Microaneurysm Turnover in Mild Non-Proliferative Diabetic Retinopathy is Associated with Progression and Development of Vision-Threatening Complications: A 5-Year Longitudinal Study

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.

Correlation between Topographic Vessel Density and Retinal Thickness Changes in Patients with Diabetic Macular Edema Treated with Anti-VEGF Therapy: Is It a Suitable OCTA Biomarker?

The objective of this study was to determine the correlation between topographic vessel density (VD) and retinal thickness (RT) reductions induced by vascular endothelial growth factor inhibitors (anti-VEGF) in patients with diabetic macular edema (DME) using optical coherence tomography angiography (OCTA). This was a prospective, interventional case series. VD and RT measurements were separately taken in four parafoveal subfields at baseline and after six months of treatment. This correlation was statistically assessed using Spearman's rho correlation coefficient after adjustment for multiple comparisons. The study included a total of 48 eyes in the final analysis. Mean VD decreased from baseline to month 6 (from 45.2 (±3.5) to 44.6% (±3.2) in the superficial capillary plexus and from 50 (±3.3) to 49% (±3.9) in the deep capillary plexus). Statistically significant reductions in RT were observed in all ETDRS sectors (p < 0.0001). No significant association was found between RT and VD, even when analyzing responders and non-responders separately. After six months of anti-VEGF treatment, no significant correlation was observed between the topographic VD and RT values. These findings suggest that reductions in VD values may not solely result from a reduction in microaneurysms, also being affected by the repositioning of displaced vessels due to edema and a reduction in their caliber. Therefore, VD changes may not be a suitable indirect OCTA biomarker of microaneurysm turnover and treatment response.

The relationship of diabetic retinopathy severity scales with frequency and surface area of diabetic retinopathy lesions

PURPOSE

To assess the relationship between qualitative diabetic retinopathy (DR) scales with the precise numbers and surface area of DR lesions within the Early Treatment Diabetic Retinopathy Study (ETDRS) standard seven field (S7F) region on ultrawide-field (UWF) color fundus images.

METHODS

In this study, we collected UWF images from adult patients with diabetes. Poor-quality images and eyes with any pathology precluding assessment of DR severity were excluded. The DR lesions were manually segmented. DR severity was graded according to the International Clinical Diabetic Retinopathy (ICDR) and AA protocol by two masked graders within the ETDRS S7F. These lesions' numbers and surface area were computed and correlated against the DR scores using the Kruskal-Wallis H test. Cohen's Kappa was performed to determine the agreement between two graders.

RESULTS

One thousand five hundred and twenty eyes of 869 patients (294 females, 756 right eyes) with a mean age of 58.7 years were included. 47.4% were graded as no DR, 2.2% as mild non-proliferative DR (NPDR), 24.0% as moderate NPDR, 6.3% as severe NPDR, and 20.1% as proliferative DR (PDR). The area and number of DR lesions generally increased as the ICDR level increased up to severe NPDR, but decreased from severe NPDR to PDR. There was perfect intergrader agreement on the DR severity.

CONCLUSION

A quantitative approach reveals that DR lesions' number and area generally correlate with ICDR-based categorical DR severity levels with an increasing trend in the number and area of DR lesions from mild to severe NPDR and a decrease from severe NPDR to PDR.

Quantification of Microvascular Lesions in the Central Retinal Field: Could It Predict the Severity of Diabetic Retinopathy?

Diabetic retinopathy (DR) is a neurodegenerative disease characterized by the presence of microcirculatory lesions. Among them, microaneurysms (MAs) are the first observable hallmark of early ophthalmological changes. The present work aims to study whether the quantification of MAs, hemorrhages (Hmas) and hard exudates (HEs) in the central retinal field could have a predictive value on DR severity. These retinal lesions were quantified in a single field NM-1 of 160 retinographies of diabetic patients from the IOBA's reading center. Samples included different disease severity levels and excluded proliferating forms: no DR (n = 30), mild non-proliferative (n = 30), moderate (n = 50) and severe (n = 50). Quantification of MAs, Hmas, and HEs revealed an increasing trend as DR severity progresses. Differences between severity levels were statistically significant, suggesting that the analysis of the central field provides valuable information on severity level and could be used as a clinical tool to assess DR grading in the eyecare routine. Even though further validation is needed, counting microvascular lesions in a single retinal field can be proposed as a rapid screening system to classify DR patients with different stages of severity according to the international classification.

