Image-based personalization of computational models for predicting response of high-grade glioma to chemoradiation.

ABSTRACT: High-grade gliomas are an aggressive and invasive malignancy which are susceptible to treatment resistance due to heterogeneity in intratumoral properties such as cell proliferation and density and perfusion. Non-invasive imaging approaches can measure these properties, which can then be used to calibrate patient-specific mathematical models of tumor growth and response. We employed multiparametric magnetic resonance imaging (MRI) to identify tumor extent (via contrast-enhanced T₁-weighted, and T₂-FLAIR) and capture intratumoral heterogeneity in cell density (via diffusion-weighted imaging) to calibrate a family of mathematical models of chemoradiation response in nine patients with unresected or partially resected disease. The calibrated model parameters were used to

SUBMITTER: Hormuth DA 

PROVIDER: S-EPMC8055874 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature