy samples imaged with confocal laser endomicroscopy (CLE).

Methods: CLE is an imaging technique for gastrointestinal endoscopy providing in vivo microscopy at

subcellular resolution. An important question in validating tumor angiogenesis is what proportion of the tumor vascular network is represented by pre-existing parent tissue vessels and newly formed vessels. CD105 (endoglin) represents a proliferation-associated endothelial cell adhesion molecule. In contrast to

pan-endothelial markers, such as CD31, CD105 is preferentially expressed in activated endothelial cells that participate in neovascularization. Thus, we evaluated CD105 and CD31 expression from samples of ten

patients with primary rectal adenocarcinoma, using a dedicated endomicroscopy system. A imaging software was used to obtain the Z projection of the confocal serial images from each biopsy sample previously combined into stacks. Vascular density and vessel diameters were measured within two 50 μm x 475 μm

rectangular regions of interest centered in the middle of each image in the horizontal and vertical direction. The results were averaged over all the patients and were expressed as the mean ± SE.

Results: The use of an anti-CD105 antibody was found to be suitable for the detection of blood vessels in colon cancer. Whereas anti-CD31 antibodies stained blood vessels in both normal and pathologic colon

equally, CD105 expression was observed primarily in malignant lesions, with little or no expression in the vessels of the normal mucosa (244.21 ± 130.7 vessels/mm3 in only four patients). The average diameter of

anti-CD105 stained vessels was 10.97 ± 0.6 μm in tumor tissue, and the vessel density was 2787.40 ± 134.8 vessels/mm3. When using the anti-CD31 antibody, the average diameter of vessels in the normal colon tissue was 7.67 ± 0.5 μm and the vessel density was 3191.60 ± 387.8 vessels/mm3, while in the tumors we

obtained an average diameter of 10.88 ± 0.8 μm and a vessel density of 4707.30 ± 448.85 vessels/mm3. Thus, there were more vessels stained with CD31 than CD105 (P < 0.05). The average vessel diameter was

similar for both CD31 and CD105 staining. A qualitative comparison between CLE vs immunohistochemistry lead to similar results.

Conclusion: Specific imaging and quantification of tumor microvessels are feasible in human rectal cancer using CLE examination and CD105 immunostaining of fresh tissue samples.

Another study with the aim of evaluating tumor vascularity in CRC by CE-EUS with time intensity curve (TIC) analysis backed by assessment of molecular markers of angiogenesis. The results of the study were

presented at the Digestive Disease Week conference in Washington, DC and submitted for publication in the Gastrointestinal Endoscopy journal which is indexed ISI with an impact factor of 5.37. [15]

Study protocol: Inclusion criteria: Patients who were diagnosed with primary colon and rectal tumors, age 18-90 years old,

men or women, signed informed consent for EUS with contrast- enhancement and tissue sampling. Exclusion criteria: prior treatment with chemo-radiotherapy, failure to provide informed consent and severe

coagulopathy. The EUS local staging and low mechanical index CE-EUS (MI 0.2) was performed using a radial EUS scope (EG-3670URK, Pentax, Hamburg, Germany) coupled with a Hitachi Preirus US system (Hitachi Medical Corp, Tokyo, Japan). For contrast, we used a bolus injection 4.8 ml SonoVue® (Bracco.

Italy). Sixty seconds video sequences were recorded on the embedded HDD of the ultrasound system for later analysis.

A dedicated software was used for offline TIC analysis of the recorded video sequences (VueBox™,Bracco) TIC parameters are: PE - peak enhancement, RT - rise time, mTT - mean transit time, TTP - time to peak,

AUC - area under the curve, a.u. arbitrary units.

A sample of the results is shown Figure 1 with PE = 3.58 a.u. and AUC = 34.39 a.u.

Fig. 1. TIC measurements.

The conclusions of the study were that the low mechanical index CE-EUS examination and TIC analysis enable the evaluation of tumour angiogenesis in CRC. Of all TIC parameters, PE and AUC may predict

prognosis for CRC patients. Further studies are necessary for establishing the role of CE-EUS in the evaluation of CRC as well as for identifying an optimal combination of functional and molecular markers of prognostic significance.

Activity 3.1. Development of the mathematical model for the normal and treated CRC MVN (colorectal cancer microvascular network).

