Microaneurysm turnover is a predictor of diabetic retinopathy progression

Longitudinal Quantitative Ultrawidefield Angiographic Features in Diabetic Retinopathy Treated with Aflibercept from the Intravitreal Aflibercept as Indicated by Real-Time Objective Imaging to Achieve Diabetic Retinopathy Improvement Trial

OBJECTIVE

To report longitudinal trends of quantitative ultrawidefield fluorescein angiography (qUWFA) biomarkers in the Intravitreal Aflibercept as Indicated by Real-Time Objective Imaging to Achieve Diabetic Retinopathy Improvement (PRIME) diabetic retinopathy (DR) clinical trial.

DESIGN

Post hoc analysis of the PRIME prospective randomized DR clinical trial comparing intravitreal aflibercept treatment based on the DR severity score (DRSS) or quantitative leakage index for DR improvement (ClinicalTrials.gov identifier: NCT03531294).

PARTICIPANTS

Patients were enrolled with a DRSS level of 47A to 71A and best-corrected visual acuity of 20/800 or better. Key exclusion criteria were previous intravitreal injection, panretinal photocoagulation, vitrectomy, central-involving macular edema, or vitreous hemorrhage.

METHODS

A previously validated, machine learning-based qUWFA analysis platform was used for panretinal leakage index assessment and differentiation of generalized and perivascular leakage phenotypes. Additionally, microaneurysm count and ischemic index were quantified in panretinal and macular regions. The trends in these biomarkers and therapeutic response were studied over 1 year.

MAIN OUTCOME MEASURES

Longitudinal trends of qUWFA biomarkers. The impact of these qUWFA metrics on treatment response was assessed by studying their associations with time to 2-step DRSS improvement and number of treatment-free days.

RESULTS

Forty eyes from 40 subjects with DR were enrolled. Lower baseline generalized leakage was noted in eyes that attained the 2-step DRSS improvement in < 16 weeks (1.9% vs. 2.8%; P = 0.026). Baseline macular perivascular-generalized leakage ratio had a significant correlation with the number of treatment-free days (r = 0.4; P = 0.012). At the end of 1 year, therapy significantly reduced the mean panretinal (3.9% vs. 5.8%; P = 0.002) and macular (6.2% vs. 12.2%; P = 0.008) generalized leakage indices compared with baseline, as well as the mean panretinal perivascular leakage index (1.5% vs. 2.3%; P = 0.002). The mean panretinal ischemic index demonstrated a small but likely clinically insignificant decrease from 12.5% at baseline to 11.6% at year 1 (P = 0.016).

CONCLUSIONS

Down-trending leakage indices and microaneurysm counts were demonstrated over 1 year of anti-VEGF therapy. At baseline, DR eyes with lower generalized leakage responded to therapy more rapidly. Eyes with greater perivascular leakage relative to generalized leakage showed a longer-lasting anti-VEGF treatment response.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Subthreshold Photocoagulation, Laser Endpoint Management Based on Optical Coherence Tomography Angiography in Cases of Diabetic Macular Edema Refractory to Anti-VEGF

PURPOSE

This study aimed to determine the changes that occur in the vasculature, as based on optical coherence tomography angiography (OCTA) after non-damaging endpoint management (EpM), using a continuous wave yellow laser. The study was on eyes with diabetic macular edema (DME) that were resistant to anti-vascular endothelial growth factors (anti-VEGFs).

MATERIALS AND METHODS

This was a retrospective analysis of OCTA images of 44 eyes in 44 patients with DME refractory to anti-VEGF. The eyes were treated with a PASCAL Streamline yellow laser (577 nm wavelength, 200 mm spot size). Treatment was administered to the DME area and utilized 10% continuous wave laser energy and 0.50 µm beam diameter spot spacing. Best-corrected visual acuity (BCVA) and enhanced in-depth imaging with optical coherence tomography (EDI-OCT) and fundus autofluorescence (FAF) images were recorded at baseline, and 3 and 6 months posttreatment. Total choroidal area (TCA), luminal area (LA), stromal area (SA), and the choroidal vascularity index (CVI) were calculated using Image J software. The macula was divided into five quadrants in accordance with the mapping system in the Early Treatment Diabetic Retinopathy Study (ETDRS).

RESULTS

All patients (mean age: 58.90 ± 9.55 years) were diagnosed with diabetes mellitus type 2. Mean BCVA at baseline was 0.30 ± 0.11 logarithm of the minimum angle of resolution (logMAR) versus 0.23 ± 0.10 logMAR at 3 months (p = 0.032) and 0.17 ± 0.10 logMAR at 6 months (p = 0.013). The foveal avascular zone area (FAZ) decreased in the deep capillary plexus (DCP) from baseline to 6 months (p = 0.028). Vessel densities (VDs) of the superficial capillary plexus (SCP), DCP, and choriocapillaris decreased significantly in the fovea at 3 and 6 months compared to baseline (p < 0.05 for both follow-up time points). There were significant decreases in SCP and DCP in the superior quadrant at the end of month 6 (p = 0.001 and p = 0.038, respectively). There was a significant decrease in the nasal quadrant of the DCP and choriocapillaris at the end of month 6 (p = 0.024 and p = 0.049, respectively). Although there was a significant decrease in central macular thickness (CMT) (p < 0.001), subfoveal choroidal thickness (SFCT) (p < 0.001), and LA (p = 0.034) at months 3 and 6, there was no significant change in the CVI (p = 0.19). According to the DME recovery rate, 36 eyes (81%) were irradiated once, whereas 8 eyes (19%) were irradiated twice.

