Automated segmentation and fractal analysis of high-resolution non-invasive capillary perfusion maps of the human retina.

The retina provides a window to study the pathophysiology of cerebrovascular diseases. Pathological retinal microvascular changes may reflect microangiopathic processes in the brain. Recent advances in optical imaging techniques have enabled the imaging of the retinal microvasculature at the capillary level, and the generation of high-resolution, non-invasive capillary perfusion maps (nCPMs) with the Retinal Function Imager (RFI). However, the lack of quantitative analyses of the nCPMs may limit the wider application of the method in clinical research. The goal of this project was to demonstrate the feasibility of automated segmentation and fractal analysis of nCPMs. We took two nCPMs of each subject in a group of 6 healthy volunteers and used our segmentation algorithm to do the automated segmentation for monofractal and multifractal analyses. The monofractal dimension was 1.885±0.020, and the multifractal dimension was 1.876±0.010 (P=0.108). The coefficient of repeatability was 0.070 for monofractal analysis and 0.026 for multifractal analysis. This study demonstrated that the automatic segmentation of nCPMs is feasible for fractal analyses. Both monofractal and multifractal analyses yielded similar results. The quantitative analyses of microvasculature at the capillary level may open up a new era for studying microvascular diseases such as cerebral small vessel disease.