Genome-wide association study of neovascular age-related macular degeneration in the Thai population.

We performed a genome-wide association study on 377 cases of neovascular age-related macular degeneration (AMD) and 1074 controls to determine the association of previously reported genetic variants associated with neovascular AMD in the Thai population. All patients were of Thai ancestry. We confirmed the association of age-related maculopathy susceptibility 2 (ARMS2) rs10490924 (P=7.38 × 10-17), HTRA1 rs11200638 (P=5.47 × 10-17) and complement factor H gene (CFH) rs800292 (P=2.53 × 10-8) with neovascular AMD, all loci passing the genome-wide significance level (P<5.22 × 10-8). We also found association of the previously reported CFH rs10737680 (P=1.76 × 10-6) locus in the discovery sample. Two loci not previously reported to be associated with neovascular AMD were selected for replication in 222 cases and 623 controls. The loci included LINCO1317 rs6733379 and rs2384550 on chromosome 12. LINCO1317 rs6733379 (P=3.85 × 10-2) remained significantly associated with neovascular AMD after replication. In conclusion, we confirm that ARMS2, HTRA1 and CFH variants are associated with neovascular AMD in the Thai population. Findings from this study also suggest that variants contributing to the susceptibility of neovascular AMD in the Thai population are mostly similar to other Asians with additional local genetic risks that may specifically be identified in Thai population.

Recent approaches to evaluating and monitoring geographic atrophy.

PURPOSE OF REVIEW: Given the increasing prevalence of geographic atrophy from age-related macular degeneration as the number of individuals over 85 increases throughout the world, as well as the recent increase in potential treatments to slow growth of geographic atrophy, this article discusses recent findings regarding retinal imaging of geographic atrophy to detect its presence or expansion over time. RECENT FINDINGS: During the review period, the COMPLETE (Systemic complement inhibition with eculizumab for geographic atrophy in age-related macular degeneration) and the GATE (Randomized trial to evaluate tandospirone in geographic atrophy secondary to age-related macular degeneration) studies, respectively, reported no beneficial effects of intravenous eculizumab or tandospirone eye drops, respectively, identified on the growth of geographic atrophy. Several imaging and visual function studies have evaluated the role of various techniques using fundus autofluorescence, optical coherence tomography, microperimetry, or other investigator-initiated tools to assess geographic atrophy growth or progression over time, although the ideal imaging for geographic atrophy remains unknown. Some predictive factors for geographic atrophy growth recently suggested include genetic features, geographic atrophy characteristics in the fellow eye, or the presence of outer retinal tubulation on optical coherence tomography. SUMMARY: Quantification of geographic atrophy is important for evaluating growth of geographic atrophy. Numerous new imaging techniques of geographic atrophy beyond human grading of fundus photographs or fluorescein angiograms have emerged, but the ideal imaging for geographic atrophy has yet to be determined.

Patient, family member, and health care provider perspective on barriers and facilitators to diabetic retinopathy screening in Thailand: A qualitative study.

OBJECTIVES: Diabetic retinopathy (DR) can cause significant visual impairment which can be largely avoided by early detection through proper screening and treatment. People with DR face a number of challenges from early detection to treatment. The aim of this study was to investigate factors that influence DR screening in Thailand and to identify barriers to follow-up compliance from patient, family member, and health care provider (HCP) perspectives. METHODS: A total of 15 focus group discussions (FGDs) were held, each with five to twelve participants. There were three distinct stakeholders: diabetic patients (n = 47) presenting to a diabetic retinopathy clinic in Thailand, their family members (n = 41), and health care providers (n = 34). All focus group conversations were transcribed verbatim. Thematic analysis was used to examine textual material. RESULTS: Different themes emerged from the FGD on knowledge about diabetes, self-care behaviors of diabetes mellitus (DM), awareness about DR, barriers to DR screening, and the suggested solutions to address those barriers. Data showed lower knowledge and awareness about diabetes and DR in both patients and family members. Long waiting times, financial issues, and lack of a person to accompany appointments were identified as the major deterrents for attending DR screening. Family support for patients was found to vary widely, with some patients reporting to have received adequate support while others reported having received minimal support. Even though insurance covered the cost of attending diabetes/DR screening program, some patients did not show up for their appointments. CONCLUSION: Patients need to be well-informed about the asymptomatic nature of diabetes and DR. Communication at the patient level and shared decision-making with HCPs are essential. Family members and non-physician clinicians (such as diabetes nurses, diabetes educators, physician assistants) who work in the field of diabetes play a vital role in encouraging patients to attend diabetes and DR follow-ups visits regularly.

