Habitat radiomics analysis for progression free survival and immune-related adverse reaction prediction in non-small cell lung cancer treated by immunotherapy

作者：Yuemin Wu, Wei Zhang, Xiao Liang, Pengpeng Zhang, Mengzhe Zhang, Yuqin Jiang, Yanan Cui, Yi Chen, Wenxin Zhou, Qi Liang, Jiali Dai, Chen Zhang, Jiali Xu, Jun Li, Tongfu Yu, Zhihong Zhang, Renhua Guo · 发表于：Journal of Translational Medicine · 年份：2025 · DOI：10.1186/s12967-024-06057-y · 被引用次数：22 · 研究领域：Radiomics and Machine Learning in Medical Imaging、Cancer Immunotherapy and Biomarkers、Lung Cancer Diagnosis and Treatment

BACKGROUND: Non-small cell lung cancer (NSCLC) is highly heterogeneous, leading to varied treatment responses and immune-related adverse reactions (irAEs) among patients. Habitat radiomics allows non-invasive quantitative assessment of intratumor heterogeneity (ITH). Therefore, our objective is to employ habitat radiomics techniques to develop a robust approach for predicting the efficacy of Immune checkpoint inhibitors (ICIs) and the likelihood of irAEs in advanced NSCLC patients. METHODS: In this retrospective two center study, two independent cohorts of patients with NSCLC were used to develop (n = 248) and validate signatures (n = 95). After applying four kinds of machine learning algorithms to select the key preoperative CT radiomic features, we used clinical, radiomics and habitat radiomic features to develop the clinical signature, radiomics signature and habitat radiomic signature for ICIs prognostics and irAEs prediction. By combining habitat radiomic features with corresponding clinicopathologic information, the nomogram signature was constructed in the training cohort. Next, the internal validation cohort (n = 75) of patients, and the external validation cohort (n = 20) of patients treated with ICIs were included to evaluate the predictive value of the four signatures, and their predictive performance was assessed by the area under operating characteristic curve (AUC). RESULTS: Our study introduces a radiomic nomogram model that integrates clinical and habitat radi...