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Usefulness of the Contrast‐Enhanced Ultrasound Liver Imaging Reporting and Data System in Diagnosing Focal Liver Lesions by Inexperienced Radiologists
Author(s) -
Wang JiaYu,
Feng ShaoYang,
Xu JianWei,
Li Jun,
Chu Liang,
Cui XinWu,
Dietrich Christoph F.
Publication year - 2020
Publication title -
journal of ultrasound in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 91
eISSN - 1550-9613
pISSN - 0278-4297
DOI - 10.1002/jum.15242
Subject(s) - medicine , radiology , contrast enhanced ultrasound , predictive value , hepatocellular carcinoma , ultrasound , diagnostic accuracy , ultrasonography
Objectives To evaluate the usefulness of the contrast‐enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI‐RADS) in diagnosing focal liver lesions (FLLs) by inexperienced radiologists. Methods Images and clinical data from 258 patients at risk for hepatocellular carcinoma who underwent CEUS were collected retrospectively. Two trained inexperienced radiologists and 2 experienced radiologists reviewed all CEUS clips. Each inexperienced radiologist assigned a CEUS LI‐RADS category for each observation and labeled it benign or malignant independently. Each experienced radiologist labeled each lesion malignant or benign independently using a conventional diagnostic method. Interobserver agreement of CEUS LI‐RADS was analyzed by the κ test. The overall diagnostic accuracy of the LI‐RADS category and conventional diagnosis was described by the sensitivity, specificity, positive predictive value, and negative predictive value. All test results were considered significant at P < .05. Results A κ value of 0.774 indicated that the CEUS LI‐RADS algorithm resulted in substantial consistency between the inexperienced radiologists. For the diagnosis of hepatocellular carcinoma, the sensitivity, specificity, positive predictive value, and negative predictive value were improved significantly in inexperienced radiologists using the CEUS LI‐RADS compared to conventional methods. The overall diagnostic accuracy of the experienced radiologists was almost equal to that of CEUS LI‐RADS categories assigned by the inexperienced radiologists. Conclusions The CEUS LI‐RADS algorithm can not only obtain substantial consistency among inexperienced radiologists but also have excellent diagnostic efficacy in the differentiation of benign from malignant FLLs compared to conventional methods. As a comprehensive algorithm, the CEUS LI‐RADS can act as a guide for trainees in learning how to diagnose FLLs.