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SCIENTIFIC REPORT

Molecular Imaging Evaluation of Tumor MicroEnvironment in Pancreatic AdenoCarcinoma - META

12.07.2017 – 30.12.2017: Phase I 31.12-2017 – 31.12.2018: Phase II

Phase I

A1.1 Creating a structured database and a study protocol

A1.2 Imaging assessment of angiogenesis in pancreatic cancer

A1.1 – Creating a structured database and work protocol

The premises of this stage consist in creating an electronic database which allows the

storage of patients’ data obtained subsequently to the assessment of pancreatic tumors. After

filling the informed consent and performing the medical procedures, the individual patient data

and the procedures results are stored. Similarly, the image results are organized in a digital format

for further processing.

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Figure 1: Microsoft Access database used for storing patient’s data and the imaging

methods used for diagnosing the pancreatic masses.

1. Aims Defining and organizing the patient’s inclusion criteria were correlated with highlighting the

specific objectives of the study which are relying on hybrid imaging methods used for the

assessment of pancreatic adenocarcinoma and on the quantification of angiogenesis through

molecular biology techniques, immunefluorescence and immunohistochemistry.

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2. Objectives Employing hybrid imaging methods for the assessment of pancreatic adenocarcinoma, for both

early diagnosis and a more precise cancer staging, but also for judging the opportunity of tumor

resection and for assessing a prognosis based on molecular biomarkers.

• Ex vivo endomicroscopy will be used for obtaining high quality images of the

pancreatic tissue and further correlation with the anatomopathology results.

• Ex vivo endomicroscopy examination of pancreatic tumors to determine the

expression levels of several markers: mezotelin, CD 31/CD105, VEGFR, TGF-

βR2, SMAD 4 in correlation with immunohistochemistry and quantitative PCR.

• Carrying out an endomicroscopy guided by EUS study in order to improve the

results, obtained after using acriflavine / fluorescein in vivo.

• The endomicroscopy technique will be employed in vivo at least in 5 cases, ahead

of the surgical resection, being followed by the ex vivo analysis in tandem with the

most relevant biomarkers.

Tumor angiogenesis will be assessed through different imaging techniques validated by

immunohistochemistry, immunofluorescence and molecular biology techniques.

• Validating the fluorescent markers (CD31/CD105, VEGFR1/2, TGF-βR2) used for

assessing the microvascular density or angiogenesis through ex. vivo confocal

laser endomicroscopy.

• Correlating the quantitative analysis of endomicroscopy parameters and the prog-

nosis markers identified through immunohistochemistry and immunefluorescence

tests on resection pieces.

This phase implied the establishment of the working protocol for diagnosing the patients which

will be involved in the study through endoscopic ultrasound (EUS) and confocal laser

endomicroscopy (CLE) techniques.

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3. Endoscopic ultrasound (EUS) examination In order to establish the diagnosis, EUS was performed in gray scale to reveal the pancreatic

mass and its precise localization, paying a special attention to the involvement of neighboring

organs. Also, the color Doppler and power Doppler settings were used for inspecting the tumor

blood vessels and the surrounding vessels in order to assess the resectability criteria and tumor

staging.

Contrast enhanced examination with low mechanical index (MI) implied intravenous injection

of a second generation contrast agent (Sonovue 2.4 ml) and registering the examination in a

digital format. Hence, it is possible to differentiate the pancreatic adenocarcinoma from a

neuroendocrine tumor or chronic pseudotumoral pancreatitis.

Figure 2. Pancreatic adenocarcinoma: a hypoenhanced mass

after injecting the contrast agent Sonovue 2.4 ml

EUS-guided fine needle aspiration (EUS-FNA) was performed in the newly identified mass to

confirm the diagnosis. The technique assumed the usage of a special needle designed for fine

needle aspiration (Boston Scientific or Olympus), which was used to collect tumor tissue which

was divided as it follows: first pass was placed on glass slides and sent for cytology examination,

second pass was sent for pathology exams, third pass was immersed in RNA stabilizer and stored

at -80 degrees for further tests during the next research stages. EUS examination allowed the

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staging of pancreatic lesions, defining also the resection criteria.

4. Confocal laser endomicroscopy examination Confocal laser endomicroscopy (CLE) study involved several patients who met the

resectability criteria. The pCLE system with miniprobes (Cellvizio, Mauna Kea, Technology, Paris,

Franța) carries a laser device which delivers an excitation wavelength of 488 nm that is focused

into a distinct imaging plane within the tissue acquiring optic tissue sections. Using a specific

miniprobe advanced through the scope with a 19 G needle for fine needle aspiration allowed the

real time differentiation between malignant tissue and normal tissue.

