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Imaging relative stasis of the blood column in human retinal capillaries
Phillip Bedggood1, Andrew Metha1
1Department of Optometry and Vision Sciences, The University of Melbourne, 3010, Australia.
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.
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.