Differential distribution of manifest lesions in diabetic retinopathy by fundus fluorescein angiography and fundus photography

Differential distribution of fibrovascular proliferative membranes in 25-gauge vitrectomy for proliferative diabetic retinopathy

AIM

To analyze the distribution of fibrovascular proliferative membranes (FVPMs) in proliferative diabetic retinopathy (PDR) patients that treated with pars plana vitrectomy (PPV), and to evaluate the outcomes separately.

METHODS

This was a retrospective and cross-sectional study. Consecutive 25-gauge (25-G) PPV cases operated for PDR from May 2018 to April 2020. According to the FVPMs images outlined after operations, subjects were assigned into three groups: arcade type group, juxtapapillary type group, and central type group. All patients were followed up for over one year. General characteristics, operation-related variables, postoperative parameters and complications were recorded.

RESULTS

Among 103 eyes recruited, the FVPMs distribution of nasotemporal and inferiosuperioral was significantly different (both P<0.01), with 95 (92.23%) FVPMs located in the nasal quadrants, and 74 (71.84%) in the inferior. The eyes with a central FVPM required the longest operation time, with silicon oil used in most patients, generally combined with tractional retinal detachment (RD) and rhegmatogenous RD, the worst postoperative best-corrected visual acuity (BCVA) and the highest rates of recurrent RD (all P<0.05). FVPM type, age of onset diabetes mellitus, preoperative BCVA, and combined with tractional RD and rhegmatogenous RD were significantly associated with BCVA improvement (all P<0.05). Compared with the central type group, the arcade type group had higher rates of BCVA improvement.

CONCLUSION

FVPMs are more commonly found in the nasal and inferior mid-peripheral retina in addition to the area of arcade vessels. Performing 25-G PPV for treating PDR eyes with central FVPM have relatively worse prognosis.

Segmentation of retinal microaneurysms in fluorescein fundus angiography images by a novel three-step model

Introduction

Microaneurysms serve as early signs of diabetic retinopathy, and their accurate detection is critical for effective treatment. Due to their low contrast and similarity to retinal vessels, distinguishing microaneurysms from background noise and retinal vessels in fluorescein fundus angiography (FFA) images poses a significant challenge.

Methods

We present a model for automatic detection of microaneurysms. FFA images were pre-processed using Top-hat transformation, Gray-stretching, and Gaussian filter techniques to eliminate noise. The candidate microaneurysms were coarsely segmented using an improved matched filter algorithm. Real microaneurysms were segmented by a morphological strategy. To evaluate the segmentation performance, our proposed model was compared against other models, including Otsu's method, Region Growing, Global Threshold, Matched Filter, Fuzzy c-means, and K-means, using both self-constructed and publicly available datasets. Performance metrics such as accuracy, sensitivity, specificity, positive predictive value, and intersection-over-union were calculated.

Results

The proposed model outperforms other models in terms of accuracy, sensitivity, specificity, positive predictive value, and intersection-over-union. The segmentation results obtained with our model closely align with benchmark standard. Our model demonstrates significant advantages for microaneurysm segmentation in FFA images and holds promise for clinical application in the diagnosis of diabetic retinopathy.

Conclusion

The proposed model offers a robust and accurate approach to microaneurysm detection, outperforming existing methods and demonstrating potential for clinical application in the effective treatment of diabetic retinopathy.

Aflibercept 5+PRN with retinal laser photocoagulation is more effective than retinal laser photocoagulation alone and aflibercept 3+PRN with retinal laser photocoagulation in patients with high-risk proliferative diabetic retinopathy and diabetic macular edema: a 12-month clinical trial

Objective

This study aimed to investigate and compare the efficacy and safety of retinal laser photocoagulation (PRP) alone, PRP with aflibercept 3+PRN, and PRP with aflibercept 5+PRN in patients with both high-risk proliferative diabetic retinopathy (PDR) and diabetic macular edema (DME).

Methods

Overall, 170 patients with high-risk PDR and DME (170 eyes from 170 patients) who visited our ophthalmology clinic from December 2018 to December 2020 were divided into the PRP (n=58), aflibercept 5+PRN with PRP (n=53), and aflibercept 3+PRN with PRP (n= 59) groups. General information, such as age, sex, and eye category, was obtained. Moreover, best-corrected visual acuity (BCVA), baseline central macular foveal thickness (CFT), microaneurysm (MA), area of neovascularization (NV), area of hard exudate (HE), and cytokine levels in atrial fluid before and after treatment, were assessed. The χ2 test was used for comparison between groups for statistical data. Analysis of variance was used for the statistical description of measurement data, independent samples were analyzed using Student's t-test, and Student-Newman-Keuls test was used for group comparisons. Differences were considered statistically significant at P < 0.05.