Progress 2011: Theoretical modelling methods

1. Aim of the study: To develop computer simulations of blood flow and structural adaptation of the MVN in CRC tumors.

2. Experimental Design. Specific steps of this

aim are represented schematically in the flow diagram (Figure 1).

The network architecture data (connection matrix of vessel segments, diameter and lengths for each

segment) are determined from data obtained in Specific Aim 1. Inflows and outflows will be based on typical values for vessels in this

diameter range. Absolute values may not be accurately obtained by this method, but relative changes in flow following anti-angiogenic treatment will

dictate the adaptive response. To predict the distribution of flows in the normal network:

The flow conductance of each segment (J = Q/p, where Q is the flow rate and p is pressure drop) is

calculated using Poiseuille's law, based on a typical value of blood viscosity for vessels in this diameter range.

From the condition that the net flow entering each bifurcation is zero, the following condition is satisfied

at any node at which three segments meet:

Q1 + Q2 + Q3 = 0 = J1 (p1- p0) + J2 (p2 – p0) + J3 (p3 - p0)

where p0 is the pressure at the node, p1, p2, and p3 are the pressures at adjacent nodes; Q1,Q2,and Q3 are the corresponding segment flows (negative for outflows from the node) and J1, J2, and J3 are the corresponding conductances.

These relations, when applied to each node in the network, yield a system of linear equations for the pressures at the bifurcations. This system of equations is solved to obtain the pressure at each bifurcation

and the flow in each segment. To compute new diameters for the normal network to simulate ischemic revascularization:

The distribution of flow rates and pressures in each segment is calculated as described above.

The distribution of wall shear stress in the network is calculated according to the formula:

i = DiPi/(4Li)

where Di and Li are the diameter and length of segment I and Pi is the pressure drop across segment i.

Estimate stimuli for adaptation using previously developed expression for the sum of terms representing

different adaptive stimuli (Stot)1:

Stot = log w - log e(P) + km log[Qref/QHD + 1] + kc [Sc/(Sc + S0)] - ks Eqn. #1

The mathematical expression of the sum of all adaptive stimuli (Stot) is given in equation #1. w is

wall shear stress; e is expected wall shear stress; P, pressure; km metabolic stimulus constant; Qref, reference

blood flow; Q, blood flow; HD, discharge hematocrit; kc, conducted stimulus constant; Sc, sum of conducted stimuli; S0, reference sum; ks, shrinking constant.

For each vessel segment in the normal network, the change in its diameter (D) for a time step t is assumed to be proportional to Stot and to the vessel diameter (D) as:

D = Stot · D · t Eqn. #2

The changes in vessel diameter observed following treatment will be simulated by imposing a step

increase of wall shear stress and transmural pressure to simulate the observed changes in vessel diameter. At the same time, we will simulate decreased values of the metabolic and conducted stimuli and increased shrinking tendency to correspond to decreased perfusion in that area.

To compare with experimentally observed diameters of the non-treated and treated networks.

Root mean square diameter deviation (ED) between predicted diameters (Dp) in normal and treated network diameters (Dm) will be used to assess the differences between the observed and predicted

diameters.

To adapt computer model:

Depending on results we will modify the assumptions and parameters of the adaptation model. At this

point in the modeling, we will address the hypothesis of whether or not the observed changes can be satisfactorily explained by the hypothesized model. The adaptation will consist on adapting the parameters

(km, ks, kc or S0) values and/or adding effects of other stimuli that were not considered in the rat mesenteric microcirculation model.

c. Algorithm for the three-dimensional visualization of the vascular network. To illustrate the

simulation results, we will generate three dimensional computer visualizations of the network. The grayscale pictures of the contrast filled tumor network will be imported into the Pro/Engineer software package (Parametric Technology; Needham, MA). All bifurcation points and a variable number of points at equal

distances along each vessel length will be manually identified and recorded from photographs to mark their two-dimensional coordinates. The bifurcation points will then be joined with spline curves representing the

vessel centerlines. Each vessel segment is modeled as a blend surface with a circular cross-section whose diameter varies smoothly between the points at which diameter is specified.

d. Numerical modeling of the vascular network. To present a detailed distribution of vascular flow and pressure on overall tumor network, a finite elements model and simulation will be performed using the

three-dimensional geometry developed at step “c” and as inputs the previous inflows and outflows computed at section “b”. The model will be used to evaluate the interstitial pressure in the tumor and the relationship with the anti-angiogenic treatment.