The Classification of Common Macular Diseases Using Deep Learning on Optical Coherence Tomography Images with and without Prior Automated Segmentation.

We compared the performance of deep learning (DL) in the classification of optical coherence tomography (OCT) images of macular diseases between automated classification alone and in combination with automated segmentation. OCT images were collected from patients with neovascular age-related macular degeneration, polypoidal choroidal vasculopathy, diabetic macular edema, retinal vein occlusion, cystoid macular edema in Irvine-Gass syndrome, and other macular diseases, along with the normal fellow eyes. A total of 14,327 OCT images were used to train DL models. Three experiments were conducted: classification alone (CA), use of automated segmentation of the OCT images by RelayNet, and the graph-cut technique before the classification (combination method 1 (CM1) and 2 (CM2), respectively). For validation of classification of the macular diseases, the sensitivity, specificity, and accuracy of CA were found at 62.55%, 95.16%, and 93.14%, respectively, whereas the sensitivity, specificity, and accuracy of CM1 were found at 72.90%, 96.20%, and 93.92%, respectively, and of CM2 at 71.36%, 96.42%, and 94.80%, respectively. The accuracy of CM2 was statistically higher than that of CA (p = 0.05878). All three methods achieved AUC at 97%. Applying DL for segmentation of OCT images prior to classification of the images by another DL model may improve the performance of the classification.

Capacity building in screening and treatment of diabetic retinopathy in Asia-Pacific region.

The focus of capacity building for screening and treatment of diabetic retinopathy (DR) is on health professionals who are nonophthalmologists. Both physicians and nonphysicians are recruited for screening DR. Although there is no standardization of the course syllabus for the capacity building, it is generally accepted to keep their sensitivity >80%, specificity >95%, and clinical failure rate <5% for the nonophthalmologists, if possible. A systematic literature search was performed using the PubMed database and the following search terms: diabetic retinopathy, diabetic retinopathy screening, Asia, diabetic retinopathy treatment, age-related macular degeneration, capacity building, deep learning, artificial intelligence (AI), nurse-led clinic, and intravitreal injection (IVI). AI may be a tool for improving their capacity. Capacity building on IVIs of antivascular endothelial growth factors for DR is focused on nurses. There is evidence that, after a supervision of an average of 100 initial injections, the trained nurses can do the injections effectively and safely, the rate of endophthalmitis ranges from 0.03 to 0.07%, comparable to ophthalmologists. However, laws and regulations, which are different among countries, are challenges and barriers for nonophthalmologists, particularly for nonphysicians, for both screening and treatment of DR. Even if nonphysicians or physicians who are nonophthalmologists are legally approved for these tasks, sustainability of the capacity is another important challenge, this may be achieved if the capacity building can be part of their career development. Patient acceptability is another important barrier for initiating care provided by nonophthalmologists, particularly in Asia. There are also collaborations between national eye institutes of high-income countries, nongovernment organizations, and local eye institutes to improve both the quality and quantity of ophthalmologists and retinal specialists in low-income countries in Asia. This approach may require more labor, cost, and time consuming than training nonophthalmologists.

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning.

Center-involved diabetic macular edema (ci-DME) is a major cause of vision loss. Although the gold standard for diagnosis involves 3D imaging, 2D imaging by fundus photography is usually used in screening settings, resulting in high false-positive and false-negative calls. To address this, we train a deep learning model to predict ci-DME from fundus photographs, with an ROC-AUC of 0.89 (95% CI: 0.87-0.91), corresponding to 85% sensitivity at 80% specificity. In comparison, retinal specialists have similar sensitivities (82-85%), but only half the specificity (45-50%, p < 0.001). Our model can also detect the presence of intraretinal fluid (AUC: 0.81; 95% CI: 0.81-0.86) and subretinal fluid (AUC 0.88; 95% CI: 0.85-0.91). Using deep learning to make predictions via simple 2D images without sophisticated 3D-imaging equipment and with better than specialist performance, has broad relevance to many other applications in medical imaging.

Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program.

