Measurement of spatial and temporal retinal perfusion heterogeneity using OCTA

Abstract

Purpose : Capillary perfusion is spatially and temporally heterogeneous in the retina, and likely plays a role in the pathogenesis of human retinal vascular diseases, for example Diabetic Retinopathy. We propose that variation in sequentially acquired OCT angiography (OCTA) volumes can be measured to estimate retinal perfusion heterogeneity, and investigate the sensitivity of the measurement to the OCTA acquisition parameters and OCTA processing methods used.

Methods : Ten porcine eyes were perfused with red blood cells for OCTA image acquisition by cannulation of the central retinal artery. For each eye, 20 OCTA volumes were sequentially acquired under two imaging protocols with a custom developed 200 kHz SS OCT: 2BM and 4BM, where ‘BM’ denotes the number of repeated B-scans acquired at each location. Each OCT data set was processed independently using four different methods for generating the angiography signal: subtraction, decorrelation, speckle-variance, and complex-variance. OCTA volumes were then layer-wise segmented to generate 2D superficial vascular complex (SVC) and deep vascular complex (DVC) en face images. The coefficient of variation (CoV; defined as the standard deviation of a signal divided by its mean value) was calculated for each pixel in the temporally stacked SVC and DVC images. The mean CoV for each BM acquisition and OCTA processing method combination was then calculated.

Results : The mean CoV differed significantly (P<.05) between each BM acquisition/OCTA processing method combination, as well as between each vascular complex. Mean CoV was, on average: higher for 2BM acquisition than 4BM; higher for complex- and speckle-variance OCTA than either of decorrelation or subtraction OCTA methods; and lower in the SVC than in the DVC. Quantitative CoV results are summarized in Figure 1, and these results are presented qualitatively in Figure 2 as CoV-based heat maps.

Conclusions : Retinal perfusion heterogeneity may be measured with OCTA, but measurements differ based on the OCTA acquisition and processing methods used. These differences should be further investigated to determine the optimal OCTA image acquisition and processing method for detecting retinal perfusion heterogeneity. Future work will combine this method with 3D motion correction to perform perfusion heterogeneity analysis on human OCTA data.

This is a 2021 ARVO Annual Meeting abstract.