Advances in retinal imaging for diabetic retinopathy and diabetic macular edema

Deep learning-based detection of diabetic macular edema using optical coherence tomography and fundus images: A meta-analysis

Diabetic macular edema (DME) is an important cause of visual impairment in the working-age group. Deep learning methods have been developed to detect DME from two-dimensional retinal images and also from optical coherence tomography (OCT) images. The performances of these algorithms vary and often create doubt regarding their clinical utility. In resource-constrained health-care systems, these algorithms may play an important role in determining referral and treatment. The survey provides a diversified overview of macular edema detection methods, including cutting-edge research, with the objective of providing pertinent information to research groups, health-care professionals, and diabetic patients about the applications of deep learning in retinal image detection and classification process. Electronic databases such as PubMed, IEEE Explore, BioMed, and Google Scholar were searched from inception to March 31, 2022, and the reference lists of published papers were also searched. The study followed the preferred reporting items for systematic review and meta-analysis (PRISMA) reporting guidelines. Examination of various deep learning models and their exhibition regarding precision, epochs, their capacity to detect anomalies for less training data, concepts, and challenges that go deep into the applications were analyzed. A total of 53 studies were included that evaluated the performance of deep learning models in a total of 1,414,169°CT volumes, B-scans, patients, and 472,328 fundus images. The overall area under the receiver operating characteristic curve (AUROC) was 0.9727. The overall sensitivity for detecting DME using OCT images was 96% (95% confidence interval [CI]: 0.94-0.98). The overall sensitivity for detecting DME using fundus images was 94% (95% CI: 0.90-0.96).

Predictive factors for treatment outcomes with intravitreal anti-vascular endothelial growth factor injections in diabetic macular edema in clinical practice

BACKGROUND

Intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections are the standard of care for diabetic macular edema (DME), a common complication of diabetes. This study aimed to identify factors influencing DME intravitreal anti-VEGF treatment outcomes in real-world practice.

METHODS

This was a multi-center retrospective observational study using medical chart review of participants receiving anti-VEGF injections for DME (N = 248). Demographic and clinical variables were assessed for association with best corrected visual acuity (BCVA) and central macular thickness (CMT) outcomes using regression models.

RESULTS

There was a significant improvement in BCVA (p < 0.001) and CMT (p < 0.001) after 12 months of treatment, although 21% of participants had decreased BCVA, and 41% had a < 10% CMT reduction at 12 months. Higher baseline BCVA (p = 0.022, OR=-0.024, 95% CI=-0.046,-0.004) and longer duration of diabetic retinopathy (p = 0.048, OR=-0.064, 95% CI=-0.129,-0.001) were negative predictors for BCVA response, whereas Aflibercept treatment (p = 0.017, OR = 1.107, 95% CI = 0.220,2.051) compared with other drugs and a positive "early functional response" (p < 0.001, OR=-1.393, 95% CI=-1.946,-0.857) were positive predictors. A higher baseline CMT (p < 0.001, OR = 0.019, 95% CI = 0.012,0.0261) and an "early anatomical response", (p < 0.001, OR=-1.677, 95% CI=-2.456, -0.943) were predictors for greater reduction in CMT. Overall, the variables could predict only 23% of BCVA and 52% of CMT response.

CONCLUSIONS

The study shows a significant proportion of DME patients do not respond to anti-VEGF therapy and identifies several clinical predictors for treatment outcomes.

TRIAL REGISTRATION

The study was approved through the Human Research Ethics Committee, University of Tasmania (approval number H0012902), and the Southern Adelaide Clinical Human Research Ethics Committee (approval number 86 - 067).

Detecting red-lesions from retinal fundus images using unique morphological features

One of the most important retinal diseases is Diabetic Retinopathy (DR) which can lead to serious damage to vision if remains untreated. Red-lesions are from important demonstrations of DR helping its identification in early stages. The detection and verification of them is helpful in the evaluation of disease severity and progression. In this paper, a novel image processing method is proposed for extracting red-lesions from fundus images. The method works based on finding and extracting the unique morphological features of red-lesions. After quality improvement of images, a pixel-based verification is performed in the proposed method to find the ones which provide a significant intensity change in a curve-like neighborhood. In order to do so, a curve is considered around each pixel and the intensity changes around the curve boundary are considered. The pixels for which it is possible to find such curves in at least two directions are considered as parts of red-lesions. The simplicity of computations, the high accuracy of results, and no need to post-processing operations are the important characteristics of the proposed method endorsing its good performance.

Neuroinflammation and neovascularization in diabetic eye diseases (DEDs): identification of potential pharmacotherapeutic targets