Deep learning algorithms have been used to detect diabetic retinopathy (DR) with specialist-level accuracy. This study aims to validate one such algorithm on a large-scale clinical population, and compare the algorithm performance with that of human graders. A total of 25,326 gradable retinal images of patients with diabetes from the community-based, nationwide screening program of DR in Thailand were analyzed for DR severity and referable diabetic macular edema (DME). Grades adjudicated by a panel of international retinal specialists served as the reference standard. Relative to human graders, for detecting referable DR (moderate NPDR or worse), the deep learning algorithm had significantly higher sensitivity (0.97 vs. 0.74, p < 0.001), and a slightly lower specificity (0.96 vs. 0.98, p < 0.001). Higher sensitivity of the algorithm was also observed for each of the categories of severe or worse NPDR, PDR, and DME (p < 0.001 for all comparisons). The quadratic-weighted kappa for determination of DR severity levels by the algorithm and human graders was 0.85 and 0.78 respectively (p < 0.001 for the difference). Across different severity levels of DR for determining referable disease, deep learning significantly reduced the false negative rate (by 23%) at the cost of slightly higher false positive rates (2%). Deep learning algorithms may serve as a valuable tool for DR screening.

Erratum: Author Correction: Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program.

[This corrects the article DOI: 10.1038/s41746-019-0099-8.].

Vision Preference Value Scale and Patient Preferences in Choosing Therapy for Symptomatic Vitreomacular Interface Abnormality.

Importance: While symptomatic vitreomacular interface abnormalities (VIAs) are common, assessment of vision preference values and treatment preferences of these may guide treatment recommendations by physicians and influence third-party payers. Objective: To determine preference values that individuals with VIA assign to their visual state and preferences of potential treatments. Design, Setting, and Participants: In this cross-sectional one-time questionnaire study conducted between December 2015 and January 2017, 213 patients from tertiary care referral centers in Thailand, the United Kingdom, and the United States were studied. Patients with symptomatic VIA diagnosed within 1 year of data collection, visual acuity less than 20/20 OU, and symptoms ascribed to VIAs were included. Data were analyzed from January 2017 to November 2017. Main Outcomes and Measures: The primary end points were overall mean preference value that individuals with VIA assigned to their visual state and patients' preferences for potential treatments. Preference values were graded on a scale from 0 to 1, with 0 indicating death and 1 indicating perfect health with perfect vision. Results: Of the 213 included patients, 139 (65.3%) were women, and the mean (SD) age was 65.6 (7.7) years. Diagnoses included epiretinal membrane (n = 100 [46.9%]), macular hole (n = 99 [46.5%]), and vitreomacular traction (n = 14 [6.6%]). The mean (SD) vision preference value was 0.76 (0.15), without differences identified among the 3 VIA types. More participants were enthusiastic about vitrectomy (150 [71.1%]) compared with intravitreal injection (120 [56.9%]) (difference, 14.2%; 95% CI, 5.16-23.3; P = .002). Adjusted analyses showed enthusiasm for vitrectomy was associated with fellow eye visual acuity (odds ratio, 10.99; 95% CI, 2.01-59.97; P = .006) and better-seeing eye visual acuity (odds ratio, 0.03; 95% CI, 0.001-0.66; P = .03). Overall enthusiasm for treatment was associated with fellow eye visual acuity (odds ratio, 7.22; 95% CI, 1.29-40.40; P = .02). Overall, most participants (171 [81.0%]) were enthusiastic about surgery, injection, or both. Conclusions and Relevance: Study participants reported similar preference values among 3 types of VIAs. The data suggest that most patients with these conditions would be enthusiastic about undergoing vitrectomy or an injection to treat it, likely because of the condition's effect on visual functioning, although there may be a slight preference for vitrectomy at this time.

Evaluation of Macular Vascular Abnormalities Identified by Optical Coherence Tomography Angiography in Sickle Cell Disease.

PURPOSE: To evaluate macular vascular flow abnormalities identified by optical coherence tomography angiography (OCT-A) in patients with various sickle cell genotypes. DESIGN: Prospective, observational case series. METHODS: This is a single-institution case series of adult patients with various sickle cell genotypes. All patients underwent macular OCT-A (Avanti RTVue XR). Images were analyzed qualitatively for areas of flow loss and quantitatively for measures of foveal avascular area, parafoveal flow, and vascular density. The findings were compared by sickle cell genotype and retinopathy stage and correlated to retinal thickness and visual acuity. RESULTS: OCT-A scans of 82 eyes from 46 patients (60.9% female, mean age 33.5 years) were included. Sickle cell genotypes included 27 patients with hemoglobin SS (58.7%), 14 SC (30.4%), 4 beta-thalassemia (8.7%), and 1 sickle trait (2.2%). Discrete areas of flow loss were noted in 37.8% (31/82) of eyes overall and were common in both SS (40.0%, 20/50 eyes) and SC (41.7%, 10/24 eyes). Flow loss was more extensive in the temporal and nasal parafoveal subfields of the deep plexus with sickle SC or proliferative retinopathy. Retinal thickness measurements correlated with vascular density of the fovea, parafovea, and temporal and superior subfields. Visual acuity correlated with foveal avascular zone area and parafoveal vascular density in the superficial and deep plexi. CONCLUSIONS: Areas of abnormal macular vascular flow are common in patients with various sickle cell genotypes. These areas may be seen at any retinopathy stage but may be more extensive with sickle SC or proliferative retinopathy.