Up to date, several CLE studies described pancreatic cystic lesions but only a limited number

involved solid tumors specifically. Our study design involves an AQ Flex 19 Cellvizio miniprobe

(Mauna Kea Technology Paris, France) with a diameter of 0,85 mm, a lateral resolution of 3,5 μm

and an optic field of 325 μm. The miniprobe is preloaded in a puncture needle, passed through

the working channel of the endoscope (Pentax EG 3870 UTK, Hamburg, Europe or Olympus GF-

UCT180 Tokyo, Japan) which is attached to a compatible ultrasongraphy system. The probe is

advanced inside the tumor and the exam starts after injecting the contrast agent, fluorescein 10%

5 ml iv.

The second phase of using pCLE will imply the ex-vivo examination of biopsy pieces collected

after tumor resection. Several post-resection cases will be included in the study, with both normal

and tumor tissues being examined ex-vivo. Hence, after the surgical resection, the fresh biopsies

will be covered with acriflavine and examined by eCLE. With the help of dedicated imaging

software, computer systems could identify specific patterns which will allow the distinction

between normal versus tumor tissue.

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A1.2 Imaging assessment of angiogenesis in pancreatic cancer

A preliminary study was conducted based on the tissue collected from 12 patients with

pancreatic adenocarcinoma through EUS, respectively EUS-FNA. The normal and tumor tissue

specimens were sprayed with a standard concentration acriflavine solution. Afterwards, the

imaging assessment of the tissue was performed with an experimental endomicroscopy probe-

Cellvizio Mauna Kea Technology Paris, France.

The diagnosis was confirmed by pathology exam, which included also the evaluation of the

resection margins (Figure 3). The CLE images were scanned by a specialized soft for images

analyze (Image ProPlus AMS) which generated morphometric parameters helping the

differentiation of distinct tissues types: Area, Hole Area (HA), Perimeter, Roundness, Integrated

Optical Density (IOD), Fractal Dimension (FD), Ferret max (Fmax), Ferret mean (Fmean),

Heterogeneity and Clumpiness.

Subsequently to image analysis, specific differences between normal and tumor tissue were

revealed with a correspondence between endomicroscopy and histopathology exam. Hence, the

statistical data analysis was highly significant for most of the paramethers: Area, Roundness, IOD,

Ferret and Heterogeneity (p<0.001), Perimeter and Hole area (p<0.05) which could play an

important role in the eventual potential of real time assessment of tumor resection margins.

It was obvious from the analysis of acriflavine CLE images that the vessels are not visible in

pancreatic tissue samples. Furthermore, we also demonstrated in one of our previous studies that

fluoresceine CLE guided by EUS had a very low accuracy with inconsistent intra- and

interobserver values. Consequently, we designed a multicentric trial based on EUS contrast-

enhancement and elastography in order to further analyse the angiogenesis in pancreatic cancer.

CLE has been performed in selected cases in vivo, but also ex vivo (see below A2.3).

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Figure 3. Benign lesions with dark lobular structures, clearly demarcated, showing a regular

pattern representing the pancreatic acini (A) and conjunctive tissue randomly disposed.

Malignant lesions (B) characterized by disorganized structures with different sizes nuclei and the

presence of dark aggregates representing malign lesions.

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Phase II

A2.1 Creating a structured database and a study protocol

A2.2 Inclusion of patients with pancreatic cancer (collection of tissue

from patients – EUS-FNA + surgery)

A2.3 CLE examination ex vivo + in vivo of pancreatic tumor tissue

A2.4 Immunohistochemistry, immunofluorescence and molecular

biology assessment of pancreatic tissue

A2.1 Creating a structured database and a study protocol

A multicentric study protocol has been designed to analyse angiogenesis in patients with

pancreatic cancer (adenocarcinoma and neuroendocrine tumors) and chronic pseudotumoral

pancreatitis.

1. Background

Endoscopic ultrasound (EUS) is a technique with a major clinical impact in digestive diseases,

determining a change in the diagnosis and management of more than half of examined patients

[1]. Recent advances in EUS-FNA techniques, but also the development of real-time EUS

elastography and contrast-enhancement, allowed a better characterization of focal pancreatic

masses, with possible implications in the management of patients with negative EUS-FNA and a

strong suspicion of malignancy.

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1.a Elastography Elastography is a recent ultrasound method used for the reconstruction of tissue elasticity

distribution in real-time [2]. The method allows the calculation of the elasticity modulus,

consequently showing differences in tissue hardness patterns that are determined by diseases.

