Zhao Ludong, Wang Jing, Song Jinna, Zhang Fenghua, Liu Jinghua
Jinzhou Medical University Postgraduate Training Base of Linyi People's Hospital Linyi 276000, Shandong, P. R. China.
Department of General Surgery Center, Linyi People's Hospital Linyi 276000, Shandong, P. R. China.
Am J Transl Res. 2025 Mar 15;17(3):2031-2043. doi: 10.62347/TFRF1430. eCollection 2025.
To investigate the predictive value of serum alpha - fetoprotein (AFP), lectin-reactive alpha-fetoprotein (AFP-L3), and multimodal magnetic resonance imaging (MRI) radiomics in forecasting therapeutic efficacy and prognosis following radiofrequency ablation (RFA) in patients with hepatocellular carcinoma (HCC).
A retrospective analysis was conducted on HCC patients who underwent RFA between January 2019 and December 2023. Clinical and radiologic features of HCC were analyzed. A predictive model was developed using clinical data and radiomic features collected before surgery, with the goal of predicting prognosis after RFA. The predictive performance of the model was evaluated using AUC values in both training and validation cohorts.
A total of 298 HCC patients were included in the study, divided into a good prognosis group (n=145) and a poor prognosis group (n=153). Serum AFP and AFP-L3 levels were significantly higher in the poor prognosis group (P=0.007 and P=0.02, respectively). Independent predictive factors included: AFP-L3 (95% CI -1.228, -1.1.61; P<0.001), AFP (95% CI 0.017, 0.036; P<0.001), intratumoral hemorrhage (95% CI 0.380, 0.581; P<0.001), peritumoral arterial tumor enhancement (95% CI 0.193, 0.534; P<0.001) and low signal intensity around liver and gallbladder tumors (95% CI 0.267, 0.489; P<0.001). The combined clinical-radiological-radiomics model demonstrated superior predictive performance, with AUC value of 0.897 in the training set and 0.841 in the validation set, outperforming individual models and sequences.
The integrated clinical-radiological-radiomics model showed excellent predictive performance for the prognosis of HCC patients undergoing RFA, surpassing individual models. Key predictors included serum AFP, AFP-L3 levels, intratumoral hemorrhage, and peritumoral low signal intensity. This multimodal approach offers a promising tool for individualized prognostic assessment and improved clinical decision-making.
探讨血清甲胎蛋白(AFP)、凝集素反应性甲胎蛋白(AFP-L3)和多模态磁共振成像(MRI)影像组学在预测肝细胞癌(HCC)患者射频消融(RFA)治疗疗效及预后中的价值。
对2019年1月至2023年12月期间接受RFA治疗的HCC患者进行回顾性分析。分析HCC的临床和影像学特征。利用术前收集的临床数据和影像组学特征建立预测模型,旨在预测RFA后的预后。使用训练队列和验证队列中的AUC值评估模型的预测性能。
本研究共纳入298例HCC患者,分为预后良好组(n=145)和预后不良组(n=153)。预后不良组的血清AFP和AFP-L3水平显著更高(分别为P=0.007和P=0.02)。独立预测因素包括:AFP-L3(95%CI -1.228,-1.1.61;P<0.001)、AFP(95%CI 0.017,0.036;P<0.001)、瘤内出血(95%CI 0.380,0.581;P<0.001)、瘤周动脉肿瘤强化(95%CI 0.193,0.534;P<0.001)以及肝胆囊肿瘤周围低信号强度(95%CI 0.267,0.489;P<0.001)。临床-放射学-影像组学联合模型表现出卓越的预测性能,训练集的AUC值为0.897,验证集的AUC值为0.841,优于单个模型和序列。
临床-放射学-影像组学综合模型对接受RFA治疗的HCC患者的预后显示出优异的预测性能,优于单个模型。关键预测因素包括血清AFP、AFP-L3水平、瘤内出血和瘤周低信号强度。这种多模态方法为个体化预后评估和改善临床决策提供了一个有前景的工具。