CONCLUSIONS

Non-damaging EpM therapy using a continuous wave yellow laser in eyes with DME that are resistant to anti-VEGFs induces significant changes in the SCP, choriocapillaris, and, most commonly, the DCP, which caused a significant decrease in VDs during 6 months of follow-up.

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.

A systematic literature review of machine learning based risk prediction models for diabetic retinopathy progression

Diabetic Retinopathy (DR) is the most popular debilitating impairment of diabetes and it progresses symptom-free until a sudden loss of vision occurs. Understanding the progression of DR is a pressing issue in clinical research and practice. In this systematic review of articles on Machine Learning (ML) based risk prediction models for DR progression, ever since the use of Artificial Intelligence (AI) for DR detection, there have been more cross-sectional studies with different algorithms of use of AI, there haven't been many longitudinal studies for the AI based risk prediction models. This paper proposes a novel review to fill in the gaps identified in current reviews and facilitate other researchers with current research solutions for developing AI-based risk prediction models for DR progression and closely related problems; synthesize the current results from these studies and identify research challenges, limitations and gaps to inform the selection of machine learning techniques and predictors to build novel prediction models. Additionally, this paper suggested six (6) deep AI-related technical and critical discussion of the adopted strategies and approaches. The Systematic Literature Review (SLR) methodology was employed to gather relevant studies. We searched IEEE Xplore, PubMed, Springer Link, Google Scholar, and Science Direct electronic databases for papers published from January 2017 to 30th April 2023. Thirteen (13) studies were chosen on the basis of their relevance to the review questions and satisfying the selection criteria. However, findings from the literature review exposed some critical research gaps that need to be addressed in future research to improve on the performance of risk prediction models for DR progression.

Assessment of Parafoveal Diabetic Macular Ischemia on Optical Coherence Tomography Angiography Images to Predict Diabetic Retinal Disease Progression and Visual Acuity Deterioration

Importance

The presence of diabetic macular ischemia (DMI) on optical coherence tomography angiography (OCTA) images predicts diabetic retinal disease progression and visual acuity (VA) deterioration, suggesting an OCTA-based DMI evaluation can further enhance diabetic retinopathy (DR) management.

Objective

To investigate whether an automated binary DMI algorithm using OCTA images provides prognostic value on DR progression, diabetic macular edema (DME) development, and VA deterioration in a cohort of patients with diabetes.

Design, Setting, and Participants

In this cohort study, DMI assessment of superficial capillary plexus and deep capillary plexus OCTA images was performed by a previously developed deep learning algorithm. The presence of DMI was defined as images exhibiting disruption of fovea avascular zone with or without additional areas of capillary loss, while absence of DMI was defined as images presented with intact fovea avascular zone outline and normal distribution of vasculature. Patients with diabetes were recruited starting in July 2015 and were followed up for at least 4 years. Cox proportional hazards models were used to evaluate the association of the presence of DMI with DR progression, DME development, and VA deterioration. Analysis took place between June and December 2022.

Main Outcomes and Measures

DR progression, DME development, and VA deterioration.

Results

A total of 321 eyes from 178 patients were included for analysis (85 [47.75%] female; mean [SD] age, 63.39 [11.04] years). Over a median (IQR) follow-up of 50.41 (48.16-56.48) months, 105 eyes (32.71%) had DR progression, 33 eyes (10.28%) developed DME, and 68 eyes (21.18%) had VA deterioration. Presence of superficial capillary plexus-DMI (hazard ratio [HR], 2.69; 95% CI, 1.64-4.43; P < .001) and deep capillary plexus-DMI (HR, 3.21; 95% CI, 1.94-5.30; P < .001) at baseline were significantly associated with DR progression, whereas presence of deep capillary plexus-DMI was also associated with DME development (HR, 4.60; 95% CI, 1.15-8.20; P = .003) and VA deterioration (HR, 2.12; 95% CI, 1.01-5.22; P = .04) after adjusting for age, duration of diabetes, fasting glucose, glycated hemoglobin, mean arterial blood pressure, DR severity, ganglion cell-inner plexiform layer thickness, axial length, and smoking at baseline.

Conclusions and Relevance

In this study, the presence of DMI on OCTA images demonstrates prognostic value for DR progression, DME development, and VA deterioration.