The goal of this review is to increase public knowledge of the etiopathogenesis of diabetic eye diseases (DEDs), such as diabetic retinopathy (DR) and ocular angiosarcoma (ASO), and the likelihood of blindness among elderly widows. A widow's life in North India, in general, is fraught with peril because of the economic and social isolation it brings, as well as the increased risk of death from heart disease, hypertension, diabetes, depression, and dementia. Neovascularization, neuroinflammation, and edema in the ocular tissue are hallmarks of the ASO, a rare form of malignant tumor. When diabetes, hypertension, and aging all contribute to increased oxidative stress, the DR can proceed to ASO. Microglia in the retina of the optic nerve head are responsible for causing inflammation, discomfort, and neurodegeneration. Those that come into contact with them will get blind as a result of this. Advanced glycation end products (AGE), vascular endothelial growth factor (VEGF), protein kinase C (PKC), poly-ADP-ribose polymerase (PARP), metalloproteinase9 (MMP9), nuclear factor kappaB (NFkB), program death ligand1 (PDL-1), factor VIII (FVIII), and von Willebrand factor (VWF) are potent agents for ocular neovascularisation (ONV), neuroinflammation and edema in the ocular tissue. AGE/VEGF, DAG/PKC, PARP/NFkB, RAS/VEGF, PDL-1/PD-1, VWF/FVIII/VEGF, and RAS/VEGF are all linked to the pathophysiology of DEDs. The interaction between ONV and ASO is mostly determined by the VWF/FVIII/VEGF and PDL-1/PD-1 axis. This study focused on retinoprotective medications that can pass the blood-retinal barrier and cure DEDs, as well as the factors that influence the etiology of neovascularization and neuroinflammation in the eye.

Classification of Retinal Diseases in Optical Coherence Tomography Images Using Artificial Intelligence and Firefly Algorithm

In recent years, the number of studies for the automatic diagnosis of biomedical diseases has increased. Many of these studies have used Deep Learning, which gives extremely good results but requires a vast amount of data and computing load. If the processor is of insufficient quality, this takes time and places an excessive load on the processor. On the other hand, Machine Learning is faster than Deep Learning and does not have a much-needed computing load, but it does not provide as high an accuracy value as Deep Learning. Therefore, our goal is to develop a hybrid system that provides a high accuracy value, while requiring a smaller computing load and less time to diagnose biomedical diseases such as the retinal diseases we chose for this study. For this purpose, first, retinal layer extraction was conducted through image preprocessing. Then, traditional feature extractors were combined with pre-trained Deep Learning feature extractors. To select the best features, we used the Firefly algorithm. In the end, multiple binary classifications were conducted instead of multiclass classification with Machine Learning classifiers. Two public datasets were used in this study. The first dataset had a mean accuracy of 0.957, and the second dataset had a mean accuracy of 0.954.

Ophthalmic imaging in diabetic retinopathy: A review

Retinal imaging has been a key tool in the diagnosis, evaluation, management and documentation of diabetic retinopathy (DR) and diabetic macular oedema (DMO) for many decades. Imaging technologies have rapidly evolved over the last few decades, yielding images with higher resolution and contrast with less time, effort and invasiveness. While many retinal imaging technologies provide detailed insight into retinal structure such as colour reflectance photography and optical coherence tomography (OCT), others such as fluorescein or OCT angiography and oximetry provide dynamic and functional information. Many other novel imaging technologies are in development and are poised to further enhance our evaluation of patients with DR.

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

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

Comparison of the efficiency of anti-VEGF drugs intravitreal injections treatment with or without retinal laser photocoagulation for macular edema secondary to retinal vein occlusion: A systematic review and meta-analysis

Objective: To compare the efficiency of anti-VEGF drugs intravitreal injections(IVI) treatment with or without retinal laser photocoagulation(LPC) for macular edema(ME) secondary to retinal vein occlusion(RVO).

Methods: The randomized controlled trials and retrospective studies including anti-VEGF drug IVI combined with retinal LPC and single IVI in the treatment of macular edema secondary to RVO were collected in PubMed, Medline, Embase, Cochrane Library, and Web of Science. We extracted the main outcome indicators including the best corrected visual acuity (BCVA), central macular thickness(CMT), the number of injections and the progress of retinal non-perfusion areas(NPAs) for systematic evaluation, to observe whether IVI + LPC could be more effective on the prognosis of RVO. We use Review Manager 5.4 statistical software to analyze the data

Results: 527 articles were initially retrieved. We included 20 studies, with a total of 1387 patients who were divided into the combination(IVI + LPC) treatment group and the single IVI group. All the patients completed the ocular examination including BCVA, slit-lamp test, fundus examination and Optical Coherence Tomography(OCT) test before and after each treatment. There was no statistical difference between the combination treatment group and single IVI group on BCVA(WMD = 0.12,95%CI = -3.54–3.78,p = 0.95),CMT(WMD = -4.40,95%CI = -21.33–12.53,p = 0.61) and NPAs(WMD = 0.01,95%CI = -0.28–0.30,p = 0.94).However, the number of IVI was decreased significantly in the combination treatment group in BRVO patients, compared to that in the single IVI group(WMD = -0.69,95%CI = -1.18∼-0.21,p = 0.005).

Conclusion: In the treatment of RVO patients with macular edema, the combination of IVI and retinal LPC neither improves BCVA nor reduces CMT significantly compared with the single IVI treatment. However, the combination treatment can decrease the number of intravitreal injections in patients with BRVO, while it is not observed in CRVO patients.

Connexin 43 (Cx43) regulates high-glucose-induced retinal endothelial cell angiogenesis and retinal neovascularization

Diabetic retinopathy (DR) is an important microvascular complication of type 1 and type 2 diabetes mellitus (DM) and a major cause of blindness. Retinal neovascularization plays a critical role in the proliferative DR. In this study, high glucose-induced connexin 43 (Cx43) expression in human retinal endothelial cells (hRECs) in a dose-dependent manner. Compared with hRECs under normal culture conditions, high-glucose (HG)-stimulated hRECs showed promoted tubule formation, increased ROS release, and elevated levels of tumor necrosis factor-alpha (TNF-α), interleukin-1β (IL-1β), vascular endothelial growth factor A (VEGFA), and intercellular adhesion molecule 1 (ICAM-1) in the culture medium. HG-induced alterations were further magnified after Cx43 overexpression, whereas partially eliminated after Cx43 knockdown. Finally, in the DR mouse model, impaired retinal structure, increased CD31 expression, and elevated mRNA levels of TNF-α, IL-1β, VEGFA, and ICAM-1 were observed; in-vivo Cx43 knockdown partially reversed these phenomena. Conclusively, Cx43 knockdown could inhibit hREC angiogenesis, therefore improving DR in the mouse model.

