Flowmotion imaging analysis of spatiotemporal variations in skin microcirculatory perfusion.

Abstract

Flowmotion is the rhythmical variations in measured skin blood flow that arise due to global and local regulation of the vessels and can be studied using frequency analysis of time-resolved blood flow signals. It has the potential to reveal clinically useful information about microvascular diseases, but the spatial heterogeneous nature of the microvasculature makes interpretation difficult. However, recent technological advances in multi-exposure laser speckle contrast imaging (MELSCI) enable new possibilities for simultaneously studying spatial and temporal variations in flowmotion. To develop a method for flowmotion analysis of MELSCI perfusion images. Furthermore, to investigate the spatial and temporal variations in flowmotion in forearm baseline skin perfusion. In four healthy subjects, forearm skin perfusion was imaged at 15.6 fps for 10 min in baseline. The time-trace signal in each pixel was analyzed using the wavelet transform and summarized in five physiologically relevant frequency intervals, resulting in images of flowmotion. Furthermore, a method for reducing the effect of motion artifacts in the flowmotion analysis was developed. The flowmotion images displayed patterns of high spatial heterogeneity that differed between the frequency intervals. The spatial variations in flowmotion, quantified as the coefficient of variation, was between 11 % and 31 % in four subjects. Furthermore, significant temporal variations in flowmotion were also observed, indicating the importance of a spatiotemporal analysis. The new imaging technique reveals significant spatial differences in flowmotion that cannot be obtained with single-point measurements. The results indicate that global statistics of flowmotion, such as the mean value in a large region of interest, is more representative of the microcirculation than data measured only in a single point. Therefore, imaging techniques have potential to increase the clinical usefulness of flowmotion analysis. • Flowmotion imaging displays significant spatiotemporal variations in forearm skin blood flow. • Flowmotion imaging has potential to be more accurate than single-point techniques. • A simple and effective method for motion artifact removal is presented.