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Lookup NU author(s): Dr George KourounisORCiD, Dr Sam Tingle, Robin Nandi, Professor Neil SheerinORCiD, Professor Colin Wilson
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Introduction: Accurate evaluation of liver steatosis and overall organ quality is critical for optimizing safe organ utilisation in liver transplantation. Recent advances in computer vision offer promising tools to standardise and enhance this process. This review maps the current evidence on AI-enabled photographic evaluation methods and identifies areas for future development. Methods: A scoping review of the literature, including searches of PubMed, SCOPUS, and Web of Science, was conducted to identify studies published from inception to 27/03/2025 reporting on the development of AI-enabled tools for assessing liver organ quality from photographs taken during the donation process. A qualitative synthesis and critical review of the literature was conducted in accordance with PRISMA-ScR guidelines. The review protocol was registered with the Open Science Framework (osf.io/zfcuk). Results: After screening 219 citations, six studies from three independent research groups met the inclusion criteria. Sample sizes ranged from 40 to 192 donors. Five studies employed binary classification models using a 30% steatosis threshold, while one study reported a graded approach. Reported accuracies ranged from 0.81 to 0.92. Common challenges included small and imbalanced datasets with a dependence on supplementary donor data, such as blood tests and radiological findings. None of the studies conducted external validation. Discussion: There is international interest in developing AI-enabled photographic assessment tools in liver transplantation. Future studies should address the limitations discussed herein while incorporating clinician and patient input, ensuring integration of these AI tools into clinical practice to improve patient outcomes.
Author(s): Kourounis G, Tingle S, Elmahmudi A, Thomson B, Nandi R, Stephenson B, Hunter J, Ugail H, Sheerin NS, Wilson C
Publication type: Article
Publication status: Published
Journal: Clinical Transplantation
Year: 2026
Volume: 40
Issue: 2
Print publication date: 01/02/2026
Online publication date: 31/01/2026
Acceptance date: 18/12/2025
Date deposited: 09/02/2026
ISSN (print): 0902-0063
ISSN (electronic): 1399-0012
Publisher: Wiley
URL: https://doi.org/10.1111/ctr.70433
DOI: 10.1111/ctr.70433
Data Access Statement: Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study
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