In-silico solute transport via perivascular networks in the human intracranial space

The mechanisms of intracranial solute transport are fundamental to human brain health. However, our understanding of their interplay remains incomplete, in part due to the complexity of integrating insights across scales, between species, and from different modalities. In this work, we combine mixed-dimensional mathematical modeling, multi-modal magnetic resonance images, and high performance computing to present a computational framework for calculating the spatiotemporal spreading of a solute across the subarachnoid space, ventricular system, and brain parenchyma, including surface perivascular spaces. To illustrate applicability, we simulate a series of scenarios relating to intrathecal tracer injections, including variations in cerebrospinal fluid production, intracranial pulsatility, perivascular fluid flow and -structure. This openly available framework allows for evaluating the integrated effect of different transport mechanisms, bridging from the vascular mesoscale to the organ-level macroscale and across time scales of seconds to hours, in subject-specific geometries. This work introduces a multiscale, integrative modeling framework for brain fluid flow and solute transport, bridging mesoscale perivascular networks with the organ-level macroscale and timescales of seconds to hours in subject-specific geometries.