A Reliable Criterion for the Correct Delimitation of the Foveal Avascular Zone in Diabetic Patients

BACKGROUND

Manual segmentation of the Foveal Avascular Zone (FAZ) has a high level of variability. Research into retinas needs coherent segmentation sets with low variability.

METHODS

Retinal optical coherence tomography angiography (OCTA) images from type-1 diabetes mellitus (DM1), type-2 diabetes mellitus (DM2) and healthy patients were included. Superficial (SCP) and deep (DCP) capillary plexus FAZs were manually segmented by different observers. After comparing the results, a new criterion was established to reduce variability in the segmentations. The FAZ area and acircularity were also studied.

RESULTS

The new segmentation criterion produces smaller areas (closer to the real FAZ) with lower variability than the different criteria of the explorers in both plexuses for the three groups. This was particularly noticeable for the DM2 group with damaged retinas. The acircularity values were also slightly reduced with the final criterion in all groups. The FAZ areas with lower values showed slightly higher acircularity values. We also have a consistent and coherent set of segmentations with which to continue our research.

CONCLUSIONS

Manual segmentations of FAZ are generally carried out with little attention to the consistency of the measurements. A novel criterion for segmenting the FAZ allows segmentations made by different observers to be more similar.

Confocal MultiColor Signal Depends on Perfusion Characteristics of Retinal Microaneurysms in Diabetic Retinopathy as Detected by OCTA

Purpose

To propose a noninvasive way of classifying multimodal imaging of retinal microaneurysms (MA) secondary to diabetic retinopathy (DR).

Methods

The research was designed as a cross-sectional, observational study of patients affected by DR. Multimodal imaging included confocal MultiColor imaging, optical coherence tomography (OCT) and OCT angiography (OCTA). MA green- and infrared-reflectance components were assessed by confocal MultiColor imaging, reflectivity properties by OCT, and MA perfusion features by OCTA. In addition, we included high-resolution (HR) and high-speed (HS) OCTA scans to assess HR-HS agreement in detecting retinal MA and to highlight different perfusion features detected by both OCTA acquisitions.

Results

We analyzed 216 retinal MAs, divided into green (46; 21%), red (58; 27%) and mixed types (112; 52%). Green MAs were mainly hyper-reflective on OCT, with no or poor filling on OCTA. Red MAs were characterized by an isoreflective signal on OCT and full filling on OCTA. Mixed MAs showed a hyper-reflective border and a hyporeflective core on OCT and partial filling on OCTA. No differences in red MA HR/HS size discrepancy and reflectivity were found, whereas these progressively increased as the MA MultiColor signal changed from infrared to green. MA types significantly correlated with visual acuity, DR duration, and DR severity.

Conclusions

Retinal MA can be classified reliably by means of a fully noninvasive multimodal imaging-based assessment. MA types are matched with visual acuity, DR duration and DR severity. Both HR and HS OCTA are highly effective in detecting MA, although HR OCTA is to be preferred in the presence of fibrotic evolution.

Translational Relevance

This study outlines a proposed novel MA classification based on noninvasive multimodal imaging. The findings presented in this paper endorse the clinical relevance of this approach, highlighting how this classification is associated with both DR duration and severity.

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.

Longitudinal Quantitative Ultrawide-field Fluorescein Angiography Dynamics in the RUBY Diabetic Macular Edema Study

OBJECTIVE

The purpose of this study was to evaluate the longitudinal change in quantitative ultrawide-field angiographic (UWFA) parameters and correlate them with functional outcomes and spectral domain-OCT metrics.

DESIGN

This study is a post hoc analysis of the phase II RUBY study: a prospective, randomized trial of patients with diabetic macular edema (DME) treated with either intravitreal aflibercept injection (IAI) or combined IAI/nesvacumab (antiangiopoietin 2 mAb).

SUBJECTS

Subjects with DME that underwent UWFA across all treatment groups (n = 44).

METHODS

A machine learning-enabled feature extraction system generated panretinal quantitative UWFA metrics, including leakage, ischemia, and microaneurysm (MA) burden. Zonal assessments were performed corresponding to the macula, midperiphery, and far periphery.

MAIN OUTCOME MEASURES

Changes in ischemic area and index (proportion of nonperfusion in analyzable retina), leakage area and index (proportion of leakage in analyzable retina), and MA count at baseline, week 12, week 24, and week 36 were analyzed. Spectral-domain-OCT quantitative metrics, such as central subfield thickness, ellipsoid zone (EZ) integrity parameters, intraretinal fluid (IRF) volume, and subretinal fluid (SRF) volume were extracted via a machine learning-enhanced OCT feature extraction platform and analyzed. Additionally, the effect of these changes on best-corrected visual acuity (BCVA) was evaluated.

RESULTS

Mean panretinal leakage index, zonal leakage area, and panretinal MA count improved significantly between baseline and week 36. Panretinal ischemic index decreased between baseline and week 36, with some aspects showing significant improvement. Mean BCVA significantly improved from baseline to week 36. There was a significant inverse correlation between change in BCVA and change in macular leakage area. A direct correlation was observed between both baseline macular leakage area and panretinal leakage index with IRF volume, SRF volume, and EZ disruption on OCT.

