目标：本研究旨在调查基于Δ放射组学模型的多相增强磁共振成像（CE-MRI）对于鉴别糖蛋白3（GPC3）阳性肝细胞癌（HCC）的价值。方法：回顾性纳入了126例经病理学证实的HCC患者（训练队列：n = 88，验证队列：n = 38）。从病历中获取基本信息。复查术前多相CE-MRI图像，对非对比T1加权成像（T1）、动脉期（AP）、门静脉期（PVP）、延迟期（DP）和肝胆期（HBP）上肿瘤的三维兴趣区域（VOIs）进行勾画。从每个期相提取107个原始放射组学特征，计算Δ放射组学特征。经过两步特征选择策略后，使用两种分类算法构建放射组学模型。通过组合最佳放射组学模型和临床危险因素构建了诊断模型。结果：血清甲胎蛋白（AFP）（p = 0.013）与GPC3阳性HCC显著相关。最佳放射组学模型由八个Δ放射组学特征组成，训练队列和验证队列的AUC分别为0.805和0.857。诊断模型将放射组学评分和AFP很好地结合起来（训练队列：AUC = 0.844，验证队列：AUC = 0.862）。校准曲线显示预测概率和GPC3实际表达在训练队列和验证队列中具有良好的一致性。决策曲线分析进一步证明了诊断模型的临床实用性。结论：基于Δ放射组学模型的多相CE-MRI能够非侵入性地预测GPC3阳性HCC，可作为个体化诊断和治疗的有用方法。版权所有 © 2023 Han, Dai, Chen, Gao, Chen, Yan, Ye和李。

Objectives: The aim of this study is to investigate the value of multi-phase contrast-enhanced magnetic resonance imaging (CE-MRI) based on the delta radiomics model for identifying glypican-3 (GPC3)-positive hepatocellular carcinoma (HCC). Methods: One hundred and twenty-six patients with pathologically confirmed HCC (training cohort: n = 88 and validation cohort: n = 38) were retrospectively recruited. Basic information was obtained from medical records. Preoperative multi-phase CE-MRI images were reviewed, and the 3D volumes of interest (VOIs) of the whole tumor were delineated on non-contrast T1-weighted imaging (T1), arterial phase (AP), portal venous phase (PVP), delayed phase (DP), and hepatobiliary phase (HBP). One hundred and seven original radiomics features were extracted from each phase, and delta-radiomics features were calculated. After a two-step feature selection strategy, radiomics models were built using two classification algorithms. A nomogram was constructed by combining the best radiomics model and clinical risk factors. Results: Serum alpha-fetoprotein (AFP) (p = 0.013) was significantly related to GPC3-positive HCC. The optimal radiomics model is composed of eight delta-radiomics features with the AUC of 0.805 and 0.857 in the training and validation cohorts, respectively. The nomogram integrated the radiomics score, and AFP performed excellently (training cohort: AUC = 0.844 and validation cohort: AUC = 0.862). The calibration curve showed good agreement between the nomogram-predicted probabilities and GPC3 actual expression in both training and validation cohorts. Decision curve analysis further demonstrates the clinical practicality of the nomogram. Conclusion: Multi-phase CE-MRI based on the delta-radiomics model can non-invasively predict GPC3-positive HCC and can be a useful method for individualized diagnosis and treatment.Copyright © 2023 Han, Dai, Chen, Gao, Chen, Yan, Ye and Li.