Results

After treatment, no significant improvement in the BCVA (logMAR) of patients in the PRP group was observed. The BCVA (log MAR) decreased from 0.72 ± 0.17 and 0.74 ± 0.17 to 0.50 ± 0.13 and 0.53 ± 0.17 in PRP with aflibercept 5+PRN and PRP with aflibercept 3+PRN groups, respectively, with a statistically significant difference compared to those in the PRP group (P<0.05 in all cases). However, no statistically significant difference was observed between the combined treatment groups (P>0.05). The CFT in the PRP-only group decreased slightly from 361.80 ± 36.70 μm to 353.86 ± 40.88 μm, with no statistically significant difference (P>0.05), whereas the CFT in the aflibercept 5+PRN with PRP and aflibercept 3+PRN with PRP groups decreased from 356.57 ± 37.57 μm and 358.17 ± 44.66 μm to 284.87 ± 31.52 μm and 303.19 ± 37.00 μm, respectively, with statistically significant differences before and after treatment (P<0.05 for both groups). Statistically significant differences were observed in CFT between the three groups after treatment (P<0.05 in all cases). The number of MA (pcs) in the PRP, aflibercept 5+PRN with PRP, and aflibercept 3+PRN with PRP groups decreased from 118.34 ± 27.96, 118.60 ± 33.34, and 116.59 ± 28.95 to 92.95 ± 29.04, 44.60 ± 20.73, and 54.26 ± 25.43, respectively. The two-way comparison of the three groups revealed statistically significant differences in MA (P<0.05 in all cases). In the three groups, NV decreased from 1.00 ± 0.21 mm², 1.01 ± 0.18 mm², and 0.98 ± 0.20 mm² before treatment to 0.49 ± 0.17 mm², 0.31 ± 0.16 mm², and 0.38 ± 0.14 mm², respectively, with statistically significant differences (P<0.05 in all cases). After 12 months of treatment, 13, 18, and 18 patients had reduced HE area in the PRP-only, aflibercept 5+PRN with PRP, and aflibercept 3+PRN with PRP groups, respectively, with statistically significant differences (P<0.05 in all cases). After 12 months of treatment, vascular endothelial growth factor, monocyte chemoattractant protein-1, and glial fibrilliary acidic protein levels (pg/mL) in the aqueous humor decreased in both combined treatment groups compared with that at baseline, with statistically significant differences; however, no significant difference was observed between the two combined treatment groups (P>0.05).

Conclusion

Aflibercept 5+PRN combined with PRP was safe and effective in treating patients with high-risk PDR and DME, and was more effective than PRP-only and aflibercept 3+PRN with PRP in improving CFT and MA.

Application of non-mydriatic fundus photography-assisted telemedicine in diabetic retinopathy screening

BACKGROUND

Early screening and accurate staging of diabetic retinopathy (DR) can reduce blindness risk in type 2 diabetes patients. DR's complex pathogenesis involves many factors, making ophthalmologist screening alone insufficient for prevention and treatment. Often, endocrinologists are the first to see diabetic patients and thus should screen for retinopathy for early intervention.

AIM

To explore the efficacy of non-mydriatic fundus photography (NMFP)-enhanced telemedicine in assessing DR and its various stages.

METHODS

This retrospective study incorporated findings from an analysis of 93 diabetic patients, examining both NMFP-assisted telemedicine and fundus fluorescein angiography (FFA). It focused on assessing the concordance in DR detection between these two methodologies. Additionally, receiver operating characteristic (ROC) curves were generated to determine the optimal sensitivity and specificity of NMFP-assisted telemedicine, using FFA outcomes as the standard benchmark.

RESULTS

In the context of DR diagnosis and staging, the kappa coefficients for NMFP-assisted telemedicine and FFA were recorded at 0.775 and 0.689 respectively, indicating substantial intermethod agreement. Moreover, the NMFP-assisted telemedicine's predictive accuracy for positive FFA outcomes, as denoted by the area under the ROC curve, was remarkably high at 0.955, within a confidence interval of 0.914 to 0.995 and a statistically significant P-value of less than 0.001. This predictive model exhibited a specificity of 100%, a sensitivity of 90.9%, and a Youden index of 0.909.

