Detection of the Microvascular Changes of Diabetic Retinopathy Progression Using Optical Coherence Tomography Angiography

Optical coherence tomography angiography in diabetic retinopathy: A major review

Diabetic retinopathy (DR) is characterized by retinal vasculopathy and is a leading cause of visual impairment. Optical coherence tomography angiography (OCTA) is an innovative imaging technology that can detect various pathologies and quantifiable changes in retinal microvasculature. We briefly describe its functional principles and advantages over fluorescein angiography and perform a comprehensive review on its clinical applications in the screening or management of people with prediabetes, diabetes without clinical retinopathy (NDR), nonproliferative DR (NPDR), proliferative DR (PDR), and diabetic macular edema (DME). OCTA reveals early microvascular alterations in prediabetic and NDR eyes, which may coexist with sub-clinical neuroretinal dysfunction. Its applications in NPDR include measuring ischemia, detecting retinal neovascularization, and timing of early treatment through predicting the risk of retinopathy worsening or development of DME. In PDR, OCTA helps characterize the flow within neovascular complexes and evaluate their progression or regression in response to treatment. In eyes with DME, OCTA perfusion parameters may be of predictive value regarding the visual and anatomical gains associated with treatment. We further discussed the limitations of OCTA and the benefits of its incorporation into an updated DR severity scale.

OCTA-500: A retinal dataset for optical coherence tomography angiography study

Optical coherence tomography angiography (OCTA) is a novel imaging modality that has been widely utilized in ophthalmology and neuroscience studies to observe retinal vessels and microvascular systems. However, publicly available OCTA datasets remain scarce. In this paper, we introduce the largest and most comprehensive OCTA dataset dubbed OCTA-500, which contains OCTA imaging under two fields of view (FOVs) from 500 subjects. The dataset provides rich images and annotations including two modalities (OCT/OCTA volumes), six types of projections, four types of text labels (age/gender/eye/disease) and seven types of segmentation labels (large vessel/capillary/artery/vein/2D FAZ/3D FAZ/retinal layers). Then, we propose a multi-object segmentation task called CAVF, which integrates capillary segmentation, artery segmentation, vein segmentation, and FAZ segmentation under a unified framework. In addition, we optimize the 3D-to-2D image projection network (IPN) to IPN-V2 to serve as one of the segmentation baselines. Experimental results demonstrate that IPN-V2 achieves an about 10% mIoU improvement over IPN on CAVF task. Finally, we further study the impact of several dataset characteristics: the training set size, the model input (OCT/OCTA, 3D volume/2D projection), the baseline networks, and the diseases. The dataset and code are publicly available at: https://ieee-dataport.org/open-access/octa-500.

Accuracy of peripapillary OCTA in patients with acute nonarteritic anterior ischemic optic neuropathy

OBJECTIVE

To evaluate the accuracy of peripapillary optical coherence tomography angiography (OCTA) segmentation in eyes with acute nonarteritic anterior ischemic optic neuropathy (NAION) and healthy eyes.

METHOD

In this retrospective study, en face OCTA images of the optic disc of healthy eyes and eyes with unilateral acute NAION were obtained. The disc boundary and radial peripapillary capillary (RPC) segmentation were generated automatically by the instrument software and then corrected by 2 expert investigators. The frequency of segmentation errors and its impact on vessel density and nerve fibre layer (NFL) thickness measurements were evaluated.

RESULTS

Thirty-eight eyes of 38 subjects (18 in the healthy group and 20 in the acute NAION group) were studied. A misidentified disc border was noted in 5 healthy eyes (27.7%) and 19 eyes with NAION (95.0%; p < 0.001). Segmentation error at the RPC level was found in 6 healthy eyes (33.33%) and 19 eyes with NAION (95.0%; p < 0.001). The nerve fibre layer thickness and RPC density did not change statistically significantly after error corrections in both groups.

