Accurate prediction of histological grading of intraductal papillary mucinous neoplasia using deep learning

Authors: Dominik Schulz, Markus Heilmaier, Veit Phillip, Matthias Treiber, Ulrich Mayr, Tobias Lahmer, Julius Mueller, Ihsan Ekin Demir, Helmut Friess, Maximilian Reichert, Roland M. Schmid, Mohamed Abdelhafez

Published: 2022-11-03

DOI: 10.1055/a-1971-1274

Source: Full article

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Abstract

Background Risk stratification and recommendation for surgery for intraductal papillary mucinous neoplasm (IPMN) are currently based on consensus guidelines. Risk stratification from presurgery histology is only potentially decisive owing to the low sensitivity of fine-needle aspiration. In this study, we developed and validated a deep learning-based method to distinguish between IPMN with low grade dysplasia and IPMN with high grade dysplasia/invasive carcinoma using endoscopic ultrasound (EUS) images.