Department of Radiology, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha 410005, China.
Department of Pharmaceutical Diagnosis, GE Healthcare, Changsha 410005, China.
Comput Math Methods Med. 2022 Sep 27;2022:7099476. doi: 10.1155/2022/7099476. eCollection 2022.
To establish and validate an MRI T2WI-based radiomics nomogram model and to discriminate hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICCA).
174 patients were retrospectively collected, who were diagnosed with primary hepatic carcinoma by surgery or puncture pathology and received preoperative MRI scans including T2WI scans. There were 113 cases of HCC and 61 cases of mass-type ICCA. T2WI was used for feature extraction, the extent of the lesions was manually outlined at the largest lesions layer of the T2WI, and the feature dimension reduction was performed by the mRMR and LASSO to obtain the optimal feature set. The radiomics features and clinical risk factors were combined to establish the radiomics nomogram model. In both training and validation groups, calibration curves and ROC curves were applied to validate the efficacy of the established model. Finally, calibration curves were applied to assess the degree of fitting and DCA to assess the clinical utility of the established model.
The radiomics model had the AUC of 0.90 (95% CI, 0.85-0.96) and 0.91 (95% CI, 0.83-0.99) in the training and validation groups, respectively; the AUC of the radiomics nomogram was 0.97 (95% CI, 0.94-0.99) in the training group and 0.95 (95% CI, 0.95-0.99) in the validation group. DCA suggested the clinical application value of the nomogram model.
Radiomics nomogram model based on MRI T2WI scan without enhancement can be used to discriminate HCC from ICCA.
建立并验证一种基于 MRI T2WI 的放射组学列线图模型，以区分肝细胞癌（HCC）和肝内胆管细胞癌（ICCA）。
回顾性收集了 174 名经手术或穿刺病理诊断为原发性肝癌并接受术前 MRI 扫描（包括 T2WI 扫描）的患者。其中 113 例为 HCC，61 例为肿块型 ICCA。使用 T2WI 进行特征提取，在 T2WI 的最大病变层手动勾勒病变范围，并通过 mRMR 和 LASSO 进行特征降维，以获得最佳特征集。将放射组学特征与临床危险因素相结合，建立放射组学列线图模型。在训练组和验证组中，均应用校准曲线和 ROC 曲线验证模型的疗效。最后，应用校准曲线评估模型的拟合程度，应用 DCA 评估模型的临床实用性。
在训练组和验证组中，放射组学模型的 AUC 分别为 0.90（95%CI，0.85-0.96）和 0.91（95%CI，0.83-0.99）；放射组学列线图模型在训练组中的 AUC 为 0.97（95%CI，0.94-0.99），在验证组中的 AUC 为 0.95（95%CI，0.95-0.99）。DCA 提示了该列线图模型的临床应用价值。
基于 MRI T2WI 平扫的放射组学列线图模型可用于区分 HCC 和 ICCA。
