背景 识别肝切除后晚期肝细胞癌 (HCC) 复发高风险的患者可能会提高患者的生存率。目的 开发一个包含 MRI 特征的模型，用于预测术后晚期 HCC 复发。材料和方法 这项单中心回顾性研究包括连续接受术前对比增强 MRI 和治疗性切除术的早中期 HCC 成年患者（2011 年 12 月至 2021 年 4 月）。三名放射科医生评估了 MRI 扫描的 52 个定性特征。在训练集中，进行了细灰色比例次分布风险分析，以确定要包含在预测模型中的临床、实验室、影像、病理和手术变量。在测试集中，计算了一致性指数（C 指数），以将开发的模型与当前的分期系统进行比较。使用对数秩检验比较 Kaplan-Meier 生存曲线。结果 该研究包括 532 名患者（中位年龄 54 岁；IQR 46-62 岁；465 名男性患者），训练组中的 302 名患者（中位年龄 54 岁；IQR 46-63 岁；265 名男性患者），测试集中的 128 名患者（中位年龄 53 岁；IQR 46-63 岁；108 名男性患者）。训练组和测试组的 302 名患者中分别有 38 名 (12.6%) 和 128 名患者中有 15 名 (11.7%) 出现晚期复发。血清中性粒细胞计数 (109/L)、肿瘤大小（厘米）和 MRI 扫描动脉期过度增强比例与晚期复发相关（亚分布风险比范围，1.16-3.83；95% CI：1.02，7.52；P值范围，<.001 至 .02）并包含在预测模型中。该模型对晚期复发的测试集预测优于四种分期系统（2 年 C 指数，0.82 [95% CI：0.74，0.91] vs 0.63-0.68 [95% CI：0.52，0.82]；P 值范围，.001-.03)。与 HCC 复发低风险患者相比，HCC 复发高风险患者（模型评分≥15 分）的晚期复发率更高，全期无复发生存期 (RFS)、晚期 RFS 和总生存期更差（P 值范围，<.001 至 .02）。结论 结合血清中性粒细胞计数、肿瘤大小和动脉期高增强比例的模型比当前分期系统更好地预测晚期 HCC 复发，并且可以识别高风险患者。根据 CC BY 4.0 许可证发布。本文提供了补充材料。另请参阅本期 Tsai 和 Mellnick 的社论。

Background Identifying patients at high risk for advanced-stage hepatocellular carcinoma (HCC) recurrence after liver resection may improve patient survival. Purpose To develop a model including MRI features for predicting postoperative advanced-stage HCC recurrence. Materials and Methods This single-center, retrospective study includes consecutive adult patients who underwent preoperative contrast-enhanced MRI and curative-intent resection for early- to intermediate-stage HCC (from December 2011 to April 2021). Three radiologists evaluated 52 qualitative features on MRI scans. In the training set, Fine-Gray proportional subdistribution hazard analysis was performed to identify clinical, laboratory, imaging, pathologic, and surgical variables to include in the predictive model. In the test set, the concordance index (C-index) was computed to compare the developed model with current staging systems. The Kaplan-Meier survival curves were compared using the log-rank test. Results The study included 532 patients (median age, 54 years; IQR, 46-62 years; 465 male patients), 302 patients from the training set (median age, 54 years; IQR, 46-63 years; 265 male patients), and 128 patients from the test set (median age, 53 years; IQR, 46-63 years; 108 male patients). Advanced-stage recurrence was observed in 38 of 302 (12.6%) and 15 of 128 (11.7%) of patients from the training and test sets, respectively. Serum neutrophil count (109/L), tumor size (in centimeters), and arterial phase hyperenhancement proportion on MRI scans were associated with advanced-stage recurrence (subdistribution hazard ratio range, 1.16-3.83; 95% CI: 1.02, 7.52; P value range, <.001 to .02) and included in the predictive model. The model showed better test set prediction for advanced-stage recurrence than four staging systems (2-year C-indexes, 0.82 [95% CI: 0.74, 0.91] vs 0.63-0.68 [95% CI: 0.52, 0.82]; P value range, .001-.03). Patients at high risk for HCC recurrence (model score, ≥15 points) showed increased advanced-stage recurrence and worse all-stage recurrence-free survival (RFS), advanced-stage RFS, and overall survival than patients at low risk for HCC recurrence (P value range, <.001 to .02). Conclusion A model combining serum neutrophil count, tumor size, and arterial phase hyperenhancement proportion predicted advanced-stage HCC recurrence better than current staging systems and may identify patients at high risk. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Tsai and Mellnick in this issue.