CONCLUSIONS

Assessment of UWFA parameters demonstrates a significant improvement in panretinal leakage index, leakage area, and MA burden in eyes treated with IAI with or without nesvacumab. A numeric reduction in panretinal ischemic index and area was noted. The analysis also shows the critical association of leakage with visual and OCT features. This highlights the potential role of UWFA in disease burden assessment, with leakage parameters serving as a primary end point.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

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.

Evaluation of microaneurysms as predictors of therapeutic response to anti-VEGF therapy in patients with DME

Administration of intravitreal anti-vascular endothelial growth factor (anti-VEGF) therapy is the first-line therapy for diabetic macular oedema (DME). However, some patients show no or insufficient response to repeated anti-VEGF injections. Therefore, it is necessary to identify factors that can predict this resistance against anti-VEGF treatment. Presence of microaneurysms (MAs) is a predictor of the development and progression of DME, but its relationship with the treatment response to the anti-VEGF agents is not well known. Therefore, we aimed to elucidate the relationship between the distribution of MAs and the response to anti-VEGF therapy in patients with DME. The number of MAs was measured before anti-VEGF therapy in each region using fluorescein angiography, indocyanine green angiography (IA), and optical coherence tomography angiography. Patients with DME were divided into the responder and non-responder groups after three loading phases. Differences in the distribution of MAs between the groups were investigated. Pre-treatment IA revealed more MAs in the nasal area in the non-responder group than in the responder group (10.7 ± 10.7 and 5.7 ± 5.7, respectively, in the nasal macula) (1.4 ± 2.1 and 0.4 ± 0.7, respectively, in the nasal fovea). Whereas, pre-treatment FA and OCTA could not reveal significantly difference between the groups. Detection of MAs in the nasal macula using pre-treatment IA may indicate resistance to anti-VEGF therapy. We recommend the clinicians confirm the presence of MAs in the nasal macula, as shown by IA, as a predictor of therapeutic response to anti-VEGF therapy in patients with treatment naive DME.

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.

Automatic Detection of Abnormalities and Grading of Diabetic Retinopathy in 6-Field Retinal Images: Integration of Segmentation Into Classification

Purpose

Classification of diabetic retinopathy (DR) is traditionally based on severity grading, given by the most advanced lesion, but potentially leaving out relevant information for risk stratification. In this study, we aimed to develop a deep learning model able to individually segment seven different DR-lesions, in order to test if this would improve a subsequently developed classification model.

Methods

First, manual segmentation of 34,075 different DR-lesions was used to construct a segmentation model, with performance subsequently compared to another retinal specialist. Second, we constructed a 5-step classification model using a data set of 31,325 expert-annotated retinal 6-field images and evaluated if performance was improved with the integration of presegmentation given by the segmentation model.

Results

The segmentation model had higher average sensitivity across all abnormalities compared to the retinal expert (0.68 and 0.62) at a comparable average F1-score (0.60 and 0.62). Model sensitivity for microaneurysms, retinal hemorrhages and intraretinal microvascular abnormalities was higher by 42.5%, 8.8%, and 67.5% and F1-scores by 15.8%, 6.5%, and 12.5%, respectively. When presegmentation was included, grading performance increased by 29.7%, 6.0%, and 4.5% for average per class accuracy, quadratic weighted kappa, and multiclass macro area under the curve, with values of 70.4%, 0.90, and 0.92, respectively.

Conclusions

The segmentation model matched an expert in detecting retinal abnormalities, and presegmentation substantially improved accuracy of the automated classification model.

Translational Relevance

Presegmentation may yield more accurate automated DR grading models and increase interpretability and trust in model decisions.

A digital online platform for education and certification of diabetic retinopathy health care professionals in the Region of Southern Denmark

PURPOSE

The incidence of diabetes continues to increase across the world. As the number of patients rises, so does the need for educated health care professionals. Diabetic retinopathy (DR) remains one of the primary complications in diabetes, and screening has proved to be a cost-effective measure to avoid DR-related blindness. Denmark has an established screening programme, but no formal training of the people responsible for analysing retinal images.

METHODS

We here present an online learning platform that offers a diabetic eye screening course for health care professionals undertaking screening responsibility in the Region of Southern Denmark. The course is divided into lectures, each focussed on identifying different levels of DR or detecting related lesions. The course is free to use on-demand, contains instructional videos, interactive tests and exercises, and it is concluded with a certification test. The tools on the platform can in addition be used to generate data for research purposes, such as comparing users or experts in detection of lesions or annotating data for the development of machine learning models.

RESULTS

More than 150 participants have so far completed the course, and the platform is being adopted for education in other regions of Denmark.

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.

Capillary density and caliber as assessed by optical coherence tomography angiography may be significant predictors of diabetic retinopathy severity

PURPOSE

To validate retinal capillary density and caliber associations with diabetic retinopathy (DR) severity in different clinical settings.