CONCLUSION

NMFP-assisted telemedicine represents a pragmatic, objective, and precise modality for fundus examination, particularly applicable in the context of endocrinology inpatient care and primary healthcare settings for diabetic patients. Its implementation in these scenarios is of paramount significance, enhancing the clinical accuracy in the diagnosis and therapeutic management of DR. This methodology not only streamlines patient evaluation but also contributes substantially to the optimization of clinical outcomes in DR management.

Programmatically Localizing Diabetic Retinopathy Features in 45-Degree Retinal Photographs Using Anatomical Colocation

Background: The aim in this study was to investigate the localization of diabetic retinopathy features at the posterior pole. Methods: This study extracted diabetic retinopathy feature locations from 757 macula-centered 45-degree fundus photographs in the publicly available DDR dataset. Arteriole and venule locations were also extracted from the RITE (n = 35) and IOSTAR (n = 29) datasets. Images were normalized to collocate optic disc and macula positions, and feature positions were collated to generate a frequency distribution matrix. Sørensen-Dice coefficients were calculated to compare the location of different features. Results: Arterioles occurred in two main, distinct arcuate patterns. Venules showed a more diffuse distribution. Microaneurysms were diffusely located around the posterior pole. Hemorrhages and exudates occurred more frequently at the temporal aspect of the macula. Cotton wool spots occurred in a region approximating the radial peripapillary capillaries. Intraretinal microvascular abnormalities and neovascularization were seen throughout the posterior pole, with neovascularization at the disc (n = 65) being more common than neovascularization elsewhere (n = 46). Venous beading occurred primarily between the first and third bifurcations of the venules. Diabetic retinopathy overall was more frequent in the temporal aspect of the macula. The location of cotton wool spots and exudates showed moderate similarity (0.52) when all data were considered, reducing to low similarity (0.18) when areas of low frequency were removed. Conclusions: Diabetic retinopathy occurs throughout the posterior pole but is more frequent in the temporal aspect of the macula. Understanding the location of diabetic retinopathy features may help inform visual search strategies for diabetic retinopathy screening.

An artificial intelligence system for the whole process from diagnosis to treatment suggestion of ischemic retinal diseases

Ischemic retinal diseases (IRDs) are a series of common blinding diseases that depend on accurate fundus fluorescein angiography (FFA) image interpretation for diagnosis and treatment. An artificial intelligence system (Ai-Doctor) was developed to interpret FFA images. Ai-Doctor performed well in image phase identification (area under the curve [AUC], 0.991-0.999, range), diabetic retinopathy (DR) and branch retinal vein occlusion (BRVO) diagnosis (AUC, 0.979-0.992), and non-perfusion area segmentation (Dice similarity coefficient [DSC], 89.7%-90.1%) and quantification. The segmentation model was expanded to unencountered IRDs (central RVO and retinal vasculitis), with DSCs of 89.2% and 83.6%, respectively. A clinically applicable ischemia index (CAII) was proposed to evaluate ischemic degree; patients with CAII values exceeding 0.17 in BRVO and 0.08 in DR may be associated with increased possibility for laser therapy. Ai-Doctor is expected to achieve accurate FFA image interpretation for IRDs, potentially reducing the reliance on retinal specialists.

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.

Reduced macula microvascular densities may be an early indicator for diabetic peripheral neuropathy

Purpose: To assess the alteration in the macular microvascular in type 2 diabetic patients with peripheral neuropathy (DPN) and without peripheral neuropathy (NDPN) by optical coherence tomography angiography (OCTA) and explore the correlation between retinal microvascular abnormalities and DPN disease. Methods: Twenty-seven healthy controls (42 eyes), 36 NDPN patients (62 eyes), and 27 DPN patients (40 eyes) were included. OCTA was used to image the macula in the superficial vascular complex (SVC) and deep vascular complex (DVC). In addition, a state-of-the-art deep learning method was employed to quantify the microvasculature of the two capillary plexuses in all participants using vascular length density (VLD). Results: Compared with the healthy control group, the average VLD values of patients with DPN in SVC (p = 0.010) and DVC (p = 0.011) were significantly lower. Compared with NDPN, DPN patients showed significantly reduced VLD values in the SVC (p = 0.006) and DVC (p = 0.001). Also, DPN patients showed lower VLD values (p < 0.05) in the nasal, superior, temporal and inferior sectors of the inner ring of the SVC when compared with controls; VLD values in NDPN patients were lower in the nasal section of the inner ring of SVC (p < 0.05) compared with healthy controls. VLD values in the DVC (AUC = 0.736, p < 0.001) of the DPN group showed a higher ability to discriminate microvascular damage when compared with NDPN. Conclusion: OCTA based on deep learning could be potentially used in clinical practice as a new indicator in the early diagnosis of DM with and without DPN.

