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    • 基于增强CT影像组学特征预测难治性恶性黑色素瘤肺转移患者的免疫治疗疗效

    崔传亮,朱海涛, 常燃,高顺禹,李晓婷,侯芳婧,孙应实

    Chinese Journal of Medical Imaging Technology（2021）

    Cited 1|Views16
    Abstract
    目的 探讨基于胸部增强CT影像组学特征预测免疫治疗用于难治性恶性黑色素瘤肺转移疗效的价值.方法 回顾性分析49例难治性恶性黑色素瘤肺内转移患者,均接受程序性死亡受体(PD-1)单抗免疫治疗,采用实体瘤疗效评价标准(RECIST)1.1评价疗效,并将患者分为进展组(n=17)和未进展组[n= 32,包括稳定组(n=16)及部分缓解组(n=16)].提取免疫治疗前增强CT图像中肺转移病灶信息,以3D-Slicer软件手动逐层勾画整个病灶并进行分割;采用Pyradiomics程序提取病灶形状特征、灰度一阶特征、纹理特征和小波特征,以Pearson相关性分析和递归式特征消除策略进行降维.以支持向量机(SVM)方法建立分类模型,预测病变进展的可能性.绘制受试者工作特征(ROC)曲线,评价模型预测进展组、非进展组的效能.结果 对每个靶病灶提取841个增强CT影像组学特征,最终筛选出3个影像组学纹理特征,分别为wavelet-HHH_glszm_Low Gray Level Zone Emphasis、wavelet-HHL_first order Skewness 和 wavelet-LLL_gldm_Small Dependence High Gray Level Emphasis,用于构建影像组学模型.模型预测训练组病变进展的曲线下面积(AUC)为0.913[(95％CI(0.777,1.000)],测试组为0.860[95％CI(0.643,1.000)];预测训练组病变进展的敏感度、特异度、准确率、阳性预测值和阴性预测值分别为83.3％、95.5％、91.2％、90.9％和91.3％,测试组分别为80.0％、80.0％、80.0％、66.7％和88.9％.结论 基于治疗前胸部增强CT影像组学特征建立的模型对恶性黑色素瘤肺转移免疫治疗疗效具有较好预测价值.
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