METHODS

This cross-sectional study assessed retinal capillary density and caliber in the superficial retinal layer of 3-mm OCTA scans centered on the fovea. Images were collected from non-diabetic controls and subjects with mild or referable DR (defined DR worse than mild DR) between February 2016 and December 2019 at secondary and tertiary eye care centers. Vessel Skeleton Density (VSD), a measure of capillary density, and Vessel Diameter Index (VDI), a measure of vascular caliber, were calculated from these images. Discriminatory performance of VSD and VDI was evaluated using multivariable logistic regression models predicting DR severity with adjustments for sex, hypertension, and hyperlipidemia. Area under the curve (AUC) was estimated. Model performance was evaluated in two different cohorts.

RESULTS

This study included 594 eyes from 385 subjects. Cohort 1 was a training cohort of 509 eyes including 159 control, 155 mild non-proliferative DR (NPDR) and 195 referable DR eyes. Cohort 2 was a validation cohort consisting of 85 eyes including 16 mild NPDR and 69 referable DR eyes. In Cohort 1, addition of VSD and VDI to a model using only demographic data significantly improved the model's AUC for discrimination of eyes with any DR severity from controls (0.91 [95% CI, 0.88-0.93] versus 0.80 [95% CI, 0.76-0.83], p < 0.001) and eyes with referable DR from mild NPDR (0.90 [95% CI, 0.86-0.93] versus 0.69 [95% CI, 0.64-0.75], p < 0.001). The transportability of this regression model was excellent when implemented in Cohort 2 for the referable DR versus mild NPDR comparison. The odds ratio of having any DR compared to control subjects, and referable DR compared to mild DR decreased by 15% (95% CI: 12-18%), and 13% (95% CI: 10-15%), respectively, for every 0.001 unit increase in VSD after adjusting for comorbidities.

CONCLUSION

OCTA-derived capillary density has real world clinical value for rapidly assessing DR severity.

Effect of Chinese herbal compounds on ocular fundus signs and vision in conventional treated-persons with non-proliferative diabetic retinopathy: A systematic review and meta-analysis

BACKGROUND

Changes in fundus signs and loss of visual acuity are an important basis for screening and treating diabetic patients with retinopathy, and conventional Western medicine is moderately effective in treating diabetic retinopathy(DR),To systematically evaluate the effectiveness and safety of Chinese herbal compounds(CHCs) in the combined treatment of diabetic retinopathy.

METHOD

Six electronic databases, including PubMed, were searched to screen eligible literature. Randomized controlled trials of non-proliferative diabetic retinopathy(NPDR) were included, in which the control group was treated with conventional Western-based drugs or retinal laser photocoagulation, and the intervention group was treated with CHCs in combination based on the control group.The Cochrane Risk of Bias Assessment Tool was used to evaluate the quality of the literature, and the RevMan 5.4 software was used for statistical analysis.

RESULTS

Compared with Conventional group alone,CHCs group was superior at improving clinical efficacy [RR=1.29, 95%CI=(1.23, 1.36),P<0.01] and best corrected visual acuity(BCVA) [MD=0.10,95%CI=(0.09,0.12),P<0.01],it was also superior at reducing the number of microangiomas [MD=-2.37, 95%CI=(-3.26, -1.49),P<0.01], microangioma volume [MD=-4.72, 95%CI=(-5.14, -4.29), P<0.01], hemorrhagic spots [MD=-2.05, 95%CI=(-2.51,-1.59), P<0.01], hemorrhagic area [MD=-0.76, 95%CI=(-1.06, -0.47), P<0.01], hard exudates [MD= -1.86, 95%CI=(-2.43, -1.28), P<0.01], cotton lint spots [MD= -0.93, 95%CI= (-1.31, -0.55), P<0.01], central macular thickness(CMT) [SMD=-1.52, 95%CI=(-1.85, -1.19),P<0.01], Chinese medicine evidence score [SMD=-1.33,95%CI=(-1.58, -1.08),P<0.01], fasting blood glucose (FBG) [SMD=-0.47, 95%CI=(-0.61,-0.33),P<0.01], 2h postprandial blood glucose(2hPBG) [SMD=-0.87, 95% CI=(-1.06, -0.67), P<0.01], glycosylated hemoglobin (HbAlc) [SMD=-0.76, 95%CI=(-1.16, -0.3),P<0.01], total cholesterol(TC) [SMD=-0.33,95%CI=(-0.51,-0.16),P<0.01],and CHCs group with less adverse events occurred [RR=0.46, 95%CI=(0.29, 0.74),P<0.01].

CONCLUSION

CHCs combined with conventional medicine for NPDR has better clinical efficacy and higher safety, but the above findings need further validation in more large sample, multicenter, and low-bias RCTs due to the limitation of the quality and quantity of included literature.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier CRD42022342137.

