背景：目前还不清楚多参数双能CT（DECT）提供的额外信息是否能够改善侵袭性宏观小梁-巨大（MTM）亚型肝细胞癌（HCC）的非侵入性诊断。目的：评估双相增强多参数DECT在预测MTM HCC方面的诊断性能。材料和方法：回顾性收集2019年6月至2022年6月期间接受对比增强DECT检查并经病理学检查证实HCC的患者，来自三个独立中心（中心1为训练和内部测试数据集，中心2和中心3为外部测试数据集）。对放射学特征进行视觉分析，并结合临床信息建立临床 - 放射学模型。基于来自双相上的虚拟单能量成像和材料成分成像的DL特征和手工特征提取的DL放射学模型，使用二值化最小绝对收缩和选择算子进行多变量logistic回归分析开发了DL放射学预测模型。采用受试者操作特征曲线下面积（AUC）评估模型性能，并使用对数秩检验分析无复发生存时间。结果：共纳入262例患者（平均年龄54岁 ± 12 [SD]；男性225例[86%]；训练数据集n = 146[56%]；内部测试数据集n = 35[13%]；外部测试数据集n = 81[31%]）。DL放射学预测模型在训练组中（AUC = 0.91对0.77，P < .001），内部测试数据集中（AUC = 0.87对0.72，P = .04），以及外部测试数据集中（AUC = 0.89对0.79，P = .02）更好地预测MTM，与临床 - 放射学模型相比，在外部测试数据集中具有类似的敏感性（80%对87%，P = .63），更高的特异性（90%对63%，P < .001）。在所有三个数据集中，DL放射学预测模型预测为MTM阳性组的复发无生存期较短（训练数据集P = .04；内部测试数据集P = .01；外部测试数据集P = .03）。结论：由多参数DECT推导的DL放射学预测模型能够准确预测HCC患者中的MTM亚型。© RSNA，2023 本文附有补充资料。本期编辑评论请参见Chu和Fishman的社论。

Background It is unknown whether the additional information provided by multiparametric dual-energy CT (DECT) could improve the noninvasive diagnosis of the aggressive macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC). Purpose To evaluate the diagnostic performance of dual-phase contrast-enhanced multiparametric DECT for predicting MTM HCC. Materials and Methods Patients with histopathologic examination-confirmed HCC who underwent contrast-enhanced DECT between June 2019 and June 2022 were retrospectively recruited from three independent centers (center 1, training and internal test data set; centers 2 and 3, external test data set). Radiologic features were visually analyzed and combined with clinical information to establish a clinical-radiologic model. Deep learning (DL) radiomics models were based on DL features and handcrafted features extracted from virtual monoenergetic images and material composition images on dual phase using binary least absolute shrinkage and selection operators. A DL radiomics nomogram was developed using multivariable logistic regression analysis. Model performance was evaluated with the area under the receiver operating characteristic curve (AUC), and the log-rank test was used to analyze recurrence-free survival. Results A total of 262 patients were included (mean age, 54 years ± 12 [SD]; 225 men [86%]; training data set, n = 146 [56%]; internal test data set, n = 35 [13%]; external test data set, n = 81 [31%]). The DL radiomics nomogram better predicted MTM than the clinical-radiologic model (AUC = 0.91 vs 0.77, respectively, for the training set [P < .001], 0.87 vs 0.72 for the internal test data set [P = .04], and 0.89 vs 0.79 for the external test data set [P = .02]), with similar sensitivity (80% vs 87%, respectively; P = .63) and higher specificity (90% vs 63%; P < .001) in the external test data set. The predicted positive MTM groups based on the DL radiomics nomogram had shorter recurrence-free survival than predicted negative MTM groups in all three data sets (training data set, P = .04; internal test data set, P = .01; and external test data set, P = .03). Conclusion A DL radiomics nomogram derived from multiparametric DECT accurately predicted the MTM subtype in patients with HCC. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Chu and Fishman in this issue.