The first and second parts of the mathematical modeling are underway as described below. The results were

presented at the Annual Meeting of the Biomedical Engineering Society and published in the abstract form in the Annals of Biomedical Engineering Journal. The extended version of the results will be submitted to the Annals of Biomedical Engineering Journal or similar.

Algorithm for the three-dimensional visualization of the vascular network.

The 3D model was developed from B&W serial sections using manual tracing of bifurcation points and Matlab and SolidWorks software packages as described before (Gruionu et al. Am. J. Physiol., 2005) (Figure 1).

Numerical modeling of the vascular network. To present a detailed distribution of vascular flow and pressure on overall tumor network, a finite elements model and simulation was developed using the three-dimensional geometry and as inputs the previous inflows and outflows. The model was used to evaluate the

interstitial pressure in the CRC tumor and the relationship with the anti-angiogenic treatment. Diffusion simulation was performed using ANSYS CFX module on a porous domain that involves one fluid and a

solid. A full porous model formulation was used with a porosity that modifies all terms in the governing equations as well as the loss term (Figure 2). This method supports models for the interaction between the fluid and solid parts of the domain. The results were presented at the 2012 Annual Biomedical Engineering

Society [4].

Normal Tumor

Figure 1. 3D network model

The first and second parts of the mathematical modeling are described below. The results were presented at the Annual Meeting of the Biomedical Engineering Society and published in the abstract form in the Annals

of Biomedical Engineering Journal. The extended version of the results will be submitted to the Annals of Biomedical Engineering Journal or similar.

Algorithm for the three-dimensional visualization of the vascular network.

The 3D model was developed from B&W serial sections using manual tracing of bifurcation points and

Matlab and SolidWorks software packages as described before (Gruionu et al. Am. J. Physiol., 2005) (Fig. 3).

Numerical modeling of the vascular network. To present a detailed distribution of vascular flow and

pressure on overall tumor network, a finite elements model and simulation was developed using the three-dimensional geometry and as inputs the previous inflows and outflows. The model was used to evaluate the

interstitial pressure in the CRC tumor and the relationship with the anti-angiogenic treatment. Diffusion simulation was performed using ANSYS CFX module on a porous domain that involves one fluid and a solid. A full porous model formulation was used with a porosity that modifies all terms in the governing

equations as well as the loss term (Figure 2). This method supports models for the interaction between the fluid and solid parts of the domain. The results were presented at the 2012 Annual Biomedical Engineering

Society. [4]

Blood velocity

Normal Tumor

Figure 2. Blood velocity and diffusion model

Normal Tumor

Figure 3. 3D network model

A more extensive mathematical model of a normal and tumor vascular network was presented at the Experimental Biology [8] and Biomedical Engineering Society Annual meetings [9] and prepared for

publication in Vascular Research journal (see abstracts below).

Experimental Biology Annual Meeting: “Flow-Induced Structural Adaptation of Tumor Vasculature by Selective Micro-Laser Ablation”. [8]

The effects of anti-angiogenesis therapy on tumor vasculature are transient, and the exact mechanisms of vessel remodeling are not known. Here we developed experimental and theoretical models of tumor vascular

remodeling for customizing the dose and timing of vessel-targeted drugs. We used a multiphoton laser to interrupt vessel segments downstream from a bifurcation and observed remodeling in the adjacent branches in normal skin vasculature and AK4.4 pancreatic tumors implanted in the mouse dorsal skin fold chamber.

We assessed blood flow and cellular dynamics using fluorescence stereomicroscopy and optical frequency-domain imaging. The theoretical simulation of the vascular network dynamics is based on a previous

network model developed by Gruionu et al (Am J Physiol, 2005). A finite element model was used to simulate oxygen and nutrient delivery in the surrounding tissue. The laser microsurgery caused significant remodeling in both arterial (mean: 151%, max: 229%) and venous (mean: 153%, max: 581%) sides of the

circulation. The predictions of the model showed good correlation with the observed changes in the dorsal skinfold chamber. The models will help us define the contribution of local stimuli to remodeling of tumor

vascular beds and generate predictions for altering tumor blood flow and development of future therapies.

