The Effects of Transit Time Heterogeneity on Brain Oxygenation during Rest and Functional Activation

Rasmussen, Peter Mondrup; Jespersen, Sune Nørhøj; Østergaard, Leif

doi:10.1038/jcbfm.2014.213

Cited by 57 publications

(77 citation statements)

References 49 publications

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“…Combining measurements with model simulations in a network‐oriented analysis allows for reconstruction of the complete network flow pattern and also allows the modeler to derive latent network parameters or physiological indices, eg, transit time distributions as illustrated here. Such “global” indices serve as inputs to recent macroscopic models that aim to make claims about oxygenation at the “tissue level” . The probabilistic analysis readily identifies such indices and provides estimates of their uncertainty intervals. While we assumed rheological model parameters to be fixed in this study, these parameters could also be associated with uncertainty.…”

Section: Discussionmentioning

confidence: 99%

Model‐based inference from microvascular measurements: Combining experimental measurements and model predictions using a Bayesian probabilistic approach

et al. 2017

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Objective In vivo imaging of the microcirculation and network-oriented modeling have emerged as powerful means of studying microvascular function and understanding its physiological significance. Network-oriented modeling may provide the means of summarizing vast amounts of data produced by high-throughput imaging techniques in terms of key, physiological indices. To estimate such indices with sufficient certainty, however, network-oriented analysis must be robust to the inevitable presence of uncertainty due to measurement errors as well as model errors. Methods We propose the Bayesian probabilistic data analysis framework as a means of integrating experimental measurements and network model simulations into a combined and statistically coherent analysis. The framework naturally handles noisy measurements and provides posterior distributions of model parameters as well as physiological indices associated with uncertainty. Results We applied the analysis framework to experimental data from three rat mesentery networks and one mouse brain cortex network. We inferred distributions for more than five hundred unknown pressure and hematocrit boundary conditions. Model predictions were consistent with previous analyses, and remained robust when measurements were omitted from model calibration. Conclusion Our Bayesian probabilistic approach may be suitable for optimizing data acquisition and for analyzing and reporting large datasets acquired as part of microvascular imaging studies.

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Section: Discussionmentioning

confidence: 99%

Model‐based inference from microvascular measurements: Combining experimental measurements and model predictions using a Bayesian probabilistic approach

et al. 2017

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“…The laminar transit time distribution should be investigated during functional activation [65] as well as during microvascular dysfunction. A more detailed picture of how metabolic needs are met under these conditions will require additional, simultaneous measures of flow and oxygenation.…”

Section: Discussionmentioning

confidence: 99%

Laminar microvascular transit time distribution in the mouse somatosensory cortex revealed by Dynamic Contrast Optical Coherence Tomography

Merkle

Srinivasan

2016

NeuroImage

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The transit time distribution of blood through the cerebral microvasculature both constrains oxygen delivery and governs the kinetics of neuroimaging signals such as blood-oxygen-level-dependent functional Magnetic Resonance Imaging (BOLD fMRI). However, in spite of its importance, capillary transit time distribution has been challenging to quantify comprehensively and efficiently at the microscopic level. Here, we introduce a method, called Dynamic Contrast Optical Coherence Tomography (DyC-OCT), based on dynamic cross-sectional OCT imaging of an intravascular tracer as it passes through the field-of-view. Quantitative transit time metrics are derived from temporal analysis of the dynamic scattering signal, closely related to tracer concentration. Since DyC-OCT does not require calibration of the optical focus, quantitative accuracy is achieved even deep in highly scattering brain tissue where the focal spot degrades. After direct validation of DyC-OCT against dilution curves measured using a fluorescent plasma label in surface pial vessels, we used DyC-OCT to investigate the transit time distribution in microvasculature across the entire depth of the mouse somatosensory cortex. Laminar trends were identified, with earlier transit times and less heterogeneity in the middle cortical layers. The early transit times in the middle cortical layers may explain, at least in part, the early BOLD fMRI onset times observed in these layers. The layer-dependencies in heterogeneity may help explain how a single vascular supply manages to deliver oxygen to individual cortical layers with diverse metabolic needs.

