PhD Scientific Days 2020

Clinical Medicine IV. Lectures

Differentiation Between Pancreatic Cystic Lesions Using Image Processing Software (FIJI) by Analyzing Endoscopic-Ultrasonographic (EUS) Images

Előadó neve

Dr. Bánk, Keczer

Előadó munkahelye

Center for Therapeutic Endoscopy, 1st Department of Surgery, Semmelweis University

Előadó telefonszáma

06206632223

Előadó e-mail címe

keczer45@gmail.com

Az előadás címe

Differentiation Between Pancreatic Cystic Lesions Using Image Processing Software (FIJI) by Analyzing Endoscopic-Ultrasonographic (EUS) Images

Szerző(k) neve és munkahelye

Bánk Keczer1, Pál Miheller1, Miklós Horváth1, Balázs Tihanyi2, Ákos Szűcs2, László Nehéz2, Tamás Marjai2, Attila Szijártó2, László Harsányi2, István Hritz1
1 Center for Therapeutic Endoscopy, 1st Department of Surgery, Semmelweis Egyetem
2 1st Department of Surgery, Semmelweis Egyetem

Szekció

Clinical Medicine IV. Lectures

Language of the presentation

Hungarian

Section, first choice

Clinical Medicine

Section, second choice

Health Sciences

Összefoglaló szövege

EUS is the most accurate imaging modality for evaluation of different types of
pancreatic cystic lesions; however, distinguishing between malignant and benign lesions
remains challenging. Our aim was to analyze EUS images of pancreatic cystic lesions using
an image processing software (FIJI).
We specified echogenicity of the lesions by measuring the gray value of pixels
inside the selected areas. Besides the entire lesion, its cystic and solid parts were also
separately selected for assessment. Following the software analyzing process images were
divided into groups (serous cystic neoplasm /SCN/, non-SCN and pseudocyst) according to
the cytology results of the lesions. Intraductal papillary mucinous neoplasms (IPMNs) and
mucinous cystic neoplasms (MCNs) were classified as non-SCN category.
EUS images of 33 patients (21 females, 12 males; mean age of 60.9±10.1 and
66.3±11.6 years, respectively) were assessed. Overall 73 images were processed by the
software: 36 in non-SCN, 13 in SCN and 24 in the pseudocyst group. The mean gray value of
the entire lesion in non-SCN group was significantly higher than in SCN group (31.7 vs 25.5;
p=0.022). The area ratio (area of cystic part/entire lesion) in non-SCN, SCN and pseudocyst
group was 42%, 55% and 70%, respectively; significantly lower in non-SCN group than in
SCN and pseudocyst group (p=0.0058 and p<0.0005, respectively). The lesion density (sum
of the gray values/area of the lesion) was also significantly higher in non-SCN group
compared to the SCN- and pseudocyst group (4802.48/mm 2 vs 3865.87/mm 2 vs 3192.27/mm 2 ;
p=0.022 and p=0.004, respectively). No correlation was found between the intracystic CEA
levels and the analyzed cystic gray values.
The computer-aided diagnosis decision is being used increasingly due to the
rapid development of the information technology. The EUS image analysis process may have
a potential to be a diagnostic tool for the evaluation and differentiation of pancreatic cystic
lesions.

Additional Information

Hritz István
istvan.hritz@gmail.com

Bemutatás módja

Szóbeli

Kind

Szabad

Status

elfogadva

Accepted presentation method

szóbeli

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

4769

Start

17:15

End

17:30

Authors (legacy)

Bánk Keczer1, Pál Miheller1, Miklós Horváth1, Balázs Tihanyi2, Ákos Szűcs2, László Nehéz2, Tamás Marjai2, Attila Szijártó2, László Harsányi2, István Hritz1
1 Center for Therapeutic Endoscopy, 1st Department of Surgery, Semmelweis Egyetem
2 1st Department of Surgery, Semmelweis Egyetem