Sensitivity and specificity of MultiColor imaging in detecting proliferative diabetic retinopathy

PURPOSE

To evaluate the accuracy of MultiColor imaging (MC) compared to fluorescein angiography (FA) in detecting proliferative diabetic retinopathy (PDR) and associated diabetic retinopathy features.

METHODS

Fifty-nine eyes from 38 PDR patients were included. MC images were reviewed by 2 independent masked graders. A qualitative analysis based on the following features was performed: neovascular complexes (NVC), disc neovascularization (NVD), neovascularization elsewhere (NVE), microaneurysm (MA), intraretinal hemorrhage (IRH), vitreous hemorrhage (VH), preretinal hemorrhage (PRH), fibrosis, hard exudates (HE), epiretinal membrane (ERM), diabetic macular edema (DME), ischemia and laser spots (LS). Measures of diagnostic accuracy compared to FA were determined.

RESULTS

The sensitivity for the detection of NVC using MC was 95.1%, with a specificity of 40.0%, positive predictive value (PPV) of 92.9% and negative predictive value (NPV) of 50.0%. Sensitivity and specificity were higher in detecting NVD (88.9% and 76.9%) while NVE registered higher PPV (88.9%). MC was highly sensitive in detecting IRH, HE, ERM and LS (100%), MA (98.0%) and fibrosis (95.5%). Highest specificity was found for VH (100.0%), DME (100.0%), PRH (98.1%) and LS (89.5%). The area under the receiver-operating characteristic analysis of MC was excellent in NVD (0.83, 95% confidence interval (CI), 0.71-0.95, p < 0.001), IRH (0.89, 95% CI 0.74-1.00, p < 0.001), VH (0.81, 95% CI 0.60-1.00, p = 0.005) and PRH (0.89, 95% CI 0.68-1.00, p = 0.004) and outstanding in LS detection (0.95, 95% CI 0.87-1.00, p < 0.001). These results are likely due to the contrast and quality of the MC since better discrimination is enabled by the green wavelength.

CONCLUSION

MC is useful in evaluation of PDR patients and can complement noninvasive imaging. MC detected some PDR features more accurately than FA such as NVD, IRH, VH, PRH, and LS.

Update on Optical Coherence Tomography and Optical Coherence Tomography Angiography Imaging in Proliferative Diabetic Retinopathy

Proliferative diabetic retinopathy (PDR) is a major cause of blindness in diabetic individuals. Optical coherence tomography (OCT) and OCT-angiography (OCTA) are noninvasive imaging techniques useful for the diagnosis and assessment of PDR. We aim to review several recent developments using OCT and discuss their present and potential future applications in the clinical setting. An electronic database search was performed so as to include all studies assessing OCT and/or OCTA findings in PDR patients published from 1 January 2020 to 31 May 2021. Thirty studies were included, and the most recently published data essentially focused on the higher detection rate of neovascularization obtained with widefield-OCT and/or OCTA (WF-OCT/OCTA) and on the increasing quality of retinal imaging with quality levels non-inferior to widefield-fluorescein angiography (WF-FA). There were also significant developments in the study of retinal nonperfusion areas (NPAs) using these techniques and research on the impact of PDR treatment on NPAs and on vascular density. It is becoming increasingly clear that it is critical to use adequate imaging protocols focused on optimized segmentation and maximized imaged retinal area, with ongoing technological development through artificial intelligence and deep learning. These latest findings emphasize the growing applicability and role of noninvasive imaging in managing PDR with the added benefit of avoiding the repetition of invasive conventional FA.

Interactive Blood Vessel Segmentation from Retinal Fundus Image Based on Canny Edge Detector

Optometrists, ophthalmologists, orthoptists, and other trained medical professionals use fundus photography to monitor the progression of certain eye conditions or diseases. Segmentation of the vessel tree is an essential process of retinal analysis. In this paper, an interactive blood vessel segmentation from retinal fundus image based on Canny edge detection is proposed. Semi-automated segmentation of specific vessels can be done by simply moving the cursor across a particular vessel. The pre-processing stage includes the green color channel extraction, applying Contrast Limited Adaptive Histogram Equalization (CLAHE), and retinal outline removal. After that, the edge detection techniques, which are based on the Canny algorithm, will be applied. The vessels will be selected interactively on the developed graphical user interface (GUI). The program will draw out the vessel edges. After that, those vessel edges will be segmented to bring focus on its details or detect the abnormal vessel. This proposed approach is useful because different edge detection parameter settings can be applied to the same image to highlight particular vessels for analysis or presentation.

Development of a Preclinical Laser Speckle Contrast Imaging Instrument for Assessing Systemic and Retinal Vascular Function in Small Rodents

Purpose

To develop and test a non-contact, contrast-free, retinal laser speckle contrast imaging (LSCI) instrument for use in small rodents to assess vascular anatomy, quantify hemodynamics, and measure physiological changes in response to retinal vascular dysfunction over a wide field of view (FOV).