[Microaneurysms as a biomarker of diabetic retinopathy]

Diabetic retinopathy is a microvascular pathology, which is the most common complication of diabetes mellitus. Improvement of instrumental diagnostics of retinal pathologies has contributed to identification of various phenotypes of the progression of ocular fundus pathology in diabetes based on specific changes in the retina - biomarkers. In particular, microaneurysms initially described in diabetes, which are a manifestation of a wide range of systemic pathologies and retinal diseases, are an indicator of the severity of diabetic retinopathy. Dynamic changes in the number of microaneurysms are a confirmed prognostic biomarker of clinically significant macular edema. In diabetic retinopathy, microaneurysms are one of the earliest recognizable signs, and the dynamic of their formation and disappearance may serve as a predictor for the disease progression. This literature review presents the characteristics of microaneurysms based on various imaging techniques, and analyses the link between structural features and dynamic changes in microaneurysms, and progression of diabetic retinopathy.

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

Background: Analysis of retinal microaneurysm turnover (MAT) has been previously shown to contribute to the identification of eyes at risk of developing clinically significant complications associated with diabetic retinopathy (DR). We propose to further characterize MAT as a predictive biomarker of DR progression and development of vision-threatening complications. Methods: 212 individuals with type 2 diabetes (T2D; ETDRS grades 20 and 35) were evaluated annually in a 5-year prospective, longitudinal study, by color fundus photography and optical coherence tomography. Endpoints were diabetic macular edema (DME) or proliferative retinopathy (PDR). MAT analysis included determination of MA formation and disappearance rates, automatically assessed using the RetMarkerDR^®. Retinopathy severity progression was evaluated using step increases in ETDRS severity levels. Results: Of the 212 individuals, 172 completed the 5-year follow-up study or developed an endpoint (n = 27). MAT calculated at 1 year showed a significant difference between groups of endpoint developments (p = 0.018), particularly MA disappearance rate (p = 0.007). MAT also showed a significant difference between eyes with different ETDRS severity progression in the 5-year period (p = 0.035). Conclusions: MAT is an indicator of the development of DME and/or PDR as well as of DR severity progression in T2D individuals with mild retinopathy.

Phenotypic Differences in a PRPH2 Mutation in Members of the Same Family Assessed with OCT and OCTA

Choroidal dystrophies comprise a group of chorioretinal degenerations. However, the different findings observed among these patients make it difficult to establish a correct clinical diagnosis. The objective of this study was to characterize new clinical findings by optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) in these patients. Four family members with a PRPH2 gene mutation (p.Arg195Leu) were included. OCT was performed at the macula, and the thickness of the outer and inner retina, total retina, and choroid was measured. The features of the vascular network were analyzed by OCTA. Patients showed a decreased outer nuclear layer in the avascular area compared with the controls. Two patients presented greater foveal and parafoveal degeneration of the outer retina, whereas the most degenerated area in the rest was the perifovea. Disruption of the third outer band at the foveola is one of the first-altered outer bands. Slow blood flow areas or capillary dropout were main signs in the deep capillary plexus. Microaneurysms were frequently observed in less degenerated retinas. Vascular loops and intraretinal microvascular abnormalities (IRMAs) were present in the superficial plexus. Extensive degeneration of the choriocapillaris was detected. Phenotypic differences were found between patients: two showed central areolar choroidal dystrophy and the rest had extensive chorioretinal atrophy. These signs observed in OCT and OCTA can help to more appropriately define the clinical disease in patients with choroidal dystrophies.

The Effect of Anti-Vascular Endothelial Growth Factor on Retinal Microvascular Changes in Diabetic Macular Edema Using Swept-Source Optical Coherence Tomography Angiography

Purpose

This study evaluates the effect of anti-vascular endothelial growth factor (anti-VEGF) therapy on microaneurysm changes and foveal avascular zone (FAZ) using optical coherence tomography angiography (OCTA) in patients with diabetic macular edema (DME).

Design

Prospective observational study.

Materials and Methods

This study involved patients with DME undergoing anti-VEGF treatment (aflibercept, ranibizumab, and bevacizumab). Macula OCTA images were obtained before (visit 0) and 1 month after (visit 1) anti-VEGF injection. Microaneurysm counts were performed, and the FAZ was evaluated in the superficial capillary plexus (SCP) and deep capillary plexus (DCP). The differences in microaneurysms, FAZ, and clinical correlations were analyzed.

Results

A total of 152 eyes were analyzed. The patients' mean age was 59 years. Bevacizumab was used in 69.7%, ranibizumab in 15.1%, and aflibercept in 15.1%. There was a significant reduction in the FAZ in the SCP and DCP between visits 0 and 1. All anti-VEGF medications reduced the number of microaneurysms (p<0.01). After treatment, changes in the FAZ in SCP and DCP corresponded with changes in visual acuity (p<0.01).

Conclusion

Microaneurysms as detected by OCTA might serve as a biomarker for a clinical response to anti-VEGF treatment in the short term. The FAZ might also predict visual acuity improvement after anti-VEGF injection.

