<p>Age-related macular degeneration (AMD) is a vision-threatening disease that affects the outer retina and choroid of elderly adults. Because photoreceptors are found in the outer retina and rely primarily on the trophic support of the underlying choriocapillaris, imaging of flow or lack thereof in choriocapillaris by optical coherence tomography angiography (OCTA) has great clinical potential in AMD assessment. We introduce a metric using OCTA, named “focal perfusion loss” (FPL) to describe the effects of age and non-neovascular AMD on choriocapillaris flow. Because OCTA imaging of choriocapillaris is vulnerable to artifacts—namely motion, projections, segmentation errors, and shadows—they are removed by postprocessing software. The shadow detection software is a machine learning algorithm recently developed for the evaluation of the retinal circulation and here adapted for choriocapillaris analysis. It aims to exclude areas with unreliable flow signal due to blocking of the OCT beam by objects anterior to the choriocapillaris (e.g., drusen, retinal vessels, vitreous floaters, and iris). We found that both the FPL and the capillary density were able to detect changes in the choriocapillaris of AMD and healthy age-matched subjects with respect to young controls. The dominant cause of shadowing in AMD is drusen, and the shadow exclusion algorithm helps determine which areas under drusen retain sufficient signal for perfusion evaluation and which areas must be excluded. Such analysis allowed us to determine unambiguously that choriocapillaris density under drusen is indeed reduced.</p>
We propose a three-dimensional (3-D) registration method to correct motion artifacts and construct the volume structure for angiographic and structural optical coherence tomography (OCT). This algorithm is particularly suitable for the nonorthogonal wide-field OCT scan acquired by a ultrahigh-speed swept-source system (>200 kHz A-scan rate). First, the transverse motion artifacts are corrected by the between-frame registration based on en face OCT angiography (OCTA). After A-scan transverse translation between B-frames, the axial motions are corrected based on the rebuilt boundary of inner limiting membrane. Finally, a within-frame registration is performed for local optimization based on cross-sectional OCTA. We evaluated this algorithm on retinal volumes of six normal subjects. The results showed significantly improved retinal smoothness in 3-D-registered structural OCT and image contrast on en face OCTA.
A microfluidic chip with microchannels ranging from 8 to 96 μm was used to mimic blood vessels down to the capillary level. Blood flow within the microfluidic channels was analyzed with split-spectrum amplitude-decorrelation angiography (SSADA)-based optical coherence tomography (OCT) angiography. It was found that the SSADA decorrelation value was related to both blood flow speed and channel width. SSADA could differentiate nonflowing blood inside the microfluidic channels from static paper. The SSADA decorrelation value was approximately linear with blood flow velocity up to a threshold Vsat of 5.83±1.33 mm/s (mean±standard deviation over the range of channel widths). Beyond this threshold, it approached a saturation value Dsat. Dsat was higher for wider channels, and approached a maximum value Dsm as the channel width became much larger than the beam focal spot diameter. These results indicate that decorrelation values (flow signal) in capillary networks would be proportional to both flow velocity and vessel caliber but would be capped at a saturation value in larger blood vessels. These findings are useful for interpretation and quantification of clinical OCT angiography results.