Deep Learning Models for Segmenting Non-perfusion Area of Color Fundus Photographs in Patients With Branch Retinal Vein Occlusion

Purpose

To develop artificial intelligence (AI)-based deep learning (DL) models for automatically detecting the ischemia type and the non-perfusion area (NPA) from color fundus photographs (CFPs) of patients with branch retinal vein occlusion (BRVO).

Methods

This was a retrospective analysis of 274 CFPs from patients diagnosed with BRVO. All DL models were trained using a deep convolutional neural network (CNN) based on 45 degree CFPs covering the fovea and the optic disk. We first trained a DL algorithm to identify BRVO patients with or without the necessity of retinal photocoagulation from 219 CFPs and validated the algorithm on 55 CFPs. Next, we trained another DL algorithm to segment NPA from 104 CFPs and validated it on 29 CFPs, in which the NPA was manually delineated by 3 experienced ophthalmologists according to fundus fluorescein angiography. Both DL models have been cross-validated 5-fold. The recall, precision, accuracy, and area under the curve (AUC) were used to evaluate the DL models in comparison with three types of independent ophthalmologists of different seniority.

Results

In the first DL model, the recall, precision, accuracy, and area under the curve (AUC) were 0.75 ± 0.08, 0.80 ± 0.07, 0.79 ± 0.02, and 0.82 ± 0.03, respectively, for predicting the necessity of laser photocoagulation for BRVO CFPs. The second DL model was able to segment NPA in CFPs of BRVO with an AUC of 0.96 ± 0.02. The recall, precision, and accuracy for segmenting NPA was 0.74 ± 0.05, 0.87 ± 0.02, and 0.89 ± 0.02, respectively. The performance of the second DL model was nearly comparable with the senior doctors and significantly better than the residents.

Conclusion

These results indicate that the DL models can directly identify and segment retinal NPA from the CFPs of patients with BRVO, which can further guide laser photocoagulation. Further research is needed to identify NPA of the peripheral retina in BRVO, or other diseases, such as diabetic retinopathy.

Effects of intensive insulin therapy on the retinal microvasculature in patients with type 2 diabetes mellitus: a prospective observational study

Background

We examined the retinal microvascular changes and associated factors in type 2 diabetes mellitus (T2DM) before and after intensive insulin therapy.

Methods

This prospective observational study recruited patients with T2DM and divided them into intensive insulin therapy and oral hypoglycemic agent groups. All patients enrolled in this study had diabetes without retinopathy or non-proliferative diabetic retinopathy. Optical coherence tomography angiography (OCTA) was used in all patients before treatment and at 1, 3, and 6 months after treatment. Vessel density (VD) and thickness changes in the macular and optic disc areas were assessed.

Results

The study included 36 eyes in the intensive insulin therapy group and 36 in the oral hypoglycemic agent group. One month after treatment, VD in the deep capillary plexus (DCP) and peripapillary capillary VD (ppVD) were significantly decreased by intensification (P = 0.009, 0.000). At three months after treatment, decreases in VD induced by intensification were found in the superficial capillary plexus (SCP), DCP, foveal density in a 300-μm-wide region around the foveal avascular area (FD-300), and ppVD (P = 0.032, 0.000, 0.039, 0.000). Six months after treatment, decreases in VD by intensification were observed in the DCP and ppVD groups (P = 0.000, 0.000). Vessel density showed no significant change in the oral hypoglycemic agent group after treatment. The amount of DCP-VD reduction was correlated with macular thickening (r = 0.348, P = 0.038; r = 0.693, P = 0.000 and r = 0.417, P = 0.011, respectively) after intensive insulin therapy.

Conclusions

Insulin-intensive treatment caused a transient reduction in vessel density in the macular and optic disc areas. DCP-VD and ppVD were more susceptible at an earlier stage. Retinal microvasculature monitoring using OCTA is vital for patients with type 2 diabetes receiving intensive insulin therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12886-022-02397-9.