Trial Registration

Thai Clinical Trials Registry (TCTR20161010005).

Prospective, Single-Center, Six-Month Study of Intravitreal Ranibizumab for Macular Edema with Nonproliferative Diabetic Retinopathy: Effects on Microaneurysm Turnover and Non-Perfused Retinal Area

Purpose

To analyze the effects on microaneurysm (MA) and perifoveal perfusion in nonproliferative diabetic retinopathy (NPDR) patients with macular edema (ME) after early intensive treatment using intravitreal ranibizumab (IVR) injections.

Patients and Methods

Prospectively, 25 eyes of 25 type 2 diabetes mellitus patients with ME were included between August 2016 and February 2019. For 6 months, patients were administered 0.5-mg IVR injections monthly. Ocular evaluation, including best-corrected visual acuity (BCVA; using the Early Treatment Diabetic Retinopathy Study chart), central retinal thickness (CRT; using optical coherence tomography), fundus photography, and fluorescein angiography, was performed for all participants. Results obtained at baseline were compared to those observed after 6 months.

Results

Mean BCVA increased significantly from 67.6±3.29 letters at baseline to 76.36±1.61 letters after 6 months (P=0.002) of IVR therapy. CRT decreased significantly from 479.12±16.66 µm at baseline to 369.12±13.02 µm at 6 months. Similarly, the total number of MAs decreased significantly from 5.68±3.41 to 1.60±1.73 (P<0.0001). MA turnover, calculated by adding the MA formation rate to the MA disappearance rate (both calculated as MA number/month) also decreased significantly from 6.88±3.83 to 1.92±1.75 after treatment (P<0.0001). Perifoveal non-perfused area decreased from 2.517±0.456 mm² at baseline to 2.495±0.293 mm² at 6 months, but the results were not statistically significant (P=0.954).

Conclusion

Treatment with early intensive IVR therapy in NPDR patients with ME not only improved BCVA and CRT but also decreased MA turnover. However, in the study period of 6 months, IVR therapy did not show significant improvement in perifoveal non-perfused area.

Retinopathy Phenotypes in Type 2 Diabetes with Different Risks for Macular Edema and Proliferative Retinopathy

Our group reported that three diabetic retinopathy (DR) phenotypes: A, characterized by low microaneurysm turnover (MAT < 6) and normal central retinal thickness (CRT); B, low MAT (<6) and increased CRT, and C, high MAT (≥6), present different risks for development of macular edema (DME) and proliferative retinopathy (PDR). To test these findings, 212 persons with type 2 diabetes (T2D) and mild nonproliferative retinopathy (NPDR), one eye per person, were followed for five years with annual visits. Of these, 172 completed the follow-up or developed an outcome: PDR or DME (considering both clinically significant macular edema (CSME) and center-involved macular edema (CIME)). Twenty-seven eyes (16%) developed either CSME (14), CIME (10), or PDR (4), with one eye developing both CSME and PDR. Phenotype A showed no association with development of vision-threatening complications. Seven eyes with phenotype B and three with phenotype C developed CIME. Phenotype C showed higher risk for CSME development, with 17.41 odds ratio (p = 0.010), compared with phenotypes A + B. All eyes that developed PDR were classified as phenotype C. Levels of HbA_1c and triglycerides were increased in phenotype C (p < 0.001 and p = 0.018, respectively). In conclusion, phenotype C identifies eyes at higher risk for development of CSME and PDR, whereas phenotype A identifies eyes at very low risk for vision-threatening complications.

Microaneurysms detection in color fundus images using machine learning based on directional local contrast

Background

As one of the major complications of diabetes, diabetic retinopathy (DR) is a leading cause of visual impairment and blindness due to delayed diagnosis and intervention. Microaneurysms appear as the earliest symptom of DR. Accurate and reliable detection of microaneurysms in color fundus images has great importance for DR screening.

Methods

A microaneurysms' detection method using machine learning based on directional local contrast (DLC) is proposed for the early diagnosis of DR. First, blood vessels were enhanced and segmented using improved enhancement function based on analyzing eigenvalues of Hessian matrix. Next, with blood vessels excluded, microaneurysm candidate regions were obtained using shape characteristics and connected components analysis. After image segmented to patches, the features of each microaneurysm candidate patch were extracted, and each candidate patch was classified into microaneurysm or non-microaneurysm. The main contributions of our study are (1) making use of directional local contrast in microaneurysms' detection for the first time, which does make sense for better microaneurysms' classification. (2) Applying three different machine learning techniques for classification and comparing their performance for microaneurysms' detection. The proposed algorithm was trained and tested on e-ophtha MA database, and further tested on another independent DIARETDB1 database. Results of microaneurysms' detection on the two databases were evaluated on lesion level and compared with existing algorithms.

