Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China.
Clinical Trials Unit, The First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Road 2, Guangzhou, 510080, China.
Eur Radiol. 2021 Nov;31(11):8615-8627. doi: 10.1007/s00330-021-07941-7. Epub 2021 Apr 20.
Pretreatment evaluation of tumor biology and microenvironment is important to predict prognosis and plan treatment. We aimed to develop nomograms based on gadoxetic acid-enhanced MRI to predict microvascular invasion (MVI), tumor differentiation, and immunoscore.
This retrospective study included 273 patients with HCC who underwent preoperative gadoxetic acid-enhanced MRI. Patients were assigned to two groups: training (N = 191) and validation (N = 82). Univariable and multivariable logistic regression analyses were performed to investigate clinical variables and MRI features' associations with MVI, tumor differentiation, and immunoscore. Nomograms were developed based on features associated with these three histopathological features in the training cohort, then validated, and evaluated.
Predictors of MVI included tumor size, rim enhancement, capsule, percent decrease in T1 images (T1%), standard deviation of apparent diffusion coefficient, and alanine aminotransferase levels, while capsule, peritumoral enhancement, mean relaxation time on the hepatobiliary phase (T1), and alpha-fetoprotein levels predicted tumor differentiation. Predictors of immunoscore included the radiologic score constructed by tumor number, intratumoral vessel, margin, capsule, rim enhancement, T1%, relaxation time on plain scan (T1), and alpha-fetoprotein and alanine aminotransferase levels. Three nomograms achieved good concordance indexes in predicting MVI (0.754, 0.746), tumor differentiation (0.758, 0.699), and immunoscore (0.737, 0.726) in the training and validation cohorts, respectively.
MRI-based nomograms effectively predict tumor behaviors in HCC and may assist clinicians in prognosis prediction and pretreatment decisions.
• This study developed and validated three nomograms based on gadoxetic acid-enhanced MRI to predict MVI, tumor differentiation, and immunoscore in patients with HCC. • The pretreatment prediction of tumor microenvironment may be useful to guide accurate prognosis and planning of surgical and immunological therapies for individual patients with HCC.
肿瘤生物学和微环境的预处理评估对于预测预后和制定治疗计划非常重要。本研究旨在基于钆塞酸增强 MRI 建立预测微血管侵犯（MVI）、肿瘤分化和免疫评分的列线图。
本回顾性研究纳入了 273 例接受术前钆塞酸增强 MRI 的 HCC 患者。患者被分为两组：训练组（N=191）和验证组（N=82）。进行单变量和多变量逻辑回归分析，以研究临床变量和 MRI 特征与 MVI、肿瘤分化和免疫评分的相关性。基于训练队列中与这三种组织病理学特征相关的特征，建立列线图，然后进行验证和评估。
MVI 的预测因素包括肿瘤大小、边缘强化、包膜、T1 图像（T1%）减少百分比、表观扩散系数标准差和丙氨酸氨基转移酶水平，而包膜、肿瘤周围强化、肝胆期平均弛豫时间（T1）和甲胎蛋白水平则预测肿瘤分化。免疫评分的预测因素包括由肿瘤数量、肿瘤内血管、边缘、包膜、边缘强化、T1%、平扫 T1 弛豫时间（T1）和甲胎蛋白及丙氨酸氨基转移酶水平构建的影像学评分。在训练和验证队列中，三个列线图在预测 MVI（0.754、0.746）、肿瘤分化（0.758、0.699）和免疫评分（0.737、0.726）方面均取得了良好的一致性指数。
基于 MRI 的列线图可有效预测 HCC 中的肿瘤行为，有助于临床医生进行预后预测和术前决策。
本研究基于钆塞酸增强 MRI 建立了三个列线图，用于预测 HCC 患者的 MVI、肿瘤分化和免疫评分。
肿瘤微环境的术前预测可能有助于指导 HCC 患者个体化的准确预后和手术及免疫治疗方案的制定。
