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©The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Gastroenterol. Jan 8, 2026; 7(1): 115054
Published online Jan 8, 2026. doi: 10.35712/aig.v7.i1.115054
Published online Jan 8, 2026. doi: 10.35712/aig.v7.i1.115054
Integrating artificial intelligence in the diagnostic pathway of duodenal gastrointestinal stromal tumors: A case report
Himanshu Agrawal, Garima Dwivedi, Rahul Rohitaj, Himanshu Tanwar, Shailender Maurya, Department of Surgery, University College of Medical Sciences, University of Delhi, Guru Teg Bahadur Hospital, New Delhi 110095, Delhi, India
Nikhil Gupta, Department of Surgery, Atal Bihari Vajpayee Institute of Medical Sciences, Dr. Ram Manohar Lohia Hospital, New Delhi 110001, Delhi, India
Author contributions: Agrawal H contributed to conceptualization; patient assessment and clinical management, data curation and writing-original draft; Dwivedi G contributed to literature review, methodology, write the case history and discussion section, and make pictures and tables; Rohitaj R contributed to diagnostic work-up, imaging/Lab collation, data curation; Rohitaj R, Tanwar H, Maurya S, and Gupta N contributed to writing - review and editing; Tanwar H contributed to supervision, clinical oversight, and validation; Maurya S contributed to resources, project administration, patient follow-up and documentation, and ethics/consent coordination; Gupta N contributed to methodology, procedural/operative input and interpretation, and visualization. All authors approved the final manuscript and agree to be accountable for all aspects of the work.
Informed consent statement: Informed written consent was obtained from the patient for publication of this report and any accompanying images.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
CARE Checklist (2016) statement: The authors have read the CARE Checklist (2016), and the manuscript was prepared and revised according to the CARE Checklist (2016).
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: Nikhil Gupta, Department of Surgery, Atal Bihari Vajpayee Institute of Medical Sciences, Dr. Ram Manohar Lohia Hospital, Baba Kharak Singh Marg, Connaught Place, New Delhi 110001, Delhi, India. nikhil_ms26@yahoo.co.in
Received: October 9, 2025
Revised: October 28, 2025
Accepted: December 1, 2025
Published online: January 8, 2026
Processing time: 92 Days and 1.6 Hours
Revised: October 28, 2025
Accepted: December 1, 2025
Published online: January 8, 2026
Processing time: 92 Days and 1.6 Hours
Core Tip
Core Tip: Duodenal gastrointestinal stromal tumors (GISTs) are rare and often mimic periampullary or pancreatic tumors, leading to misdiagnosis, especially when presenting with obstructive jaundice. This case highlights how artificial intelligence (AI) could significantly enhance preoperative diagnosis by analyzing subtle imaging features that differentiate GISTs from other malignancies. AI-driven radiomics and deep learning models can improve tumor characterization, predict biological behavior, and guide timely treatment decisions. Integrating AI into diagnostic workflows may prevent unnecessary major surgeries and improve outcomes in rare gastrointestinal tumors like duodenal GISTs.