Towards standardizing retinal optical coherence tomography angiography: a review

Abstract

The visualization and assessment of retinal microvasculature are important in the study, diagnosis, monitoring, and guidance of treatment of ocular and systemic diseases. With the introduction of optical coherence tomography angiography (OCTA), it has become possible to visualize the retinal microvasculature volumetrically and without a contrast agent. Many lab-based and commercial clinical instruments, imaging protocols and data analysis methods and metrics, have been applied, often inconsistently, resulting in a confusing picture that represents a major barrier to progress in applying OCTA to reduce the burden of disease. Open data and software sharing, and cross-comparison and pooling of data from different studies are rare. These inabilities have impeded building the large databases of annotated OCTA images of healthy and diseased retinas that are necessary to study and define characteristics of specific conditions. This paper addresses the steps needed to standardize OCTA imaging of the human retina to address these limitations. Through review of the OCTA literature, we identify issues and inconsistencies and propose minimum standards for imaging protocols, data analysis methods, metrics, reporting of findings, and clinical practice and, where this is not possible, we identify areas that require further investigation. We hope that this paper will encourage the unification of imaging protocols in OCTA, promote transparency in the process of data collection, analysis, and reporting, and facilitate increasing the impact of OCTA on retinal healthcare delivery and life science investigations.

Fig. 1. Number of retinal optical coherence tomography angiography peer-reviewed publications by year since 2004.

Data sourced: Pubmed, with “optical coherence tomography angiography”, “OCT-angiography” and “retina” as the search key words. Data retrieved on 28 January 2022

Fig. 2. Drawing of retinal circulation.

Light impinges on the retina from above. SVP (superficial vascular plexus) comprises superficial arterioles and venules and SCP (superficial capillary plexus); DVC (deep vascular complex) includes ICP (intermediate capillary plexus) and DCP (deep capillary plexus). SCP, ICP, and DCP are thin vascular complexes that are connected to one another and receive the arteriolar supply (red) from SVP arterioles and drain (blue) to SVP venules. NFL, nerve fiber layer; GCL, ganglion cell layer; IPL, inner plexiform layer; INL, inner nuclear layer; OPL, outer plexiform layer; HFL, Henle fiber layer; ONL, outer nuclear layer; PR, photoreceptors; RPE, retinal pigment epithelium. The Bruch’s membrane (BM) is just below the RPE. The inner retina is defined as the NFL to OPL, and the outer retina (which contains no vessels) as the HFL, ONL, PR, and RPE. Not shown: in the peripapillary retina (near the optic disc, not shown here but presented in Fig. 3), an additional vascular plexus is present: RPCP (radial peripapillary capillary plexus). RPCP and SVP together are commonly known as the SVC (superficial vascular complex). Adapted with permission from Nesper and Fawzi

Fig. 3. Retinal microvasculature in practice.

a Fundus camera image from a healthy volunteer with marked retinal sections; b Matched OCT structural B-scan with detected vessel overlay; red—retinal and yellow—choroidal vessels; c anatomic localization on the OCT image of the retinal vascular plexuses and their names; d Confocal microscopy ex vivo showing in-depth organization of retinal vasculature at different transverse distances (eccentricities) from the fovea; e, f Confocal microscopy fundus view of retinal vasculature at different eccentricities (left) and different plexuses from the parafoveal region (right). Images in d, e and f obtained from deceased human donor eyes perfused with fluorescent contrast agent without retinal disease (d, e) and with diabetic retinopathy (f) Yellow arrows in f indicate microaneurysms and the yellow star marks an area of impaired capillary perfusion. Reduced vessel density in the subject with diabetic retinopathy is observed. d, e, f Adapted with permission from An et al.

Fig. 4. Comparison of OCTA, fluorescein angiography (FA), indocyanine green angiography (ICGA), and histology.

a, b FA, ICGA, and OCTA segmented to superficial vascular plexus (SVP), deep capillary plexus (DCP), choriocapillaris, and choroid, from a patient with choroidal neovascularization secondary to age-related macular degeneration. a FA shows leakage of dye obscuring details of the fine blood vessels within the choroidal neovascularization that can be more clearly seen in OCTA at the level of choriocapillaris than ICGA in (b). c Confocal microscopy and OCTA from an isolated perfused porcine eye ex vivo. For the OCTA image acquisition, the whole porcine eyeball was used, and the retinal vasculature was perfused using red blood cells. After the OCTA experiment, retinal vasculature histology was performed. The retina was perfused with fluorescein as a contrast agent, and the eyeball was cut open, flat-mounted and imaged using confocal scanning laser microscopy. Both images are maximum intensity projections from the full retinal thickness. c Adapted with permission from Yu et al.

Fig. 5. Simplified schematic of OCTA scanning protocol.

a A raster scanning protocol is applied to visualize blood vessels; A-scans per B-scan sets x-axis sampling density; B scans per volume sets y-axis sampling density. b Four repeated B-scans at one y-location are used to create an OCTA B-scan; the procedure is repeated for successive positions along the y-axis; the final number of OCTA B-scans impacts on sampling density along y-axis; ΔT—interscan time; T_a—acquisition time. c Maximum intensity projection (MIP) is applied to OCTA B-scan over depth range of interest (where vessels are located) to generate one line of the en face OCTA image. d Illustration of how the same number of sampling points is distributed for smaller and larger imaging areas

Fig. 6. Comparison of OCTA images versus FOV and sampling density.

All images acquired with AngioVue. First row shows original images. Second row shows zoomed images of the same 1 × 1-mm region of interest with transverse scanning density (left to right) of 2, 1, and 0.85, respectively, strongly suggesting only the images in the first column are of sufficient quality for quantification purposes

Fig. 7. Effect of varying axial length on OCTA scan dimensions.

The incident beam is shown for three scan paths (green, red, and yellow; β₀ is the incident angle at the cornea and γ₀ is the angle subtended on the retina); green and yellow paths represent the maximum deviations, and the red path is on axis. Refraction from the scan lens (not shown), cornea, and lens focuses each light path on the retina. a Axial length equal to the defined ocular axial length of OCTA instrument so the linear size of the measured retinal diameter (D_m) corresponds to the true retinal diameter (D_t). b Axial length shorter than defined ocular axial length results in D_t1 < D_m. c Axial length longer than defined ocular axial length results in D_t2 > D_m. Below each schematic diagram, a visual representation demonstrates how the OCTA instrument would measure a ring of 1 mm diameter (without correction for axial length variation, red circle) in each case versus the true 1 mm diameter (blue ring). Adapted with permission from Sampson et al.

Fig. 8. OCTA microvascular metrics.

Visual representation of recommended OCTA-based retinal microvascular metrics as defined in Table 1