摘要：Quantitative imaging using optical coherence tomography angiography (OCTA) could provide objective tools for the detection and characterization of diabetic retinopathy (DR). In this study, an operator combining the second derivative and Gaussian multiscale convolution is applied to identify the retinal orientation at each pixel in the OCTA image. We quantified the pattern of retinal vascular orientation and developed three novel quantitative metrics including vessel preferred orientation, vessel anisotropy, and vessel area. Each of eight 45º sectors of the circular disk centered at the macular region was defined as the region of interest. Significant sectoral differences were observed in the preferred orientation (p < 0.0001) and vessel area (p < 0.0001) in the 34 healthy subjects, whereas vessel anisotropy did not demonstrate a significant difference among the eight sectors (p = 0.054). Differential retinal microvascular orientation patterns were observed between healthy controls (n = 34) and the DR subjects (n = 7). The vessel area characterized from the vascular orientation pattern was shown to be strongly correlated with the traditionally reported vessel density (Pearson R > 0.97, p < 0.0001). With three metrics calculated from the vascular orientation pattern simultaneously and sectorally, our quantitative assessment for retinal microvasculature provides more information than vessel density alone and thereby may enhance the detection of DR. These preliminary results suggest the feasibility and advantage of our vessel orientation-based quantitative approach using OCTA to characterize DR-associated changes in retinal microvasculature.
