Optical Coherence Tomography Angiography in Diabetes

Patterns of Progression of Nonproliferative Diabetic Retinopathy Using Non-Invasive Imaging

Purpose

To identify progression of nonproliferative diabetic retinopathy (NPDR) in patients with type 2 diabetes by combining optical coherence tomography angiography (OCTA) metrics and color fundus photography (CFP) images.

Methods

This study was a post hoc analysis of a prospective longitudinal cohort study (CORDIS, NCT03696810) with 2-year duration. This study enrolled 122 eyes. Ophthalmological examinations included OCTA and CFP. OCTA metrics included skeletonized vessel density (SVD) and perfusion density (PD) at the superficial capillary plexus (SCP) and deep capillary plexus (DCP). Microaneurysm turnover analysis and Early Treatment Diabetic Retinopathy Study (ETDRS) grading for diabetic retinopathy (DR) severity assessment were performed on 7-field CFP.

Results

Eyes graded as ETDRS level 20 showed significant capillary nonperfusion predominantly in the inner ring area in the SCP (P < 0.001), whereas eyes graded as ETDRS level 35 and ETDRS levels 43 and 47 showed significant capillary nonperfusion in both the SCP and DCP in both inner and outer rings (P < 0.001). When evaluating rates of progression in capillary nonperfusion for the 2-year period of follow-up, changes were found predominantly in the DCP for SVD and PD and were better identified in the outer ring area. Microaneurysm turnover contributes to the characterization of NPDR progression by discriminating ETDRS level 35 from ETDRS levels 43 and 47 (P < 0.001), which could not be achieved using only OCTA metrics.

Conclusions

Patterns of progression of NPDR can be identified combining OCTA examinations of the superficial and deep retinal capillary plexi of central retina and determination of microaneurysm turnover from fundus photographs.

Translational Relevance

Our study reports results from a registered clinical trial that advances understanding of disease progression in NPDR.

Imaging Biomarkers of Mesopic and Dark-Adapted Macular Functions in Eyes With Treatment-Naïve Mild Diabetic Retinopathy

PURPOSE

To investigate the relationship between imaging biomarkers and mesopic and dark-adapted (ie, scotopic) functions in patients with treatment-naïve mild diabetic retinopathy (DR) and normal visual acuity.

DESIGN

Prospective cross-sectional study.

METHODS

In this study, 60 patients with treatment-naïve mild DR (Early Treatment of Diabetic Retinopathy Study levels 20-35) and 30 healthy control subjects underwent microperimetry, structural optical coherence tomography (OCT), and OCT angiography (OCTA).

RESULTS

The foveal mesopic (22.4 ± 4.5 dB and 25.8 ± 2.0 dB, P = .005), parafoveal mesopic (23.2 ± 3.8 and 25.8 ± 1.9, P < .0001), and parafoveal dark-adapted (21.1 ± 2.8 dB and 23.2 ± 1.9 dB, P = .003) sensitivities were reduced in DR eyes. For foveal mesopic sensitivity, the regression analysis showed a significant topographic association with choriocapillaris flow deficits percentage (CC FD%; β = -0.234, P = .046) and ellipsoid zone (EZ) normalized reflectivity (β = 0.282, P = .048). Parafoveal mesopic sensitivity was significantly topographically associated with inner retinal thickness (β = 0.253, P = .035), deep capillary plexus (DCP) vessel length density (VLD; β = 0.542, P = .016), CC FD% (β = -0.312, P = .032), and EZ normalized reflectivity (β = 0.328, P = .031). Similarly, parafoveal dark-adapted sensitivity was topographically associated with inner retinal thickness (β = 0.453, P = .021), DCP VLD (β = 0.370, P = .030), CC FD% (β = -0.282, P = .048), and EZ normalized reflectivity (β = 0.295, P = .042).

CONCLUSIONS

In treatment-naïve mild DR eyes, both rod and cone functions are affected and they are associated with both DCP and CC flow impairment, which suggests that a macular hypoperfusion at these levels might implicate a reduction in photoreceptor function. Normalized EZ reflectivity may be a valuable structural biomarker for assessing photoreceptor function in DR. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

Deep Learning in Optical Coherence Tomography Angiography: Current Progress, Challenges, and Future Directions

Optical coherence tomography angiography (OCT-A) provides depth-resolved visualization of the retinal microvasculature without intravenous dye injection. It facilitates investigations of various retinal vascular diseases and glaucoma by assessment of qualitative and quantitative microvascular changes in the different retinal layers and radial peripapillary layer non-invasively, individually, and efficiently. Deep learning (DL), a subset of artificial intelligence (AI) based on deep neural networks, has been applied in OCT-A image analysis in recent years and achieved good performance for different tasks, such as image quality control, segmentation, and classification. DL technologies have further facilitated the potential implementation of OCT-A in eye clinics in an automated and efficient manner and enhanced its clinical values for detecting and evaluating various vascular retinopathies. Nevertheless, the deployment of this combination in real-world clinics is still in the "proof-of-concept" stage due to several limitations, such as small training sample size, lack of standardized data preprocessing, insufficient testing in external datasets, and absence of standardized results interpretation. In this review, we introduce the existing applications of DL in OCT-A, summarize the potential challenges of the clinical deployment, and discuss future research directions.

Towards standardizing retinal optical coherence tomography angiography: a review

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.

Optical coherence tomography angiography in the management of diabetic retinopathy

The introduction of optical coherence tomography angiography (OCTA) has granted a significant improvement in the assessment of patients with diabetes. In this review, we will provide a description of the prominent OCTA findings in diabetes. In detail, this imaging technology proved that both the retinal and choroidal circulation is affected in diabetic subjects. The recent employment of widefield technology and a three-dimensional (3D) visualization in OCTA imaging are also discussed.