Radiomics-based mapping of glioblastoma infiltration beyond contrast enhancement: diffusion–perfusion correlations and survival analysis in large public cohorts

Background
Radiomic models from multiparametric MRI can characterize tumor infiltration within the non-enhancing peritumoral region but remain insufficiently compared with diffusion and perfusion. This study assessed concordance between voxelwise radiomic predictions and these physiological modalities and evaluated prognostic value of infiltration metrics in two external cohorts.
Methods
UPenn-GBM and UCSF-PDGM datasets were analyzed. Voxelwise radiomic classification generated peritumoral infiltration-probability maps from standard MRI. Fractional anisotropy (FA), dynamic susceptibility contrast–derived relative cerebral blood volume (DSC-rCBV; UPenn), and arterial spin labeling–derived relative cerebral blood flow (ASL-CBF; UCSF) were compared between peritumoral regions classified as high- versus low-infiltration. Radiomic metrics included infiltration burden (voxel fraction exceeding predefined probability thresholds) and radial extent (normalized maximum distance from enhancing margin sustaining high infiltration probability) were quantified, and survival assessed using univariable Cox models.
Results
Across 872 subjects, high-infiltration regions showed significantly lower FA (median difference: UPenn −0.232; UCSF −0.226; both p < 0.001) and higher perfusion (median difference: UPenn DSC-rCBV + 0.282; UCSF ASL-CBF + 0.565; both p < 0.001) compared with low-infiltration regions. Infiltration burden at the 0.50 threshold demonstrated prognostic value (UPenn hazard ratio (HR) 2.758, 95% confidence interval (CI) 1.189–6.396, p = 0.018; UCSF HR 21.277, 95% CI 6.024–71.429, p < 0.001). Radial extent was also associated with survival (UPenn HR 2.371, 95% CI 1.215–4.625, p = 0.011; UCSF HR 4.405, 95% CI 1.695–11.494, p = 0.002). Conclusions Voxelwise radiomic infiltration mapping from standard MRI aligns with diffusion and perfusion abnormalities and yields prognostic value. These metrics highlight the role of structural radiomics for characterizing non-enhancing infiltrative spread in glioblastoma.