The main intended use is to differentiate between benign and malignant focal lesions based on

the significantly smaller strain of the latter [3]. Second generation elastography introduces strain

ratio (SR) and strain histogram (SH) as reproducible parametric measurements that retrieve

numerical values in real time, adding quantification possibilities to the technique [4]. Elastography

typically estimates the axial strain (along the direction of insonification / compression) by analyzing

ultrasonic signals obtained with standard ultrasonographic systems - the RF signals returned from

tissue structures before and after slight compression (about 1%) are compared [5]. Tissue

elastography can be easily performed with conventional probes, including the linear EUS probes

used for the examination of the pancreas and/or lymph nodes. The calculation of tissue elasticity

distribution is performed in real-time under freehand compression and the examination results are

represented as transparent overlay colour images overimposed on the conventional gray-scale

B-mode images [6]. Thus, this method allows the characterization of many tumors, because they

are stiffer than normal tissues. Ultrasound elastography was previously used for the diagnosis of

non-digestive as well as digestive tumors: breast lesions [7], prostate cancer [8], thyroid nodules

[9], rectal tumors [10]. Regarding the diagnosis of pancreatic focal masses, some authors could

not differentiate between malignancy and benign tumors or chronic pancreatitis [11], while others

have obtained good results, especially when using computer assisted means of evaluation like

hue histogram analysis [12] and artificial neural networks [13]. More recently, lymph node

involvement of several tumors has been succesfully determined using this method: esophagus

[14], oral squamous cell carcinoma [15], breast cancer [16].

Since elastography images and movies represent a qualitative type output that entails a

subjective interpretation by the examiner, human bias is always susceptible to interfere with the

results and diagnoses, due to color perception errors, moving artifacts, or possible selection bias

induced by the analysis of still images. More objective, computer-assisted semi-quantitative

means of interpreting the results were developed, but these have the disadvantage of being labor-

intensive and using third-party software that cannot be used in real time [17]. Second generation

elastography introduces strain ratio (SR) and strain histogram (SH) as two reproducible

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measurements that retrieve numerical values in real time, thus greatly reducing the human bias

without the need for third-party software [4]. SR calculates the relative strain between two regions

of interest (ROI) (normal and pathological). SH measures the strain values of elemental areas

inside a ROI and divides the measurement range into intervals; if the strain value of an element

falls into an interval, its initial area normalized by the initial total surface area is added to the

running total of that interval; the total values of each interval are used to produce a graph and an

average value. Both SR and SH have already been used in vivo for pancreatic masses or lymph

nodes, with promising results [18].

1.b Contrast-enhancement Ultrasound contrast agents in conjunction with contrast specific imaging techniques are

increasingly accepted in clinical use for diagnostic imaging [19]. The study of the pancreas is a

new and promising application of contrast-enhanced ultrasound (CE-US), including contrast-

enhanced endoscopic ultrasound (CE-EUS). The technique is not indicated to improve the

detection of pancreatic lesions, but to improve the delineation and differential diagnosis of

pancreatic lesions [20-23]. One of the fluoro-gas-containing contrast agents used in CE-US and

CE-EUS is Sonovue®, which consists of phospholipids-stabilized bubbles of sulfurhexafluoride

(SF6) [24]. Sonovue® is isotonic, stable and resistant to pressure, with a viscosity similar to blood.

It does not diffuse into the extravascular compartment remaining within the blood vessels until the

gas dissolves and is eliminated in the expired air (blood pool contrast agent) [25]. The safety

profile of SonoVue showed a very low incidence of side effects; it is not nephrotoxic and the

incidence of severe hypersensitivity is similar to other magnetic resonance imaging contrast

agents. Moreover, Sono-Vue is approved for clinical use in EU countries. The blood supply of the

pancreas is entirely arterial, making contrast-enhanced examinations feasible and readily

available. Based on the European Federation Societies of Ultrasound in Medicine and Biology

guidelines and recommendations, updated in 2008, two phases were defined for CE-US and CE-

EUS of the pancreas: an early/arterial phase (starting from 10 to 30 seconds) and a venous/late

phase (from 30 to 120 seconds) [19].

Distinguishing pancreatic adenocarcinoma from other pancreatic masses remains challenging

with current imaging techniques [22-27]. The specificity of the discrimination between benign and

malignant focal pancreatic lesions was found to be 93.3% using power Doppler contrast-enhanced

EUS (PD-CE-EUS) compared with 83.3% for conventional EUS [26]. The hypovascular aspect of

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lesions under PD-CE-EUS seemed highly sensitive and specific (higher than 90%) for

adenocarcinoma in several published studies [22-27]. During PD-CE-EUS examinations the

ultrasound frequency returned to the transducer is the same with that transmitted, but the method

is associated with artifacts resulting from turbulent flow (flash and overpainting) [28]. At CE-EUS,

ductal adenocarcinoma is typically hypoenhanced compared to the adjacent pancreatic tissue in

all phases [19]. Furthermore, the lesion size and margins are better visualized, as well as the

relationship with peripancreatic arteries and veins. Focal lesions in chronic pancreatitis are

reported to have similar or hyper enhancement features as compared to the normal pancreatic

parenchyma [19].

Dedicated contrast-enhanced harmonic EUS techniques (based on a low mechanical index)

are recently available in new EUS systems. The harmonic frequencies returned during CEH-EUS

are different from those transmitted by the transducer and are the result of non-linear oscillations

of the microbubbles [24]. The image obtained is an addition of the signal created by the distortion

of the microbubbles and the tissue-derived signal. This can be optimized by using low MI, which

allows minimum bubble destruction and complete “subtraction” of the tissue derived signal,

obtaining a high resolution continuous real-time assessment of the microvascularization during

the contrast uptake period (real-time perfusion imaging) [29-31]. CEH-EUS allows a more precise

location of vascular structures within the parenchyma and focal abnormalities, with better

delineation of pancreatic lesions than EUS, especially in the cases where air or fat causes artifacts

and insufficient visualization of the pancreatic parenchyma. An initial pilot study described an

experimental technique of CEH-EUS based on a linear prototype EUS scope, a low mechanical

index (0.08 - 0.25) and a 2nd generation contrast agent (Sono-Vue), which allowed the

visualization of early arterial phase and late parenchymal phase enhancement of the pancreas

[32]. Another pilot study demonstrated both real-time continuous images of finely branching

vessels of the pancreas and intermittent homogenous parenchymal perfusion images, by using a

radial prototype EUS scope, a low mechanical index (0.4) and a 2nd generation contrast agent

(Sono-Vue) [33]. Several other research groups already reported the feasibility of CEH-EUS with

low mechanical index [34-36]. The sensitivity, specificity and accuracy for diagnosing pancreatic

adenocarcinoma were 88%, 89%, and 88.5% in one study [34] and 80%, 91.7%, and 86% in the

other study [33]. However, the data is still limited and a prospective, multicentric blinded study

would certainly be necessary.

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The study protocol is based on a multi-center semi-quantitative approach of EUS elastography

data in combination with contrast-enhanced EUS, consisting of measuring SR and SH for focal

pancreatic masses and lymph nodes, as well as several parameters of CE-EUS based on time-

intensity-curve (TIC) analysis. A number of parameters must be taken into consideration, as the

ROIs are still manually selected by the user. The aim of the study is to establish an EUS based

diagnostic algorithm in patients with pancreatic masses and lymph nodes, with negative or

inconclusive cytopathology after EUS-FNA, based on previously published results and cut-offs of

elastography and contrast-enhancement. The proposed algorithm of sequential use of real-time

elastography, followed by contrast-enhanced EUS could be a good clinical tool to help select the

patients with possible pancreatic adenocarcinoma or malignant lymph nodes, in the setting of

patients with negative EUS-FNA results.

2. Aims of the study The aim of the study was to assess quantitative elastography and contrast-enhancement

parameters during EUS examinations of focal pancreatic masses and lymph nodes, to standardize

an algorithm for their use and to consequently differentiate benign vs malignant pancreatic

masses and evaluate lymph node involvement in a prospective multicenter design.

3. Patients and methods The study design is prospective, blinded and multi-center, comparing endoscopic ultrasound

elastography (EG-EUS) and contrast-enhnecement (CE-EUS) results for the characterization of

focal pancreatic masses and lymph nodes by using parametric measurements, in comparison with

the gold standard represented by pathology.

The study will be performed with the approval of the institutional board (ethical committee)

review of each center. The complete study protocol and particpating centers will be uploaded on

ClinicalTrials.gov, the registry of federally and privately supported clinical trials conducted in the

United States and around the world.

Inclusion criteria • Patients diagnosed with solid pancreatic tumor masses, with cytological confirmation

• Patients with or without suspected lymph node involvement are eligible

• Age 18 to 90 years old, men or women

• Signed informed consent for EG-EUS, CE-EUS and FNA biopsy

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Exclusion criteria • Prior surgical treatment with curative intent or chemo-radiotherapy

• Patients diagnosed with mucin producing tumors, pancreatic cystic tumors, etc.

