Sun Shu-Wen, Liu Qiu-Ping, Xu Xun, Zhu Fei-Peng, Zhang Yu-Dong, Liu Xi-Sheng
Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
J Magn Reson Imaging. 2020 Aug;52(2):433-447. doi: 10.1002/jmri.27043. Epub 2020 Jan 13.
Microvascular invasion (MVI) is implicated in the poor prognosis of hepatocellular carcinoma (HCC). Presurgical stratifying schemes have been proposed for HCC-MVI but lack external validation.
To perform external validation and comparison of four presurgical stratifying schemes for the prediction of MVI using gadoxetic acid-based MRI in a cohort of HCC patients.
Retrospective.
Included were 183 surgically resected HCCs from patients who underwent pretreatment MRI.
FIELD STRENGTH/SEQUENCE: This includes 1.5-3.0 T with T , T , diffusion-weighted imaging (DWI), and dynamic gadoxetic acid contrast-enhancement imaging sequences.
A two-trait predictor of venous invasion (TTPVI), Lei model, Lee model, and Xu model were compared. We relied on preoperative characteristics and imaging findings via four independent radiologists who were blinded to histologic results, as required by the tested tools.
Tests of accuracy between predicted and observed HCC-MVI rates using receiver operating characteristic (ROC) curve and decision curve analysis. The intraclass correlation coefficient (ICC) and Cronbach's alpha statistics were used to evaluate reproducibility.
HCC-MVI was identified in 52 patients (28.4%). The average ROC curves (AUCs) for HCC-MVI predictions were 0.709-0.880, 0.714-0.828, and 0.588-0.750 for the Xu model, Lei model, and Lee model, respectively. The rates of accuracy were 60.7-81.4%, 69.9-75.9%, and 65.6-73.8%, respectively. Decision curve analyses indicated a higher benefit for the Xu and Lei models compared to the Lee model. The ICC and Cronbach's alpha index were highest in the Lei model (0.896/0.943), followed by the Xu model (0.882/0.804), and the Lee model (0.769/0.715). The TTPVI resulted in a Cronbach's alpha index of 0.606 with a sensitivity of 34.6-61.5% and a specificity of 76.3-91.6%.
Stratifying schemes relying on gadoxetic acid-enhanced MRI provide an additional insight into the presence of preoperative MVI. The Xu model outperformed the other models in terms of accuracy when performed by an experienced radiologist. Conversely, the Lei model outperformed the other models in terms of reproducibility.
3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:433-447.
微血管侵犯(MVI)与肝细胞癌(HCC)的不良预后有关。已经提出了针对HCC-MVI的术前分层方案,但缺乏外部验证。
在一组HCC患者中,对基于钆塞酸的MRI预测MVI的四种术前分层方案进行外部验证和比较。
回顾性研究。
纳入了183例接受过术前MRI检查且接受手术切除的HCC患者。
场强/序列:包括1.5 - 3.0 T的T1、T2、扩散加权成像(DWI)和动态钆塞酸对比增强成像序列。
比较了静脉侵犯双特征预测指标(TTPVI)、雷模型、李模型和徐模型。根据测试工具的要求,由四位对组织学结果不知情的独立放射科医生依据术前特征和影像表现进行判断。
使用受试者操作特征(ROC)曲线和决策曲线分析来检验预测的和观察到的HCC-MVI发生率之间的准确性。使用组内相关系数(ICC)和克朗巴哈系数统计量来评估可重复性。
52例患者(28.4%)被诊断为HCC-MVI。徐模型、雷模型和李模型对HCC-MVI预测的平均ROC曲线下面积(AUC)分别为0.709 - 0.880、0.714 - 0.828和0.588 - 0.750。准确率分别为60.7% - 81.4%、69.9% - 75.9%和65.6% - 73.8%。决策曲线分析表明,与李模型相比,徐模型和雷模型的获益更高。ICC和克朗巴哈系数在雷模型中最高(0.896/0.943),其次是徐模型(0.882/0.804),李模型(0.769/0.715)。TTPVI的克朗巴哈系数为0.606,敏感性为34.6% - 61.5%,特异性为76.3% - 91.6%。
基于钆塞酸增强MRI的分层方案为术前MVI的存在提供了额外的见解。由经验丰富的放射科医生执行时,徐模型在准确性方面优于其他模型。相反,雷模型在可重复性方面优于其他模型。
3级 技术效能阶段:2级 《磁共振成像杂志》2020年;52:433 - 447