CONCLUSIONS

Misidentification of disc border and segmentation error of the RPC layer are common in OCTA images of the optic disc. Accuracy of OCTA imaging in disc boundary detection and RPC network segmentation is reduced in edematous optic discs following acute NAION.

Choriocapillaris Flow Deficit as a Biomarker for Diabetic Retinopathy and Diabetic Macular Edema: 3-Year Longitudinal Cohort

PURPOSE

To investigate the relationship between choriocapillaris flow deficit percentage (CC FD%) by swept-source optical coherence tomography angiography (SS-OCTA) and 3-year risk of diabetic retinopathy (DR) progression and diabetic macular edema (DME) development.

DESIGN

Prospective, observational cohort study.

METHODS

A total of 903 participants with type 2 diabetes mellitus (T2DM) without DR or with mild nonproliferative DR (NPDR) free of DME at baseline were followed up annually for 3 years. All participants underwent standard 7-field fundus photography and spectral-domain OCT. SS-OCTA was used for retinal and choriocapillaris imaging and 3 × 3-mm2 macular CC FD% was quantified. Univariate and multivariate logistic models were used to evaluate the association between CC FD% and 2 or more steps of DR progression and DME development. The additional predictive value of CC FD% for outcome events was assessed using C statistic, net reclassification index (NRI), and integrated discrimination improvement index (IDI).

RESULTS

Over 3 years, 295 of 1805 eyes (16.34%) developed DR progression, and 118 eyes (6.54%) developed DME. A higher average CC FD% was correlated with DR progression (odds ratio [OR], 3.41 per SD increase, 95% CI: 2.65-4.39, P < .001) and DME development (OR, 1.37 per SD increase, 95% CI: 1.06-1.77, P = .016) after adjusting for confounders. In the ETDRS regions, increased CC FD% in all fields was associated with DR progression; however, increased CC FD% in the inferior field was associated with DME development. Compared with the models based on established risk factors, the addition of average CC FD% significantly improved the C statistics for DR progression (0.712 to 0.777, P < .001) and DME occurrence (0.743 to 0.773, P = .044). The estimated NRIs and IDIs (all >0) indicated that the addition of CC FD% led to a significant improvement in the discriminative performance for end points.

CONCLUSION

CC FD% is independently associated with DR progression and DME development in the Chinese T2DM population and provides incremental predictive value beyond traditional risk factors and retinal microvascular parameters. Further inclusion of CC FD% in DR prediction models helps guide population-based screening and personalized management.

Vascular Aging and Damage in Patients with Iron Metabolism Disorders

Vascular aging is a physiological, multifactorial process that involves every type of vessel, from large arteries to microcirculation. This manifests itself as impaired vasomotor function, altered secretory phenotype, deteriorated intercellular transport function, structural remodeling, and aggravated barrier function between the blood and the vascular smooth muscle layer. Iron disorders, particularly iron overload, may lead to oxidative stress and, among other effects, vascular aging. The elevated transferrin saturation and serum iron levels observed in iron overload lead to the formation of a non-transferrin-bound iron (NTBI) fraction with high pro-oxidant activity. NTBI can induce the production of reactive oxygen species (ROS), which induce lipid peroxidation and mediate iron-related damage as the elements of oxidative stress in many tissues, including heart and vessels' mitochondria. However, the available data make it difficult to precisely determine the impact of iron metabolism disorders on vascular aging; therefore, the relationship requires further investigation. Our study aims to present the current state of knowledge on vascular aging in patients with deteriorated iron metabolism.

Comparative study on retinal microvasculature changes between acute and chronic central serous chorioretinopathy

OBJECTIVES

Central serous chorioretinopathy (CSC) is generally a common fundus disease in young and middle-aged Asian men. Acute and chronic CSC can lead to different degrees of injury to the retinal blood flow. This study aims to observe and compare the blood flow density in different retinal capillary layers in patients with acute and chronic CSC using optical coherence tomography angiography (OCTA) technology.

