Review
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Mar 7, 2023; 29(9): 1427-1445
Published online Mar 7, 2023. doi: 10.3748/wjg.v29.i9.1427
Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liver
M Alvaro Berbís, Felix Paulano Godino, Javier Royuela del Val, Lidia Alcalá Mata, Antonio Luna
M Alvaro Berbís, Javier Royuela del Val, Department of Radiology, HT Médica, San Juan de Dios Hospital, Córdoba 14960, Spain
M Alvaro Berbís, Faculty of Medicine, Autonomous University of Madrid, Madrid 28049, Spain
Felix Paulano Godino, Lidia Alcalá Mata, Antonio Luna, Department of Radiology, HT Médica, Clínica las Nieves, Jaén 23007, Spain
Author contributions: Berbís MA, Paulano Godino F, Royuela del Val J, and Alcalá Mata L performed information compilation and manuscript writing; Luna A performed information compilation and critical reading of the manuscript.
Conflict-of-interest statement: Berbís MA is a board member of Cells IA Technologies; Luna A received institutional royalties and institutional payments for lectures, presentations, speaker bureaus, manuscript writing or educational events from Canon, Bracco, Siemens Healthineers, and Philips Healthcare and is a board member of Cells IA Technologies; the remaining authors declare no competing interests.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Antonio Luna, MD, PhD, Director, Department of Radiology, HT Médica, Clínica las Nieves, MRI Unit, 2 Carmelo Torres, Jaén 23007, Spain. aluna70@htmedica.com
Received: September 28, 2022
Peer-review started: September 28, 2022
First decision: January 3, 2023
Revised: January 13, 2023
Accepted: February 27, 2023
Article in press: February 27, 2023
Published online: March 7, 2023
Processing time: 160 Days and 6 Hours
Core Tip

Core Tip: The gastroenterology field is changing with the application of artificial intelligence (AI) solutions capable of assisting and even automating the interpretation of radiological images (ultrasound, endoscopic ultrasound, computerized tomography, magnetic resonance imaging, and positron emission tomography), generating accurate and reproducible diagnoses. AI can further be applied to other steps of the radiological workflow beyond image interpretation, including test selection, image quality improvement, acceleration of image acquisition, and prediction of patient prognosis and outcome. We herein discuss the current evidence, challenges, and future directions on the application of AI to hepatic and pancreatic radiology.