Superficial capillary perfusion on optical coherence tomography angiography differentiates moderate and severe nonproliferative diabetic retinopathy

Quantitative Analysis of the Vasculature and Cone Photoreceptors in Subjects With Diabetes Without Diabetic Retinopathy

PURPOSE

To characterize any differences in the vasculature and cone photoreceptor packing geometry (CPG) between subjects with diabetes without/no diabetic retinopathy (NDR) and healthy controls.

METHODS

Eight NDR and five controls were enrolled. Optical coherence tomography angiography (OCTA) taken at the macula was used to measure vessel density, vessel length density, and vessel density index (VDI) in three vascular plexuses, namely, the superficial vascular plexus, intermediate capillary plexus, and deep capillary plexus (DCP). The choriocapillaris (CC) flow deficit (FD) was also measured. OCTA images were binarized and processed to extrapolate the parafovea and parafoveal quadrants and the OCTA indices mentioned above. The CC was processed with six different radii to quantify FD. Adaptive optics - scanning laser ophthalmoscopy images were acquired and processed to extract CPG indices, i.e., cone density (CD), cone-to-cone spacing (CS), linear dispersion index, heterogeneity packing index and percent of cells with six neighbors at 3.6° in the temporal retina.

RESULTS

In all eyes, statistically significant differences were found (i) in parafoveal FD across the six radii (p < 0.001) and (ii) in the correlation between the parafoveal temporal quadrant (PTQ) DCP VDI and CS (r = 0.606, p = 0.048). No other significant correlations were found. For OCTA or CPG indices, no significant differences were found between the cohorts in the parafovea or parafoveal quadrants.

CONCLUSIONS

CS is the most sensitive CPG index for detecting alterations in the cone mosaic. The DCP and the cone photoreceptors are significantly correlated, indicating that alterations in the DCP can affect the cones. Future work elucidating the vascular alterations and neurodegeneration present in diabetic eyes should focus on the DCP and multiple CPG indices, not solely CD. Moreover, such alterations are highly localized, hence using larger regions e.g. parafovea versus smaller areas, such as the PTQ, will potentially mask significant correlations.

Reduced macular thickness and vascular density in abnormal glucose metabolism patients: A meta-analysis of optical coherence tomography (OCT) and OCT angiography studies

BACKGROUND

Alterations in macular thickness and vascular density before clinically visible diabetic retinopathy (DR) remain inconclusive. This study aimed to determine whether retinal manifestations in abnormal glucose metabolism (AGM) patients differ from those in the healthy individuals.

METHODS

PubMed, Embase, and Web of Science were searched between 2000 and 2021. The eligibility criteria were AGM patients without DR. Primary and secondary outcomes measured by optical coherence tomography (OCT) and OCT angiography (OCTA) were analyzed and expressed as standardized mean differences (SMDs) with 95% confidence intervals (CIs). A random-effects model was used in the data synthesis. The potential publication bias for the variables was evaluated using Egger's test.

RESULTS

A total of 86 observational studies involving 13,773 participants and 15,416 eyes were included. OCT revealed that compared to healthy controls, the total macular thickness of AGM patients was thinner, including the thickness of fovea (-0.24, 95% CI [-0.39, -0.08]; P  = 0.002, I2  = 87.7%), all regions of parafovea (-0.32, 95% CI [-0.54, -0.11]; P  = 0.003; I2  = 71.7%) and the four quadrants of perifovea; the thickness of peripapillary retinal nerve fiber layer (pRNFL), macular retinal nerve fiber layer (mRNFL), and ganglion cell layer (GCL) also decreased. OCTA indicated that the superficial and deep vascular density decreased, the foveal avascular zone (FAZ) area enlarged, and the acircularity index (AI) reduced in AGM individuals.

CONCLUSIONS

Retinal thinning and microvascular lesions have occurred before the advent of clinically detectable DR; OCT and OCTA may have the potential to detect these preclinical changes.

REGISTRATION

PROSPERO; http://www.crd.york.ac.uk/prospero/ ; No. CRD42021269885.