RECURRENCE OF VITELLIFORM LESIONS ASSOCIATED WITH TEMPORARY VISION LOSS IN BEST VITELLIFORM MACULAR DYSTROPHY.

PURPOSE: To describe visual acuity changes associated with several cycles of accumulation, disappearance, and reaccumulation of vitelliform material in Best disease, with fundus photographs, fluorescein angiograms, and optical coherence tomography images documenting these stages. METHODS: Case report with 70 months of follow-up using fundus photography, fluorescein angiography, and optical coherence tomography to image the retina. A non-Hispanic white 33-year-old man with Best disease (positive for a mutation in the BEST1 gene, namely p.Tyr167Cys:c.500A>G). RESULTS: The patient had a history of choroidal neovascularization (CNV) followed by scarring of the macula with sustained vision loss of ∼20/250 in the left eye when he was in his twenties. He subsequently presented in his thirties with acute vision loss in the right eye 3 times during a 70-month follow-up period. Each episode of vision loss in the right eye was preceded by several months of reaccumulation of vitelliform material in the macula apparent on fundus photographs, fluorescein angiograms, and optical coherence tomography, but no evidence of CNV on presentation. Each of the three episodes of vision loss in the right eye was followed by spontaneous gradual improvement in visual acuity over the next several months, correlating with decreasing amounts of the vitelliform material on clinical examination and fundus photographs. After the third documented recovery of visual acuity, at a time of stable vision, the patient developed CNV in the right eye, treated with intravitreal ranibizumab. CONCLUSION: This case demonstrates that vitelliform material can reaccumulate and resorb several times in Best disease, with temporary visual acuity decline after each episode of vitelliform material accumulation. There is a need for continued vigilance for the development of CNV in patients presenting with acute vision loss, although this patient developed CNV at a time of stable vision.

Comparison of Prevalence of Diabetic Macular Edema Based on Monocular Fundus Photography vs Optical Coherence Tomography.

IMPORTANCE: Diagnosing diabetic macular edema (DME) from monocular fundus photography vs optical coherence tomography (OCT) central subfield thickness (CST) can yield different prevalence rates for DME. Epidemiologic studies and telemedicine screening typically use monocular fundus photography, while treatment of DME uses OCT CST. OBJECTIVE: To compare DME prevalence from monocular fundus photography and OCT. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cross-sectional study of DME grading based on monocular fundus photographs and OCT images obtained from patients with diabetic retinopathy at a single visit between July 1, 2011, and June 30, 2014, at a university-based practice and analyzed between July 30, 2014, and May 29, 2015. Presence of DME, including clinically significant macular edema (CSME), on monocular fundus photographs used definitions from the Multi-Ethnic Study of Atherosclerosis (MESA) and the National Health and Nutrition Examination Survey (NHANES). Presence of DME on OCT used Diabetic Retinopathy Clinical Research Network eligibility criteria thresholds of CST for trials evaluating anti-vascular endothelial growth factor treatments. MAIN OUTCOMES AND MEASURES: Prevalence of DME based on monocular fundus photographs or OCT. RESULTS: A total of 246 eyes of 158 participants (mean [SD] age, 65.0 [11.9] years; 48.7% women; 60.8% white) were included. Among the 246 eyes, the prevalences of DME (61.4%) and CSME (48.5%) based on MESA definitions for monocular fundus photographs were greater than the DME prevalence based on OCT (21.1%) by 40.2% (95% CI, 32.8%-47.7%; P < .001) and 27.2% (95% CI, 19.2%-35.3%; P < .001), respectively. Using NHANES definitions, DME and CSME prevalences from monocular fundus photographs (28.5% and 21.0%, respectively) approximated the DME prevalence from OCT (21.1%). However, among eyes without DME on OCT, 58.2% (95% CI, 51.0%-65.3%) and 18.0% (95% CI, 12.9%-24.2%) were diagnosed as having DME on monocular fundus photographs using MESA and NHANES definitions, respectively, including 47.0% (95% CI, 39.7%-54.5%) and 10.3% (95% CI, 6.3%-15.7%), respectively, with CSME. Among eyes with DME on OCT, 26.9% (95% CI, 15.6%-41.0%) and 32.7% (95% CI, 20.3%-47.1%) were not diagnosed as having either DME or CSME on monocular fundus photographs using MESA and NHANES definitions, respectively. CONCLUSIONS AND RELEVANCE: These data suggest that many eyes diagnosed as having DME or CSME on monocular fundus photographs have no DME based on OCT CST, while many eyes diagnosed as not having DME or CSME on monocular fundus photographs have DME on OCT. While limited to 1 clinical practice, caution is suggested when extrapolating prevalence of eyes that may benefit from anti-vascular endothelial growth factor therapy based on epidemiologic surveys using photographs to diagnose DME.

