Endoscopy 2018; 50(04): S4
DOI: 10.1055/s-0038-1637669
ESGE Days 2018 oral presentations
20.04.2018 – Late breaking abstracts
Georg Thieme Verlag KG Stuttgart · New York

DIAGNOSTIC ACCURACY OF CONFOCAL LASER ENDOMICROSCOPY FOR PANCREATIC DUCTAL ADENOCARCINOMA, AN EX-VIVO PILOT STUDY

BS Ungureanu
1   Gastroenterology, Research Center of Gastroenterology and Hepatology Craiova, University of Medicine and Pharmacy Craiova, Romania, Craiova, Romania
,
D Pirici
2   Pathology, Research Center of Gastroenterology and Hepatology Craiova, University of Medicine and Pharmacy Craiova, Romania, Craiova, Romania
,
SO Dima
3   Surgery, Fundeni Clinical Institute, Bucharest, Romania
,
I Popescu
3   Surgery, Fundeni Clinical Institute, Bucharest, Romania
,
V Surlin
4   Surgery, Research Center of Gastroenterology and Hepatology Craiova, University of Medicine and Pharmacy Craiova, Romania, Craiova, Romania
,
G Hundorfean
5   Gastroenterology, University Hospital Erlangen, University of Erlangen-Nuremberg, Erlangen, Germany, Erlangen, Germany
,
A Saftoiu
1   Gastroenterology, Research Center of Gastroenterology and Hepatology Craiova, University of Medicine and Pharmacy Craiova, Romania, Craiova, Romania
› Author Affiliations
Further Information

Publication History

Publication Date:
27 March 2018 (online)

Also available at
 

Aims:

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggresive tumors, with a 20 to 25% survival rate in a resectable stage. Moreover, providing a precise resection margin ensures a better prognosis. Probe based confocal laser endomicroscopy (pCLE), with various miniprobes available is being used as a prehistopathological tool for different types of lesions. However, in PDAC there is limited experience in imaging studies.

Ex-vivo freshly surgical removed PDAC specimens were assessed using pCLE and then processed for paraffin embeding and histopathological diagnostic in an endeavour to find putative image analysis algorithms that might recognise adenocarcinoma.

Methods:

Twelve patients diagnosed with PDAC on endoscopic ultrasound and FNA confirmation underwent surgery. Removed samples were sprayed with acriflavine as contrast agent, underwent pCLE with an experimental probe and compared with previous recordings of normal pancreatic tissue. Subsequently, all samples were subjected to cross-sectional histopathology, including surgical resection margins for controls. pCLE records, as well as corespondant cytokeratin-targeted immunohistochemistry images were processed using the same morphological classifiers in the Image ProPlus AMS image analysis software. Specific morphometric classifiers were automatically generated on all images: Area, Hole Area (HA), Perimeter, Roundness, Integrated Optical Density (IOD), Fractal Dimension (FD), Ferret max (Fmax), Ferret mean (Fmean), Heterogeneity and Clumpiness.

Results:

After histopathological confirmation of adenocarcinoma areas, we have found that the same morphological classifiers could clearly differentiate between tumor and non-tumor areas on both pathology and correspondand pCLE: Area, Roundness, IOD, Ferret and Heterogeneity (p < 0.001), Perimeter and Hole area (p < 0.05).

Conclusions:

This pilot study proves that classical morphometrical classifiers can clearly differentiate adenocarcimoma on pCLE data, and the implementation in a live image-analysis algorithm might help in improving the specificity of pCLE in vivo diagnostic.