Optical coherence tomography angiography analysis methods: a systematic review and meta-analysis

Optical coherence tomography angiography (OCTA) is widely used for non-invasive retinal vascular imaging, but the OCTA methods used to assess retinal perfusion vary. We evaluated the different methods used to assess retinal perfusion between OCTA studies. MEDLINE and Embase were searched from 2014 to August 2021. We included prospective studies including ≥ 50 participants using OCTA to assess retinal perfusion in either global retinal or systemic disorders. Risk of bias was assessed using the National Institute of Health quality assessment tool for observational cohort and cross-sectional studies. Heterogeneity of data was assessed by Q statistics, Chi-square test, and I2 index. Of the 5974 studies identified, 191 studies were included in this evaluation. The selected studies employed seven OCTA devices, six macula volume dimensions, four macula subregions, nine perfusion analyses, and five vessel layer definitions, totalling 197 distinct methods of assessing macula perfusion and over 7000 possible combinations. Meta-analysis was performed on 88 studies reporting vessel density and foveal avascular zone area, showing lower retinal perfusion in patients with diabetes mellitus than in healthy controls, but with high heterogeneity. Heterogeneity was lowest and reported vascular effects strongest in superficial capillary plexus assessments. Systematic review of OCTA studies revealed massive heterogeneity in the methods employed to assess retinal perfusion, supporting calls for standardisation of methodology.

Artificial intelligence and hemodynamic studies in optical coherence tomography angiography for diabetic retinopathy evaluation: A review

Diabetic retinopathy (DR) is a rapidly emerging retinal abnormality worldwide, which can cause significant vision loss by disrupting the vascular structure in the retina. Recently, optical coherence tomography angiography (OCTA) has emerged as an effective imaging tool for diagnosing and monitoring DR. OCTA produces high-quality 3-dimensional images and provides deeper visualization of retinal vessel capillaries and plexuses. The clinical relevance of OCTA in detecting, classifying, and planning therapeutic procedures for DR patients has been highlighted in various studies. Quantitative indicators obtained from OCTA, such as blood vessel segmentation of the retina, foveal avascular zone (FAZ) extraction, retinal blood vessel density, blood velocity, flow rate, capillary vessel pressure, and retinal oxygen extraction, have been identified as crucial hemodynamic features for screening DR using computer-aided systems in artificial intelligence (AI). AI has the potential to assist physicians and ophthalmologists in developing new treatment options. In this review, we explore how OCTA has impacted the future of DR screening and early diagnosis. It also focuses on how analysis methods have evolved over time in clinical trials. The future of OCTA imaging and its continued use in AI-assisted analysis is promising and will undoubtedly enhance the clinical management of DR.

From diagnosis to prognosis: A paradigm shift for multimodal imaging in assessing diabetic macular edema

Diabetic macular edema (DME) is one of the leading causes of visual impairment in patients with diabetes. Multimodal imaging (MMI) has allowed a shift from DME diagnosis to prognosis. Although there are no accepted guidelines, MMI may also lead to treatment customization. Several study groups have tried to identify structural biomarkers that can predict treatment response and long-term visual prognosis. The purpose of this editorial is to review currently proposed optical coherence tomography (OCT) and optical coherence tomography angiography (OCT-A) biomarkers.

Application of ImageJ in Optical Coherence Tomography Angiography (OCT-A): A Literature Review

Background

This study aimed to review the literature on the application of ImageJ in optical coherence tomography angiography (OCT-A) images.

Methods

A general search was performed in PubMed, Google Scholar, and Scopus databases. The authors evaluated each of the selected articles in order to assess the implementation of ImageJ in OCT-A images.

Results

ImageJ can aid in reducing artifacts, enhancing image quality to increase the accuracy of the process and analysis, processing and analyzing images, generating comparable parameters such as the parameters that assess perfusion of the layers (vessel density (VD), skeletonized density (SD), and vessel length density (VLD)) and the parameters that evaluate the structure of the layers (fractal dimension (FD), vessel density index (VDI), and lacunarity (LAC)), and the foveal avascular zone (FAZ) that are used widely in the retinal and choroidal studies), and establishing diagnostic criteria. It can help to save time when the dataset is huge with numerous plugins and options for image processing and analysis with reliable results. Diverse studies implemented distinct binarization and thresholding techniques, resulting in disparate outcomes and incomparable parameters. Uniformity in methodology is required to acquire comparable data from studies employing diverse processing and analysis techniques that yield varied outcomes.

Conclusion

Researchers and professionals might benefit from using ImageJ because of how quickly and correctly it processes and analyzes images. It is highly adaptable and potent software, allowing users to evaluate images in a variety of ways. There exists a diverse range of methodologies for analyzing OCTA images through the utilization of ImageJ. However, it is imperative to establish a standardized strategy to ensure the reliability and consistency of the method for research purposes.