METHODS

Twelve patients with acute CSC and 8 patients with chronic CSC including 12 eyes with acute CSC (acute CSC eye group), 11 eyes with chronic CSC (chronic CSC eye group), and 17 normal eyes (normal eye group) were enrolled in this study. All patients underwent 3 mm×3 mm, 6 mm×6 mm macular OCTA scanning. The retinal microvascu-lature was divided into superficial vascular complexes (SVC), intermediate capillary plexuses (ICP), and deep capillary plexuses (DCP) using the projection resolved-OCTA algorithm. Inner retina includes SVC, ICP, and DCP. The vessel density in each retinal layer and the inner retina were calculated and compared.

RESULTS

Macular OCTA scanning of 3 mm×3 mm showed that there was no significant difference in blood flow density of SVC and ICP among the 3 groups (both P>0.05); blood flow density of DCP and inner retina in the chronic CSC eye group was significantly lower than that in the acute CSC eye group and the normal eye group (all P<0.05); there was no significant difference in retinal blood flow density of different layer between the acute CSC eye group and the normal eye group (all P>0.05). Macular OCTA scanning of 6 mm×6 mm showed that inner retinal blood flow density of the chronic CSC eye group was significantly lower than that of the acute CSC eye group and the normal eye group (both P<0.05); there was no significant difference in blood flow density of SVC among the 3 groups (P>0.05).

CONCLUSIONS

The vessel density of DCP and inner retina in the eyes with chronic CSC are significantly reduced, which may result in impaired visual function. Therefore, we recommend that patients with acute CSC should be properly treated to avoid progressing into chronic CSC.

The Role of Medical Image Modalities and AI in the Early Detection, Diagnosis and Grading of Retinal Diseases: A Survey

Traditional dilated ophthalmoscopy can reveal diseases, such as age-related macular degeneration (AMD), diabetic retinopathy (DR), diabetic macular edema (DME), retinal tear, epiretinal membrane, macular hole, retinal detachment, retinitis pigmentosa, retinal vein occlusion (RVO), and retinal artery occlusion (RAO). Among these diseases, AMD and DR are the major causes of progressive vision loss, while the latter is recognized as a world-wide epidemic. Advances in retinal imaging have improved the diagnosis and management of DR and AMD. In this review article, we focus on the variable imaging modalities for accurate diagnosis, early detection, and staging of both AMD and DR. In addition, the role of artificial intelligence (AI) in providing automated detection, diagnosis, and staging of these diseases will be surveyed. Furthermore, current works are summarized and discussed. Finally, projected future trends are outlined. The work done on this survey indicates the effective role of AI in the early detection, diagnosis, and staging of DR and/or AMD. In the future, more AI solutions will be presented that hold promise for clinical applications.

The Role of Different Retinal Imaging Modalities in Predicting Progression of Diabetic Retinopathy: A Survey

Diabetic retinopathy (DR) is a devastating condition caused by progressive changes in the retinal microvasculature. It is a leading cause of retinal blindness in people with diabetes. Long periods of uncontrolled blood sugar levels result in endothelial damage, leading to macular edema, altered retinal permeability, retinal ischemia, and neovascularization. In order to facilitate rapid screening and diagnosing, as well as grading of DR, different retinal modalities are utilized. Typically, a computer-aided diagnostic system (CAD) uses retinal images to aid the ophthalmologists in the diagnosis process. These CAD systems use a combination of machine learning (ML) models (e.g., deep learning (DL) approaches) to speed up the diagnosis and grading of DR. In this way, this survey provides a comprehensive overview of different imaging modalities used with ML/DL approaches in the DR diagnosis process. The four imaging modalities that we focused on are fluorescein angiography, fundus photographs, optical coherence tomography (OCT), and OCT angiography (OCTA). In addition, we discuss limitations of the literature that utilizes such modalities for DR diagnosis. In addition, we introduce research gaps and provide suggested solutions for the researchers to resolve. Lastly, we provide a thorough discussion about the challenges and future directions of the current state-of-the-art DL/ML approaches. We also elaborate on how integrating different imaging modalities with the clinical information and demographic data will lead to promising results for the scientists when diagnosing and grading DR. As a result of this article's comparative analysis and discussion, it remains necessary to use DL methods over existing ML models to detect DR in multiple modalities.