Artificial Intelligence for Diabetic Retinopathy Screening Using Color Retinal Photographs: From Development to Deployment

Diabetic retinopathy (DR), a leading cause of preventable blindness, is expected to remain a growing health burden worldwide. Screening to detect early sight-threatening lesions of DR can reduce the burden of vision loss; nevertheless, the process requires intensive manual labor and extensive resources to accommodate the increasing number of patients with diabetes. Artificial intelligence (AI) has been shown to be an effective tool which can potentially lower the burden of screening DR and vision loss. In this article, we review the use of AI for DR screening on color retinal photographs in different phases of application, ranging from development to deployment. Early studies of machine learning (ML)-based algorithms using feature extraction to detect DR achieved a high sensitivity but relatively lower specificity. Robust sensitivity and specificity were achieved with the application of deep learning (DL), although ML is still used in some tasks. Public datasets were utilized in retrospective validations of the developmental phases in most algorithms, which require a large number of photographs. Large prospective clinical validation studies led to the approval of DL for autonomous screening of DR although the semi-autonomous approach may be preferable in some real-world settings. There have been few reports on real-world implementations of DL for DR screening. It is possible that AI may improve some real-world indicators for eye care in DR, such as increased screening uptake and referral adherence, but this has not been proven. The challenges in deployment may include workflow issues, such as mydriasis to lower ungradable cases; technical issues, such as integration into electronic health record systems and integration into existing camera systems; ethical issues, such as data privacy and security; acceptance of personnel and patients; and health-economic issues, such as the need to conduct health economic evaluations of using AI in the context of the country. The deployment of AI for DR screening should follow the governance model for AI in healthcare which outlines four main components: fairness, transparency, trustworthiness, and accountability.

Predictive factors for microvascular recovery after treatments for diabetic retinopathy

BACKGROUND

To identify factors associated with microvascular recovery after intravitreal bevacizumab or panretinal photocoagulation (PRP) in diabetic retinopathy (DR).

METHODS

We retrospectively reviewed 320 eyes/patients with DR treated with intravitreal bevacizumab and/or PRP. Two consecutive fluorescein angiographies (FAs) of each eye were compared. The number of microaneurysms and the area of capillary non-perfusion were calculated automatically using ImageJ software. Microvascular recovery was defined as a marked reduction in the numbers of microaneurysms (< 20%) or a marked reduction in the area of capillary non-perfusion (< 50%) in 45-degree fields or a complete regression of new vessels in ETDRS 7 standard fields. Baseline FA findings and changes in the ocular and systemic factors were analyzed.

RESULTS

Twenty-eight (8.8%) of the 320 total eyes were found to meet the criteria of microvascular recovery after the treatments. Multivariate analysis revealed the presence of diffuse capillary telangiectasis (P = .003) and late disc leaking (P = .007) on baseline FA and a reduction of glycated hemoglobin (P = .005) during the follow-up period were predictive factors of microvascular recovery after the treatments. Although the microvascular recovery group presented with a significant improvement of BCVA after the treatments, the baseline BCVA could not predict the microvascular recovery after the treatments.

CONCLUSIONS

Diffuse capillary telangiectasis or late disc leaking on baseline FA and improved glycemic control positively predicted the microvascular recovery after treatments for DR.

Studies of the retinal microcirculation using human donor eyes and high-resolution clinical imaging: Insights gained to guide future research in diabetic retinopathy

The microcirculation plays a key role in delivering oxygen to and removing metabolic wastes from energy-intensive retinal neurons. Microvascular changes are a hallmark feature of diabetic retinopathy (DR), a major cause of irreversible vision loss globally. Early investigators have performed landmark studies characterising the pathologic manifestations of DR. Previous works have collectively informed us of the clinical stages of DR and the retinal manifestations associated with devastating vision loss. Since these reports, major advancements in histologic techniques coupled with three-dimensional image processing has facilitated a deeper understanding of the structural characteristics in the healthy and diseased retinal circulation. Furthermore, breakthroughs in high-resolution retinal imaging have facilitated clinical translation of histologic knowledge to detect and monitor progression of microcirculatory disturbances with greater precision. Isolated perfusion techniques have been applied to human donor eyes to further our understanding of the cytoarchitectural characteristics of the normal human retinal circulation as well as provide novel insights into the pathophysiology of DR. Histology has been used to validate emerging in vivo retinal imaging techniques such as optical coherence tomography angiography. This report provides an overview of our research on the human retinal microcirculation in the context of the current ophthalmic literature. We commence by proposing a standardised histologic lexicon for characterising the human retinal microcirculation and subsequently discuss the pathophysiologic mechanisms underlying key manifestations of DR, with a focus on microaneurysms and retinal ischaemia. The advantages and limitations of current retinal imaging modalities as determined using histologic validation are also presented. We conclude with an overview of the implications of our research and provide a perspective on future directions in DR research.