Optical coherence tomography angiography in diabetic retinopathy

There remain many unanswered questions on how to assess and treat the pathology and complications that arise from diabetic retinopathy (DR). Optical coherence tomography angiography (OCTA) is a novel and non-invasive three-dimensional imaging method that can visualize capillaries in all retinal layers. Numerous studies have confirmed that OCTA can identify early evidence of microvascular changes and provide quantitative assessment of the extent of diseases such as DR and its complications. A number of informative OCTA metrics could be used to assess DR in clinical trials, including measurements of the foveal avascular zone (FAZ; area, acircularity, 3D para-FAZ vessel density), vessel density, extrafoveal avascular zones, and neovascularization. Assessing patients with DR using a full-retinal slab OCTA image can limit segmentation errors and confounding factors such as those related to center-involved diabetic macular edema. Given emerging data suggesting the importance of the peripheral retinal vasculature in assessing and predicting DR progression, wide-field OCTA imaging should also be used. Finally, the use of automated methods and algorithms for OCTA image analysis, such as those that can distinguish between areas of true and false signals, reconstruct images, and produce quantitative metrics, such as FAZ area, will greatly improve the efficiency and standardization of results between studies. Most importantly, clinical trial protocols should account for the relatively high frequency of poor-quality data related to sub-optimal imaging conditions in DR and should incorporate time for assessing OCTA image quality and re-imaging patients where necessary.

Impaired cerebrovascular reactivity correlates with reduced retinal vessel density in patients with carotid artery stenosis: Cross-sectional, single center study

BACKGROUND

The cerebral and retinal circulation systems are developmentally, anatomically, and physiologically interconnected. Thus, we hypothesized that hypoperfusion due to atherosclerotic stenosis of the internal carotid artery (ICA) can result in disturbances of both cerebral and retinal microcirculations. We aimed to characterize parameters indicating cerebrovascular reactivity (CVR) and retinal microvascular density in patients with ICA stenosis, and assess if there is correlation between them.

METHODS

In this cross-sectional study the middle cerebral artery (MCA) blood flow velocity was measured by transcranial Doppler (TCD) and, simultaneously, continuous non-invasive arterial blood pressure measurement was performed on the radial artery by applanation tonometry. CVR was assessed based on the response to the common carotid artery compression (CCC) test. The transient hyperemic response ratio (THRR) and cerebral arterial resistance transient hyperemic response ratio (CAR-THRR) were calculated. Optical coherence tomography angiography (OCTA) was used to determine vessel density (VD) on the papilla whole image for all (VDP-WIall) and for small vessels (VDP-WIsmall). The same was done in the peripapillary region: all (VDPPall), and small (VDPPsmall) vessels. The VD of superficial (VDMspf) and deep (VDMdeep) macula was also determined. Significance was accepted when p<0.05.

RESULTS

Twenty-four ICA stenotic patients were evaluated. Both CVR and retinal VD were characterized. There was a significant, negative correlation between CAR-THRR (median = -0.40) and VDPPsmall vessels (median = 52%), as well as between VDPPall vessels (median = 58%), and similar correlation between CAR-THRR and VDP-WIsmall (median = 49.5%) and between VDP-WIall (median = 55%).

CONCLUSION

The significant correlation between impaired cerebrovascular reactivity and retinal vessel density in patients with ICA stenosis suggests a common mechanism of action. We propose that the combined use of these diagnostic tools (TCD and OCTA) helps to better identify patients with increased ischemic or other cerebrovascular risks.

Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images

Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. The condition has a great effect on the specificity of diagnosis, the monitoring of many physiological and pathological procedures, and the response and evaluation of therapeutic effectiveness in various fields of clinical practices, including primary eye diseases and systemic diseases such as diabetes. Therefore, precise diagnosis, classification, and automated image analysis models are crucial. In this paper, we propose an enhanced optical coherence tomography (EOCT) model to classify retinal OCT based on modified ResNet (50) and random forest algorithms, which are used in the proposed study's training strategy to enhance performance. The Adam optimizer is applied during the training process to increase the efficiency of the ResNet (50) model compared with the common pre-trained models, such as spatial separable convolutions and visual geometry group (VGG) (16). The experimentation results show that the sensitivity, specificity, precision, negative predictive value, false discovery rate, false negative rate accuracy, and Matthew's correlation coefficient are 0.9836, 0.9615, 0.9740, 0.9756, 0.0385, 0.0260, 0.0164, 0.9747, 0.9788, and 0.9474, respectively.

