Heterogeneity phenotypes in recurrent glioblastoma: a multimodal MRI-based spatial mapping framework for precision treatment.

ABSTRACT:

Background

To develop a multimodal magnetic resonance imaging (MRI)-based spatial mapping framework for quantitatively characterizing intratumoral heterogeneity in recurrent glioblastoma (rGBM), identifying distinct imaging subregions, and classifying heterogeneity phenotypes predictive of treatment response and survival outcomes.

Methods

A total of 140 rGBM patients were recruited and underwent standardized diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Pixel-wise colocalization of apparent diffusion coefficient (ADC) and DCE-MRI features identified four Multimodal Imaging Subregions (MIS). Entropy and Moran's I quantified heterogeneity, and hierarchical clustering defined imaging phenotypes. Treatment response to 1-(2-c

SUBMITTER: Zhu Y 

PROVIDER: S-EPMC12465940 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature