Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.
J Magn Reson Imaging. 2022 Aug;56(2):399-412. doi: 10.1002/jmri.28056. Epub 2022 Jan 7.
The Liver Imaging Reporting and Data System (LI-RADS) is widely used for diagnosing hepatocellular carcinoma (HCC), however, with unsatisfactory sensitivity, complex ancillary features, and inadequate integration with gadoxetate disodium (EOB)-enhanced MRI.
To modify LI-RADS (mLI-RADS) on EOB-MRI.
Secondary analysis of a prospective observational study.
Between July 2015 and September 2018, 224 consecutive high-risk patients (median age, 51 years; range, 26-83; 180 men; training/testing sets: 169/55 patients) with 742 (median size, 13 mm; interquartile range, 7-27; 498 HCCs) LR-3/4/5 observations.
FIELD STRENGTH/SEQUENCE: 3.0 T T -weighted fast spin-echo, diffusion-weighted spin-echo based echo-planar, and 3D T -weighted gradient echo sequences.
Three radiologists (with 5, 5, and 10 years of experience in liver MR imaging, respectively) blinded to the reference standard (histopathology or imaging follow-up) reviewed all MR images independently. In the training set, the optimal LI-RADS version 2018 (v2018) features selected by Random Forest analysis were used to develop mLI-RADS via decision tree analysis.
In an independent testing set, diagnostic performances of mLI-RADS, LI-RADS v2018, and the Korean Liver Cancer Association (KLCA) guidelines were computed using a generalized estimating equation model and compared with McNemar's test. A two-tailed P < 0.05 was statistically significant.
Five features (nonperipheral "washout," restricted diffusion, nonrim arterial phase hyperenhancement [APHE], mild-moderate T2 hyperintensity, and transitional phase hypointensity) constituted mLI-RADS, and mLR-5 was nonperipheral washout coupled with either nonrim APHE or restricted diffusion. In the testing set, mLI-RADS was significantly more sensitive (72%) and accurate (80%) than LI-RADS v2018 (sensitivity, 61%; accuracy 74%; both P < 0.001) and the KLCA guidelines (sensitivity, 64%; accuracy 74%; both P < 0.001), without sacrificing positive predictive value (mLI-RADS, 94%; LI-RADS v2018, 94%; KLCA guidelines, 92%).
In high-risk patients, the EOB-MRI-based mLI-RADS was simpler and more sensitive for HCC than LI-RADS v2018 while maintaining high positive predictive value.
2 TECHNICAL EFFICACY: Stage 2.
肝脏影像报告和数据系统（LI-RADS）广泛用于诊断肝细胞癌（HCC），但敏感性不理想，辅助特征复杂，与钆塞酸二钠（EOB）增强 MRI 的整合不足。
对 EOB-MRI 上的 LI-RADS（mLI-RADS）进行修改。
前瞻性观察研究的二次分析。
2015 年 7 月至 2018 年 9 月，224 例连续高危患者（中位年龄 51 岁；范围 26-83 岁；180 名男性；训练/测试集：169/55 例患者），742 例（中位大小 13mm；四分位间距 7-27；498 例 HCCs）LR-3/4/5 观察。
场强/序列：3.0T T1 加权快速自旋回波、扩散加权自旋回波基于回波平面和 3D T1 加权梯度回波序列。
三位放射科医生（分别具有 5、5 和 10 年肝脏 MRI 成像经验）对参考标准（组织病理学或影像学随访）进行了盲法评估。在训练集中，使用随机森林分析选择的最佳 LI-RADS 2018 版（v2018）特征，通过决策树分析开发 mLI-RADS。
在独立测试集中，使用广义估计方程模型计算 mLI-RADS、LI-RADS v2018 和韩国肝癌协会（KLCA）指南的诊断性能，并使用 McNemar 检验进行比较。双侧 P<0.05 具有统计学意义。
5 个特征（非外周“洗脱”、受限扩散、非边缘动脉期强化[APHE]、轻度至中度 T2 高信号和过渡期低信号）构成了 mLI-RADS，mLR-5 是非外周洗脱，伴有非边缘 APHE 或受限扩散。在测试集中，mLI-RADS 的敏感性（72%）和准确性（80%）明显高于 LI-RADS v2018（敏感性 61%，准确性 74%；均 P<0.001）和 KLCA 指南（敏感性 64%，准确性 74%；均 P<0.001），而不影响阳性预测值（mLI-RADS，94%；LI-RADS v2018，94%；KLCA 指南，92%）。
在高危患者中，与 LI-RADS v2018 相比，基于 EOB-MRI 的 mLI-RADS 更简单、更敏感，可用于 HCC，同时保持较高的阳性预测值。
2 技术功效：第 2 阶段。
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