Perivenular Capillary Rarefaction in Diabetic Retinopathy: Interdevice Characterization and Association to Clinical Staging

Purpose

Geometric perfusion deficit (GPD) is a newly described OCT angiography (OCTA) parameter identifying the total area of presumed retinal ischemia. The aim of our study is to characterize differences in GPD and other common quantitative OCTA parameters between macular full field, perivenular zones, and periarteriolar zones for each clinical stage of nonproliferative diabetic retinopathy (DR) and to assess the influence of ultrahigh-speed acquisition and averaging on the described differences.

Design

Prospective observational study.

Participants

Forty-nine patients, including 11 (22.4%) with no sign of DR, 12 (24.5%) with mild DR, 13 (26.5%) with moderate DR, and 13 (26.5%) with severe DR. Patients with diabetic macular edema, proliferative DR, media opacity, head tremor, and overlapping retinal diseases or systemic diseases influencing OCTA were excluded.

Methods

OCT angiography was performed 3 times for each patient: 1 using Solix Fullrange single volume (V1) mode, 1 using Solix Fullrange 4 volumes mode with automatically averaged scan (V4), and 1 using AngioVue.

Main Outcome Measures

Full macular, periarteriolar, and perivenular perfusion density (PD), vessel length density (VLD), vessel density index, and GPD for both the superficial capillary plexus (SCP) and deep capillary plexus (DCP).

Results

In patients showing no sign of DR, PD and VLD were significantly lower in the perivenular area in both the DCP and SCP using V1 and V4, whereas GPD was significantly higher in the perivenular zone in the DCP and SCP with all 3 devices. In patients with mild DR, all 3 measurements (PD, VLD, and GPD) were significantly different in the perivenular zone with all 3 devices. In patients with moderate DR, PD and VLD were lower in the DCP and SCP when measured with V1 and V4. Moreover, GPD was higher in the perivenular zone in the DCP with all 3 devices, whereas only V4 detected a difference in the SCP. In severe DR, only V4 detected a lower PD and VLD and a higher GPD in the DCP of the perivenular zone. V4 also detected a higher GPD in the SCP.

Conclusions

Geometric perfusion deficit highlights prevalent perivenular location of macular capillary ischemia in all stages of DR. In severe DR patients, only averaging technology allows detection of the same finding.

Financial Disclosures

The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Optical Coherence Tomography Angiography of Volumetric Arteriovenous Relationships in the Healthy Macula and Their Derangement in Disease

Purpose

To characterize relative arteriovenous connectivity of the healthy macula imaged by optical coherence tomography angiography (OCTA) using a new volumetric tool.

Methods

OCTA volumes were obtained for 20 healthy controls (20 eyes). Two graders identified superficial arterioles and venules. We implemented a custom watershed algorithm to identify capillaries most closely connected to arterioles and venules by using the large vessels as seeds to flood the vascular network. We calculated ratios of arteriolar- to venular-connected capillaries (A/V ratios) and adjusted flow indices (AFIs) for superficial capillary plexuses (SCPs), middle capillary plexuses (MCPs), and deep capillary plexuses (DCPs). We also analyzed two eyes with proliferative diabetic retinopathy (PDR) and one eye with macular telangiectasia (MacTel) to evaluate the utility of this method in visualizing pathological vascular connectivity.

Results

In healthy eyes, the MCP showed a greater proportion of arteriolar-connected vessels than the SCP and DCP (all P < 0.001). In the SCP, the arteriolar-connected AFI exceeded the venular-connected AFI, but this pattern reversed in the MCP and DCP, with higher venular-connected AFI (all P < 0.001). In PDR eyes, preretinal neovascularization originated from venules, whereas intraretinal microvascular abnormalities were heterogeneous, with some originating from venules and others representing dilated MCP capillary loops. In MacTel, diving SCP venules formed the epicenter of the outer retinal anomalous vascular network.

Conclusions

Healthy eyes showed a higher MCP A/V ratio but relatively slower arteriolar vs. venular flow velocity in the MCP and DCP, which may explain deep retinal vulnerability to ischemia. In eyes with complex vascular pathology, our connectivity findings were consistent with histopathologic studies.

Deep Capillary Nonperfusion on OCT Angiography Predicts Complications in Eyes with Referable Nonproliferative Diabetic Retinopathy

OBJECTIVE

To evaluate the ability of capillary nonperfusion parameters on OCT angiography (OCTA) to predict the development of clinically significant outcomes in eyes with referable nonproliferative diabetic retinopathy (NPDR).

DESIGN

Prospective longitudinal observational study.

