Multi-scale, multi-domain analysis of microvascular flow dynamics

Abstract

To date, time and frequency domain metrics of signals acquired through laser Doppler fluximetry have been unable to provide consistent and robust measures of the changes that occur in the microcirculation either in healthy individuals at rest, or in response to a provocation, or in patient cohorts. Recent studies have shown that in many disease states, such as metabolic and cardiovascular disease, there appears to be a reduction in the adaptive capabilities of the microvascular network and a consequent reduction in physiological information content. Here, we introduce nonlinear measures for assessing the information content of fluximetry signals and demonstrate how they can yield deeper understanding of network behaviour. In addition, we show how these methods may be adapted to accommodate the multiple time scales modulating blood flow and how they can be used in combination with time and frequency domain metrics to discriminate more effectively between the different mechanistic influences on network properties.

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Identifiers

ORCID for A.J. Chipperfield: orcid.org/0000-0002-3026-9890

ORCID for M. Thanaj: orcid.org/0000-0002-1789-7112

ORCID for G.F. Clough: orcid.org/0000-0002-6226-8964

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