Li Shengshu, Geng Ziying, Hong Shuang, Zhang Jianxin, Yang Yanli, Wei Qin, Zhang Xinxin, Zhuang Xiaofei, Huo Rujie, Han Songyan, Wang Jie
Department of Respiratory Medicine, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated with Shanxi Medical University, Taiyuan, China.
Department of Respiratory Medicine, University Hospital, Ludwig Maximilians University, Munich, Germany.
Front Immunol. 2025 Sep 2;16:1656063. doi: 10.3389/fimmu.2025.1656063. eCollection 2025.
In recent years, the introduction of immune checkpoint inhibitors (ICIs) has revolutionized the treatment landscape for malignant tumors, markedly improving survival outcomes across various cancers, such as lung cancer, esophageal cancer, and melanoma. Consequently, ICIs have become a cornerstone of first-line therapy for numerous malignancies. However, while ICIs effectively modulate immune responses to combat tumor cells, they may also trigger excessive immune activation and T-cell dysfunction, thereby leading to a spectrum of immune-related adverse events (irAEs). The organs most frequently affected by these irAEs include the skin, gastrointestinal tract, endocrine system, and lungs. Among these adverse events, the development of severe immune checkpoint inhibitor-related pneumonitis (CIP) may result in significant disability, permanent discontinuation of ICIs, and even death, with real-world incidence rates exceeding those reported in clinical trials. Early detection, precise diagnosis, and timely intervention are critical for optimizing patient outcomes. However, diagnosing CIP remains challenging because it relies heavily on high-resolution chest CT imaging and a detailed treatment history. The radiological features of CIP are often nonspecific, complicating its identification. This complexity is further exacerbated in patients receiving consolidative immunotherapy following concurrent or sequential chemoradiotherapy for stage III unresectable non-small cell lung cancer, where distinguishing between radiation pneumonitis and CIP becomes particularly difficult. To address these challenges, an increasing number of imaging experts are investigating the potential of radiomics and machine learning techniques in predicting the occurrence and assessing the prognosis of CIP. This article comprehensively reviews the pathogenesis of CIP, the predictive value of radiomics in identifying this condition and recent advancements in treatment strategies, with the aim of providing novel insights for future research and clinical management of CIP.
近年来，免疫检查点抑制剂（ICIs）的引入彻底改变了恶性肿瘤的治疗格局，显著改善了包括肺癌、食管癌和黑色素瘤等多种癌症的生存结果。因此，ICIs已成为众多恶性肿瘤一线治疗的基石。然而，尽管ICIs能有效调节免疫反应以对抗肿瘤细胞，但它们也可能引发过度的免疫激活和T细胞功能障碍，从而导致一系列免疫相关不良事件（irAEs）。这些irAEs最常累及的器官包括皮肤、胃肠道、内分泌系统和肺部。在这些不良事件中，严重的免疫检查点抑制剂相关肺炎（CIP）的发生可能导致严重残疾、ICIs永久停用，甚至死亡，其在现实世界中的发病率超过了临床试验报告的发病率。早期检测、精确诊断和及时干预对于优化患者预后至关重要。然而，诊断CIP仍然具有挑战性，因为它严重依赖于高分辨率胸部CT成像和详细的治疗史。CIP的放射学特征往往不具有特异性，这使其识别变得复杂。在接受同步或序贯放化疗后的III期不可切除非小细胞肺癌患者中，接受巩固性免疫治疗时，区分放射性肺炎和CIP变得尤为困难，这进一步加剧了这种复杂性。为应对这些挑战，越来越多的影像专家正在研究放射组学和机器学习技术在预测CIP发生和评估其预后方面的潜力。本文全面综述了CIP的发病机制、放射组学在识别该疾病中的预测价值以及治疗策略的最新进展，旨在为CIP的未来研究和临床管理提供新的见解。
