Li Zongwen, Song Wenlong, Zhang Jiayan, Li Qian, Song Zuhua, Ren Xiaofang, Wen Youjia, Li Xintong, Yao Hui, Gao Yunjing, Tang Zhuoyue
Chongqing Medical University, Chongqing, China.
Department of Radiology, Chongqing General Hospital, Chongqing, China.
Quant Imaging Med Surg. 2024 Dec 5;14(12):8586-8600. doi: 10.21037/qims-24-315. Epub 2024 Oct 17.
The value of Liver Imaging Reporting and Data System (LI-RADS) radiological features and tumor three-dimensional volumetric quantification in preoperative magnetic resonance imaging (MRI) for predicting the vessels encapsulating tumor clusters (VETC) pattern of solitary hepatocellular carcinoma (HCC) is unknown. This study aimed to assess the value of these indicators for predicting the VETC pattern of solitary HCC.
In total, 36 patients with HCC were selected from a cohort containing 126 patients for further data evaluation. VETC was evaluated by histopathologists, and the three-dimensional tumor volume (TV) was analyzed in the arterial phase (AP) and portal venous phase. LI-RADS radiological characteristics were defined on the basis of LI-RADS version 2018. Quantitative parameters were derived from multiparametric MRI data. Significant MRI biomarkers for predicting VETC-positive status in solitary HCC were ascertained via logistic regression analysis. A nomogram was accordingly constructed and evaluated in terms of discrimination, calibration, clinical utility, and accuracy.
A total of 15 cases were VETC positive, while 21 cases were VETC negative. The values for nodule-in-nodule architecture, mosaic architecture, total liver volume, TV, necrosis tumor volumetric percentage, necrosis tumor burden, and tumor-to-liver signal intensity (SI) ratio on AP images were higher in VETC-positive HCCs than in VETC-negative HCCs (P<0.05). Multivariate logistic analysis indicated that necrosis tumor volumetric percentage, tumor-to-liver SI ratio on AP images, and nodule-in-nodule architecture were independent predictive factors of VETC status (P<0.05). The calibration and discrimination performance of the nomogram were good, with an area under curve of 0.942, and the prediction accuracy was a satisfactory 88.89%, indicating that the nomogram possessed potential clinical benefits.
Preoperative MRI features possess the potential to identify VETC pattern in solitary HCC.
肝脏影像报告和数据系统（LI-RADS）的放射学特征及肿瘤三维体积定量在术前磁共振成像（MRI）中对预测孤立性肝细胞癌（HCC）的肿瘤簇包绕血管（VETC）模式的价值尚不清楚。本研究旨在评估这些指标对预测孤立性HCC的VETC模式的价值。
从126例患者的队列中选取36例HCC患者进行进一步的数据评估。VETC由组织病理学家评估，在动脉期（AP）和门静脉期分析肿瘤三维体积（TV）。基于LI-RADS 2018版定义LI-RADS放射学特征。从多参数MRI数据中得出定量参数。通过逻辑回归分析确定预测孤立性HCC中VETC阳性状态的重要MRI生物标志物。据此构建列线图，并在区分度、校准度、临床实用性和准确性方面进行评估。
共15例VETC阳性，21例VETC阴性。VETC阳性的HCC在AP图像上的结节内结节结构、镶嵌结构、全肝体积、TV、坏死肿瘤体积百分比、坏死肿瘤负荷以及肿瘤与肝脏信号强度（SI）比值的值高于VETC阴性的HCC（P<0.05）。多因素逻辑分析表明，坏死肿瘤体积百分比、AP图像上肿瘤与肝脏的SI比值以及结节内结节结构是VETC状态的独立预测因素（P<0.05）。列线图的校准和区分性能良好，曲线下面积为0.942，预测准确率为88.89%，令人满意，表明该列线图具有潜在的临床益处。
术前MRI特征具有识别孤立性HCC中VETC模式的潜力。
