Biomechanical Mapping of Tumor Growth: A Novel Method to Quantify Glioma Infiltration and Mass Effect

TL;DR

This study introduces the dynamic infiltration rate (DIR), an MRI-derived biomarker that quantifies glioma infiltration and mass effect, correlates strongly with tumor phenotype, and independently predicts patient survival, aiding personalized treatment strategies.

Contribution

The paper presents a novel MRI-based biomarker, DIR, which effectively differentiates glioma phenotypes and predicts prognosis, advancing non-invasive tumor characterization.

Findings

DIR correlates strongly with ground truth ($R^{2}=0.85$).

High and low infiltration groups show significant survival differences.

DIR is an independent prognostic factor in multivariate analysis.

Abstract

Glioblastoma (GBM) exhibits two principal growth phenotypes: infiltrative, characterized by diffuse invasion with minimal mass effect, and proliferative, characterized by pronounced tissue compression. Their quantitative delineation and prognostic implications remain uncertain. We introduce an MRI-derived biomarker, the dynamic infiltration rate (DIR), defined as the ratio of tumor-volume expansion to mass-effect--induced peritumoral compression, and evaluate it in silico and clinically. In a synthetic dataset spanning realistic infiltrative-proliferative spectra, DIR correlates strongly with ground truth ($R^{2}=0.85$). Applied to patient data, a data-driven threshold separates high- and low-infiltration groups with markedly different overall survival (median 16.0 versus 35.2 weeks; log-rank $p<0.001$; hazard ratio 2.49). Multivariate Cox analysis adjusted for age, sex, and MGMT status confirms DIR as an independent prognostic factor (HR = 1.38, 95% CI 1.12-1.70; $p=0.0027$). DIR therefore differentiates proliferative from infiltrative GBM phenotypes and provides prognostic information that could inform personalized therapy and follow-up.