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. 2026 Feb 16.
doi: 10.1186/s40644-026-00998-x. Online ahead of print.

Evaluation of the performance of radiologists assisted by AI in detecting colorectal liver metastases on contrast-enhanced CT

Jeong Hee Yoon  1   2 , Hyo-Jin Kang  1   2 , Jae Seok Bae  1   2 , Jae Hyun Kim  1   2 , Jin Sol Choi  1   3 , Won Hyeong Im  1 , Alexandre Bône  4 , Jeong Min Lee  5   6   7
Affiliations
Free article

Evaluation of the performance of radiologists assisted by AI in detecting colorectal liver metastases on contrast-enhanced CT

Jeong Hee Yoon et al. Cancer Imaging. .
Free article
No abstract available

Keywords: Artificial intelligence; Colorectal neoplasms; Computed tomography; Computer-assisted diagnosis; Diagnostic accuracy; Liver metastasis; Radiologist performance; Workflow efficiency.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study was approved by the Institute Review Board of Seoul National University Hospital (No. 1812-013-991). The requirement for written informed consent was waived by the institutional review board due to the retrospective nature of the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments. Consent for publication: Not applicable. Competing interests: Jeong Min Lee received grant from Guerbet for this study. One of the authors (A.B.) is an employee of Guerbet.

References

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    1. Rompianesi G, Pegoraro F, Ceresa CD, Montalti R, Troisi RI. Artificial intelligence in the diagnosis and management of colorectal cancer liver metastases. World J Gastroenterol. 2022;28:108–22.
    1. Nakai H, Sakamoto R, Kakigi T, Coeur C, Isoda H, Nakamoto Y. Artificial intelligence-powered software detected more than half of the liver metastases overlooked by radiologists on contrast-enhanced CT. Eur J Radiol. 2023;163:110823.
    1. Ying H, Liu X, Zhang M, Ren Y, Zhen S, Wang X, et al. A multicenter clinical AI system study for detection and diagnosis of focal liver lesions. Nat Commun. 2024;15:1131.
    1. Kim DW, Lee G, Kim SY, Ahn G, Lee J-G, Lee SS, et al. Deep learning–based algorithm to detect primary hepatic malignancy in multiphase CT of patients at high risk for HCC. Eur Radiol. 2021;31:7047–57.

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