Abstract

Departures of normal blood flow and metabolite distribution from the cerebral microvasculature into neuronal tissue have been implicated with age-related neurodegeneration. Mathematical models informed by spatially and temporally distributed neuroimage data are becoming instrumental for reconstructing a coherent picture of normal and pathological oxygen delivery throughout the brain. Unfortunately, current mathematical models of cerebral blood flow and oxygen exchange become excessively large in size. They further suffer from boundary effects due to incomplete or physiologically inaccurate computational domains, numerical instabilities due to enormous length scale differences, and convergence problems associated with condition number deterioration at fine mesh resolutions. Our proposed simple finite volume discretization scheme for blood and oxygen microperfusion simulations does not require expensive mesh generation leading to the critical benefit that it drastically reduces matrix size and bandwidth of the coupled oxygen transfer problem. The compact problem formulation yields rapid and stable convergence. Moreover, boundary effects can effectively be suppressed by generating very large replica of the cortical microcirculation in silico using an image-based cerebrovascular network synthesis algorithm, so that boundaries of the perfusion simulations are far removed from the regions of interest. Massive simulations over sizeable portions of the cortex with feature resolution down to the micron scale become tractable with even modest computer resources. The feasibility and accuracy of the novel method is demonstrated and validated with in vivo oxygen perfusion data in cohorts of young and aged mice. Our oxygen exchange simulations quantify steep gradients near penetrating blood vessels and point towards pathological changes that might cause neurodegeneration in aged brains. This research aims to explain mechanistic interactions between anatomical structures and how they might change in diseases or with age. Rigorous quantification of age-related changes is of significant interest because it might aide in the search for imaging biomarkers for dementia and Alzheimer’s disease.

Highlights

  • Late-onset neurodegenerative diseases are believed to interrupt or degrade the coordination between vascular blood flow and neural tissue oxygenation

  • We demonstrate the novel mesh generation-free (MGF), multi-scale simulation approach through realistic in vivo case studies of cortical microperfusion in the mouse brain

  • First we show that the proposed structured, cuboid Cartesian mesh discretization significantly improves the matrix structure of the transport equations compared to traditional tetrahedral meshing as exemplified by Fig 1

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Summary

Introduction

Late-onset neurodegenerative diseases are believed to interrupt or degrade the coordination between vascular blood flow and neural tissue oxygenation. Normal aging (aging without dementia) entails similar morphological changes [3], so that normal age related changes are hard to distinguish from diseases. In order to better diagnose and eventually treat age-related dementia, it is imperative to be able to precisely quantify changes in vascular topology that potentially impair adequate oxygen supply to the brain. While the link between vascular restructuring and reduced tissue oxygenation have been established [4,9,10,11,12], the quantitative contribution of hemodynamic factors to abnormal oxygen distribution have not been characterized due to the difficulty in posing and solving problems on a massive scale

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