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<p>High-grade glioma (HGG) exhibits substantial biological heterogeneity, which complicates prognosis and treatment, and clarifying the interplay between proliferating tumor cells and tumor-associated microvasculature may improve patient outcomes. We prospectively enrolled 221 patients with HGG from four institutions and integrated diffusion-weighted and dynamic contrast-enhanced MRI within a supervoxel-based framework to delineate tumor subregions termed density-enhancement compounded voxels (DECV). Four DECV subregions (DECV1-4) with distinct imaging characteristics were identified. DECV4, characterized by low apparent diffusion coefficient and gradual enhancement, was strongly associated with tumor aggressiveness and treatment resistance. Clustering analysis further revealed two DECV phenotypes that differed significantly in progression-free and overall survival; phenotype II showed a higher DECV4 proportion and a poorer prognosis. DECV phenotypes outperformed conventional imaging markers as independent predictors of survival and were validated in an independent cohort. These DECV-based imaging phenotypes provide a robust, non-invasive biomarker for characterizing HGG heterogeneity and show potential to enhance prognostic stratification and guide personalized therapy.</p>

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Supervoxel-based multimodal MRI biomarkers reveal tumor heterogeneity in high-grade glioma for prognostic stratification and therapy response prediction

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月17日

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  • Yan Zhu,
  • Xiwen Zhu,
  • Dian Huang,
  • Yang Ji,
  • Ranchao Wang,
  • Yang Li,
  • Yuhao Xu,
  • Yifeng Luo,
  • Yan Zhuang,
  • Zhe Liu,
  • Wei Wang,
  • Subo Zhang,
  • Yuefeng Li

摘要

High-grade glioma (HGG) exhibits substantial biological heterogeneity, which complicates prognosis and treatment, and clarifying the interplay between proliferating tumor cells and tumor-associated microvasculature may improve patient outcomes. We prospectively enrolled 221 patients with HGG from four institutions and integrated diffusion-weighted and dynamic contrast-enhanced MRI within a supervoxel-based framework to delineate tumor subregions termed density-enhancement compounded voxels (DECV). Four DECV subregions (DECV1-4) with distinct imaging characteristics were identified. DECV4, characterized by low apparent diffusion coefficient and gradual enhancement, was strongly associated with tumor aggressiveness and treatment resistance. Clustering analysis further revealed two DECV phenotypes that differed significantly in progression-free and overall survival; phenotype II showed a higher DECV4 proportion and a poorer prognosis. DECV phenotypes outperformed conventional imaging markers as independent predictors of survival and were validated in an independent cohort. These DECV-based imaging phenotypes provide a robust, non-invasive biomarker for characterizing HGG heterogeneity and show potential to enhance prognostic stratification and guide personalized therapy.