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©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Nov 27, 2025; 17(11): 110092
Published online Nov 27, 2025. doi: 10.4240/wjgs.v17.i11.110092
Published online Nov 27, 2025. doi: 10.4240/wjgs.v17.i11.110092
Advanced imaging techniques at the crossroads of cholangiocarcinoma and liver transplantation: Can we bridge the gap?
Cristian Lindner, Department of Radiology, Faculty of Medicine, University of Concepcion, Concepcion 4030000, Biobío, Chile
Cristian Lindner, Department of Radiology, Hospital Clínico Regional Dr. Guillermo Grant Benavente, Concepcion 4030000, Biobío, Chile
Author contributions: Lindner C wrote and reviewed the article, and approved the final version of the manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
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: Cristian Lindner, MD, Department of Radiology, Faculty of Medicine, University of Concepcion, No. 1290 Victor Lamas, Concepcion 4030000, Biobío, Chile.
Received: June 3, 2025
Revised: July 6, 2025
Accepted: September 17, 2025
Published online: November 27, 2025
Processing time: 179 Days and 1.7 Hours
Revised: July 6, 2025
Accepted: September 17, 2025
Published online: November 27, 2025
Processing time: 179 Days and 1.7 Hours
Core Tip
Core Tip: This perspective advocates for paradigm shifts in cholangiocarcinoma imaging for transplantation: Liver Imaging Reporting and Data System standardization to reduce diagnostic variability; artificial intelligence radiomics for recurrence risk prediction; and contrast-enhanced ultrasound adoption to bridge resource gaps. Together, these innovations can transform ambiguous evaluations into precision-driven pathways, optimizing post-transplant survival.