Methods

A custom LSCI instrument capable of wide-field and non-contact imaging in small rodents was constructed. The effect of camera gain, laser power, and exposure duration on speckle contrast variance was standardized before the repeatability of LSCI measurements was determined in vivo. Finally, the ability of LSCI to detect alterations in local and systemic vascular function was evaluated using a laser-induced branch retinal vein occlusion and isoflurane anesthesia model, respectively.

Results

The LSCI system generates contrast-free maps of retinal blood flow with a 50° FOV at >376 frames per second (fps) and under a short exposure duration (>50 µs) with high reliability (intraclass correlation R = 0.946). LSCI was utilized to characterize retinal vascular anatomy affected by laser injury and longitudinally measure alterations in perfusion and blood flow profile. Under varied doses of isoflurane, LSCI could assess cardiac and systemic vascular function, including heart rate, peripheral resistance, contractility, and pulse propagation.

Conclusions

We present a LSCI system for detecting anatomical and physiological changes in retinal and systemic vascular health and function in small rodents.

Translational Relevance

Detecting and quantifying early anatomical and physiological changes in vascular function in animal models of retinal, systemic, and neurodegenerative diseases could strengthen our understanding of disease progression and enable the identification of new prognostic and diagnostic biomarkers for disease management and for assessing treatment efficacies.

Diabetic retinopathy and diabetic macular oedema pathways and management: UK Consensus Working Group

The management of diabetic retinopathy (DR) has evolved considerably over the past decade, with the availability of new technologies (diagnostic and therapeutic). As such, the existing Royal College of Ophthalmologists DR Guidelines (2013) are outdated, and to the best of our knowledge are not under revision at present. Furthermore, there are no other UK guidelines covering all available treatments, and there seems to be significant variation around the UK in the management of diabetic macular oedema (DMO). This manuscript provides a summary of reviews the pathogenesis of DR and DMO, including role of vascular endothelial growth factor (VEGF) and non-VEGF cytokines, clinical grading/classification of DMO vis a vis current terminology (of centre-involving [CI-DMO], or non-centre involving [nCI-DMO], systemic risks and their management). The excellent UK DR Screening (DRS) service has continued to evolve and remains world-leading. However, challenges remain, as there are significant variations in equipment used, and reproducible standards of DMO screening nationally. The interphase between DRS and the hospital eye service can only be strengthened with further improvements. The role of modern technology including optical coherence tomography (OCT) and wide-field imaging, and working practices including virtual clinics and their potential in increasing clinic capacity and improving patient experiences and outcomes are discussed. Similarly, potential roles of home monitoring in diabetic eyes in the future are explored. The role of pharmacological (intravitreal injections [IVT] of anti-VEGFs and steroids) and laser therapies are summarised. Generally, IVT anti-VEGF are offered as first line pharmacologic therapy. As requirements of diabetic patients in particular patient groups may vary, including pregnant women, children, and persons with learning difficulties, it is important that DR management is personalised in such particular patient groups. First choice therapy needs to be individualised in these cases and may be intravitreal steroids rather than the standard choice of anti-VEGF agents. Some of these, but not all, are discussed in this document.

Diabetic retinal neurodegeneration as a form of diabetic retinopathy

PURPOSE

To review the evidence supporting diabetic retinal neurodegeneration (DRN) as a form of diabetic retinopathy.

METHOD

Review of literature.

RESULTS

DRN is recognized to be a part of retinopathy in patients with diabetes mellitus (DM), in addition to the well-established diabetic retinal vasculopathy (DRV). DRN has been noted in the early stages of DM, before the onset of clinically evident diabetic retinopathy. The occurrence of DRN has been confirmed in animal models of DM, histopathological examination of donor's eyes from diabetic individuals and assessment of neural structure and function in humans. DRN involves alterations in retinal ganglion cells, photoreceptors, amacrine cells and bipolar cells, and is thought to be driven by glutamate, oxidative stress and dysregulation of neuroprotective factors in the retina. Potential therapeutic options for DRN are under evaluation.

CONCLUSIONS

Literature is divided on the temporal relation between DRN and DRV, with evidence of both precedence and simultaneous occurrence. The relationship between DRN and multi-system neuropathy in DM is yet to be evaluated critically.

Panretinal laser photocoagulation decreases large foveal avascular zone area in non-proliferative diabetic retinopathy: A prospective OCTA study

PURPOSE

To analyze the macular microvascular changes after panretinal photocoagulation (PRP) in patients with non-proliferative diabetic retinopathy (NPDR) and a large foveal avascular zone area, using optical coherence tomography angiography.

METHODS

Twenty-four eyes of 24 patients with peripheral ischemia, superficial foveal avascular zone (FAZ) area of larger than 0.350 mm², naive severe NPDR, and no clinically significant diabetic macular edema were included in this prospective study. The PRP was applied in 360-degree in a single session. The main outcome measures of the study were the difference in best-corrected visual acuity, central macular thickness, superficial and deep vascular plexus vessel densities, FAZ features, choroidal and outer retinal flow areas at the baseline versus at one and six months after PRP treatment.