Sutureless 25-Gauge Vitrectomy for Rhegmatogenous Retinal Detachment Caused by Superior Breaks Using Air Tamponade.

PURPOSE: This study was aimed to evaluate the efficacy and safety of 25-gauge sutureless vitrectomy in repairing primary rhegmatogenous retinal detachment (RRD) with air tamponade. DESIGN: This is a prospective, clinic-based, case series. METHODS: Twenty consecutive eyes of 20 patients with primary RRD caused by superior breaks of less than a month underwent transconjunctival sutureless 25-gauge vitrectomy with intraocular air tamponade. Patients who had a follow-up of less than 6 months were excluded. Outcome measures included best corrected visual acuity (BCVA), reattachment rate by a single procedure, final reattachment rate by additional procedures, and complications. RESULTS: The mean follow-up was 10 months (range, 6-15 months). The proportion of eyes with BCVA of between 20/200 and 20/70 increased significantly from 15% at baseline to 65% on day 14 (P = 0.024). At final follow-up, 15%, 60%, and 25% had BCVA worse than 20/200, between 20/200 and 20/70, and better than 20/70, respectively. The mean BCVA was significantly better than baseline (logMAR, 1.4) by day 14 (logMAR, 0.87). The reattachment rate by a single procedure was 70%, and the final success rate was 100% after 1 additional procedure. The primary success rate increased to 77.8% after excluding 2 eyes with proliferative vitreoretinopathy grade C1. High myopia and large retinal break were 2 other conditions associated with failed primary reattachment. No postoperative complication was observed. CONCLUSIONS: Selected eyes with primary RRD may gain the benefit of early visual recovery when treated with 25-gauge vitrectomy and air tamponade.

Macular Vascular Abnormalities Identified by Optical Coherence Tomographic Angiography in Patients With Sickle Cell Disease.

IMPORTANCE: Patients with sickle cell disease may develop various macular vascular abnormalities that have not been described previously and can be seen using optical coherence tomographic angiography. OBSERVATIONS: Ten eyes from 5 consecutive patients (3 men and 2 women) with sickle cell disease (4 patients with hemoglobin SS disease and 1 patient with hemoglobin SC disease) were included. The mean age was 37.6 years. Five of 10 eyes (50%) had retinal thinning that was identified using spectral-domain optical coherence tomography. Each of these eyes had corresponding loss of vascular density in the superficial or deep retinal plexus (or both). CONCLUSIONS AND RELEVANCE: Optical coherence tomographic angiography provides a novel way to view the retinal vasculature, including the superficial and deep capillary plexus, and may provide a sensitive method for identifying macular vascular abnormalities in patients with sickle cell disease.

Automated segmentation of geographic atrophy of the retinal epithelium via random forests in AREDS color fundus images.

BACKGROUND: Age-related macular degeneration (AMD), left untreated, is the leading cause of vision loss in people older than 55. Severe central vision loss occurs in the advanced stage of the disease, characterized by either the in growth of choroidal neovascularization (CNV), termed the "wet" form, or by geographic atrophy (GA) of the retinal pigment epithelium (RPE) involving the center of the macula, termed the "dry" form. Tracking the change in GA area over time is important since it allows for the characterization of the effectiveness of GA treatments. Tracking GA evolution can be achieved by physicians performing manual delineation of GA area on retinal fundus images. However, manual GA delineation is time-consuming and subject to inter-and intra-observer variability. METHODS: We have developed a fully automated GA segmentation algorithm in color fundus images that uses a supervised machine learning approach employing a random forest classifier. This algorithm is developed and tested using a dataset of images from the NIH-sponsored Age Related Eye Disease Study (AREDS). GA segmentation output was compared against a manual delineation by a retina specialist. RESULTS: Using 143 color fundus images from 55 different patient eyes, our algorithm achieved PPV of 0.82±0.19, and NPV of 0:95±0.07. DISCUSSION: This is the first study, to our knowledge, applying machine learning methods to GA segmentation on color fundus images and using AREDS imagery for testing. These preliminary results show promising evidence that machine learning methods may have utility in automated characterization of GA from color fundus images.