Zhao Xiangtian, Zhou Yukun, Zhang Yuan, Han Lujun, Mao Li, Yu Yizhou, Li Xiuli, Zeng Mengsu, Wang Mingliang, Liu Zaiyi
Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Front Oncol. 2021 Oct 13;11:744756. doi: 10.3389/fonc.2021.744756. eCollection 2021.
This study aims to develop and externally validate a contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics-based model for preoperative differentiation between fat-poor angiomyolipoma (fp-AML) and hepatocellular carcinoma (HCC) in patients with noncirrhotic livers and to compare the diagnostic performance with that of two radiologists.
This retrospective study was performed with 165 patients with noncirrhotic livers from three medical centers. The dataset was divided into a training cohort ( = 99), a time-independent internal validation cohort ( = 24) from one center, and an external validation cohort ( = 42) from the remaining two centers. The volumes of interest were contoured on the arterial phase (AP) images and then registered to the venous phase (VP) and delayed phase (DP), and a total of 3,396 radiomics features were extracted from the three phases. After the joint mutual information maximization feature selection procedure, four radiomics logistic regression classifiers, including the AP model, VP model, DP model, and combined model, were built. The area under the receiver operating characteristic curve (AUC), diagnostic accuracy, sensitivity, and specificity of each radiomics model and those of two radiologists were evaluated and compared.
The AUCs of the combined model reached 0.789 (95%CI, 0.579-0.999) in the internal validation cohort and 0.730 (95%CI, 0.563-0.896) in the external validation cohort, higher than the AP model (AUCs, 0.711 and 0.638) and significantly higher than the VP model (AUCs, 0.594 and 0.610) and the DP model (AUCs, 0.547 and 0.538). The diagnostic accuracy, sensitivity, and specificity of the combined model were 0.708, 0.625, and 0.750 in the internal validation cohort and 0.619, 0.786, and 0.536 in the external validation cohort, respectively. The AUCs for the two radiologists were 0.656 and 0.594 in the internal validation cohort and 0.643 and 0.500 in the external validation cohort. The AUCs of the combined model surpassed those of the two radiologists and were significantly higher than that of the junior one in both validation cohorts.
The proposed radiomics model based on triple-phase CE-MRI images was proven to be useful for differentiating between fp-AML and HCC and yielded comparable or better performance than two radiologists in different centers, with different scanners and different scanning parameters.
本研究旨在开发并外部验证一种基于对比增强磁共振成像（CE-MRI）的放射组学模型，用于非肝硬化肝脏患者术前鉴别乏脂性血管平滑肌脂肪瘤（fp-AML）和肝细胞癌（HCC），并将其诊断性能与两名放射科医生的诊断性能进行比较。
本回顾性研究纳入了来自三个医疗中心的165例非肝硬化肝脏患者。数据集被分为一个训练队列（n = 99）、来自一个中心的时间独立内部验证队列（n = 24）和来自其余两个中心的外部验证队列（n = 42）。在动脉期（AP）图像上勾勒出感兴趣体积，然后将其配准到静脉期（VP）和延迟期（DP），并从三个阶段共提取3396个放射组学特征。经过联合互信息最大化特征选择程序后，构建了四个放射组学逻辑回归分类器，包括AP模型、VP模型、DP模型和联合模型。评估并比较了每个放射组学模型以及两名放射科医生的受试者操作特征曲线下面积（AUC）、诊断准确性、敏感性和特异性。
联合模型在内部验证队列中的AUC为0.789（95%CI：0.579 - 0.999），在外部验证队列中的AUC为0.730（95%CI：0.563 - 0.896），高于AP模型（AUC分别为0.711和0.638），且显著高于VP模型（AUC分别为0.594和0.610）以及DP模型（AUC分别为0.547和0.538）。联合模型在内部验证队列中的诊断准确性、敏感性和特异性分别为0.708、0.625和0.750，在外部验证队列中分别为0.619、0.786和0.536。两名放射科医生在内部验证队列中的AUC分别为0.6... 展开全部内容，字数有限制，完整内容看这里：https://www.51test.net/show/11087772.html 0.656和0.594，在外部验证队列中分别为0.643和0.500。联合模型的AUC超过了两名放射科医生的AUC，并且在两个验证队列中均显著高于资历较浅的放射科医生。
基于三相CE-MRI图像提出的放射组学模型被证明可用于区分fp-AML和HCC，并且在不同中心、使用不同扫描仪和不同扫描参数的情况下，其性能与两名放射科医生相当或更优。