Results

The proposed method has achieved better performance compared with existing algorithms on accuracy and computation time. On e-ophtha MA and DIARETDB1 databases, the area under curve (AUC) of receiver operating characteristic (ROC) curve was 0.87 and 0.86, respectively. The free-response ROC (FROC) score on the two databases was 0.374 and 0.210, respectively. The computation time per image with resolution of 2544×1969, 1400×960 and 1500×1152 is 29 s, 3 s and 2.6 s, respectively.

Conclusions

The proposed method using machine learning based on directional local contrast of image patches can effectively detect microaneurysms in color fundus images and provide an effective scientific basis for early clinical DR diagnosis.

MultiColor imaging to detect different subtypes of retinal microaneurysms in diabetic retinopathy

BACKGROUND

Retinal microaneurysms (MAs) are among the earliest signs of diabetic retinopathy (DR) and are typically detected by fluorescein angiography (FA). Confocal MultiColor is a noninvasive-imaging technique able to analyze different retinal features by capturing three simultaneous reflectance images. The main aim of the present study was to characterize morphological features of MAs by means of MultiColor images and to compare these with spectral domain optical coherence tomography (SD-OCT) and FA findings.

METHODS

A cross-sectional, observational study setting was chosen. Multimodal imaging included MultiColor, SD-OCT and FA images. We performed a qualitative analysis in order to assess the relationship between MultiColor and its green- and red-reflectance components, SD-OCT (hyperreflective, hyporeflective and mixed reflectivity) and FA findings. MAs detected on our MultiColor images were then categorized in accordance with a previously published histological classification.

RESULTS

In our study FA images were used to detect 153 MAs in 30 eyes displaying DR. MultiColor was able to distinguish 122 MAs (80%). We identified green (16%), red (19%), and mixed (65%) MAs, corresponding to different reflectivity features detected by SD-OCT. MAs not visualized on MultiColor images corresponded to tiny hyperreflective lesions on SD-OCT. We compared our imaging findings with a histological MA classification reported in the literature. Our findings showed a strict relationship between MA subtypes and SD-OCT, suggesting that the composition of MAs (cells + endothelium + fibrosis) may influence the signal detected in MultiColor images.

CONCLUSIONS

MultiColor appears to be a useful technique for investigating MA features in patients with DR.

Applications of Artificial Intelligence for the Detection, Management, and Treatment of Diabetic Retinopathy

Rates of diabetic retinopathy (DR) and diabetic macular edema (DME), a common ocular complication of diabetes mellitus, are increasing worldwide. There is a substantial burden concerning the detection and management of this condition, particularly in low-resource settings, due to limitations such as the time, cost, and labor associated with current screening and treatment methods. Artificial intelligence (AI) is a modality of pattern recognition that has the potential to combat these limitations in a reliable and cost-effective way. This review explores the various applications of AI on the screening, management, and treatment of DR and DME. AI applications for detecting referable DR and DME have been the most thoroughly researched applications for this condition. While some studies exist using AI to stratify DR patients based on the risk of progression, predict treatment outcomes to anti-VEGF therapy, and explore the utilization of AI for clinical trials to develop new treatments for DR, further validation studies on larger datasets are warranted.

Deep learning algorithm predicts diabetic retinopathy progression in individual patients

The global burden of diabetic retinopathy (DR) continues to worsen and DR remains a leading cause of vision loss worldwide. Here, we describe an algorithm to predict DR progression by means of deep learning (DL), using as input color fundus photographs (CFPs) acquired at a single visit from a patient with DR. The proposed DL models were designed to predict future DR progression, defined as 2-step worsening on the Early Treatment Diabetic Retinopathy Diabetic Retinopathy Severity Scale, and were trained against DR severity scores assessed after 6, 12, and 24 months from the baseline visit by masked, well-trained, human reading center graders. The performance of one of these models (prediction at month 12) resulted in an area under the curve equal to 0.79. Interestingly, our results highlight the importance of the predictive signal located in the peripheral retinal fields, not routinely collected for DR assessments, and the importance of microvascular abnormalities. Our findings show the feasibility of predicting future DR progression by leveraging CFPs of a patient acquired at a single visit. Upon further development on larger and more diverse datasets, such an algorithm could enable early diagnosis and referral to a retina specialist for more frequent monitoring and even consideration of early intervention. Moreover, it could also improve patient recruitment for clinical trials targeting DR.

Artificial intelligence for diabetic retinopathy screening: a review

Diabetes is a global eye health issue. Given the rising in diabetes prevalence and ageing population, this poses significant challenge to perform diabetic retinopathy (DR) screening for these patients. Artificial intelligence (AI) using machine learning and deep learning have been adopted by various groups to develop automated DR detection algorithms. This article aims to describe the state-of-art AI DR screening technologies that have been described in the literature, some of which are already commercially available. All these technologies were designed using different training datasets and technical methodologies. Although many groups have published robust diagnostic performance of the AI algorithms for DR screening, future research is required to address several challenges, for examples medicolegal implications, ethics, and clinical deployment model in order to expedite the translation of these novel technologies into the healthcare setting.