SUBJECTS

In total, 59 patients (74 eyes) with treatment-naive moderate and severe (referable) NPDR.

METHODS

Patients were imaged with OCTA at baseline and then followed-up for 1 year. We evaluated 2 OCTA capillary nonperfusion metrics, vessel density (VD) and geometric perfusion deficits (GPDs), in the superficial capillary plexus, middle capillary plexus (MCP), and deep capillary plexus (DCP). We compared the predictive accuracy of baseline OCTA metrics for clinically significant diabetic retinopathy (DR) outcomes at 1 year.

MAIN OUTCOME MEASURES

Significant clinical outcomes at 1 year, defined as 1 or more of the following-vitreous hemorrhage, center-involving diabetic macular edema, and initiation of treatment with pan-retinal photocoagulation or anti-VEGF injections.

RESULTS

Overall, 49 patients (61 eyes) returned for the 1-year follow-up. Geometric perfusion deficits and VD in the MCP and DCP correlated with clinically significant outcomes at 1 year (P < 0.001). Eyes with these outcomes had lower VD and higher GPD, indicating worse nonperfusion of the deeper retinal layers than those that remained free from complication. These differences remained significant (P = 0.046 to < 0.001) when OCTA parameters were incorporated into models that also considered sex, baseline corrected visual acuity, and baseline DR severity. Adjusted receiver operating characteristic curve for DCP GPD achieved an area under the curve (AUC) of 0.929, with sensitivity of 89% and specificity of 98%. In a separate analysis focusing on high-risk proliferative diabetic retinopathy outcomes, MCP and DCP GPD and VD remained significantly predictive with comparable AUC and sensitivities to the pooled analysis.

CONCLUSIONS

Evidence of deep capillary nonperfusion at baseline in eyes with clinically referable NPDR can predict short-term DR complications with high accuracy, suggesting that deep retinal ischemia has an important pathophysiologic role in DR progression. Our results suggest that OCTA may provide additional prognostic benefit to clinical DR staging in eyes with high risk.

Racial differences in quantitative optical coherence tomography angiography findings between older non-diabetics with co-morbidities

This cross-sectional study compared optical coherence tomography angiography (OCTA) parameters between older Black and White adults with systemic comorbidities in an effort to further understand racial differences in the retinal microvasculature. We analyzed vessel density at the superficial (SCP), intermediate (ICP), and deep capillary plexuses (DCP), foveal avascular zone (FAZ) parameters, and blood flow area (BFA) at the choriocapillaris. We used a mixed-effects linear regression model, controlling for hypertension and two eyes from the same subject, to compare OCTA parameters. Black subjects had lower foveal vessel density at the SCP and ICP, while no differences were observed at the parafovea or 3x3 mm macular area of any capillary layer. Black subjects had greater FAZ area, perimeter, and FD-300, a measurement of vessel density in a 300 μm wide ring around the FAZ. Black subjects also had lower BFA at the choriocapillaris. Within a cohort of subjects without hypertension, these differences remained statistically significant, with the exception of foveal vessel density at the SCP and foveal BFA of the choriocapillaris. These findings suggest that normative databases of OCTA parameters must strive to be diverse in nature to adequately capture differences across patient populations. Further study is required to understand if baseline differences in OCTA parameters contribute to epidemiological disparities in ocular diseases.

Hemodynamic Effects of Anti-Vascular Endothelial Growth Factor Injections on Optical Coherence Tomography Angiography in Diabetic Macular Edema Eyes

Purpose

To evaluate retinal hemodynamic responses to anti-vascular endothelial growth factor (VEGF) injection in eyes with diabetic macular edema using optical coherence tomography angiography (OCTA). We performed a comparison of two different thresholding methods to identify the most accurate for studying the vessel density (VD) in diabetic macular edema eyes.

Methods

The study prospectively included 26 eyes of 22 subjects (aged 60.2 ± 13.7 years) who underwent OCTA scan before and after anti-VEGF injection (mean interval between OCTA = 31.1 ± 17.3 days). We analyzed adjusted flow index, VD, and Skeletonized vessel length density in the parafoveal area (3-mm annulus with a 1-mm inner circle), along with full-thickness fovea avascular zone area and central foveal thickness (CFT). Using averaged scans VD as the ground truth, we compared two different algorithms for VD at the different plexuses. Longitudinal changes were assessed using a generalized linear model correcting for central foveal thickness and Q-score.