Retinal Neurodegeneration in Different Risk Phenotypes of Diabetic Retinal Disease

Diabetic retinopathy (DR) has been considered a microvascular disease, but it has become evident that neurodegeneration also plays a key role in this complex pathology. Indeed, this complexity is reflected in its progression which occurs at different rates in different type 2 diabetic (T2D) individuals. Based on this concept, our group has identified three DR progression phenotypes that might reflect the interindividual differences: phenotype A, characterized by low microaneurysm turnover (MAT <6), phenotype B, low MAT (<6) and increased central retinal thickness (CRT); and phenotype C, with high MAT (≥6). In this study, we evaluated the progression of DR neurodegeneration, considering ganglion cell+inner plexiform layers (GCL+IPL) thinning, in 170 T2D individuals followed for a period of 5 years, to explore associations with disease progression or risk phenotypes. Ophthalmological examinations were performed at baseline, first 6 months, and annually. GCL+IPL average thickness was evaluated by optical coherence tomography (OCT). Microaneurysm turnover (MAT) was evaluated using the RetMarkerDR. ETDRS level and severity progression were assessed in seven-field color fundus photography. In the overall population there was a significant loss in GCL+IPL (−0.147 μm/year), independently of glycated hemoglobin, age, sex, and duration of diabetes. Interestingly, this progressive thinning in GCL + IPL reached higher values in phenotypes B and C (−0.249 and −0.238 μm/year, respectively), whereas phenotype A remained relatively stable. The presence of neurodegeneration in all phenotypes suggests that it is the retinal vascular response to the early neurodegenerative changes that determines the course of the retinopathy in each individual. Therefore, classification of different DR phenotypes appears to offer relevant clarification of DR disease progression and an opportunity for improved management of each T2D individual with DR, thus playing a valuable role for the implementation of personalized medicine in DR.

Characterization of One-Year Progression of Risk Phenotypes of Diabetic Retinopathy

Introduction

We characterized the progression of different diabetic retinopathy (DR) phenotypes in type 2 diabetes (T2D).

Methods

A prospective longitudinal cohort study (CORDIS, NCT03696810) was conducted with three visits (baseline, 6 months, and 1 year). Demographic and systemic data included age, sex, diabetes duration, lipid profile, and hemoglobin A1c (HbA1c). Ophthalmological examinations included best-corrected visual acuity (BCVA), color fundus photography (CFP), and optical coherence tomography (OCT and OCTA). Phenotype classification was performed at the 6-month visit based on microaneurysm turnover (MAT, on CFP) and central retinal thickness (CRT, on OCT). Only risk phenotypes B (MAT < 6 and increased CRT) and C (MAT ≥ 6 with or without increased CRT) were included. ETDRS grading was performed at the baseline visit based on seven-field CFP.

Results

A total of 133 T2D individuals were included in the study; 81 (60%) eyes were classified as phenotype B and 52 (40%) eyes as phenotype C. Of these, 128 completed the 1-year follow-up. At baseline, eyes with phenotype C showed greater capillary closure (superior capillary plexus, deep capillary plexus, and full retina, p < 0.001) and increased foveal avascular zone (FAZ) area (p < 0.001), indicating more advanced microvascular disease. Neurodegeneration represented by thinning of the ganglion cell layer + inner plexiform layer (GCL + IPL) was present in both phenotypes. When analyzing the 1-year progression of each phenotype, only phenotype C revealed a significant decrease in BCVA (p = 0.02) and enlargement of the FAZ (p = 0.03). A significant progressive decrease in the vessel density of the deep capillary layer and in MAT occurred in both phenotypes, but these changes were particularly relevant in phenotype C and ETDRS grades 43–47. During the 1-year period, both phenotypes B and C showed progression in GCL + IPL thinning (p < 0.001).

Conclusions

In the 1-year period of follow-up, both phenotypes B and C showed progression in retinal neurodegeneration, whereas phenotype C showed more marked disease progression at the microvascular level.

Characterization of Risk Profiles for Diabetic Retinopathy Progression

Diabetic retinopathy (DR) is a frequent complication of diabetes and, through its vision-threatening complications, i.e., macular edema and proliferative retinopathy, may lead to blindness. It is, therefore, of major relevance to identify the presence of retinopathy in diabetic patients and, when present, to identify the eyes that have the greatest risk of progression and greatest potential to benefit from treatment. In the present paper, we suggest the development of a simple to use alternative to the Early Treatment Diabetic Retinopathy Study (ETDRS) grading system, establishing disease severity as a necessary step to further evaluate and categorize the different risk factors involved in the progression of diabetic retinopathy. It needs to be validated against the ETDRS classification and, ideally, should be able to be performed automatically using data directly from the examination equipment without the influence of subjective individual interpretation. We performed the characterization of 105 eyes from 105 patients previously classified by ETDRS level by a Reading Centre using a set of rules generated by a decision tree having as possible inputs a set of metrics automatically extracted from Swept-source Optical Coherence Tomography (SS-OCTA) and Spectral Domain- OCT (SD-OCT) measured at different localizations of the retina. When the most relevant metrics were used to derive the rules to perform the organization of the full pathological dataset, taking into account the different ETDRS grades, a global accuracy equal to 0.8 was obtained. In summary, it is now possible to envision an automated classification of DR progression using noninvasive methods of examination, OCT, and SS-OCTA. Using this classification to establish the severity grade of DR, at the time of the ophthalmological examination, it is then possible to identify the risk of progression in severity and the development of vision-threatening complications based on the predominant phenotype.