Effective tumor kinetics inferred from single routine H&E biopsies enable counterfactual virtual radiotherapy trials
Abstract
Routine H&E-histopathology captures spatial snapshots of tumor ecosystems, yet computational pathology largely treats them as textures without explicit links to underlying kinetics. We show that patient-specific parameters of a mechanistic reaction-diffusion model can be inferred from a single biopsy. Cell-nucleus point patterns are fitted jointly to the analytical two-point correlation function and power spectral density, recovering patient-specific mechanistic proliferation and diffusion rates across eleven multicenter cohorts. Derived dispersion length and front velocity define mechanistic phenotypes stratifying progression-free and overall survival and adding information independent of routine covariates. We illustrate counterfactual radiotherapy simulations in glioblastoma and show that a virtual clinical trial deescalating histology-calibrated faster-growing tumors to hypofractionation while dose-intensifying slower-growing tumors adds 96.7 days of restricted mean progression-free in silico survival over standard of care (permutation p < 0.001 against random allocation to the same arms). This provides a low-barrier transition from routine histopathology to mechanistically interpretable model-based forward simulations.
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