Interstitial fluid transport dynamics predict glioblastoma invasion and progression

Abstract

Glioblastoma is characterized by aggressive infiltration into surrounding brain tissue, hindering complete surgical resection and contributing to poor patient outcomes. Identifying tumor-specific invasion patterns is essential for advancing our understanding of glioblastoma progression and improving surgical and radiotherapeutic strategies. Here, we leverage in vivo dynamic contrastenhanced magnetic resonance imaging (DCE-MRI) to noninvasively quantify interstitial fluid velocity, direction, and diffusion within and around glioblastomas. We introduce a novel vector-based pathline analysis to trace downstream accumulation of fluid flow originating from the tumor core, providing a spatially explicit perspective on local flow patterns. We find that localized fluid transport metrics predict glioblastoma invasion and progression, offering a new framework to non-invasively identify high-risk regions and guide targeted treatment approaches.