4. Data collection • Personal data (name, surname, age, admission date, SSN, diagnosis at admission)

5. Imaging tests • All patients with a suspicion of pancreatic masses or lymph nodes should undergo EUS,

with sequential EG-EUS and CE-EUS

• EUS with EUS-guided FNA and elastography o Protocol of EUS with EUS-FNA should include linear EUS instruments with complete

examinations of the pancreas.

o Tumor characteristics (echogenicity, echostructure, size) will be described as well as

presence / absence of power Doppler signals.

o EUS-FNA will be performed in all pancreatic masses with at least three passes

o All examiners should be blinded for the results of pathology

• EG-EUS procedure: o EUS-EG will be performed during usual EUS examinations, with two movies of 10 seconds

recorded on the embedded HDD in order to minimize variability and to increase repeatability of

acquisition.

o A two panel image with the usual conventional gray-scale B-mode EUS image on the right

side and with the elastography image on the left side will be used. The same parameters will be

set-up in all systems used: e-dynamic range 2, persistence 3, etc.

o The region of interest for EUS-EG will be preferably larger than the focal mass

(approximately 50%-50%), in order to include the surrounding structures. If the focal mass is larger

than 3 cm, part of the mass will be included in the ROI, as well as the surrounding structures

(preferably avoiding large vessels). Very large ROI for the elastography calculations will be

avoided due to the appearance of side artifacts.

o The following pre-settings will be used in all centers: elastography colour map 1, frame

rejection 2, noise rejection 2, persistence 3, dynamic rage 4, smoothing 2, blend 50%.

o SR and SH will be measured; with three measurements made and recorded on the

embedded HDD. For SR, the reference area should be placed at the same level with the lesion,

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if possible.

• CE-EUS procedure: o A two panel image with the usual conventional gray-scale B-mode EUS image on the right

side and with the contrast harmonic image on the left side will be used, according to pre-

established presets.

o The starting point of the timer will be considered the moment of intravenous contrast

injection (Sonovue 4.8 mL).

o CE-EUS will be performed during usual EUS examinations, with the whole movie (T0-

T120s) recorded on the embedded HDD of the ultrasound system, for later analysis.

o A low mechanical index procedure (dynamic wide-band contrast harmo-nic imaging mode)

will be used, with a mechanical index of 0.2 and corresponding powers.

o The following pre-settings will be used in all centers: contrast mode dCHI-W, WPI-R/P

(resolution / penetration for superficial vs deep structures), mechanical index (variable starting

with 0.1, preferred 0.2), MI gray-scale (0.03), grey map 4, AGC 0, R-filter C, persistence 2,

dynamic range 50, B-colour 21, smoothing 3, gamma curve linear.

o In order to minimize human bias, all post-processing and computer analysis of digital

movies will be performed within the coordinating IT Center, with all programmers and statisticians

being blinded to the clinical, imaging and pathological data.

o Off-line analysis of time-intensity curves will be performed using Vue-Box, which yields the

following quantitative parameters: Peak Enhancement (PE), Wash-in Area Under the Curve (Wi-

AUC), Rise Time (RT), mean Transit Time (mTT), Time To Peak (TTP), Wash-in Rate (WiR) and

Wash-in Perfusion Index (WiPI). The software also provides referenced values (expressed in

percentages), aligning the set of values for the tumor ROI to the parenchymal ones.

6. Final diagnosis • A positive cytological diagnosis will be taken as a final proof of malignancy of the pancreas

mass or lymph node. The diagnoses obtained by EUS-FNA will be further verified either by surgery

or during a clinical follow-up of at least 6 months.

• The diagnosis of chronic pancreatitis will be based on the clinical information (history of

alcohol abuse, previous diagnosis of chronic pancreatitis or diabetes mellitus), as well as a

combination of imaging methods (ultrasound, CT and EUS). At least four criteria of chronic

pancreatitis during EUS will be considered for the positive diagnosis. The diagnosis of chronic

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pseudotumoral pancreatitis or benign lymph nodes will always be confirmed by surgery or by a

follow-up of at least six months used to exclude malignancy in the patients that will not be operated

on.

• Pathology samples obtained from duodeno-pancreatectomies or caudal pancreatecto-mies

done with curative intent, as well as microhistological fragments obtained through EUS-FNA

biopsy will be processed by paraffin embedding with usual stainings (haematoxylin-eosin), with

subsequent immune-histochemistry at the discretion of the participating centers pathologists in

order to exclude neuroendocrine tumors / pancreatic metastases.

• The patients will be followed-up for at least six months through clinical examination,

biological exams and transabdominal ultrasound, eventually with a repeat spiral CT / EUS after

six months.

7. Statistical analysis • Descriptive statistics

o All results will be expressed as mean ± standard deviation (SD). Differences between the

patients with pancreatic cancer and chronic pancreatitis will performed by the two-sample t-test

(two independent samples). Since this parametric method makes assumptions about normality

and similar variances, we will initially perform both the Kolmogorov-Smirnov and Shapiro-Wilk W

normality tests and verify the equality of variances assumption with the F test. In the case of the

two-sample t-test, we will also perform the non-parametric alternative given by the Mann-Whitney

U test, since in some instances it may even offer greater power to reject the null hypothesis than

the t-test.

o Since with more than two groups of observations it is far better to use a single analysis that

enables us to look at all the data in the same time, we will also perform the one-way analysis of

variance (ANOVA) method with the same baseline assumptions. A p-value less than 0.05 will be

considered as statistically significant.

• Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of

EG-EUS and CE-EUS will be determined in comparison with the final diagnosis. Also, the

sensitivity, specificity, positive predictive value, negative predictive value and accuracy for the

subgroup of patients with negative EUS-FNA and a positive diagnosisi of malignancy during

ensuing follow-up will be calculated separately.

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8. Power analysis • The estimated number of patients included in all centers was at least 210, based on at least

10 centers with at least 20 patients each, which will be enrolled in a 12 months period. The power

analysis was based on the following assumption: in order to use the powerful t-test for independent

samples, a sample size equaling 105 patients in each group is sufficient to provide 95% statistical

power to detect a difference of 5% in mean, for a type I error alpha = 0.05, and the population

standard deviation = 10%.

• The difference in mean was based on previously published data which report an accuracy

of approximately 80-85% for EUS-FNA, and 90% for EG-EUS and/or CE-EUS.

A2.2 Inclusion of patients with pancreatic cancer (collection of tissue) All fresh pancreatic tissue specimens were subjected to endomicroscopy investigations for

future assessment of different morphology patterns. As we described the examination technique

in the previous report, we assessed the tissue samples by a predesigned protocol while using two

different endomicroscopes: one from Mauna Kea Technologies with a ColoFlex UHD – Cellvizio

Confocal Miniprobe and one from Pentax Tokio Japan, an EC-3870 CIFK. While the two systems

possess different characteristics we decided to use them both for a future comparison between

resolution and accuracy.

We assessed the tissue samples with direct contact from the endomicroscopes and pointed

out several patterns of interest from cellular shape properties and organization to vascular

patterns and other details that might relate and help distinguish between normal tissue and

adenocarcinoma. After harvesting, the specimens were thoroughly washed and separate into

different groups for different setting.

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A2.3 CLE examination ex vivo + in vivo of pancreatic tumor tissue Firstly, we used acriflavine to point out the cell’s nuclei, thus distinguishing between, the

irregular shape pattern that may be encountered within an adenocarcinoma sequence and the

general coffee bean appearance, which is seen in normal pancreatic tissue. Both normal and fresh

unfixed specimens pathologic were harvested from previously diagnosed patients with pancreatic

adenocarcinoma and were incubated in acriflavine hydrochloride 0.05% (Sigma Pharmaceuticals)

for 5 minutes each. The ColoFlex UHD was directly brought into full contact with the tissue and

microscopic images were immediately available and recorded. We performed several attempts on

each sample, by gently moving around the probe covering the entire surface and the recordings

not surpassing 1 minute. The analyzed samples were than fixed in 4% formaldehyde solution and

sent for pathology analysis, which will be described in Objective 2.4.

Figure 4. Image Pro-Plus morphometric pattern analysis

The recordings were analyzed and several images were selected which led to morphology

assessment and comparison between the normal and pathologic tissue. Images were uploaded

in Image Pro Plus and morphological denominators were used on selected image sections: (1)

total area of the signal, (2) hole area and (3) heterogeneity – as indicators of inner irregularity, (4)

Integrated optical density (IOD), as a measure of pixel intensity and area, (5) roundness and (6)

fractal dimension as measures of edge and silhouette-related irregularity, (7) ferret as a measure

of average and maximum diameters of the ROIs and (8) clumpiness, as an indicator of pixel

variations in the inner areas of the ROIs. We found different patterns of morphology between the

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normal and adenocarcinoma specimens, with the analyzed parameters proving that this may be

a useful tool for rapid diagnosis.

Table 2. Image analysis results of endomicroscopy parameters.

We also performed needle confocal laser endomicroscopy using the Mauna Kea

Technology system. The needle confocal probe was inserted through a 19 G EUS-FNA needle of

the previously detected pancreatic mass. The flexible catheter (AQ-Flex 19™, Mauna Kea, Paris,

France) we used had a diameter of 0.85mm, a field of view of 325µm and a 3.5µm lateral

resolution. Just before examining with nCLE catheter intravenous administration of five mL of

fluorescein 10% was made which allowed to enhance certain characteristics of pancreatic or

tumor tissue. We individualized from dark aggregates to dilated irregular vessels with fluorescein

leakage, dark lobular structures, fibrous bands which helped set a pattern similar to pathologic

examination. Recordings were also performed for each patient and images were digitally stored

for a future offline analysis.

Figure 4. Endomicroscopy image after fluorescein leakage in a PDAC sample

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A2.4 Immunohistochemistry, immunofluorescence and molecular biology

1. Immunohistochemistry and immunofluorescence In an endeavor of finding a morphological denominator that could differentiate between normal

pancreatic tissue and ductal adenocarcinoma, we turned first to histopathology. On formalin fixed

paraffin embedded tissue (FFPE), we were thus interested to find a simple immunostaining that

would enable us to seek morphological differences between the two histopathologies. Since we

were interested in overall morphology changes, we performed an anti-AE1/AE3 pan-cytokeratin

staining for all the FFPE tissue collected during the project (Figure 4).

Figure 4. AE1/AE3 cytokeratin staining on control pancreas tissue (A, B) and ductal

adenocarcinoma cases (C, D); A,C- 20x, B, D- 40x.

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It was clear that the morphology of the acini and ducts on normal tissue were more regulated,

round and equidistant compare to the tortuous and irregular silhouettes that were stained in the

tumor cases. We acquired 40x images from both control cases and all the available casuistry, with

an average of 5 images /slide, with the same illumination and exposure settings on our Nikon 90i

microscope equipped with the Image ProPlus image analysis package. Next we defined the RGB

profile of the DAB staining for this antibody, and from all images the correspondent regions of

interest (ROI) were extracted utilizing the same RGB profile (Figure 5).

Figure 5. Segmented ROIs on both control and tumor tissue.

On these images a set of morphological denominators were applied to all the ROIs: (1) total

area of the signal, (2) hole area and (3) heterogeneity – as indicators of inner irregularity, (4)

Integrated optical density (IOD), as a measure of pixel intensity and area, (5) roundness and (6)

fractal dimension as measures of edge and silhouette-related irregularity, (7) ferret as a measure

of average and maximum diameters of the ROIs and (8) clumpiness, as an indicator of pixel

variations in the inner areas of the ROIs. All the denominators’ values were first averaged per

slide, then per patient, and in the end control cases were compared with tumor patients utilizing a

simple Student t test. Total area and hole area did not show significant differences (p=0.0749 and

respectively 0.0820), while IOD, roundness and heterogeneity showed significant differences

(p<0.05), and the perimeter, fractal dimension, ferret and clumpiness showed extremely

significant differences (p<0.001).

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Thus it is clear that most of these morphological denominators can be utilized to create specific

and different patterns for both the normal histology and overall ductal adenocarcinomas (which

were not considered separately based on grading or disease extension). An automated image

analysis algorithm, or a trainable neural network utilizing these parameters would thus be able to

appreciate the probability of viewing a tumor or a control tissue without the intervention of the

user, once the images have been acquired.

Since the proof-of principle test showed that simple algorithms can differentiate large

histological structures, without considering sub-cellular details, it was conceivable that ex-vivo or

even in-vivo staining with fluorescently labeled pan cytokeratin might yield detectable differences

on images captured with pCLE, where large ducts and acini should be visible even on lower

resolution images.

We have thus applied the same set of morphological algorithms on ex-vivo pCLE images, and

found that these morphological parameters can indeed differentiate tumor biopsies from peri-

lesional control tissue. Moreover, there was a strong correlation for the same morphological

parameter when comparing pCLE with histopathology, asserting once more than these features

can predict with great accuracy the morphology of the tumor as visualized on FFPE, and can be

good candidates for fast screening on ex-vivo and in-vivo images on automated imaging stations.

