Lindner C. Advanced imaging techniques at the crossroads of cholangiocarcinoma and liver transplantation: Can we bridge the gap? World J Gastrointest Surg 2025; 17(11): 110092 [DOI: 10.4240/wjgs.v17.i11.110092]
Corresponding Author of This Article
Cristian Lindner, MD, Department of Radiology, Faculty of Medicine, University of Concepcion, No. 1290 Victor Lamas, Concepcion 4030000, Biobío, Chile. clindner@udec.cl
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Radiology, Nuclear Medicine & Medical Imaging
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Field of Vision
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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
Nov 27, 2025 (publication date) through Nov 25, 2025
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World Journal of Gastrointestinal Surgery
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1948-9366
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Lindner C. Advanced imaging techniques at the crossroads of cholangiocarcinoma and liver transplantation: Can we bridge the gap? World J Gastrointest Surg 2025; 17(11): 110092 [DOI: 10.4240/wjgs.v17.i11.110092]
World J Gastrointest Surg. Nov 27, 2025; 17(11): 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
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. clindner@udec.cl
Received: June 3, 2025 Revised: July 6, 2025 Accepted: September 17, 2025 Published online: November 27, 2025 Processing time: 179 Days and 1.6 Hours
Abstract
In order to evaluate emerging imaging strategies for optimizing cholangiocarcinoma (CCA) assessment in liver transplantation (LT) candidates, addressing gaps in standardization, diagnostic ambiguity, and equitable access. Critical analysis of current evidence and innovations in CCA imaging, focusing on three pillars: (1) Adaptation of Liver Imaging Reporting and Data System for standardized reporting; (2) Integration of artificial intelligence (AI)-driven radiomics for risk stratification; and (3) Expanded utilization of contrast-enhanced ultrasound (CEUS) in resource-limited settings. Current imaging criteria for LT eligibility in CCA rely heavily on tumor size and vascular invasion, but lack standardized protocols for lesion characterization in cirrhotic livers. Liver Imaging Reporting and Data System, validated for hepatocellular carcinoma, shows promise in reducing interobserver variability when adapted to CCA-specific features (e.g., targetoid appearance on magnetic resonance imaging). AI-driven radiomics can predict microvascular invasion and post-LT recurrence risk with 85% accuracy in preliminary studies, while CEUS demonstrates 92% specificity for differentiating intrahepatic CCA from dysplastic nodules in cirrhosis. A harmonized approach combining standardized reporting systems, AI-powered analytics, and accessible imaging modalities like CEUS could redefine LT pathways for CCA. Collaborative efforts between radiologists and transplant teams are essential to translate these innovations into equitable, precision-driven care.
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.
