Advances in Multimodal Imaging Techniques for Evaluating and Predicting the Efficacy of Immunotherapy for NSCLC

作者：Jingyi Liu, Mei Xie, Jing Shen, Jie Yao, Xuwen Lin, Xinyu Bao, Xin Zhang, Yiran Liang, Yunsheng Yang, Gege Jiang, Ximeng Diao, Wenya Han, Hai Du, Xinying Xue, Jian‐Lin Wu · 发表于：Cancer Management and Research · 年份：2025 · DOI：10.2147/cmar.s522136 · 被引用次数：7 · 研究领域：Cancer Immunotherapy and Biomarkers、Lung Cancer Diagnosis and Treatment、Esophageal Cancer Research and Treatment

Immunotherapy has emerged as a transformative treatment for non-small cell lung cancer (NSCLC), yet its clinical benefits remain variable among patients. Early and accurate evaluation of treatment response is critical to guide therapeutic adjustments and improve outcomes. This review synthesizes recent advancements in multimodal imaging techniques-computed tomography (CT), positron emission tomography (PET)/CT, magnetic resonance imaging (MRI), and radiomics-for evaluating and predicting immunotherapy efficacy in NSCLC. We analyze the strengths and limitations of conventional morphological criteria (eg, RECIST, iRECIST) and highlight emerging quantitative biomarkers, including CT texture analysis, metabolic parameters (MTV, TLG), and diffusion-weighted MRI metrics. Notably, radiomics demonstrates promise in decoding tumor heterogeneity, PD-L1 expression, and immune microenvironment features, while immuno-PET probes targeting immune checkpoints offer novel insights into immune activity in vivo. Challenges such as pseudo-progression, nodal immune flare, and discrepancies between imaging responses and pathological responses are critically discussed. By integrating morphological, metabolic, and microenvironmental data, multimodal imaging enhances precision in patient stratification and therapeutic monitoring. Future research should prioritize multicenter, AI-driven radiomics validation and targeted tracer development to optimize NSCLC immunotherapy management. This review provide...