Biomedical Engineering Society Annual Meeting: “Selective Vascular Blockage by Multiphoton Laser Ablation Causes Flow-Induced Remodeling in Tumor Blood Vessels”.[9]

Introduction Normal vasculature adapts in response to changes in flow in normal and pathological conditions. Numerous

studies show that tumor vasculature undergoes similar structural changes in response to anti-angiogenesis treatment, improving flow in tumors, but little is known about the mechanisms of flow-induced vascular

remodeling in tumors. To address this issue, we have created a novel experimental model of flow induced remodeling by altering flow in selected tumor feeding vessels.

Materials and Methods. We used a custom built multiphoton laser to selectively ablate small arterial and venous vessel segments (20-100µm) through the glass window of the dorsal skin fold chamber in a novel

model of RAG1 double transgenic mice which express GFP in Tie-2-positive cells and Ds red in -SMA-positive cells. An orthotropic tumor was induced by implanting a 30µl construct consisting of Mu89 human

melanoma cells embedded in a fibrin gel in the center of the dorsal chamber. We assessed diameter, length,

Blood

velocity

Normal Tumor

Figure 2. Blood velocity and diffusion

model

and blood flow changes before and after ablation using a new adaptation of Optical Frequency-Domain Imaging (OFDI) that provides blood flow measurements. The simulation of blood flow was based on the

observed structure of the arterial network and a previous structural adaptation model developed by Gruionu et al. The model simulates the adaptation of vascular diameters resulting from the combined action of

hemodynamic (wall shear stress and intravascular pressure) and metabolic signals (Fig. 4). In addition to the flow simulation, a finite element model was developed using the ANSYS and SolidWorks software packages to develop a 3D visualization of vascular elements and simulation of blood flow.

Figure 4. Experiental and theoretical model of the blood flow in a microcirculatory network.

Results and Discussion. Arteries and veins were interrupted downstream from a bifurcation and the

resulting vascular remodeling was observed in the adjacent branches and parent vessels. The laser microsurgery caused significant remodeling in both arterial and venous sides of the circulation with a more pronounced remodeling on the venous side. Morphometric parameters were imported into the mathematical

model and the entire vascular network was reconstructed. The predictions of the model showed good correlation with the observed changes in the dorsal skinfold chamber.

Conclusions. The present experimental and theoretical models show that flow induced remodeling plays a significant role in tumor vascular beds; this process may be a viable target for development of future

therapies.

The first and second parts of the mathematical modeling are underway as described below. We have created a mathematical model of incomplete networks as tumor vascular networks from biopsies are incomplete (Figure 1).

OFDI RBC Velocity

Pre Ablation Day 0 Post Ablation Day 6 Post Ablation

Pre Ablation Day 0 Post Ablation Day 2 Post Ablation

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THEORETICAL SIMULATION OF ENGINEERED VASCULAR NETWORKS

Initial Flow Direction Simulated Preablation Flow Simulated Postblation Flow

(red - changed flow direction)

For incomplete networks we are using a novel mathematical modeling procedure which uses an annealing function method, which helps us simulate the blood flow when the boundary conditions are not know. Briefly, for a given distribution of flow directions the annealing function finds the optimum pressure

distribution to achieve the minimum number of segments with changed direction, ideally zero. Figure 2 shows an incomplete vascular network and the results of the annealing function simulation where the

number of segments with reversed flow is 3-5. The results of this study were submitted to publication in the to a ISI journal. A similar approach will be used for the vascular networks of the colorectal tumors obtained from the experimental part of the grant.

Figure 2. Vascular network representation and annealing method simulation.

We are currently working on a mathematical model of incomplete networks as tumor vascular networks

from biopsies are incomplete (Figure 2). For incomplete networks we are using a novel mathematical modeling procedure which uses an annealing function method, which helps us simulate the blood flow when

the boundary conditions are not know. We are using a model of a normal microvascular network from the dorsal skinfold chamber to develop the mathematical model of the simulated annealing method (SAM). Briefly, SAM finds a global minimum for an error function, E (in this case the number of segments with

reversed flow) with many local minima. To implement this method, we have chosen an initial distribution of intravascular pressures in each vessel segment of the network. We match the initial direction of the flow

according to the experimental observations. The boundary segment pressure is varied randomly:

PA=120- ∆PA(1-rand); PV=2+ ∆PV*rand

Where ∆PA= ∆PV= 50mmHg;

The “wrong” solution is accepted with a probability 0.0015*exp(-(E(n)-E(n-1))/T); where n= the annealing method iteration number and T= 10,000 is an arbitrary parameter called the temperature of the cooling

function. The annealing method algorithm was run successively 5,000 times. The result of the SAM application is a distribution of intravascular pressure that corresponds to the observed flow direction. A similar function is implemented separately for the venous circulation (Figure 2).