RESULTS

The study group consisted of 13 men and 11 women with a mean age of 68.11 ± 6.47 years. The baseline FAZ area was higher than at one and six months after PRP (0.416 ± 0.70, 0.399 ± 0.065 and 0.407 ± 0.066 mm²; p = 0.001 and p = 0.002, respectively). At one month after PRP, deep capillary plexus vascular density in perifoveal region was statistically significantly lower than at six months after PRP and the baseline. (45.43 ± 4.27, 47.91 ± 4.26 and 49.04 ± 5.64 %; p = 0.001 and p = 0.001, respectively).

CONCLUSION

The PRP effects retinal microvascular morphology in patients with NPDR and a large FAZ area.

Deep multispectral image registration network

Multispectral imaging (MSI) of the ocular fundus provides a sequence of narrow-band images to show the different depths in the retina and choroid. One challenge in analyzing MSI images comes from the image-to-image spatial misalignment, which occurs because the acquisition time of eye MSI images is commonly longer than the natural time scale of the eye's saccadic movement. It is necessary to align images because ophthalmologists usually overlay two of the images to analyze specific features when analyzing MSI images. In this paper, we propose a weakly supervised MSI image registration network, called MSI-R-NET, for multispectral fundus image registration. Compared to other deep-learning-based registration methods, MSI-R-NET utilizes the blood vessel segmentation label to provide spatial correspondence. In addition, we employ a feature equilibrium module to connect the aggregating layers better, and propose a multiresolution auto-context structure to adapt the registration task. In the testing stage, given a new pair of MSI images, the trained model can predict the pixelwise spatial correspondence without labeled blood vessel information. The experimental results demonstrate that the proposed segmentation-driven registration method is highly accurate.

Performance evaluation of two fundus oculi angiographic imaging system: Optos 200Tx and Heidelberg Spectralis

The present study aimed to compare the imaging performance of two ultra-wide-field fluorescein angiography imaging systems, namely the OptosOptomap 200Tx (Optos 200Tx) and the Heidelberg Spectralis (Spectralis). A total of 18 patients (36 eyes) underwent angiography using the two systems at the Department of Ophthalmology, Beijing Friendship Hospital (Beijing, China) between January and June 2017. The images were obtained as a single shot centered on the macula. The total area and area within each of four visualized quadrants were calculated and compared. The averages of the total and individual quadrant area captured by the Optos 200Tx were all larger than those obtained with the Spectralis (P<0.05). For pair-wise comparison, the circular area centered on the macula (radius of 10 and 15 mm) was displayed: Optos 200Tx 10 mm (295.57 mm²) < Spectralis (520.11 mm²) < Optos 200Tx 15 mm (596.45 mm²) < Optos 200Tx (804.36 mm²) (P<0.01). The differences of each of the four quadrant areas were statistically significant between the two systems (P<0.05). The mean size of the areas was in the following order: Inferior < temporal < superior < nasal for the Optos 200Tx, and inferior < temporal < nasal < superior for the Spectralis. Further comparison of the four-quadrant area indicated that the inferior quadrant of the Optos 200Tx was smaller than the other three quadrants (P<0.01) and the inferior quadrant of the Spectralis was smaller than the superior quadrant (P<0.01). The total retinal area and the retinal area of each quadrant captured by the Optos 200Tx were larger than those captured with the Spectralis. The total retinal area captured with the Optos 200Tx was able to cover the mid-peripheral area and part of the far-peripheral area of the retina, whereas the Spectralis only covered the mid-peripheral area.

Optical coherence tomography features of neovascularization in proliferative diabetic retinopathy: a systematic review

Background

Diabetic retinopathy (DR) is a leading cause of blindness due to diabetic macular edema (DME) or complications of proliferative diabetic retinopathy (PDR). Optical coherence tomography (OCT) is a noninvasive imaging technique well established for DME but less used to assess neovascularization in PDR. Developments in OCT imaging and the introduction of OCT angiography (OCTA) have shown significant potential in PDR.

Objectives

To describe the tomographic features of PDR, namely of neovascularization, both of the optic disc (NVD) and elsewhere (NVE), intraretinal microvascular abnormalities (IRMA), retinal nonperfusion areas (NPA), status of the posterior vitreous, vitreoschisis and vitreous and subhyaloid/sub-ILM hemorrhages.

Data sources

Electronic database search on PubMed and EMBASE, last run on December 19th 2019.

Study eligibility criteria, participants and interventions

Publications assessing OCT and/or OCTA findings in PDR patients. All study designs were allowed except for case-reports, conference proceedings and letters.

Study appraisal

Newcastle–Ottawa Scale for observational studies was used for purposes of risk of bias assessment.

Results

From the 1300 studies identified, 283 proceeded to full-text assessment and 60 were included in this comprehensive review. OCT was useful in detecting NVD and NVE, such as in characterizing disease activity and response to laser and/or anti-VEGF therapies. The absence of posterior vitreous detachment seemed determinant for neovascular growth, with the posterior hyaloid acting as a scaffold. OCTA allowed a more detailed characterization of the neovascular complexes, associated NPA and disease activity, allowing the quantification of neovessel area and flow index. However, changes in OCTA blood flow signal following local therapies did not necessarily correlate with structural regression. Widefield and ultra-widefield OCTA were highly sensitive in the detection of PDR, adding value to disease staging and monitoring. Compared to fluorescein angiography, OCTA was more sensitive in detecting microvascular changes indicating disease progression.

Limitations

Publication languages were restricted. Most included studies were observational and non-comparative. Risk of bias regarding case representativeness.

