Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence

Cristian Anghel
ORCID logo ,
Grasu Cristian Mugur
* ,
Denisa Andreea Anghel
ORCID logo ,
Gina Ionela Rusu-Munteanu
,
Radu Lucian Dumitru
,
Ioana Gabriela Lupescu
ORCID logo
Version 1 : Received: 10 January 2024 / Approved: 11 January 2024 / Online: 11 January 2024 (10:14:50 CET)

A peer-reviewed article of this Preprint also exists.

Anghel, C.; Grasu, M.C.; Anghel, D.A.; Rusu-Munteanu, G.-I.; Dumitru, R.L.; Lupescu, I.G. Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images. Diagnostics 2024, 14, 438. Anghel, C.; Grasu, M.C.; Anghel, D.A.; Rusu-Munteanu, G.-I.; Dumitru, R.L.; Lupescu, I.G. Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images. Diagnostics 2024, 14, 438.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the most common malignant tumor of the pancreas, carrying a poor prognosis, in most cases patients being diagnosed in a nonresectable stage. Image-based artificial intelligence (AI) models implemented in tumor detection, segmentation and classification could improve diagnosis with better treatment options and increased survival. This review included papers published in the last 5 years and describes the current trends in AI algorithms used in PDAC. We analyzed the applications of AI in detection of PDAC, segmentation of the lesion and classification algorithms used in differential diagnosis, prognosis, and histopathological and genomic prediction. The results show lack of multi-institutional collaboration and stresses the need for bigger datasets in order for AI models to be implemented in a clinically relevant manner.

Keywords

pancreatic adenocarcinoma; artificial intelligence; pancreas imaging

Subject

Medicine and Pharmacology, Oncology and Oncogenics

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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