Case Report: Self-Resolved Macular Edema Secondary to Congenital Retinal Macrovessels

PurposeTo report a case of macular edema secondary to congenital retinal macrovessels (CRMs), which resolved spontaneously without any treatment.ObservationsA 39-year-old female presented with blurry vision of the right eye for one day. Fundus examination revealed a branch of artery and vein of the inferior retinal arcade crossing the horizontal raphe. Optical coherence tomography (OCT) through the fovea showed cystoid macular edema in the outer plexiform layer. However, no leakage of the vessels was noticed by fundus fluorescein angiography (FFA). Observation was recommended with close follow-up. Two weeks later, the patient returned with good visual acuity, and the macular edema was resolved spontaneously.ConclusionsMacular edema is a possible complication of CRM by increasing retinal capillary hydrostatic pressure. Treatment is not necessary for this kind of macular edema if no leakage of the vessels is noticed on FFA.

Diabetic macular edema and proliferative diabetic retinopathy treated with anti-vascular endothelial growth factor under the reimbursement policy in Taiwan

The purpose of this retrospective interventional case series is to compare the functional and anatomical outcomes in eyes with diabetic macular edema (DME) and proliferative diabetic retinopathy (PDR) treated intravitreally with aflibercept or ranibizumab under the Taiwan National Insurance Bureau reimbursement policy. 84 eyes were collected and all eyes were imaged with spectral-domain optical coherence tomography (SD-OCT), color fundus photographs (CFPs), and fluorescein angiography (FA). At 24 months after therapy initiation, the logMAR BCVA improved from 0.58 ± 0.33 to 0.47 ± 0.38 (p < 0.01), the CRT decreased from 423.92 ± 135.84 to 316.36 ± 90.02 (p < 0.01), and the number of microaneurysms decreased from 142.14 ± 57.23 to 75.32 ± 43.86 (p < 0.01). The mean injection count was 11.74 ± 5.44. There was no intergroup difference in logMAR BCVA (p = 0.96), CRT (p = 0.69), or injection count (p = 0.81). However, the mean number of microaneurysms was marginally reduced (p = 0.06) in eyes treated with aflibercept at the end of the follow-up, and the incidence rates of supplementary panretinal photocoagulation (PRP) (p = 0.04) and subthreshold micropulse laser (SMPL) therapy sessions (p = 0.01) were also reduced. Multivariate analysis revealed that only initial logMAR BCVA influenced the final VA improvements (odds ratio (OR) 0.49, 95% confidence interval (CI) 0.21 ~ 0.93, p < 0.01); in contrast, age (OR − 0.38, 95% CI − 6.97 ~ − 1.85, p < 0.01) and initial CRT (OR 0.56, 95% CI 0.34 ~ 0.84, p < 0.01) both influenced the final CRT reduction at 24 months. To sum up, both aflibercept and ranibizumab are effective in managing DME with PDR in terms of VA, CRT and MA count. Eyes receiving aflibercept required less supplementary PRP and SMPL treatment than those receiving ranibizumab. The initial VA influenced the final VA improvements at 24 months, while age and initial CRT were prognostic predictors of 24-month CRT reduction.

Optical Coherence Tomographic Features and Prognostic Values of Macular Edema in Vogt-Koyanagi-Harada Disease