22

Results

At this stage, 4 articles had been written and accepted for publication in a high impact ISI Web

of Science journals (Endoscopic Ultrasound IF 3.323), including a multicentric trial. Other 2 articles

have been accepted for publication in a Medline journal (Current Health Sciences Journal). One

article is currently under review in PLoS One (Open Access IF 2.766). Also, one abstract was

accepted and presented during Digestive Disease Week, Washington DC, USA, 1-5 June 2018.

Another abstract has been presented during ESGE Days in April 2018. Two more abstracts have

been submitted to DDW 2019 and ESGE Days 2019.

Original papers 1. Iordache S, Albulescu DM, Săftoiu A. The borderline resectable/locally advanced

pancreatic ductal adenocarcinoma: EUS oriented. Endosc Ultrasound 2017; 6(Suppl

3): S83-S86. doi: 10.4103/eus.eus_68_17.

2. Costache MI, Dumitrescu D, Săftoiu A. Technique of qualitative and semiquantitative

EUS elastography in pancreatic examination. Endosc Ultrasound 2017; 6(Suppl 3):

S111-S114. doi: 10.4103/eus.eus_75_17.

3. Cazacu IM, Luzuriaga Chavez AA, Saftoiu A, Vilmann P, Bhutani MS. A quarter

century of EUS-FNA: Progress, milestones, and future directions. Endosc Ultrasound.

2018 May-Jun;7(3):141-160. doi: 10.4103/eus.eus_19_18.

4. Cazacu IM Luzuriaga Chavez AA, Saftoiu A, Whitlow TG, Bhosale P, Bhutani MS. A

Diagnostic Challenge: Pancreatic Cancer or Autoimmune Pancreatitis? Current

Health Sciences Journal 2018; 44(2): 181-185.

5. Costache MI, Cazacu IM, Dietrich CF, Petrone MC, Arcidiacono PG, Giovannini M,

Bories E, Iglesias Garcia J, Siyu S, Santo E, Popescu CF, Constantin A, Bhutani BS,

Saftoiu A. Clinical impact of strain histogram EUS elastography and contrast-

enhanced EUS for the differential diagnosis of focal pancreatic masses: a prospective

multicentric study. Endoscopic Ultrasound 2019, in press.

6. Constantin A, Tanase AD, Saftoiu A, Copaescu C. Primary Retroperitoneal Diffuse

Large B-Cell Lymphoma: a challenging diagnosis. Current Health Sciences Journal

23

2019, in press.

7. Ungureanu BS, Pirici D, Dima SO, Popescu I, Surlin V, Săftoiu A. Diagnostic accuracy

of confocal laser endomicroscopy for pancreatic ductal adenocarcinoma, an ex-vivo

experimental study. PLoS One 2019, under review.

Abstracts 1. Bogdan Silviu Ungureanu, Daniel Pirici, Simona Olimpia Dima, Irinel Popescu, Valeriu

Surlin, Gheorghe Hundorfean, Tudorel Ciurea, Adrian Săftoiu; Diagnostic accuracy of

confocal laser endomicroscopy for pancreatic ductal adenocarcinoma, an ex-vivo pilot

study. ESGE Days Budapest late breaking abstracts, Hungary, 19-21 April 2018.

Endoscopy 2018; 50(04): 4-4. DOI: 10.1055/s-0038-1637669

2. Irina Mihaela Cazacu, Péter Varju, Péter Matrai, Irina Florina Cherciu, Cristian Virgil

Lungulescu, Peter Hegyi, Manoop S. Bhutani, Adrian Saftoiu. Molecular markers

performed on EUS-FNA samples in assessing diagnosis of pancreatic cancer: a

systematic review and meta-analysis. DDW 2018: Sa1372, Washington DC, USA, 1-

5 June 2018.

3. Anca Udristoiu, Lucian Gheorghe Gruionu, Gabriel Gruionu, Andreea Valentina Iacob,

Daniela Elena Burtea, Bogdan Ungureanu, Mădălin Ionuț Costache, Carmen Florina

Popescu, Adrian Săftoiu. Real-time differential diagnosis of focal pancreatic masses

based on convolutional neural networks and advanced endoscopic ultrasound

imaging combining gray-scale, color doppler, contrast-enhancement and

elastography. Submitted for DDW 2019.

4. Bogdan Silviu Ungureanu, Daniel Pirici, Simona Dima, Irinel Popescu, Valeriu Surlin,

Irina Mihaela Cazacu, Adrian Saftoiu. Pancreatic cancer angiogenesis assessment by

confocal laser endomicroscopy and ANTI CD105 antibody in pancreatic cancer – a

pilot study. Submitted for ESGE Days 2019.

Date Signature

05.12.2018 Prof. Univ. Dr. Adrian Săftoiu