Glioblastomas are aggressive, highly heterogeneous brain tumours with poor prognosis and limited treatment options. Their complex microenvironment, characterised by elevated interstitial fluid pressure and irregular microstructure, creates major barriers to effective therapeutic delivery. 

 

We present a novel, patient-specific, multiscale computational model that integrates electric field modulation into the simulation of interstitial fluid dynamics in glioblastoma. Using MRI-derived brain geometries and histology informed microstructures, we simulate spatial distributions of pressure, velocity, and electric field across key tissue compartments: necrotic core, tumour, peritumoral edema, and white matter, each assigned distinct dielectric and hydraulic properties. 

Through asymptotic homogenisation, we derive effective transport properties that bridge macroscale anatomy with microscale heterogeneity. We solve homogenised Darcy and Laplace-type equations and compute physiologically relevant interstitial pressure and flow fields. 

 

Our simulations show elevated pressure and outward flow in tumour and edema regions. Regions of highest  interstitial fluid velocity (IFV) correlated with areas of tumour progression on follow-up imaging, suggesting a mechanistic link between IFV and glioblastoma invasion, and its potential use as a predictive biomarker. We demonstrate that applying an external electric field reverses this flow, promoting inward transport and potentially improving drug uptake, offering a new strategy for targeted drug delivery. 

 

To our knowledge, this is the first model that combines patient-specific geometry and multiscale physics in the context of electric field-driven glioblastoma treatment, establishing a new computational framework for personalised therapy planning.