Results

We found significantly decreased adjusted flow index in the DCP layer (P = 0.010) at the follow-up. Furthermore, foveal avascular zone (P < 0.001) and central foveal thickness (P = 0.003) showed significant decrease on follow-up compared with baseline. Comparing the thresholding algorithms showed that vessel length density-based thresholding was more accurate for quantifying the DCP VD.

Conclusions

The adjusted flow index decreased significantly in the DCP layer on follow-up OCTA scan, suggesting vascular flow disruption and decreased deep retinal perfusion after anti-VEGF injection. Our results also highlight the fact that the choice of thresholding method is particularly critical for DCP quantification in eyes with diabetic macular edema.

Translational Relevance

Findings confirmed impaired deep retinal capillary flow after anti-VEGF injection.

Diabetic macular ischaemia- a new therapeutic target?

Diabetic macular ischaemia (DMI) is traditionally defined and graded based on the angiographic evidence of an enlarged and irregular foveal avascular zone. However, these anatomical changes are not surrogate markers for visual impairment. We postulate that there are vascular phenotypes of DMI based on the relative perfusion deficits of various retinal capillary plexuses and choriocapillaris. This review highlights several mechanistic pathways, including the role of hypoxia and the complex relation between neurons, glia, and microvasculature. The current animal models are reviewed, with shortcomings noted. Therefore, utilising the advancing technology of optical coherence tomography angiography (OCTA) to identify the reversible DMI phenotypes may be the key to successful therapeutic interventions for DMI. However, there is a need to standardise the nomenclature of OCTA perfusion status. Visual acuity is not an ideal endpoint for DMI clinical trials. New trial endpoints that represent disease progression need to be developed before irreversible vision loss in patients with DMI. Natural history studies are required to determine the course of each vascular and neuronal parameter to define the DMI phenotypes. These DMI phenotypes may also partly explain the development and recurrence of diabetic macular oedema. It is also currently unclear where and how DMI fits into the diabetic retinopathy severity scales, further highlighting the need to better define the progression of diabetic retinopathy and DMI based on both multimodal imaging and visual function. Finally, we discuss a complete set of proposed therapeutic pathways for DMI, including cell-based therapies that may provide restorative potential.

Nonperfusion Area and Other Vascular Metrics by Wider Field Swept-Source OCT Angiography as Biomarkers of Diabetic Retinopathy Severity

Purpose

To study the wider field swept-source optical coherence tomography angiography (WF SS-OCTA) metrics, especially non-perfusion area (NPA), in the diagnosing and staging of DR.

Design

Cross-sectional observational study (November 2018-September 2020).

Participants

473 eyes of 286 patients (69 eyes of 49 control patients and 404 eyes of 237 diabetic patients).

Methods

We imaged using 6mm×6mm and 12mm×12mm angiograms on WF SS-OCTA. Images were analyzed using the ARI Network and FIJI ImageJ. Mixed effects multiple regression models and receiver operator characteristic analysis was used for statistical analyses.

Main Outcome Measures

Quantitative metrics such as vessel density (VD); vessel skeletonized density (VSD); foveal avascular zone (FAZ) area, circularity, and perimeter; and NPA in DR and their relative performance for its diagnosis and grading.

Results

Among patients with diabetes (median age 59 years), 51 eyes had no DR, 185 eyes (88 mild, 97 moderate-severe) had non-proliferative DR (NPDR); and 168 eyes had proliferative DR (PDR). Trend analysis revealed a progressive decline in superficial capillary plexus (SCP) VD and VSD, and increased NPA with increasing DR severity. Additionally, there was a significant reduction in deep capillary plexus (DCP) VD and VSD in early DR (mild NPDR), but the progressive reduction in advanced DR stages was not significant. NPA was the best parameter to diagnose DR (AUC:0.96), whereas all parameters combined on both angiograms efficiently diagnosed (AUC:0.97) and differentiated between DR stages (AUC range:0.83-0.97). The presence of diabetic macular edema was associated with reduced SCP and DCP VD and VSD within mild NPDR eyes, whereas an increased VD and VSD in SCP among moderate-severe NPDR group.

Conclusions

Our work highlights the importance of NPA, which can be more readily and easily measured with WF SS-OCTA compared to fluorescein angiography. It is additionally quick and non-invasive, and hence can be an important adjunct for DR diagnosis and management. In our study, a combination of all OCTA metrics on both 6mm×6mm and 12mm×12mm angiograms had the best diagnostic accuracy for DR and its severity. Further longitudinal studies are needed to assess NPA as a biomarker for progression or regression of DR severity.