Evaluation of an Artificial Intelligence System for the Detection of Diabetic Retinopathy in Chinese Community Healthcare Centers

Objective

To evaluate the sensitivity and specificity of a Comprehensive Artificial Intelligence Retinal Expert (CARE) system for detecting diabetic retinopathy (DR) in a Chinese community population.

Methods

This was a cross-sectional, diagnostic study. Participants with a previous diagnosis of diabetes from three Chinese community healthcare centers were enrolled in the study. Single-field color fundus photography was obtained and analyzed by the AI system and two ophthalmologists. Primary outcome measures included the sensitivity, specificity, positive predictive value, and negative predictive value with their 95% confidence intervals (CIs) of the AI system in detecting DR and diabetic macular edema (DME).

Results

In this study, 443 subjects (848 eyes) were enrolled, and 283 (63.88%) were men. The mean age was 52.09 (11.51) years (range 18–82 years); 266 eyes were diagnosed with any DR, 233 with more-than-mild diabetic retinopathy (mtmDR), 112 with vision-threatening diabetic retinopathy (vtDR), and 57 with DME. The image ability of the AI system was as high as 99.06%, whereas its sensitivity and specificity varied significantly in detecting DR with different severities. The sensitivity/specificity to detect any DR was 75.19% (95%CI 69.47–80.17)/93.99% (95%CI 91.65–95.71), mtmDR 78.97% (95%CI 73.06–83.90)/92.52% (95%CI 90.07–94.41), vtDR 33.93% (95%CI 25.41–43.56)/97.69% (95%CI 96.25–98.61), and DME 47.37% (95%CI 34.18–60.91)/93.99% (95%CI 91.65–95.71).

Conclusions

This multicenter cross-sectional diagnostic study noted the safety and reliability of the CARE system for DR (especially mtmDR) detection in Chinese community healthcare centers. The system may effectively solve the dilemma faced by Chinese community healthcare centers: due to the lack of ophthalmic expertise of primary physicians, DR diagnosis and referral are not timely.

Functional Optical Coherence Tomography for Intrinsic Signal Optoretinography: Recent Developments and Deployment Challenges

Intrinsic optical signal (IOS) imaging of the retina, also termed as optoretinogram or optoretinography (ORG), promises a non-invasive method for the objective assessment of retinal function. By providing the unparalleled capability to differentiate individual retinal layers, functional optical coherence tomography (OCT) has been actively investigated for intrinsic signal ORG measurements. However, clinical deployment of functional OCT for quantitative ORG is still challenging due to the lack of a standardized imaging protocol and the complication of IOS sources and mechanisms. This article aims to summarize recent developments of functional OCT for ORG measurement, OCT intensity- and phase-based IOS processing. Technical challenges and perspectives of quantitative IOS analysis and ORG interpretations are discussed.

Zone-wise examination of optical coherence tomography features and their correspondence to multifocal electroretinography in eyes with nonproliferative diabetic retinopathy

PURPOSE

To examine (1) the retinal structure by optical coherence tomography (OCT) and function by means of multifocal electroretinography (mfERG) in eyes with and without nonproliferative diabetic retinopathy (NPDR) (2) for correspondence between local retinal function and OCT zones with retinal lesions.

METHODS

One hundred and thirty-two eligible participants (30 with nonproliferative DR (NPDR) and 102 with diabetes with no DR) underwent comprehensive ophthalmic examination, optical coherence tomography for retinal thickness measures, mfERG, and ultra-wide field fundus photography. OCT Early Treatment Diabetic Retinopathy Study (ETDRS) grid was overlaid on to mfERG plots.

RESULTS

Those with NPDR had significantly thicker full retinal measures in the nine (ETDRS) zones compared to no DR. mfERG P1 latencies in rings 1-6 were significantly delayed, while the response densities in rings 4-6 were lower in the NPDR group. Significant negative correlation was noted between OCT thickness and mfERG P1 response densities in many ETDRS zones. Significant positive correlation was noted between P1 latencies and OCT thickness in a few zones. The combination of cystic spaces, microaneurysms, and hard exudates were present in all zones and were associated with a decrease in P1 response densities compared to no lesions. Reduced P1 response densities were associated with a sporadic delay in the mfERG latencies and vice versa. The number of lesions did not show correspondence to the mfERG measures.

CONCLUSIONS

In eyes with NPDR, retinal function is differentially correlated with the DR lesions on OCT and can be assessed using multimodal imaging modalities.