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中华肺部疾病杂志(电子版) ›› 2026, Vol. 19 ›› Issue (04) : 705 -709. doi: 10.3877/cma.j.issn.1674-6902.2026.04.028

综述

基于CT影像学评估非小细胞肺癌免疫治疗疗效的研究进展
李秋韵, 王爽()   
  1. 400037 重庆,陆军(第三)军医大学第二附属医院放射科
  • 收稿日期:2026-02-12 出版日期:2026-08-25
  • 通信作者: 王爽

Research progress on the evaluation of immunotherapy efficacy of non-small cell lung cancer based on CT imaging

Qiuyun Li, Shuang Wang()   

  • Received:2026-02-12 Published:2026-08-25
  • Corresponding author: Shuang Wang
引用本文:

李秋韵, 王爽. 基于CT影像学评估非小细胞肺癌免疫治疗疗效的研究进展[J/OL]. 中华肺部疾病杂志(电子版), 2026, 19(04): 705-709.

Qiuyun Li, Shuang Wang. Research progress on the evaluation of immunotherapy efficacy of non-small cell lung cancer based on CT imaging[J/OL]. Chinese Journal of Lung Diseases(Electronic Edition), 2026, 19(04): 705-709.

免疫检查点抑制剂(immune checkpoint inhibitors, ICIs)明显改善非小细胞肺癌(non-small cell lung cancer, NSCLC)患者的生存状况,但其疗效存在个体差异,因此急需一种可靠的无创评定方法。基于CT的影像学方法通过整合形态学、功能及代谢信息,在评估免疫治疗的疗效时有着重要意义。常规CT是临床上随访的基本工具,但其主要依赖肿瘤大小变化。双能CT可以定量分析血液供应量和物质含量,给肿瘤微环境的评价带来额外的信息,而正电子发射断层显像/X线计算机体层成像仪(positron emission tomography/computed tomography, PET/CT)从代谢角度来表现肿瘤的生物学特性,有益于判断免疫治疗的效果以及预测病情的发展。近年来,随着人工智能(artificial intelligence, AI)的应用,影像组学和深度学习加强了对肿瘤空间异质性,动态变化以及多模态信息的表达能力。基于CT的AI模型有望构建无创影像生物标志物,为NSCLC免疫治疗的个体化决策提供更加精准的影像学支持。

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