Normal Tumor

Figure 1. 3D network model

a b c

Figure 2. An incomplete arterial and venous vascular network (a), the mathematical simulation of the

network (b) and the annealing function simulation including the blood flow values (c).

The results of this study was submitted to the ISI ranked journal Microcirculation Journal and is currently under review. A similar approach will be used for the vascular networks of the colorectal tumors obtained from the experimental part of the grant.

Activity 4.1 Forecasting the angiogenesis before and after the angiogenesis treatment The mathematical approach for forecasting the malignant potential of a vascular network is using the

morphometric characteristics of the tumour vasculature to generate several parameters such as the fractal dimension, which could enhance the diagnostic of tumour vs. normal tissues based on the vasculature.

Briefly, the images generated during eCLE examinations are stored for offline processing. We only use images without procedural artifacts such as bowel movement or slippage of particulate matter (bubbles, fecal debris). We process the images using a computer aided diagnosis (CAD) module of a proprietary

medical imaging system (NAVICAD) developed with the Matlab programming software (Matlab, The MathWorks Inc. USA). The CAD application includes image processing functions, a module for fractal

analysis, grey-level co-occurrence matrix (GLCM) computation module, an anatomical feature identification module based on Marching Squares and linear interpolation methods. A two-layer neural network integrates the image analysis parameters (fractal dimension, lacunarity, contrast correlation, energy, homogeneity, and

feature number) derived from the imaging processing step and automatically generates a diagnosis. The application diagram is presented in Figure 3.

Figure 3. Diagram of the diagnosis algorithm.

An example of how the algorithm works is presented in Figure 4. Several parameters of the morphometric

analysis are presented: Fractal dimension, Lacunarity, Contrast, Correlation; Energy; Homogeneity; Features number.

Figure 4. a. Normal colon mucosa with round shaped crypts (blue circle), situated at relatively equal

distance one from another, dark goblet cells (yellow circles), and narrow and regular blood vessels surrounding the crypts (red arrows). b. Normal colon mucosa image processed: Fractal

dimension=1.732; Lacunarity=0.13; Contrast=0.26; Correlation=0.97; Energy=0.24; Homogeneity=0.89; Features No=14.

The complete set of data from the study was published in PLoS One journal in 2016. [14]

Abstract

Introduction

Confocal laser endomicroscopy (CLE) is becoming a popular method for optical biopsy of digestive mucosa for both diagnostic and therapeutic procedures. Computer aided diagnosis of CLE images, using image processing and fractal analysis can be used to quantify the histological structures in the CLE generated

images. The aim of this study is to develop an automatic diagnosis algorithm of colorectal cancer (CRC), based on fractal analysis and neural network modeling of the CLE-generated colon mucosa images.

Materials and Methods

We retrospectively analyzed a series of 1035 artifact-free endomicroscopy images, obtained during CLE

examinations from normal mucosa (356 images) and tumor regions (679 images). The images were processed using a computer aided diagnosis (CAD) medical imaging system in order to obtain an automatic

diagnosis. The CAD application includes image reading and processing functions, a module for fractal analysis, grey-level co-occurrence matrix (GLCM) computation module, and a feature identification module based on the Marching Squares and linear interpolation methods. A two-layer neural network was trained to

automatically interpret the imaging data and diagnose the pathological samples based on the fractal dimension and the characteristic features of the biological tissues.

Results

Normal colon mucosa is characterized by regular polyhedral crypt structures whereas malignant colon mucosa is characterized by irregular and interrupted crypts, which can be diagnosed by CAD. For this

purpose, seven geometric parameters were defined for each image: fractal dimension, lacunarity, contrast correlation, energy, homogeneity, and feature number. Of the seven parameters only contrast, homogeneity

and feature number were significantly different between normal and cancer samples. Next, a two-layer feed forward neural network was used to train and automatically diagnose the malignant samples, based on the seven parameters tested. The neural network operations were cross-entropy with the results: training: 0.53,

validation: 1.17, testing: 1.17, and percent error, resulting: training: 16.14, validation: 17.42, testing: 15.48. The diagnosis accuracy error was 15.5%.

