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The Application Value of MRI TWI Radiomics Nomogram in Discriminating Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma
Computational and Mathematical Methods in Medicine Pub Date : 2022-9-27 , DOI: 10.1155/2022/7099476
Feng Huang 1 , Xiaoyun Liu 1 , Peng Liu 1 , Dan Xu 1 , Zeda Li 1 , Huashan Lin 2 , An Xie 1
Affiliation  

Objective. To establish and validate an MRI TWI-based radiomics nomogram model and to discriminate hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICCA). Methods. 174 patients were retrospectively collected, who were diagnosed with primary hepatic carcinoma by surgery or puncture pathology and received preoperative MRI scans including TWI scans. There were 113 cases of HCC and 61 cases of mass-type ICCA. TWI was used for feature extraction, the extent of the lesions was manually outlined at the largest lesions layer of the TWI, 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. Results. 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. Conclusion. Radiomics nomogram model based on MRI TWI scan without enhancement can be used to discriminate HCC from ICCA.

中文翻译:

MRI TWI放射组学列线图在鉴别肝细胞癌和肝内胆管癌中的应用价值

客观。建立和验证基于 MRI T WI 的放射组学列线图模型,并区分肝细胞癌 (HCC) 和肝内胆管癌 (ICCA)。方法。回顾性收集经手术或穿刺病理诊断为原发性肝癌的174例患者,并接受了包括T WI扫描在内的术前MRI扫描。HCC 113 例,肿块型ICCA 61 例。使用T WI进行特征提取,在T的最大病灶层手动勾勒病灶范围WI,并通过mRMR和LASSO进行特征降维以获得最优特征集。结合放射组学特征和临床危险因素建立放射组学列线图模型。在训练组和验证组中,应用校准曲线和 ROC 曲线来验证所建立模型的有效性。最后,应用校准曲线评估拟合程度,并应用 DCA 评估所建立模型的临床效用。结果. 放射组学模型在训练组和验证组中的 AUC 分别为 0.90(95% CI,0.85-0.96)和 0.91(95% CI,0.83-0.99);训练组放射组学列线图的 AUC 为 0.97(95% CI,0.94-0.99),验证组为 0.95(95% CI,0.95-0.99)。DCA 提出了列线图模型的临床应用价值。结论。基于MRI T WI无增强扫描的放射组学列线图模型可用于区分HCC和ICCA。
更新日期:2022-09-27
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