Automated Diagnosis of Optical Coherence Tomography Angiography (OCTA) Based on Machine Learning Techniques

Diabetic retinopathy (DR) refers to the ophthalmological complications of diabetes mellitus. It is primarily a disease of the retinal vasculature that can lead to vision loss. Optical coherence tomography angiography (OCTA) demonstrates the ability to detect the changes in the retinal vascular system, which can help in the early detection of DR. In this paper, we describe a novel framework that can detect DR from OCTA based on capturing the appearance and morphological markers of the retinal vascular system. This new framework consists of the following main steps: (1) extracting retinal vascular system from OCTA images based on using joint Markov-Gibbs Random Field (MGRF) model to model the appearance of OCTA images and (2) estimating the distance map inside the extracted vascular system to be used as imaging markers that describe the morphology of the retinal vascular (RV) system. The OCTA images, extracted vascular system, and the RV-estimated distance map is then composed into a three-dimensional matrix to be used as an input to a convolutional neural network (CNN). The main motivation for using this data representation is that it combines the low-level data as well as high-level processed data to allow the CNN to capture significant features to increase its ability to distinguish DR from the normal retina. This has been applied on multi-scale levels to include the original full dimension images as well as sub-images extracted from the original OCTA images. The proposed approach was tested on in-vivo data using about 91 patients, which were qualitatively graded by retinal experts. In addition, it was quantitatively validated using datasets based on three metrics: sensitivity, specificity, and overall accuracy. Results showed the capability of the proposed approach, outperforming the current deep learning as well as features-based detecting DR approaches.

Retinal Vascularization Abnormalities Studied by Optical Coherence Tomography Angiography (OCTA) in Type 2 Diabetic Patients with Moderate Diabetic Retinopathy

Diabetic retinopathy (DR) is the most severe and frequent retinal vascular disease that causes significant visual loss on a global scale. The purpose of our study was to evaluate retinal vascularization in the superficial capillary plexus (SCP), the deep capillary plexus (DCP) and the choriocapillaris (CC) and changes in the foveal avascular zone (FAZ) by optical tomography angiography (OCTA) in patients with type 2 diabetes mellitus (DM2) with moderate DR but without diabetic macular oedema (DME). Fifty-four eyes of DM2 with moderate DR (level 43 in the ETDRS scale) and without DME and 73 age-matched healthy eyes were evaluated using OCTA with swept-source (SS)-OCT to measure microvascularization changes in SCP, DCP, CC and the FAZ. The mean ages were 64.06 ± 11.98 and 60.79 ± 8.62 years in the DM2 and control groups, respectively. Visual acuity (VA) was lower in the DM2 patients (p = 0.001), OCTA showed changes in the SCP with a significant diminution in the vascular density and the FAZ area was significantly higher compared to healthy controls, with p < 0.001 at the SCP level. The most prevalent anatomical alterations were peripheral disruption in the SCP (83.3%), microaneurysms (MA) in the SCP and in the DCP (79.6% and 79.6%, respectively) and flow changes in the DCP (81.5%). A significant positive correlation was observed between the DM2 duration and the FAZ area in the SCP (0.304 with p = 0.025). A significant negative correlation was also found between age and CC central perfusion (p < 0.001). In summary, a decrease in the vascular density in DM2 patients with moderate DR without DME was observed, especially at the retinal SPC level. Furthermore, it was found that the FAZ was increased in the DM2 group in both retinal plexuses and was greater in the SCP group.

A Deep Learning Algorithm for Classifying Diabetic Retinopathy Using Optical Coherence Tomography Angiography

Purpose

To develop an automated diabetic retinopathy (DR) staging system using optical coherence tomography angiography (OCTA) images with a convolutional neural network (CNN) and to verify the feasibility of the system.

Methods

In this retrospective cross-sectional study, a total of 918 data sets of 3 × 3 mm² OCTA images and 917 data sets of 6 × 6 mm² OCTA images were obtained from 1118 eyes. A deep CNN and four traditional machine learning models were trained with annotations made by a retinal specialist based on ultra-widefield fluorescein angiography. Separately, the same images of the test data sets were independently graded by two human experts. The results of the CNN algorithm were compared with those of traditional machine learning–based classifiers and human experts.

Results

The proposed CNN achieved an accuracy of 0.728, a sensitivity of 0.675, a specificity of 0.944, an F1 score of 0.683, and a quadratic weighted κ of 0.908 for a six-level staging task, which were far superior to the results of traditional machine learning methods or human experts. The CNN algorithm showed a better performance using 6 × 6 mm² rather than 3 × 3 mm² sized OCTA images and using combined data rather than a separate OCTA layer alone.