Conclusions

OCT-based retinal imaging technologies are advancing rapidly and the trend is to be noninvasive and wide-field. OCT has proven invaluable in diagnosing, staging and management of proliferative diabetic disease with daily application in clinical and surgical practices.

VASCULAR ABNORMALITIES IN DIABETIC RETINOPATHY ASSESSED WITH SWEPT-SOURCE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY WIDEFIELD IMAGING

PURPOSE

To detect vascular abnormalities in diabetic retinopathy using swept-source optical coherence tomography angiography (SS-OCTA) widefield images, and to compare the findings with color fundus photographs (CFPs) using Early Treatment Diabetic Retinopathy Study severity grading.

METHODS

3 mm × 3 mm and 12 mm × 12 mm scans were acquired to cover 70° to 80° of the posterior pole using a 100-kHz SS-OCTA instrument. Two masked graders assessed the presence of vascular abnormalities on SS-OCTA and the Early Treatment Diabetic Retinopathy Study level on CFP. The grading results were then compared.

RESULTS

A total of 120 diabetic eyes (60 patients) were imaged with the SS-OCTA instrument. Cohort 1 (91 eyes; SS-OCTA grading only) showed microaneurysms in 91% (n = 83), intraretinal microvascular abnormalities in 79% (n = 72), and neovascularization in 21% (n = 19) of cases. Cohort 2 (52 eyes; CFP grading compared with SS-OCTA) showed microaneurysms on CFP in 90% (n = 47) and on SS-OCTA in 96% (n = 50) of cases. Agreement in intraretinal microvascular abnormality detection was fair (k = 0.2). Swept-source optical coherence tomography angiography detected 50% of intraretinal microvascular abnormality cases (n = 26), which were missed on CFP. Agreement in detecting neovascularization was moderate (k = 0.5).

CONCLUSION

Agreement in detection of diabetic retinopathy features on CFP and SS-OCTA varies depending on the vascular changes examined. Swept-source optical coherence tomography angiography shows a higher detection rate of intraretinal microvascular abnormalities (P = 0.039), compared with Early Treatment Diabetic Retinopathy Study grading.

Depthwise Separable Convolutional Neural Network Model for Intra-Retinal Cyst Segmentation

Intra-retinal cysts (IRCs) are significant in detecting several ocular and retinal pathologies. Segmentation and quantification of IRCs from optical coherence tomography (OCT) scans is a challenging task due to present of speckle noise and scan intensity variations across the vendors. This work proposes a convolutional neural network (CNN) model with an encoder-decoder pair architecture for IRC segmentation across different cross-vendor OCT scans. Since deep CNN models have high computational complexity due to a large number of parameters, the proposed method of depthwise separable convolutional filters aids model generalizability and prevents model over-fitting. Also, the swish activation function is employed to prevent the vanishing gradient problem. The optima cyst segmentation challenge (OCSC) dataset with four different vendor OCT device scans is used to evaluate the proposed model. Our model achieves a mean Dice score of 0.74 and mean recall/precision rate of 0.72/0.82 across different imaging vendors and it outperforms existing algorithms on the OCSC dataset.

Wide-field angiography in retinal vein occlusions

BACKGROUND

Retinal vein occlusion (RVO) is the second most common retinal vascular disease after diabetic retinopathy. It can result in significant visual loss from complications like macula edema, retinal and iris neovascularization, and vitreous hemorrhage. Recently, ultra-widefield imaging (UWF) has been developed for posterior pole visualization and has shown to be useful in the evaluation and treatment of RVO.

MAIN TEXT

Ultra-widefield imaging (UWF) imaging allows for visualization of the retina up to an angle of 200°. This is especially important in detecting peripheral retinal pathologies, especially in retinal conditions such as RVO, where the disease process affects the peripheral as well as central retina. In particular, retinal non-perfusion in RVO is a risk factor for neovascularization. Various techniques, such as ischemic index and stereographic projection, have been described to assess areas of ischemia on UWF images. Retinal non-perfusion has an impact on disease complications, such as macular edema, and retinal and iris neovascularization. Retinal non-perfusion also has implications on disease response, including visual acuity, reduction in retinal edema and treatment burden.

CONCLUSION

Ultra-widefield imaging (UWF) imaging plays an important role in the assessment and management of RVO, especially in measuring retinal non-perfusion in the peripheries.

The Relationship Between Macular Cyst Formation and Ischemia in Diabetic Macular Edema

Objectives:

To evaluate the relationship between cyst characteristics and macular and peripheral ischemia in diabetic macular edema (DME).

Materials and Methods:

We retrospectively reviewed eyes with DME and included those with clinically significant macular edema as defined by ETDRS (Early Treatment Diabetic Retinopathy Study) and cystoid spaces in optical coherence tomography scans in this study. Central subfield thickness (CSFT), horizontal and vertical diameters of the largest cyst, cyst area, and the remaining retinal thickness outside the cyst were determined. The presence and number of hyperreflective foci in the cyst wall and the internal reflectivity of the cyst were analyzed. Outer retinal damage was graded. Fluorescein angiography was used to determine the areas of macular and peripheral ischemia, which were graded as mild or severe. Correlations between macular and peripheral ischemia and cyst-related measurements and structural changes in the retina were evaluated.