Conclusions

Computed aided diagnosis via fractal analysis of glandular structures can complement the traditional

histological and minimally invasive imaging methods. A larger dataset from colorectal and other pathologies should be used to further validate the diagnostic power of the method.

The last article from this grant is “Assessing tumour angiogenesis in colorectal cancer by quantitative contrast-enhanced endoscopic ultrasound and molecular and immunohistochemical analysis”. We have

revised and resubmitted to Gastrointestinal Endoscopy according to reviewer’s comments.

Abstract: Background and study aims: Data on contrast-enhanced endoscopic ultrasound (CE-EUS) for colorectal cancer (CRC) diagnosis is scarce. Therefore, we aimed to assess the vascular perfusion pattern in CRC by

quantitative CE-EUS and compare it to immunohistochemical and genetic markers of angiogenesis. Patients and methods: We performed a retrospective analysis of CE-EUS examinations of 42 CRC patients,

prior to any therapy. CE-EUS movies were processed using a dedicated software. Ten descriptive parameters were automatically generated from the time-intensity curve (TIC) analysis: peak enhancement (PE), rise time (RT), mean transit time (mTT), time to peak (TTP), wash-in area under the curve (WiAUC),

wash-in rate (WiR), wash-in perfusion index (WiPI), wash-out AUC (WoAUC) and wash-in and wash-out AUC (WiWoAUC). The expression levels of the vascular endothelial growth factor receptor 1 (VEGFR1)

and VEGFR2 genes were assessed from biopsy samples harvested during colonoscopy. Microvascular density and vascular area were calculated after CD31 and CD105 immunostaining.

Results: Forty-two CE-EUS video sequences were analysed. We found positive correlations between the parameters PE, WiAUC, WiR, WiPI, WoAUC, WiWoAUC and N staging (Spearman r 0.437, 0.336, 0.462,

0.437, 0.358, and 0.378, respectively, p<0.05), and also between RT and TTP and CD31 vascular area (r = 0.415, and 0.421 respectively, p<0.05). VEGFR1 and VEGFR2 expression did not correlate with any of the TIC parameters.

Conclusions: CE-EUS with TIC analysis enables minimally invasive assessment of CRC angiogenesis, and

may provide information regarding the lymph nodes invasion. However further studies are needed for defining its role in the evaluation of CRC patients.

Summary: This grant program was very successful with 15 published or soon to be published ISI rated

scientific articles and conference presentations, three times more that was originally predicted. We have made a lot of interesting discoveries about the cancer vascular biology, new mathematical models and new imaging and diagnosis methods which will be used in clinical practice. In the future we plan to continue this

research with more biological markers for better diagnostic and treatment of cancer.

Bibliography:

1. T. Cârţână, L. Gruionu, D. I. Gheonea, D. Pirici, G. Gruionu, A. Săftoiu. Feasibility study for the use

of confocal laser microscopy for the morphometric evaluation of microvessels in human colorectal biopsy samples with targeted anti-cd31 antibodies. United European Gastroenterology Week

(UEGW), 2011, oral presentation Copenhagen, Sweden.

2. Gabriel Gruionu, T. Cârţână, L. Gruionu, D. I. Gheonea, D. Pirici, A. Saftoiu Feasibility Study for the Use of Confocal Laser Endomicroscopy (CLE) for the Morphometric Evaluation of Microvessels

in Human Colorectal Biopsy Samples with Targeted Anti-CD31 Antibodies. Cajal International Symposium. Bucharest, Romania.

3. Cârţână T, Săftoiu A, Gruionu LG, Gheonea DI, Pirici D, Georgescu CV, Ciocâlteu A, Gruionu G. Confocal Laser Endomicroscopy for the Morphometric Evaluation of Microvessels in Human Colorectal Cancer Using Targeted Anti-CD31 Antibodies. PLoS One. 2012;7(12).

4. Lucian Gruionu, D. Pirici, D.I. Gheonea, T. Cârţână, A. Săftoiu, L. L. Munn, Gabriel Gruionu. Clinical and Theoretical Model for Monitoring the Effect of Anti-Angiogenic Tumor Therapy

Efficiency in Human Colorectal Biopsy. 2012 Annual Meeting of the Biomedical Engineering Society. Atlanta, GA, USA.