Conclusions

CNN-based classification using OCTA images can provide reliable assistance to clinicians for DR classification.

Translational Relevance

This CNN algorithm can guide the clinical decision for invasive angiography or referrals to ophthalmology specialists, helping to create more efficient diagnostic workflow in primary care settings.

Perspectives on diabetic retinopathy from advanced retinal vascular imaging

Diabetic retinopathy (DR) is a microvascular complication of diabetes and the most common cause of acquired vision loss in adults worldwide. DR is associated with long-term chronic hyperglycaemia and its detrimental effects on the neurovascular structure and function of the retina. Direct imaging of the retinal vasculature and staging of DR has been traditionally based on fundoscopy and fluorescein angiography, which provide only 2D views of the retina, and in the case of fluorescein angiography, requires an invasive dye injection. In contrast, advanced retinal imaging modalities like optical coherence tomography angiography (OCTA) and adaptive optics (AO) are non-invasive and provide depth-resolved, 3D visualization of retinal vessel structure as well as blood flow. Recent studies utilizing these imaging techniques have shown promise in evaluating quantitative vascular parameters that correlate tightly to clinical DR staging, elucidating functional changes in early diabetes, and monitoring DR treatment response. In this article, we discuss and synthesize the results of advanced retinal imaging studies in DR and their implications for our clinical and pathophysiologic understanding of the disease. Based on the recent literature, we also propose a model to describe the differential changes in vascular structure and flow that have been described on advanced retinal imaging as DR progresses. Future studies of these imaging modalities in larger and more diverse populations, as well as corroboration with histological and functional studies, will be important to further our understanding of DR.

Toward a New Staging System for Diabetic Retinopathy Using Wide Field Swept-Source Optical Coherence Tomography Angiography

PURPOSE OF REVIEW

For over 50 years, diabetic retinopathy (DR) has been classified by pathologic features seen on clinical examination and conventional retinal photographs. However, newer technology such as optical coherence tomography angiography (OCTA) now enables rapid acquisition of retinal structural and vascular information in a reliable, non-invasive, high-resolution fashion. Here, we highlight recent studies that have explored wide field swept-source OCTA (WF SS-OCTA) for the diagnosis and management of DR.

RECENT FINDINGS

Multiple studies have demonstrated the utility of WF SS-OCTA for detection of all clinically relevant features of DR. An updated DR staging system is proposed that leverages the advantages of WF SS-OCTA, including the ability to correlate detailed vascular and structural pathology over time with longitudinal imaging. WF SS-OCTA has tremendous potential for evaluating patients with DR. A new WF SS-OCTA-based staging system may be useful in routine clinical practice and for clinical trials.

Assessment of retinal microvascular health by optical coherence tomography angiography among persons with HIV

Microvasculopathy may link HIV-related chronic inflammation and premature multimorbidity. In this proof-of-concept study, we used optical coherence tomography angiography (OCTA) to evaluate the retina as a convenient assessment of microvascular health among persons with HIV (PWH) undergoing surveillance ophthalmic care at Emory from 2018 to 2021. Among patients with longstanding HIV, OCTA identified microvascular abnormalities even among eyes without clinical retinal disease. Retinovascular evaluation by OCTA is a feasible, noninvasive technique for assessing microvasculopathy among PWH.

Widefield Optical Coherence Tomography Angiography in Diabetic Retinopathy

PURPOSE

To summarize the role of widefield optical coherence tomography angiography (WF-OCTA) in diabetic retinopathy (DR), extending from the acquisition strategies to the main clinical findings.

METHODS

A PubMed-based search was carried out using the terms "Diabetic retinopathy", "optical coherence tomography angiography", "widefield imaging", and "ultra-widefield imaging". All studies published in English up to August 2020 were reviewed.

RESULTS

WF-OCTA can be obtained with different approaches, offering advantages over traditional imaging in the study of nonperfusion areas (NPAs) and neovascularization (NV). Quantitative estimates and topographic distribution of NPA and NV are useful for treatment monitoring and artificial intelligence-based approaches. Curvature, segmentation, and motion artifacts should be assessed when using WF-OCTA.

CONCLUSIONS

WF-OCTA harbors interesting potential in DR because of its noninvasiveness and capability of objective metrics of retinal vasculature. Further studies will facilitate the migration from traditional imaging to WF-OCTA in both the research and clinical practice fields.