Euro Radio:用于预测食管癌患者无病生存期和总生存期的MR放射组学模型

2022-08-20 shaosai MedSci原创

放射组学的应用为预测癌症患者的预后提供了一种新的评估方法。

统计食道癌(EC)的发病率在全球排名第七,总死亡率排名第六。食道癌是中国最常见的恶性肿瘤之一,90%以上的食道癌是鳞状细胞癌(ESCC)。尽管有报道称EC的总体5年生存率已从20世纪60年代的不足5%上升到近10年的约20%,但晚期患者的生存率仍不令人满意。

根据疾病的不同阶段,ESCC的治疗包括手术、新辅助化疗和化放疗。然而,由于早期ESCC的临床表现并不明显,大多数患者被诊断为晚期且无法切除。肿瘤的早期发现可以大大改善ESCC患者的生存率。此外,相当一部分患者在治疗后会出现复发。因此,确定与复发有关的预测因素,可以采取个性化的治疗和随访策略,从而延长生存期。

放射组学的应用为预测癌症患者的预后提供了一种新的评估方法。目前关于ESCC的放射组学研究大多基于CT,基于PET的放射组学研究也越来越多。然而,术前的MRI放射组学特征会更有价值,具有更高的组织分辨率,但很少有研究涉及。

近日,发表在European Radiology杂志的一项研究从基于1毫米各向异性-3D对比增强StarVIBE序列的MRI图像中提取了放射组学特征。并将其与临床风险因素相结合,构建了一个预测ESCC患者生存的最佳模型。

本研究收集了2015年至2017年期间本机构的ESCC患者,并按7:3的比例随机分配到训练组和验证组。采用随机生存森林(RSF)和变量狩猎法筛选放射组学特征,并采用LASSO-Cox回归分析建立三种模型,包括仅临床模型、仅放射组学模型和临床与放射组学联合模型,通过一致性指数(CI)和校准曲线进行评估。使用列线图和决策曲线分析(DCA)来显示直观的预测信息。 

从434名患者中选出7个放射组学特征,结合具有统计学意义的临床特征构建无病生存(DFS)和总生存(OS)的预测模型。综合模型在训练组和验证组中预测DFS([CI],0.714,0.729)和OS([CI],0.730,0.712)的性能最高。DCA显示,在不同的阈值概率下,联合模型和临床模型的净收益明显高于单独的放射组学模型。 


 所有队列中列线图的校准曲线。A联合模型提名图预测DFS的校准曲线。B联合模型提名图预测OS的校准曲线

本研究表明,基于MRI的放射组学和临床因素相结合的模型可以提高ESCC患者的生存预测性能。

原文出处:

Funing Chu,Yun Liu,Qiuping Liu,et al.Development and validation of MRI-based radiomics signatures models for prediction of disease-free survival and overall survival in patients with esophageal squamous cell carcinoma.DOI:10.1007/s00330-022-08776-6

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