OIMHS: An Optical Coherence Tomography Image Dataset Based on Macular Hole Manual Segmentation.

Macular holes, one of the most common macular diseases, require timely treatment. The morphological changes on optical coherence tomography (OCT) images provided an opportunity for direct observation of the disease, and accurate segmentation was needed to identify and quantify the lesions. Developments of such algorithms had been obstructed by a lack of high-quality datasets (the OCT images and the corresponding gold standard macular hole segmentation labels), especially for supervised learning-based segmentation algorithms. In such context, we established a large OCT image macular hole segmentation (OIMHS) dataset with 3859 B-scan images of 119 patients, and each image provided four segmentation labels: retina, macular hole, intraretinal cysts, and choroid. This dataset offered an excellent opportunity for investigating the accuracy and reliability of different segmentation algorithms for macular holes and a new research insight into the further development of clinical research for macular diseases, which included the retina, lesions, and choroid in quantitative analyses.

Lesion detection with fine-grained image categorization for myopic traction maculopathy (MTM) using optical coherence tomography.

BACKGROUND: Myopic traction maculopathy (MTM) are retinal disorder caused by traction force on the macula, which can lead to varying degrees of vision loss in eyes with high myopia. Optical coherence tomography (OCT) is an effective imaging technique for diagnosing, detecting and classifying retinopathy. MTM has been classified into different patterns by OCT, corresponding to different clinical strategies. PURPOSE: We aimed to engineer a deep learning model that can automatically identify MTM in highly myopic (HM) eyes using OCT images. METHODS: A five-class classification model was developed using 2837 OCT images from 958 HM patients. We adopted a ResNet-34 architecture to train the model to identify MTM: no MTM (class 0), extra-foveal maculoschisis (class 1), inner lamellar macular hole (class 2), outer foveoschisis (class 3), and discontinuity or detachment of foveal outer hyperreflective layers (class 4). An independent test set of 604 images from 173 HM patients was used to evaluate the model's performance. Classification performance was assessed according to the area under the curve (AUC), accuracy, sensitivity, specificity. RESULTS: Our model exhibited a high training performance for classification (F1-score of 0.953; AUCs of 0.961 to 0.998). In test set, it achieved sensitivities (91.67%-97.78 %) and specificities (98.33%-99.17%) as good as, or better than, those of experienced clinicians. Heatmaps were generated to provide visual explanations. CONCLUSIONS: We established a deep learning model for MTM classification using OCT images. This model performed equally well or better than retinal specialists and is suitable for large-scale screening and identifying MTM in HM eyes.

Analysis of Retinal Microstructure in Eyes with Dissociated Optic Nerve Fiber Layer (DONFL) Appearance following Idiopathic Macular Hole Surgery: An Optical Coherence Tomography Study.

(1) Purpose: This study aimed to evaluate morphological changes of the retina in eyes with dissociated optic nerve fiber layer (DONFL) appearance following internal limiting membrane (ILM) peeling for full-thickness idiopathic macular hole (IMH) on spectral-domain optical coherence tomography (SD-OCT). (2) Methods: We retrospectively analyzed 39 eyes of 39 patients with type 1 macular hole closure after a vitrectomy with ILM peeling procedure at a six-month minimum postoperative follow-up. The retinal thickness maps and cross-sectional OCT images were obtained from a clinical OCT device. The cross-sectional area of the retinal nerve fiber layer (RNFL) on cross-sectional OCT images was manually measured by ImageJ software. (3) Results: The inner retinal layers (IRLs) thickness thinned down much more in the temporal quadrant than in nasal quadrants at 2 and 6 months postoperatively (p < 0.001). However, the cross-sectional area of the RNFL did not change significantly at 2 and 6 months postoperatively (p > 0.05) when compared to preoperative data. In addition, the thinning of the IRL did not correlate with the best-corrected visual acuity (BCVA) at 6 months postoperatively. (4) Conclusions: The thickness of the IRL decreased in eyes with a DONFL appearance after ILM peeling for IMH. The thickness of the IRL decreased more in the temporal retina than in the nasal retina, but the change did not affect BCVA during the 6 months after surgery.

Association of sex with the global burden of vision impairment caused by neonatal preterm birth: An analysis from the global burden of disease study 2019.

Aims: To investigate the sex-specific global burden of neonatal preterm birth (NPB) vision impairment by year, age, and socioeconomic status using years lived with disability (YLDs). Methods: The global, regional, and national sex-specific YLD numbers, crude YLD rates, and age-standardized YLD rates of NPB-related moderate and severe vision loss and blindness were obtained from the Global Burden of Disease Study 2019. The Wilcoxon test and linear regression were used to investigate the relationship between sex difference in age-standardized YLD rates and the Human Development Index (HDI). Results: Between 1990 and 2019, the gender disparity in age-standardized YLD rates for NPB-related vision impairment remained stable, increasing from 10.2 [95% uncertainty interval (UI) 6.7-14.6] to 10.4 (95% UI 6.9-15.0) for men and 10.3 (95% UI 6.8-14.7) to 10.7 (95% UI 7.2-15.1) for women, with women consistently having higher age-standardized YLD rates. Between the ages of 25 and 75, women had higher YLD rates than males, with the biggest disparity in the 60-64 age group. In 2019, sex difference in age-standardized YLD rates across 195 nations was statistically significant. Women had higher age-standardized YLD rates than men in both low (Z = -3.53, p < 0.001) and very high HDI countries (Z = -4.75, p < 0.001). Additionally, age-standardized YLD rates were found to be adversely associated with HDI (male: Standardized ß = -0.435, female: Standardized ß = -0.440; p < 0.001). Conclusion: Despite advancements in worldwide NPB health care, sexual differences in NPB-related vision impairment burden showed little change. Female had higher burden than male, particularly in low and very high socioeconomic status countries.