Li Yiman, Li Xiaofeng, Xiao Xixi, Cheng Jie, Li Qingrui, Liu Chen, Cai Ping, Chen Wei, Zhang Huarong, Li Xiaoming
7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Department of Radiology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Eur Radiol. 2025 Jun;35(6):3206-3222. doi: 10.1007/s00330-024-11255-9. Epub 2024 Dec 10.
To develop a novel hybrid model for preoperative prediction of tertiary lymphoid structures (TLSs) of hepatocellular carcinoma (HCC), and to identify patients who may benefit from postoperative targeted immunotherapy.
Retrospective data were gathered from 332 patients with HCC who underwent surgical resection and gadoxetate disodium (Gd-EOB-DTPA) enhanced MRI at two tertiary hospitals (training cohort, n = 205; internal validation cohort, n = 90; and external validation cohort, n = 37) between March 2020 and January 2023. Radiomic features were extracted from Gd-EOB-DTPA-enhanced MRI sequences. These signatures were integrated with clinical-radiologic (CR) factors into a hybrid model and nomogram for clinical application. The performance of the model was assessed using the area under the curve (AUC) and 95% confidence intervals (CI).
The hybrid model outperformed the radiomics and CR models in the training cohort (AUC = 0.860 [95% CI: 0.805, 0.904], 0.784 [95% CI: 0.721, 0.838], and 0.809 [95% CI: 0.748, 0.860]). The hybrid model showed optimal performance, with AUCs of 0.823 (95% CI: 0.728, 0.895) and 0.875 (95% CI: 0.725, 0.960) in the internal and external validation cohorts, respectively. The calibration curve demonstrated that the nomogram had good diagnostic ability, and decision curve analysis indicated good clinical utility across all cohorts. Importantly, patients with a predicted high risk of TLSs from the hybrid model gained a survival benefit from targeted immunotherapy.
The hybrid model showed satisfactory performance in predicting intra-tumoral TLS positivity and targeted immunotherapy benefit in patients with HCC, potentially assisting clinicians in selecting precise individualized therapies.
Question How can accurate preoperative risk stratification of tertiary lymphoid structures positivity HCC be achieved to support targeted immunotherapy decision-making? Findings A hybrid model combining radiomics model and clinical-radiological model may be a reliable marker for predicting tertiary lymphoid structures positivity HCC. Clinical relevance Using this hybrid model may be useful in predicting tertiary lymphoid structures and screening candidate patients for targeted immunotherapy based on multiparametric MRI, which has potential clinical value in guiding clinical decision-making and improving patient outcomes.
建立一种用于术前预测肝细胞癌（HCC）三级淋巴结构（TLSs）的新型混合模型，并识别可能从术后靶向免疫治疗中获益的患者。
回顾性收集2020年3月至2023年1月期间在两家三级医院接受手术切除并进行钆塞酸二钠（Gd-EOB-DTPA）增强MRI检查的332例HCC患者的数据（训练队列，n = 205；内部验证队列，n = 90；外部验证队列，n = 37）。从Gd-EOB-DTPA增强MRI序列中提取影像组学特征。将这些特征与临床放射学（CR）因素整合到一个混合模型和列线图中以供临床应用。使用曲线下面积（AUC）和95%置信区间（CI）评估模型的性能。
在训练队列中，混合模型的表现优于影像组学模型和CR模型（AUC分别为0.860 [95% CI：0.805, 0.904]、0.784 [95% CI：0.721, 0.838]和0.809 [95% CI：0.748, 0.860]）。混合模型表现出最佳性能，在内部和外部验证队列中的AUC分别为0.823（95% CI：0.728, 0.895）和0.875（95% CI：0.725, 0.960）。校准曲线表明列线图具有良好的诊断能力，决策曲线分析表明在所有队列中均具有良好的临床实用性。重要的是，混合模型预测TLSs高风险的患者从靶向免疫治疗中获得了生存益处。
混合模型在预测HCC患者肿瘤内TLS阳性和靶向免疫治疗获益方面表现出令人满意的性能，可能有助于临床医生选择精确的个体化治疗。
问题如何实现对三级淋巴结构阳性HCC进行准确的术前风险分层以支持靶向免疫治疗决策？研究结果将影像组学模型和临床放射学模型相结合的混合模型可能是预测三级淋巴结构阳性HCC的可靠标志物。临床意义使用这种混合模型可能有助于基于多参数MRI预测三级淋巴结构并筛选靶向免疫治疗的候选患者，这在指导临床决策和改善患者预后方面具有潜在的临床价值。
