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. 2024 May;42(5):476-486.
doi: 10.1007/s11604-023-01523-x. Epub 2024 Jan 31.

Systematic training of LI-RADS CT v2018 improves interobserver agreements and performances in LR categorization for focal liver lesions

Te Ba  1   2 , Hui Xu  1 , Da-Wei Yang  1 , Zhen-Chang Wang  1 , Zhenghan Yang  3 , A-Hong Ren  4
Affiliations

Systematic training of LI-RADS CT v2018 improves interobserver agreements and performances in LR categorization for focal liver lesions

Te Ba et al. Jpn J Radiol. 2024 May.

Abstract

Aim: To retrospectively explored whether systematic training in the use of Liver Imaging Reporting and Data System (LI-RADS) v2018 on computed tomography (CT) can improve the interobserver agreements and performances in LR categorization for focal liver lesions (FLLs) among different radiologists.

Materials and methods: A total of 18 visiting radiologists and the liver multiphase CT images of 70 hepatic observations in 63 patients at high risk of HCC were included in this study. The LI-RADS v2018 training procedure included three thematic lectures, with an interval of 1 month. After each seminar, the radiologists had 1 month to adopt the algorithm into their daily work. The interobserver agreements and performances in LR categorization for FLLs among the radiologists before and after training were compared.

Results: After training, the interobserver agreements in classifying the LR categories for all radiologists were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.053). After systematic training, the areas under the curve (AUCs) for LR categorization performance for all participants were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.062).

Conclusion: Systematic training in the use of the LI-RADS can improve the interobserver agreements and performances in LR categorization for FLLs among radiologists with different levels of experience.

Keywords: Computed tomography (CT); Diagnostic imaging; Liver Imaging Reporting and Data System (LI-RADS); Liver neoplasm; Training program.

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