Modeling of Cerebral Oxygen Transport Based on In vivo Microscopic Imaging of Microvascular Network Structure, Blood Flow, and Oxygenation

Abstract

Oxygen is delivered to brain tissue by a dense network of microvessels, which actively control cerebral blood flow (CBF) through vasodilation and contraction in response to changing levels of neural activity. Understanding these network-level processes is immediately relevant for (1) interpretation of functional Magnetic Resonance Imaging (fMRI) signals, and (2) investigation of neurological diseases in which a deterioration of neurovascular and neuro-metabolic physiology contributes to motor and cognitive decline. Experimental data on the structure, flow and oxygen levels of microvascular networks are needed, together with theoretical methods to integrate this information and predict physiologically relevant properties that are not directly measurable. Recent progress in optical imaging technologies for high-resolution in vivo measurement of the cerebral microvascular architecture, blood flow, and oxygenation enables construction of detailed computational models of cerebral hemodynamics and oxygen transport based on realistic three-dimensional microvascular networks. In this article, we review state-of-the-art optical microscopy technologies for quantitative in vivo imaging of cerebral microvascular structure, blood flow and oxygenation, and theoretical methods that utilize such data to generate spatially resolved models for blood flow and oxygen transport. These “bottom-up” models are essential for the understanding of the processes governing brain oxygenation in normal and disease states and for eventual translation of the lessons learned from animal studies to humans.

Insights into cerebral haemodynamics and oxygenation utilising in vivo mural cell imaging and mathematical modelling

“…We used our flow solutions from the discrete-network model to parametrise the following well-established approach which describes steady-state intravascular and tissue oxygen transport, where by tissue is represented as a homogeneous medium with oxygen diffusivity D and solubility α , as outlined in a series of papers 19 , 43 , 44 . Derived from Fick’s Law, tissue PO 2 , P , conservation satisfies where M ( P ) is the oxygen consumption rate.…”

Insights into cerebral haemodynamics and oxygenation utilising in vivo mural cell imaging and mathematical modelling

“…We used our flow solutions from the discrete-network model to parametrise the following well-established approach which describes steady-state intravascular and tissue oxygen transport, whereby tissue is represented as a homogeneous medium with oxygen diffusivity D and solubility α , as outlined in a series of papers 10,20,44 .…”

Predicting retinal tissue oxygenation using an image-based theoretical model

“…For example, Secomb et al have developed strategies for predicting oxygen transport in a heterogeneous network using techniques from potential theory involving Green's functions and have applied them to microvascular networks in the mesentery, in striated muscle, and in tumors [16,17]. Concurrently, imaging studies in the coronary microvasculature coupled with improved computational techniques have allowed for prediction of blood flow rates in large networks [19][20][21][22], and progress is being made in using in vivo imaging of the cerebral vasculature to predict flows and oxygenation in the microcirculation of the brain [23].…”