Purpose: To determine optical coherence tomographic (OCT) features of macular edema (ME) and identify potential prognostic values for ME and visual outcomes in Vogt-Koyanagi-Harada disease (VKH).Methods: In the retrospective case series, a total of 1,377 VKH patients who were seen in a tertiary uveitis center between September 2011 and January 2018 were reviewed on their demographics, visual acuity, ocular and extraocular manifestations, modes of treatment, and OCT examinations. Of these patients, 79 (5.7%) having ME were included for analysis of OCT features. Four patients were missed without ME resolution, and the remaining 75 patients who either had ME resolved or were followed up for 2 years were included for analysis of disease outcomes.Results: Of the 115 affected eyes in these 79 patients, 100 (87.0%) had cystoid ME (CME), accounting for the most common OCT feature of VKH-related ME. Disruption of the inner-segment/outer-segment junction (IS/OS) band seen in 33 (28.7%) affected eyes of 24 (30.4%) patients was found as a risk factor for the development of persistent ME [10 of 62 (16.1%) vs. 13 of 13 (100%); P &lt; 0.001] and a poor visual outcome (1.16 ± 0.42 vs. 1.17 ± 0.46 in logMAR unit; P = 0.89). CME patients with a concurrent choroidal neovascular membrane often had a disrupted IS/OS band, thus becoming refractory cases. A 6-month well-controlled intraocular inflammation following standard treatment regimens was found to associate with complete resolution of the refractory edema [4 of 5 (80%) vs. 2 of 13 (15%); P = 0.02].Conclusions: Intraretinal cystoid changes are most commonly seen in the edematous macula of VKH patients. Disruption of the IS/OS band is a useful risk sign for poor ME and visual outcomes in VKH-related ME, and a long-term well-controlled intraocular inflammation may be critical for the resolution of refractory cases.

Factors Associated With the Presence of Foveal Bulge in Eyes With Resolved Diabetic Macular Edema

Purpose: To evaluate factors associated with the presence of foveal bulge (FB) in resolved diabetic macular edema (DME) eyes.Methods: A total of 165 eyes with complete integrity of ellipsoid zone (EZ) at the fovea and resolved DME were divided into two groups according to the presence of FB at 6 months after intravitreal injection of ranibizumab treatment. Best-corrected visual acuity (BCVA), central foveal thickness (CFT), outer nuclear layer (ONL) thickness, height of serous retinal detachment (SRD) and non-SRD, and inner segment (IS) and outer segment (OS) lengths of the two groups were measured and compared at baseline and each follow-up. The correlations between the presence of FB and pre- and post-treatment factors were determined by logistic regression analysis.Results: At baseline, BCVA was significantly better, and CFT and incidence and height of SRD were significantly lower in the FB (+) group (all P &lt; 0.05). At 6 months, FB was present in 65 (39.39%) eyes. Post-treatment BCVA was significantly better and OS length was significantly longer in the FB (+) group at 6 months (all P &lt; 0.05). Multivariate analysis identified younger age, better BCVA, and lower CFT before treatment as significant predictors of the existence of FB at 6 months (all P &lt; 0.05). At 6 months, better BCVA and longer OS length were significantly correlated with the existence of FB (all P &lt; 0.05).Conclusions: Factors associated with the presence of FB after the resolution of DME include younger age, better baseline BCVA and lower baseline CFT, and better post-treatment BCVA and longer post-treatment OS length.

Automated detection of diabetic retinopathy using custom convolutional neural network

Diabetic retinopathy is an eye deficiency that affects retina as a result of the patient having diabetes mellitus caused by high sugar levels, which may eventually lead to macular edema. The objective of this study is to design and compare several deep learning models that detect severity of diabetic retinopathy, determine risk of leading to macular edema, and segment different types of disease patterns using retina images. Indian Diabetic Retinopathy Image Dataset (IDRiD) dataset was used for disease grading and segmentation. Since images of the dataset have different brightness and contrast, we employed three techniques for generating processed images from the original images, which include brightness, color and, contrast (BCC) enhancing, color jitters (CJ), and contrast limited adaptive histogram equalization (CLAHE). After image preporcessing, we used pre-trained ResNet50, VGG16, and VGG19 models on these different preprocessed images both for determining the severity of the retinopathy and also the chances of macular edema. UNet was also applied to segment different types of diseases. To train and test these models, image dataset was divided into training, testing, and validation data at 70%, 20%, and 10% ratios, respectively. During model training, data augmentation method was also applied to increase the number of training images. Study results show that for detecting the severity of retinopathy and macular edema, ResNet50 showed the best accuracy using BCC and original images with an accuracy of 60.2% and 82.5%, respectively, on validation dataset. In segmenting different types of diseases, UNet yielded the highest testing accuracy of 65.22% and 91.09% for microaneurysms and hard exudates using BCC images, 84.83% for optic disc using CJ images, 59.35% and 89.69% for hemorrhages and soft exudates using CLAHE images, respectively. Thus, image preprocessing can play an important role to improve efficacy and performance of deep learning models.