Optical coherence tomography angiography (OCTA) is a noninvasive method of 3D imaging of the retinal and choroidal circulations. However, vascular depth discrimination is limited by superficial vessels projecting flow signal artifact onto deeper layers. The projection-resolved (PR) OCTA algorithm improves depth resolution by removing projection artifact while retaining in-situ flow signal from real blood vessels in deeper layers. This novel technology allowed us to study the normal retinal vasculature in vivo with better depth resolution than previously possible. Our investigation in normal human volunteers revealed the presence of 2 to 4 distinct vascular plexuses in the retina, depending on location relative to the optic disc and fovea. The vascular pattern in these retinal plexuses and interconnecting layers are consistent with previous histologic studies. Based on these data, we propose an improved system of nomenclature and segmentation boundaries for detailed 3-dimensional retinal vascular anatomy by OCTA. This could serve as a basis for future investigation of both normal retinal anatomy, as well as vascular malformations, nonperfusion, and neovascularization.

Shadowgraphic projection artifacts from superficial vasculature interfere with the visualization of deeper vascular networks in optical coherence tomography angiography (OCT-A). We developed a novel algorithm to remove this artifact by resolving the ambiguity between in situ and projected flow signals. The algorithm identifies voxels with in situ flow as those where intensity-normalized decorrelation values are higher than all shallower voxels in the same axial scan line. This "projection-resolved" (PR) algorithm effectively suppressed the projection artifact on both en face and cross-sectional angiograms and enhanced depth resolution of vascular networks. In the human macula, the enhanced angiograms show three distinct vascular plexuses in the inner retina and no vessels in the outer retina. We demonstrate that PR OCT-A cleanly removes flow projection from the normally avascular outer retinal slab while preserving the density and continuity of the intermediate and deep retinal capillary plexuses.

Optical coherence tomography angiography (OCTA) is a noninvasive approach that can visualize blood vessels down to the capillary level. With the advent of high-speed OCT and efficient algorithms, practical OCTA of ocular circulation is now available to ophthalmologists. Clinical investigations that used OCTA have increased exponentially in the past few years. This review will cover the history of OCTA and survey its most important clinical applications. The salient problems in the interpretation and analysis of OCTA are described, and recent advances are highlighted.

Purpose To detect macular perfusion defects in glaucoma using projection-resolved optical coherence tomography (OCT) angiography. Design Prospective observation study. Participants 30 perimetric glaucoma and 30 age-matched normal participants were included. Methods One eye of each participant was imaged using 6mm×6mm macular OCT angiography (OCTA) scan pattern by 70-kHz 840-nm spectral-domain OCT. Flow signal was calculated by the split-spectrum amplitude-decorrelation angiography algorithm (SSADA). A projection-resolved OCTA (PR-OCTA) algorithm was used to remove flow projection artifacts. Four en face OCTA slabs were analyzed: the superficial vascular complex (SVC), intermediate capillary plexus (ICP), deep capillary plexus (DCP) and all-plexus retina (SVC+ICP+DCP). The vessel density (VD), defined as the percentage area occupied by flow pixels, was calculated from en face OCTA. A novel algorithm was used to adjust the vessel density to compensate for local variations in OCT signal strength. Main Outcome Measures Macular retinal VD, ganglion cell complex (GCC) thickness, and visual field (VF) sensitivity. Results Focal capillary dropout could be visualized in the SVC, but not the ICP and DVP, in glaucomatous eyes. In the glaucoma group, the SVC and all-plexus retinal VD (mean±SD: 47.2%±7.1% and 73.5%±6.6%) were lower than the normal group (60.5%±4.0% and 83.2%±4.2%, both P <0.001, t test). The ICP and DCP VD were not significantly lower in the glaucoma group. Among the overall macular VD parameters, the SVC VD had the best diagnostic accuracy as measured by the area under the receiver operating characteristic curve (AROC). The accuracy was even better when the worse hemisphere (inferior or superior) was used, achieving an AROC of 0.983 and a sensitivity of 96.7% at a specificity of 95%. Among the glaucoma participants, the hemispheric SVC VD values were highly correlated with the corresponding GCC thickness and VF sensitivity (P<0.003). The reflectance compensation step in VD calculation significantly improved repeatability, normal population variation, and correlation with VF and GCC thickness. Conclusions Based on PR-OCTA, glaucoma preferentially affects perfusion in the SVC in the macula more than the deeper plexuses. Reflectance-compensated SVC VD measurement by PR-OCTA detected glaucoma with high accuracy and could be useful in the clinical evaluation of glaucoma.

This article provides an overview of advanced image processing for three dimensional (3D) optical coherence tomographic (OCT) angiography of macular diseases, including age-related macular degeneration (AMD) and diabetic retinopathy (DR). A fast automated retinal layers segmentation algorithm using directional graph search was introduced to separates 3D flow data into different layers in the presence of pathologies. Intelligent manual correction methods are also systematically addressed which can be done rapidly on a single frame and then automatically propagated to full 3D volume with accuracy better than 1 pixel. Methods to visualize and analyze the abnormalities including retinal and choroidal neovascularization, retinal ischemia, and macular edema were presented to facilitate the clinical use of OCT angiography.

PurposeThe purpose of this study was to evaluate an automated algorithm for detecting avascular area (AA) in optical coherence tomography angiograms (OCTAs) separated into three individual plexuses using a projection-resolved technique.MethodsA 3 × 3 mm macular OCTA was obtained in 13 healthy and 13 mild nonproliferative diabetic retinopathy (NPDR) participants. A projection-resolved algorithm segmented OCTA into three vascular plexuses: superficial, intermediate, and deep. An automated algorithm detected AA in each of the three plexuses that were segmented and in the combined inner-retinal angiograms. We assessed the diagnostic accuracy of extrafoveal and total AA using segmented and combined angiograms, the agreement between automated and manual detection of AA, and the within-visit repeatability.ResultsThe sum of extrafoveal AA from the segmented angiograms was larger in the NPDR group by 0.17 mm2 (P < 0.001) and detected NPDR with 94.6% sensitivity (area under the receiver operating characteristic curve [AROC] = 0.99). In the combined inner-retinal angiograms, the extrafoveal AA was larger in the NPDR group by 0.01 mm2 (P = 0.168) and detected NPDR with 26.9% sensitivity (AROC = 0.62). The total AA, inclusive of the foveal avascular zone, in the segmented and combined angiograms, detected NPDR with 23.1% and 7.7% sensitivity, respectively. The agreement between the manual and automated detection of AA had a Jaccard index of >0.8. The pooled SDs of AA were small compared with the difference in mean for control and NPDR groups.ConclusionsAn algorithm to detect AA in OCTA separated into three individual plexuses using a projection-resolved algorithm accurately distinguishes mild NPDR from control eyes. Automatically detected AA agrees with manual delineation and is highly repeatable.

Abstract:Artifacts introduced by eye motion in optical coherence tomography angiography (OCTA) affect the interpretation of images and the quantification of parameters with clinical value. Eradication of such artifacts in OCTA remains a technical challenge. We developed an algorithm that recognizes five different types of motion artifacts and used it to evaluate the performance of three motion removal technologies. On en face maximum projection of flow images, the summed flow signal in each row and column and the correlation between neighboring rows and columns were calculated. Bright line artifacts were recognized by large summed flow signal. Drifts, distorted lines, and stretch artifacts exhibited abnormal correlation values. Residual lines were simultaneously a local maximum of summed flow and a local minimum of correlation. Tracking-assisted scanning integrated with motion correction technology (MCT) demonstrated higher performance than tracking or MCT alone in healthy and diabetic eyes. Huang, and Y. Jia, "Advanced image processing for optical coherence tomographic angiography of macular diseases," Biomed. Opt. Express 6(12), 4661-4675 (2015).

Optical coherence tomography angiography (OCTA) is limited by projection artifacts from the superficial blood vessels onto deeper layers. We have recently described projection-resolved (PR) OCTA that solves the ambiguity between in situ flow and flow projection along each axial scan and suppresses the artifact on both en face and crosssectional angiograms. While this method significantly improved the depth resolution of OCTA, the vascular integrity of the deeper layers was not fully preserved. In this study, we propose a novel reflectance-based projection-resolved (rbPR) OCTA algorithm which uses OCT reflectance to enhance the flow signal and suppress the projection artifacts in 3-dimensional OCTA. We demonstrated quantitatively that rbPR improved the vascular connectivity and improved the discrimination of the deeper plexus angiograms in healthy eyes, compared to prior PR-OCTA method. We also demonstrated qualitatively that rbPR removes flow projection artifacts more completely from the outer retinal slab in the eyes with age-related macular degeneration, and preserves vascular integrity of the intermediate and deep capillary plexuses in the eyes with diabetic retinopathy. Additionally, this method improves the resolution of the choriocapillaris and demonstrates details comparable to scanning electron microscopy. Huang, and Y. Jia, "Advanced image processing for optical coherence tomographic angiography of macular diseases," Biomed. Opt. Express 6(12), 4661-4675 (2015).