Abstract
Capillary flow largely consists of alternating red cells and plasma whose speed oscillates predictably with the cardiac cycle. Superimposed on this regular background are sporadic events potentially disruptive to capillary exchange: the passage of white cells, aggregates of red cells, epochs of sparse haematocrit, or unusually slow flow. Such events are not readily differentiated with velocimetry or perfusion mapping. Here we propose a method to identify these phenomena in retinal capillaries imaged with high frame-rate adaptive optics, by calculating and representing pictorially the autocorrelation of intensity through time at each pixel during short epochs. The phenomena described above manifest as bright regions which transiently appear and propagate across an otherwise dark image. Drawing data from normal subjects and those with Type I diabetes, we demonstrate proof of concept and high sensitivity and specificity of this metric to variations in capillary contents and rate of flow in health and disease. The proposed metric offers a useful adjunct to velocimetry and perfusion mapping in the study of normal and abnormal capillary blood flow.
Highlights
With adaptive optics (AO) it is possible to image the microvascular networks of the retina in living human eyes, allowing observations of capillary structure and perfusion [1,2]
To assign pixels of high decay time to the proximal vessel, we identified outlier image pixels using the default settings of the Matlab 2018a “isoutlier” function, which flags pixels with intensity differences greater than 3 scaled median absolute deviations from the median
The average decay time during the sequence is shown in Fig. 2(B); both segments appear dark, decay time outliers were identified for both segments for individual epochs within the sequence
Summary
With adaptive optics (AO) it is possible to image the microvascular networks of the retina in living human eyes, allowing observations of capillary structure and perfusion [1,2]. With high speed it is possible to track individual red cells, white cells, platelets and lengths of plasma as they traverse the network [3,4,5,6] Such approaches offer a uniquely non-invasive “window” to the internal microvasculature of the body, in particular that located within neural tissue, which is not afforded by other investigative means. Previous work has demonstrated structural vascular adaptations including altered branching [11], tortuosity [12,13], wall thickening with narrowing of the lumen [12,14,15,16,17], and the formation of overt microstructural abnormalities such as microaneurysms [18,19] In many cases these are detectable prior to pathology observable on standard clinical examinations
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