Spatial heterogeneity of cutaneous blood flow respiratory-related oscillations quantified via laser speckle contrast imaging

PLoS One. 2021 May 27;16(5):e0252296. doi: 10.1371/journal.pone.0252296. eCollection 2021.

Abstract

LSCI technique provides experimental data which can be considered in the context of spatial blood flow coherency. Analysis of vascular tone oscillations gives additional information to ensure a better understanding of the mechanisms affecting microvascular physiology. The oscillations with different frequencies are due to different physiological mechanisms. The reasons for the generation of peripheral blood flow oscillations in the 0.14-0.6 Hz frequency band are as follows: cardio-respiratory interactions, pressure variations in the venous part of the circulatory system, and the effect of the sympathetic nervous system on the vascular tone. Earlier, we described the spatial heterogeneity of around 0.3 Hz oscillations and this motivated us to continue the research to find the conditions for the occurrence of spatial phase synchronization. For this purpose, a number of physiological tests (controlled respiration, breath holder, and venous occlusion tests) which influence the blood flow oscillations of 0.14-0.6 Hz were considered, an appropriate measurement system and the required data processing algorithms were developed. At spontaneous respiration, the oscillations with frequencies around 0.3 Hz were stochastic, whereas all the performed tests induced an increase in spatial coherence. The protocols and methods proposed here can help to clarify whether the heterogeneity of respiratory-related blood flow oscillations exists on the skin surface.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Blood Flow Velocity*
  • Female
  • Hemodynamics*
  • Humans
  • Laser Speckle Contrast Imaging / methods*
  • Microcirculation
  • Regional Blood Flow*
  • Skin / blood supply*

Grants and funding

This study was supported by RFBR under project No. 19-32-90253. VD kindly acknowledges personal support from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 839888.