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bioRxiv · 10.64898/2026.10.26.761772

Estimating glioblastoma migration-to-proliferation ratio from single time-point MRI data via radial density distribution

Bravo, R. R.·Hormuth, D. A.·Lima, E. A. B. F.·Tercan, B.·Aguilar, B.·Yankeelov, T. E.
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Abstract

Glioblastoma (GBM) tumors with a high migration-to-proliferation ratio (D/k) are associated with treatment resistance, motivating the estimation of D/k from routine pre-treatment magnetic resonance imaging (MRI) data and the investigation of mechanisms underlying its heterogeneity across patients. Unlike previous approaches based on nested spherical approximations of enhancing and non-enhancing tumor volumes, we incorporate the spatial arrangement of the enhancing and non-enhancing tumor regions by deriving a 1D tumor density distribution from their segmentations and fitting a 1D reaction-diffusion model to estimate D/k. We achieved an error of under 5% when comparing our method to synthetic density distributions and found excellent correlation with synthetic tumor segmentations (Pearson correlation coefficient (PCC) = 0.996). We then evaluated associations between patient-specific D/k values and their clinical, transcriptomic, and radiomic features. When applied to 102 pre-treatment MRI scans from the Brain Tumor Segmentation (BraTS) 2017 dataset, elevated D/k significantly correlated with reduced overall survival (log-rank p = 0.01), older age (p = 0.04), and a trend toward lower Karnofsky Performance Status (p = 0.059). In a subset of 91 patients with available microarray data, mesenchymal-like phenotypes consistently exhibited elevated D/k across three established molecular subtype classifications (p = 0.013, p = 0.055, and p = 0.127). Elastic Net regularization followed by overrepresentation analysis revealed an enrichment of glycosylation-related pathways among genes associated with D/k variability (p = 0.0123 and p = 0.0368). Furthermore, Multi-Omic Factor Analysis identified a radiomic factor correlated with D/k (r = 0.57, p = 4x10-9), with the highest-weighted features corresponding to smoothness of the non-enhancing tumor region on T2 and FLAIR.

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Bravo, R. R., Hormuth, D. A., Lima, E. A. B. F., Tercan, B., Aguilar, B., Yankeelov, T. E.. 2026-10-31. Estimating glioblastoma migration-to-proliferation ratio from single time-point MRI data via radial density distribution. https://doi.org/10.64898/2026.10.26.761772

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