Singh Ranjit, Wilson Mitchell P, Manolea Florin, Ahmed Bilal, Fung Christopher, Receveur Darryn, Low Gavin
Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Canada.
SA J Radiol. 2022 May 19;26(1):2386. doi: 10.4102/sajr.v26i1.2386. eCollection 2022.
Hepatocellular carcinoma (HCC) can be diagnosed non-invasively, provided certain imaging criteria are met. However, the recent Liver Imaging Reporting and Data System (LI-RADS) version 2018 has not been widely validated.
This study aimed to evaluate the diagnostic accuracy and reader reliability of the LI-RADS version 2018 lexicon amongst fellowship trained radiologists compared with an expert consensus reference standard.
This retrospective study was conducted between 2018 and 2020. A total of 50 contrast enhanced liver magnetic resonance imaging (MRI) studies evaluating focal liver observations in patients with cirrhosis, hepatitis B virus (HBV) or prior HCC were acquired. The standard of reference was a consensus review by three fellowship-trained radiologists. Diagnostic accuracy including sensitivity, specificity, positive predictive value (PPV), negative predictive values (NPV) and area under the curve (AUC) values were calculated per LI-RADS category for each reader. Kappa statistics were used to measure reader agreement.
Readers demonstrated excellent specificities (88% - 100%) and NPVs (85% - 100%) across all LI-RADS categories. Sensitivities were variable, ranging from 67% to 83% for LI-RADS 1, 29% to 43% for LI-RADS 2, 100% for LI-RADS 3, 70% to 80% for LI-RADS 4 and 80% to 84% for LI-RADS 5. Readers showed excellent accuracy for differentiating benign and malignant liver lesions with AUC values > 0.90. Overall inter-reader agreement was 'good' (kappa = 0.76, < 0.001). Pairwise inter-reader agreement was 'very good' (kappa ≥ 0.90, < 0.001).
The LI-RADS version 2018 demonstrates excellent specificity, NPV and AUC values for risk stratification of liver observations by radiologists. Liver Imaging Reporting and Data System can reliably differentiate benign from malignant lesions when used in conjunction with corresponding LI-RADS management recommendations.
只要满足某些影像学标准，肝细胞癌（HCC）就可以通过非侵入性方法进行诊断。然而，最新的2018版肝脏影像报告和数据系统（LI-RADS）尚未得到广泛验证。
本研究旨在评估与专家共识参考标准相比，2018版LI-RADS词汇表在接受专科培训的放射科医生中的诊断准确性和阅片者可靠性。
本回顾性研究于2018年至2020年进行。共收集了50例对比增强肝脏磁共振成像（MRI）研究，评估肝硬化、乙型肝炎病毒（HBV）或既往有HCC患者的肝脏局灶性病变。参考标准是由三名接受专科培训的放射科医生进行的共识评估。为每位阅片者计算每个LI-RADS类别包括敏感性、特异性、阳性预测值（PPV）、阴性预测值（NPV）和曲线下面积（AUC）值在内的诊断准确性。使用Kappa统计量来衡量阅片者之间的一致性。
在所有LI-RADS类别中，阅片者表现出优异的特异性（88% - 100%）和NPV（85% - 100%）。敏感性各不相同，LI-RADS 1为67%至83%，LI-RADS 2为29%至43%，LI-RADS 3为100%，LI-RADS 4为70%至80%，LI-RADS 5为80%至84%。阅片者在区分良性和恶性肝脏病变方面表现出优异的准确性，AUC值> 0.90。总体阅片者间一致性为“良好”（kappa = 0.76，P < 0.001）。两两阅片者间一致性为“非常好”（kappa≥0.90，P < 0.001）。
2018版LI-RADS在放射科医生对肝脏病变进行风险分层时表现出优异的特异性、NPV和AUC值。肝脏影像报告和数据系统与相应的LI-RADS管理建议联合使用时，能够可靠地区分良性和恶性病变。