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“…Note the dramatic decrease in tissue levels of ATP and glucose at the time of CSD, whereas cerebral blood flow (CBF) remains unaltered. Increases in capillary transit time heterogeneity (CTH) reduces the apparent capillary surface area available for solutes to cross the blood-brain barrier 22,36 and more so for oxygen than for glucose. 37 If capillary flow disturbances develop during CSD, the efficient production of ATP by oxidative phosphorylation may therefore be impaired, and glucose preferably converted to lactate instead, with limited ATP yields.…”

Section: Elevated Cth In the Injured Brain: The Effects Of Preexistinmentioning

confidence: 99%

Neurovascular Coupling During Cortical Spreading Depolarization and –Depression

Østergaard

Dreier

Hadjikhani

et al. 2015

Stroke

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A B Figure 1. A, The importance of capillary flow patterns (yellow arrows) for the efficacy of oxygen extraction. Intravascular colors indicate blood saturation (red, fully oxygenated; darker blue, more deoxygenated) and surrounding darker blue colors indicate lower tissue oxygen tension-adapted from Østergaard et al. 23 Copyright ©2013, The Authors (see: http://creativecommons.org/licenses/by-nc-sa/3.0/). In the resting, normal brain (top), erythrocyte velocities vary greatly among capillaries, with little oxygen being extracted from fast-flowing blood. 22 As cerebral blood flow (CBF) increases (right), capillary flow patterns homogenize in parallel. 22 This phenomenon reduces the functional shunting that otherwise occurs when erythrocytes pass through capillaries at short transit times. Although the mean transit time (MTT) of blood through the capillary bed is related to CBF through the central volume theorem (MTT=CBV/CBF, where CBV is the capillary blood volume), capillary transit time heterogeneity (CTH) indicates the distribution of capillary transit times relative to this mean (eg, in terms of their standard deviation). Both MTT and CTH are measured in seconds, and the degree of functional shunting generally increases as CTH approaches MTT.24 Bottom, Capillary dysfunction, characterized by elevated CTH relative to MTT, and failure of capillary flow patterns to homogenize during hyperemia. The conditions may be the result of pericyte dysfunction, changes in blood viscosity or capillary wall morphology, or external capillary compression. These changes hinder the redistribution of blood across the capillary bed, with less affected capillary paths tending to act as functional shunts for oxygenated blood. Biophysically, the only means of attenuating the accompanying oxygen loss is to reduce transit times across all capillaries, that is, to attenuate CBF and CBF responses. 25 The accompanying reduction in net oxygen supply reduces tissue oxygen tension as cells continue to use oxygen, increasing blood-tissue concentration gradients and net oxygen extraction. 25 With flow responses attenuated, oxygen extraction can be increased from the 30% of normal brain up to near unity, and normal brain function maintained although capillary dysfunction becomes more severe. 25 It is important to note that current state-of-the-art algorithms to generate maps of transit time-related metrics based on perfusion-weighted magnetic resonance imaging or computed tomography cannot distinguish changes in tracer retention caused by prolonged MTT (reduced CBF) from changes caused by capillary flow disturbances (capillary dysfunction). 25 The effects of CTH must therefore be separately modeled to ascertain whether clinical signs of ischemia are indeed caused by limited blood supply or by capillary dysfunction.26 B, The acute changes in capillary morphology that accompany conditions in which CSD are common. In traumatic brain injury (TBI; i), massive swelling of the perivascular astrocytic end feet (AE) and flattening or compression of the...

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The Effects of Transit Time Heterogeneity on Brain Oxygenation during Rest and Functional Activation

Cited by 57 publications

References 49 publications

Model‐based inference from microvascular measurements: Combining experimental measurements and model predictions using a Bayesian probabilistic approach

Model‐based inference from microvascular measurements: Combining experimental measurements and model predictions using a Bayesian probabilistic approach

Laminar microvascular transit time distribution in the mouse somatosensory cortex revealed by Dynamic Contrast Optical Coherence Tomography

Neurovascular Coupling During Cortical Spreading Depolarization and –Depression

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