Results:

This retrospective study included 250 eyes of 186 patients with DME. Mean CSFT was significantly greater in eyes with macular ischemia (510.4±144.7 μm) compared to eyes without macular ischemia (452.1±114.6 μm) (p=0.001). Horizontal and vertical diameter of the largest cyst increased with the presence and severity of macular ischemia (p=0.045 and p=0.016, respectively). Remaining retinal thickness increased with the presence and severity of peripheral ischemia (p=0.009). There was a statistically significant relationship between the number of the hyperreflective foci in the cyst wall and internal reflectivity of the cyst (p=0.007). Patients with greater CSFT had a 1.04-times higher odds of having macular ischemia and 0.25-times higher odds of having outer retinal damage.

Conclusion:

The likelihood of macular ischemia increases with larger cyst diameter, CSFT, and extent of outer retinal damage. Thickness of the noncystic area is increased in the presence of peripheral ischemia.

Comparison of Subjective Assessment and Precise Quantitative Assessment of Lesion Distribution in Diabetic Retinopathy

Importance

Predominantly peripheral disease in eyes with nonproliferative diabetic retinopathy (DR) is suggested as a potential strong risk factor for progression to proliferative disease. However, the reliability and optimal method for the assessment of lesion distribution are still uncertain.

Objective

To compare agreement between subjective assessment and precise quantification of lesion burden in ultrawidefield (UWF) images of eyes with DR.

Design, Setting, and Participants

This multisite cross-sectional study examines UWF pseudocolor images acquired from DR screening clinic patients from December 20, 2014, through August 1, 2014. Of 104 cases, 161 eyes with DR were included. Data analysis was conducted from June 1, 2016, through December 1, 2016 at the Doheny Image Reading Center.

Main Outcomes and Measures

Distribution of DR lesions in eyes was assessed subjectively and quantitatively, and eyes were classified as having predominantly central lesions (PCLs) or predominantly peripheral lesions (PPLs). The frequency and surface area (SA) of each lesion type were quantified. Intergrader and subjective vs quantitative classification were compared for level of agreement. Several methods of determining PPL distribution were also compared.

Results

On subjective frequency-based evaluation by graders, 133 eyes were classified as having PCL, and 28 eyes as having PPL. On exact quantification of lesion SA, 121 eyes were classified as PCL, and 40 eyes as having PPL. On SA-based quantification, 134 eyes were classified as having PCL, and 27 eyes as having PPL. There was a significant difference between qualitative and quantitative classification of DR lesion distribution for both frequency-based (mean difference [SD]: PCL, 6 [2]; PPL, 13 [6]; P < .001) and SA-based (mean difference [SD]: PCL, 6 [1]; PPL, 20 [7]; P < .001) methods. Both intergrader reproducibility and subjective vs quantitative agreement were higher with frequency-based classification.

Conclusions and Relevance

Subjective assessment of PPL DR lesions on UWF images differed in some cases from precise quantitative assessments, particularly when considering the area of lesions. These findings highlight the benefit of objective quantitative approaches to DR assessment, which may facilitate the development of a more precise DR scoring system.

Comparison of ranibizumab alone versus ranibizumab with targeted retinal laser for branch retinal vein occlusion with macular edema

Purpose:

To determine the effect of ultra-widefield fluorescein angiography (UWFFA)-guided targeted retinal photocoagulation (TRP) in branch retinal vein occlusion (BRVO) with macular edema after intravitreal Ranibizumab (RBZ).

Methods:

33 eyes of 32 treatment naïve patients diagnosed as BRVO with macular edema were prospectively randomized to 0.5 mg Ranibizumab only (RBZ group) (n = 17) or Ranibizumab with UWFFA-guided laser (RBZ + TRP group) (n = 16). Both groups received three injections at monthly intervals and PRN henceforth. RBZ + TRP group additionally underwent UWFFA-guided TRP of peripheral capillary nonperfusion areas 1 week post injection. Outcome measures included improvement in visual acuity, central subfoveal thickness (CST), and the number of injections required with a minimum follow-up of 9 months.

Results:

Both groups showed significant improvement in mean BCVA (25.7 ± 8.19 letters, P < 0.001 vs. 23.38 ± 7.56 letters, P < 0.001; in RBZ and RBZ + TRP group, respectively) and reduction in mean central subfoveal thickness (379.12 ± 242.7 μm, P < 0.001 vs. 253.75 ± 137.9 μm, P < 0.001 in RBZ and RBZ + TRP group, respectively) at 9 months. The number of injections in the RBZ group (5.76 ± 1.3) was significantly greater than RBZ + TRP (4.06 ± 0.99) (P < 0.001). Both groups had significant improvement in contrast sensitivity and mean deviation on visual fields; however, the difference between the groups was not significant (P = 0.62 and P = 0.79, respectively).

Conclusion:

UWFFA-guided TRP reduced the number of injections of Ranibizumab in patients having BRVO with macular edema, while maintaining similar benefits in the improvement of BCVA, central subfoveal thickness without deleterious effect on the visual field, and contrast sensitivity.

Quantitative Ultra-Widefield Angiographic Features and Associations with Diabetic Macular Edema

PURPOSE

To examine the relationship between diabetic macular edema (DME) and quantitative ultra-widefield fluorescein angiography (UWFA) metrics of ischemia, leakage, and microaneurysms.

DESIGN

Retrospective image analysis study.

PARTICIPANTS

Eyes with diabetic retinopathy that had undergone spectral-domain OCT, UWFA, and ultra-widefield fundus photography.

