Acute Vogt-Koyanagi-Harada (VKH) disease and acute central serous chorioretinopathy (CSCR) are two common disorders with serous retinal detachment caused by dysfunction of choroid. The purpose of this study is to compare the morphological changes of these two diseases with spectral domain optical coherence tomography (SD-OCT).

Purpose: To evaluate the anatomical and functional outcomes of internal limiting membrane (ILM) peeling and the inverted ILM flap technique for rhegmatogenous retinal detachment coexisting with macular hole. Methods: This retrospective study evaluated the medical records of 79 eyes with concurrent rhegmatogenous retinal detachment and macular hole received vitrectomy and silicone oil tamponade, with ILM peeling on 56 eyes and the inverted ILM flap technique on 23 eyes. Results: The Type 1 closure rate was greater in the inverted ILM flap group than the ILM peeling group (82.6% vs. 55.4%, P = 0.038). Lines of improvement were 7.8 ± 5.3 in the ILM peeling group and 8.9 ± 5.6 in the inverted ILM flap group. Postoperative epiretinal membrane and retinal reattachment rates were similar in two surgical groups (16.1% vs. 21.7%, P = 0.535 and 94.6% vs. 95.7%, P = 0.999, respectively). Type 1 closure was significantly correlated with the inverted ILM flap technique (OR = 5.568, P = 0.023). The inverted ILM flap technique showed no significant association with the final logarithm of the minimum angle of resolution best-corrected visual acuity in multivariate model analysis. Conclusion: The inverted ILM flap technique was more effective in restoring the macular structure in patients with rhegmatogenous retinal detachment and coexisting macular hole, but the functional outcomes of the two strategies were comparable.

Diabetic macular edema (DME) is a leading cause of vision loss in diabetes, with variable responses to anti-vascular endothelial growth factor (anti-VEGF) therapy in DME patients. Current diagnosis relies on optical coherence tomography (OCT) imaging, but manual interpretation is limited. This study aims to integrate 3D-OCT features and clinical variables to develop machine learning (ML) models for predicting anti-VEGF treatment outcomes. Medical records and 3D-OCT images of DME patients were included in this study. The 3D-OCT images were categorized into good and poor visual response groups based on the best corrected visual acuity at one month after three consecutive anti-VEGF treatments. The images and clinical features were subjected to assessment by 11 automatic classification models for anti-VEGF treatment responses in DME patients. The top 3 performing models were selected to build an ensemble model, and evaluated in the test dataset. This study included 142 patients with 3D-OCT images of 170 eyes. A total of 20 image and clinical features were selected for the model construction and test in DME patients responded to anti-VEGF therapy. Adaptive boosting (AdaBoost), GradientBoosting, and light gradient boosting machine (LightGBM) exhibited better performances than the remaining 8 models. The ensemble model constructed achieved a sensitivity of 0.941, specificity of 0.882, and accuracy of 0.912 in the test dataset, with an area under the receiver operating characteristic curve of 0.976. This study established an ensemble ML algorithm based on 3D-OCT images and clinical features for automatic detection of treatment responses to anti-VEGF treatment in DME patients to predict the efficacy of anti-VEGF treatment in DME patients and assist clinicians in optimal treatment decisions.

Objective To evaluate the cost-effectiveness of telemedicine-based diabetic retinopathy (DR) screening with artificial intelligence (AI)-based grading in rural and urban China. Methods The cost effectiveness of telemedicine-based diabetic retinopathy screening with AI-based grading was compared to no DR screening in rural area and urban area from social perspective. Increment cost-effectiveness ratio (ICER) using quality-adjusted life year (QALY) was calculated and compared to the per capita GDP in China 2022. Results The ICERs of AI and manual screening were $11132.39/QALY and $11239.22/QALY gained in rural area and $6764.12/QALY and $6923.77/QALY in urban area respectively as compared to no screening. The ICERs of both strategies were less than the threshold, and considered to be cost-effective in rural area and very cost-effective in urban area. Moreover, AI-based screening was more cost-effective than human assessor-based screening in both areas. Conclusion DR screenings based on fundus photography and telemedicine are both cost-effective in rural and urban area. AI-based screening is more cost-effective than human assessor-based screening, extending the application of DR screening across China.

Purpose: To evaluate independent preoperative risk factors for secondary macular hole (MH) after fovea-off rhegmatogenous retinal detachment (RRD) and their impact on postoperative visual outcomes. Methods: This retrospective study included fovea-off RRD patients with preoperative optical coherence tomography (OCT) confirmed subfoveal fluid and complete pre- and postoperative demographics, clinical features, and OCT images. Based on postoperative OCT images, patients were subdivided into No MH, lamellar MH, and full-thickness MH groups after RRD surgery. Multivariate logistic regression and linear regression were applied to identify the factors associated with postoperative secondary MH and best-corrected visual acuity, respectively. Results: Of these 705 patients, 57 developed secondary MH after RRD surgery, whereas the remaining 648 patients served as the control group. Multivariate logistic regression analysis demonstrated that Müller cell cone (MCC) loss (OR = 4.401, P = 0.001), bacillary layer detachment (OR = 2.528, P = 0.041), retinal detachment (RD) extent (OR = 1.136, P = 0.031), and foveal neurosensory thickness (OR = 0.992, P = 0.030) were independent MH risk factors. Multiple linear regression analysis showed that MCC loss (β = 0.308, P < 0.001), greater RD extent (β = 0.024, P = 0.010), longer RD duration (β = 0.001, P = 0.036), outer nuclear layer thinning (β = 0.144, P = 0.001), and worse preoperative best-corrected visual acuity (β = 0.129, P < 0.001) predicted poorer visual outcomes. Conclusion: MCC loss is the strongest risk factor for both MH development and worse visual prognosis after RRD surgery.

Adult-onset Coats’ disease is an uncommon, vision-threatening disorder characterized by exudation and vascular abnormalities in the peripheral and ma