术前MRI是胶质瘤的重要诊断和治疗参考。本研究旨在评估一个影像组学生物标志物在胶质瘤预后方面的作用，并进一步探讨其与肿瘤微环境和巨噬细胞浸润的关系。我们对来自三个独立数据集的664例胶质瘤患者进行了术前MRI检查：江苏省医院（JSPH，n = 338），The Cancer Genome Atlas数据集（TCGA，n = 252）和分子性脑肿瘤数据库（REMBRANDT，n = 74）。结合多步骤后处理工作流程，选择了20个影像组学特征（Rads）并开发了一个影像组学生存生物标志物（RadSurv），证明了其在胶质瘤（截断 = 1.06）、低级别胶质瘤（截断 = 0.64）和胶质母细胞瘤（截断 = 1.80）的风险分层中具有高效性，通过三个固定的截断值。通过免疫浸润分析，我们发现RadSurv与巨噬细胞浸润呈正相关（RMΦ = 0.297，p < 0.001；RM2Φ = 0.241，p < 0.001），这一发现在GLIOL2亚型（glioblastomas，n = 32）的免疫组织化学染色和单细胞测序（多灶生长的胶质母细胞瘤，n = 2）中得到了进一步证实。总之，RadSurv作为胶质瘤的强预后生物标志物，与巨噬细胞浸润呈非常重要的正相关，特别是与M2型巨噬细胞的关联，这极大地显示出影像组学模型作为术前替代传统基因组学用于预测肿瘤巨噬细胞浸润的潜力，并为免疫治疗提供临床指导。版权所有 © 2023。由Elsevier B.V.出版。

Preoperative MRI is an essential diagnostic and therapeutic reference for gliomas. This study aims to evaluate the prognostic aspect of a radiomics biomarker for glioma and further investigate its relationship with tumor microenvironment and macrophage infiltration. We covered preoperative MRI of 664 glioma patients from three independent datasets: Jiangsu Province Hospital (JSPH, n = 338), The Cancer Genome Atlas dataset (TCGA, n = 252), and Repository of Molecular Brain Neoplasia Data (REMBRANDT, n = 74). Incorporating a multistep post-processing workflow, 20 radiomics features (Rads) were selected and a radiomics survival biomarker (RadSurv) was developed, proving highly efficient in risk stratification of gliomas (cut-off = 1.06), as well as lower-grade gliomas (cut-off = 0.64) and glioblastomas (cut-off = 1.80) through three fixed cut-off values. Through immune infiltration analysis, we found a positive correlation between RadSurv and macrophage infiltration (RMΦ = 0.297, p < 0.001; RM2Φ = 0.241, p < 0.001), further confirmed by immunohistochemical-staining (glioblastomas, n = 32) and single-cell sequencing (multifocal glioblastomas, n = 2). In conclusion, RadSurv acts as a strong prognostic biomarker for gliomas, exhibiting a non-negligible positive correlation with macrophage infiltration, especially with M2 macrophage, which strongly suggests the promise of radiomics-based models as a preoperative alternative to conventional genomics for predicting tumor macrophage infiltration and provides clinical guidance for immunotherapy.Copyright © 2023. Published by Elsevier B.V.