5. Adriana Ciocâlteu, Adrian Săftoiu, Tatiana Cârţână, Lucian Gheorghe Gruionu, Dan I. Gheonea,

Daniel Pirici, Claudia- Valentina Georgescu, Gabriel Gruionu. Evaluation of new morphometric parameters of neoangiogenesis in human colorectal cancer using confocal laser microscopy (CLE)

and targeted panendothelial markers. UEGW, Berlin, Germany, 2013. 6. Ciocâlteu A, Săftoiu A, Cârţână T, Gruionu LG, Pirici D, Georgescu CV, Gheonea DI, Gruionu G.

Evaluation of New Morphometric Parameters of Neoangiogenesis in Human Colorectal Cancer

Using Confocal Laser Endomicroscopy (CLE) and Targeted Panendothelial Markers PLoS One. 2014; 3(9), e91084.

7. T. Cartana , L. Brink, D. I. Gheonea, J. G. Karstensen, A. Ciocalteu, D. Pirici, C. V. Georgescu, M. L. Malmstrøm A. Saftoiu, P. Vilmann G. Gruionu. Quantitative assessment of tumour perfusion of colorectal cancer patients by using Contrast-enhanced endoscopic ultrasonography: a feasibility

study. United European Gastroenterology Week (UEGW), 2013, poster presentation Berlin, Germany.

8. Gabriel Gruionu, Lucian Gruionu, Lance L. Munn. Flow-Induced Structural Adaptation of Tumor Vasculature by Selective Micro-Laser Ablation. Experimental Biology, 2013, Boston, MA, USA.

9. Gabriel Gruionu, Lucian Gruionu, Lance L. Munn. Flow-Induced Remodeling of Normal and Tumor

Microvasculature. 2013 Annual Meeting of the Biomedical Engineering Society, Seattle, WA, USA. 10. Ciocâlteu A, Săftoiu A, Cârţână T, Cherciu I, Gruionu LG, Pirici D, Georgescu CV, Gheonea DI,

Gruionu G. Feasibility Study for the Evaluation of Morphopatological Pattern of Neoangiogenesis in Human Colorectal Cancer using Confocal Laser Endomicroscopy and Targeted Anti- CD105 Antibodies. UEGW 2014, Vienna, Austria.

11. Cârţână T, Brink L, Streba TC, Pirici D, Gheonea DI, Cherciu IF, Karstensen JG, Săftoiu A, Vilmann P, Gruionu G. Low Mechanical Index Contrast-Enhanced Endoscopic Ultrasound for

Quantitative Assessment of Tumour Perfusion in Colorectal Cancer Patients: Preliminary Study. DDW 2014, Chicago, USA.

12. Ciocâlteu A, Săftoiu A, Pirici D, Georgescu CV, Cârţână T, Gheonea DI, Gruionu LG, Cristea CG,

Gruionu G. Tumor neoangiogenesis detection by confocal laser endomicroscopy and anti-CD105 antibody: Pilot study. World J Gastrointest Oncol 2015; 7(11): 361-368.

13. Cârțână ET, Streata I, Nicoli E, Uscatu D, Ciocalteu AM, Cherciu IF, Gheonea DI, Georgescu CV, Ioana MI, Gruionu G, Saftoiu A. Evaluation of Tumour Angiogenesis in Colorectal Cancer Based on Quantitative Contrast-Enhanced Endoscopic Ultrasonography and Molecular Analysis. Digestive

Disease Week, Washington, DC. Gastrointest Endosc 2015;81:AB175.

14. Ştefănescu, D, Streba S, Cârţână ET, Săftoiu A, Gruionu G, Gruionu LG. Computer Aided Diagnosis

For Confocal Laser Endomicroscopy. PLoS One. 2016 May 4;11(5):e0154863. doi: 10.1371/journal.pone.0154863.

15. Cârţână ET, Gheonea DI, Cherciu IF, Bărbălan A, Streață I, Ioana M, Pirici D, Georgescu CV, Șurlin

V, Gruionu G, Săftoiu A. Assessing tumour angiogenesis in colorectal cancer by quantitative contrast-enhanced endoscopic ultrasound and molecular and immunohistochemical analysis.

Gastrointestinal Endoscopy (under review).

Project Director:

Conf. Dr. Gabriel Gruionu