本研究旨在应用数学框架预测高级别胶质瘤(HGGs)细胞对正常组织的侵袭，以指导临床靶区划定，并探讨使用肿瘤浸润图预测患者总生存率(OS)的可能性。该模型描述了肿瘤对正常组织的浸润，共应用于93例HGG患者。生成了肿瘤浸润图和相应的具有不同细胞密度的等值线图。使用ROC曲线寻找患者OS与特定等值线图包围的体积之间的相关性。使用曲线下面积(AUC)值确定具有最高预测能力的等值线图。对于每个等值线图，使用具有最高敏感性和特异性的最佳截断体积将患者分为两组进行Kaplan-Meier生存分析。细胞密度为1000个细胞/mm3和2000个细胞/mm3的等值线图获得了最高的AUC值，为0.77 (p < 0.05)。与GTV的相关性得到了0.73的AUC值 (p < 0.05)。使用细胞密度为1000个细胞/mm3的等值线图和ROC最佳截断体积进行患者组选择的Kaplan-Meier生存分析得到了风险比(HR)为2.7 (p < 0.05)，而GTV得到了HR = 1.6 (p < 0.05)。模拟的肿瘤细胞浸润是总生存率的更强预测因子，表明使用数学模型辅助定义HGG患者的靶区的重要性。版权所有 © 2023. Elsevier出版。

This study aimed at applying a mathematical framework for the prediction of high-grade gliomas (HGGs) cell invasion into normal tissues for guiding the clinical target delineation, and at investigating the possibility of using tumor infiltration maps for patient overall survival (OS) prediction.A model describing tumor infiltration into normal tissue was applied to 93 HGG cases. Tumor infiltration maps and corresponding isocontours with different cell densities were produced. ROC curves were used to seek correlations between the patient OS and the volume encompassed by a particular isocontour. Area-Under-the-Curve (AUC) values were used to determine the isocontour having the highest predictive ability. The optimal cut-off volume, having the highest sensitivity and specificity, for each isocontour was used to divide the patients in two groups for a Kaplan-Meier survival analysis.The highest AUC value was obtained for the isocontour of cell densities 1000 cells/mm3 and 2000 cells/mm3, equal to 0.77 (p < 0.05). Correlation with the GTV yielded an AUC of 0.73 (p < 0.05). The Kaplan-Meier survival analysis using the 1000 cells/mm3 isocontour and the ROC optimal cut-off volume for patient group selection rendered a hazard ratio (HR) of 2.7 (p < 0.05), while the GTV rendered a HR = 1.6 (p < 0.05).The simulated tumor cell invasion is a stronger predictor of overall survival than the segmented GTV, indicating the importance of using mathematical models for cell invasion to assist in the definition of the target for HGG patients.Copyright © 2023. Published by Elsevier Ltd.