METHODS

OCT images were analyzed to determine the presence or absence of DME, central subfield thickness (CST), and subretinal fluid. Using a semiautomated analysis platform, UWFA images were segmented for ischemia, leakage, and microaneurysms with manual correction as needed. Clinical variables, including age, gender, race, hemoglobin A1C levels, blood pressure, cholesterol levels, use of blood thinners, smoking status, and lens status also were evaluated.

MAIN OUTCOME MEASURES

Factors associated with the presence and severity of DME.

RESULTS

A total of 304 eyes (156 right eyes, 148 left eyes) from 178 diabetic patients were analyzed in the study. Panretinal leakage index, microaneurysm count, and ischemic index were not significantly different between eyes with and without DME in univariate assessment. Zonal assessments of macular microaneurysms and macular leakage index values revealed that eyes with DME showed a significantly higher microaneurysm count (P = 0.001) and leakage index (P < 0.0001) in the posterior pole compared with eyes without DME. Severity of macular thickening (i.e., CST) was associated significantly with macular leakage index and posterior pole microaneurysm count (P = 0.0002 and P = 0.03, respectively). In addition to posterior pole leakage index and microaneurysm count, DME was associated with older age (P < 0.01), higher systolic blood pressure (P < 0.001), and white race (P = 0.03). Multivariate assessment confirmed the independent association of presence of DME with macular leakage index and macular microaneurysm count (P < 0.01).

CONCLUSIONS

Quantitative measures of leakage index and microaneurysm count in the posterior pole on UWFA images were associated with the presence and severity of DME. Panretinal analyses were not linked to DME as strongly. Additional research is needed to determine the role of quantitative UWFA in predicting DME development and characterizing patient prognosis.

Multimodal imaging of diabetic retinopathy

PURPOSE OF REVIEW

Diabetic retinopathy is the most common microvascular complication of diabetes mellitus and a leading cause of blindness throughout the world. Ocular imaging continues to play a vital role in the diagnosis, management and monitoring of diabetic retinopathy. Major technological advancements in imaging over the past decade have improved our understanding and knowledge of diabetic retinopathy and therefore a multimodal approach to imaging has become the standard of care.

RECENT FINDINGS

Updates to traditional technologies such as digital fundus photography along with recent advancements in optical coherence tomography (OCT) and OCT angiography (OCTA) have provided clinicians with new information and improved efficiency.

SUMMARY

In this review, we describe the benefits and clinical applications of several imaging techniques in diabetic retinopathy including color photography, fluorescein angiography, OCT, OCTA and adaptive optics. Understanding the indications and limitations of each technology allows clinicians to gain the most information from each modality and thereby optimize patient care.

Telemedicine for diabetic retinopathy screening using an ultra-widefield fundus camera

OBJECTIVE

Telemedicine reporting of diabetic retinopathy (DR) screening using ultra-widefield (UWF) fundus camera.

MATERIALS AND METHODS

Cross-sectional study of diabetic patients who visited the endocrinology department of a private multi-specialty hospital in United Arab Emirates between April 2015 and January 2017 who underwent UWF fundus imaging. Fundus pictures are then accessed at the Retina Clinic in the Department of Ophthalmology. Primary outcome measure was incidence of any form of DR detected. The secondary outcome measure was failure to take good image and inability to grade.

RESULTS

A total of 1,024 diabetic individuals were screened for DR from April 2015 to January 2017 in the department of Endocrinology. Rate of DR was 9.27%; 165 eyes of 95 individuals were diagnosed to have some form of DR. Mild non-proliferative DR (NPDR) was seen in 114 of 165 eyes (69.09%), moderate NPDR in 32 eyes (19.39%), severe NPDR in six eyes (3.64%), and proliferative DR (PDR) in 13 eyes (7.88%). The secondary outcome measure of poor image acquisition was seen in one individual who had an image acquired in one eye that could not be graded due to bad picture quality.

CONCLUSIONS

The present study has shown the effectiveness of DR screening using UWF fundus camera. It has shown the effectiveness of trained nursing personnel taking fundus images. This model can be replicated in any private multi-specialty hospital and reduce the burden of DR screening in the retina clinic and enhance early detection of treatable DR.

Effects of Silymarin on Diabetes Mellitus Complications: A Review

Diabetes mellitus is a common metabolic disorder that is caused by a deficit in the production of (type 1) or response to (type 2) insulin. Diabetes mellitus is characterized by a state of chronic hyperglycemia and such symptoms as weight loss, thirst, polyuria, and blurred vision. These disturbances represent one of the major causes of morbidity and mortality nowadays, despite available treatments, such as insulin, insulin secretagogues, insulin sensitizers, and oral hypoglycemic agents. However, many efforts have been made to discover new drugs for diabetes treatment, including medicinal plant extracts. Silymarin is a powder extract of the seeds from Silybum marianum, a plant from the Asteraceae family. The major active ingredients include four isomers: silybin, isosilybin, silychristin, and silydianin. Silymarin is indicated for the treatment of hepatic disorders, such as cirrhosis, chronic hepatitis, and gallstones. Moreover, several studies of other pathologies, including diabetes, sepsis, osteoporosis, arthritis, hypercholesterolemia, cancer, viral infections, and Alzheimer's and Parkinson's diseases, have tested the effects of silymarin and reported promising results. This article reviews data from clinical, in vivo, and in vitro studies on the use of silymarin, with a focus on the complications of diabetes, including nephropathy, neuropathy, healing delays, oxidative stress, hepatotoxicity, and cardiomyopathy. Copyright © 2017 John Wiley & Sons, Ltd.