Analysis of microvascular blood flow and oxygenation: Discrimination between two haemodynamic steady states using...

This study investigates the feasibility of the use of nonlinear complexity methods as a tool to identify altered microvascular function often associated with pathological conditions. We evaluate the efficacy of multiscale nonlinear complexity methods to account for the multiple time-scales of processes modulating microvascular network perfusion.

Microvascular blood flux (BF) and oxygenation (OXY: oxyHb, deoxyHb, totalHb and SO₂%) signals were recorded simultaneously at the same site, from the skin of 15 healthy young male volunteers using combined laser Doppler fluximetry (LDF) and white light spectroscopy. Skin temperature was clamped at 33 °C prior to warming to 43 °C to generate a local thermal hyperaemia (LTH). Conventional and multiscale variants of sample entropy (SampEn) were used to quantify signal regularity and Lempel and Ziv (LZ) and effort to compress (ETC) to determine complexity.

SampEn showed a decrease in entropy during LTH in BF (p = 0.007) and oxygenated haemoglobin (oxyHb) (p = 0.029). Complexity analysis using LZ and ETC also showed a significant reduction in complexity of BF (LZ, p = 0.003; ETC, p = 0.002) and oxyHb (p < 0.001, for both) with LTH. Multiscale complexity methods were better able to discriminate between haemodynamic states (p < 0.001) than conventional ones over multiple time-scales.

Our findings show that there is a good discrimination in complexity of both BF and oxyHb signals between two haemodynamic steady states which is consistent across multiple scales.

Complexity-based and multiscale-based analysis of BF and OXY signals can identify different microvascular functional states and thus has potential for clinical application in the prognosis and the diagnosis of pathophysiological conditions such as microvascular dysfunction observed in non-alcoholic fatty liver disease and type 2 diabetes.