Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, P.R. China.
Department of Radiology, People's Hospital of Beijing DaXing District, Capital Medical University, Beijing, P.R. China.
J Magn Reson Imaging. 2019 Sep;50(3):746-755. doi: 10.1002/jmri.26640. Epub 2019 Jan 15.
The Liver Imaging Reporting and Data System (LI-RADS) is widely adopted for noninvasive diagnosis of hepatocellular carcinoma (HCC). It's updated to version 2018 recently, with some major changes compared with v2017. However, the diagnostic performance of LI-RADS v2018 and its difference with v2017 are yet to be validated.
To compare the diagnostic performances of LI-RADS on MR for diagnosing HCC between v2017 and v2018.
Retrospective.
In all, 181 patients with 217 hepatic observations (146 HCCs, 16 non-HCC malignancies and 55 benign lesions) with liver MRI and pathological or follow-up imaging diagnoses.
FIELD STRENGTH/SEQUENCE: 1.5 T or 3 T MRI. Dual-echo T WI, T WI, diffusion-weighted imaging, and a liver acquisition with volume acceleration. Assessment Images were independently interpreted by three radiologists, and then in consensus for observations with different LR categories, according to LI-RADS v2017 and v2018, separately.
Sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (+LR), and Youden index.
When adopting LR-5 as a predictor of HCC, the sensitivity (80.8% vs. 71.2%), NPV (69.6% vs. 60.7%), and accuracy (83.9% vs. 77.9%) were all increased for LI-RADS v2018 compared with v2017, with a greater Youden index (0.709 vs. 0.627). However, the diagnostic performances of MRI for diagnosing HCC were not changed while adopting LR-4/5 as a predictor. The threshold growths of 76% (19/25) observations in v2017 were revised to subthreshold growth in v2018, and 16 LR-4 observations in v2017 were changed to LR-5 based on v2018.
The diagnostic performance of LI-RADS v2018 for diagnosing HCC is superior to v2017, with a greater sensitivity, NPV, and accuracy. The revisions in v2018 mainly affect the categorization when adopting LR-5 as a predictor of HCC.
4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:746-755.
肝脏影像报告和数据系统（LI-RADS）广泛应用于肝细胞癌（HCC）的非侵入性诊断。最近它已更新至 2018 版本，与 2017 版本相比有一些重大变化。然而，LI-RADS v2018 的诊断性能及其与 v2017 的差异尚未得到验证。
比较 2017 版和 2018 版 LI-RADS 在 MRI 诊断 HCC 中的诊断性能。
回顾性。
共纳入 181 例患者的 217 个肝脏观察结果（146 个 HCC、16 个非 HCC 恶性肿瘤和 55 个良性病变），均行肝脏 MRI 检查和病理或随访影像学检查。
磁场强度/序列：1.5T 或 3T MRI。双回波 TWI、TWI、扩散加权成像和容积加速采集。根据 LI-RADS v2017 和 v2018，分别对评估图像由三位放射科医生独立解读，然后对不同 LR 类别进行共识解读。
敏感性、特异性、准确性、阳性预测值（PPV）、阴性预测值（NPV）、阳性似然比（+LR）和 Youden 指数。
当采用 LR-5 作为 HCC 的预测因子时，与 v2017 相比，v2018 的敏感性（80.8% vs. 71.2%）、NPV（69.6% vs. 60.7%）和准确性（83.9% vs. 77.9%）均提高，且 Youden 指数更大（0.709 vs. 0.627）。然而，当采用 LR-4/5 作为预测因子时，MRI 诊断 HCC 的性能没有改变。在 v2017 中，有 25 个观察结果的生长幅度达到 76%（19/25）被修订为亚阈值生长，根据 v2018，有 16 个 LR-4 观察结果被修订为 LR-5。
LI-RADS v2018 对 HCC 的诊断性能优于 v2017，具有更高的敏感性、NPV 和准确性。v2018 的修订主要影响采用 LR-5 作为 HCC 预测因子时的分类。
4 技术功效分期：2 J. Magn. Reson. Imaging 2019;50:746-755.