Quantitative Evaluation of Retinal Microvascular Abnormalities in Patients With Type 2 Diabetes Mellitus Without Clinical Sign of Diabetic Retinopathy

Purpose

To evaluate microvascular abnormalities in the macula and peripapillary area in diabetic patients without clinical signs of diabetic retinopathy (DR) and compare them with healthy control eyes, using optical coherence tomography angiography (OCTA).

Methods

A prospective study was performed of 49 eyes from 49 diabetic patients without clinical signs of DR and a control group of 52 eyes from 52 healthy normal individuals. The 3 × 3 mm macular scans and 4.5 × 4.5 mm optic disc scans were obtained with the OCTA RTVue-XR Avanti system. Angiograms from the superficial capillary plexus, the deep capillary plexus of the macula scans, and radial peripapillary capillary plexus of the optic disc scans were analyzed with MATLAB. Multivariate binary logistic regression and the least absolute shrinkage and selection operator (LASSO) regression were used to select ideal parameters that distinguish diabetic eyes without DR from normal eyes. A receiver operating characteristic (ROC) curve was generated, and sensitivity and specificity were calculated.

Results

Our final model identified FD-300 (foveal vessel density in a 300-µm-wide region around foveal avascular zone) as the only parameter selected by both the LASSO regression and the final multivariate logistic regression model that significantly differentiates diabetic eyes without clinical signs of DR from healthy normal eyes. The area under the ROC curve of FD-300 was 0.685, and sensitivity and specificity were 65.3% and 71.2%, respectively.

Conclusions

Quantitative evaluation of retinal microvascular abnormalities using OCTA identified FD-300 as a useful biomarker versus the other macular and peripapillary OCTA metrics in the early detection of preclinical diabetic retinal abnormalities.

Translational Relevance

OCTA may be useful in detecting early retinal microvascular abnormalities in diabetic patients before the clinical findings of DR become visible.

Optical Coherence Tomography Angiography in Diabetic Patients: A Systematic Review

Background: Diabetic retinopathy (DR) is the leading cause of legal blindness in the working population in developed countries. Optical coherence tomography (OCT) angiography (OCTA) has risen as an essential tool in the diagnosis and control of diabetic patients, with and without DR, allowing visualisation of the retinal and choroidal microvasculature, their qualitative and quantitative changes, the progression of vascular disease, quantification of ischaemic areas, and the detection of preclinical changes. The aim of this article is to analyse the current applications of OCTA and provide an updated overview of them in the evaluation of DR. Methods: A systematic literature search was performed in PubMed and Embase, including the keywords “OCTA” OR “OCT angiography” OR “optical coherence tomography angiography” AND “diabetes” OR “diabetes mellitus” OR “diabetic retinopathy” OR “diabetic maculopathy” OR “diabetic macular oedema” OR “diabetic macular ischaemia”. Of the 1456 studies initially identified, 107 studies were screened after duplication, and those articles that did not meet the selection criteria were removed. Finally, after looking for missing data, we included 135 studies in this review. Results: We present the common and distinctive findings in the analysed papers after the literature search including the diagnostic use of OCTA in diabetes mellitus (DM) patients. We describe previous findings in retinal vascularization, including microaneurysms, foveal avascular zone (FAZ) changes in both size and morphology, changes in vascular perfusion, the appearance of retinal microvascular abnormalities or new vessels, and diabetic macular oedema (DME) and the use of deep learning technology applied to this disease. Conclusion: OCTA findings enable the diagnosis and follow-up of DM patients, including those with no detectable lesions with other devices. The evaluation of retinal and choroidal plexuses using OCTA is a fundamental tool for the diagnosis and prognosis of DR.