Endoscopic Vitrectomy Combined with 3D Heads-Up Viewing System in Treating Traumatic Ocular Injury.

Purpose: To investigate effects and complications of endoscopic vitrectomy combined with 3D heads-up viewing system in treating traumatic ocular injury. Patients and Methods. This is a retrospective interventional case series in a tertiary referral center in Taiwan, and we included patients of traumatic ocular injury, and they underwent endoscopic vitrectomy combined with a 3D heads-up viewing system. Results: Fourteen eyes of traumatic globe injury from 14 patients were studied over a 30-month period. Preoperative VA ranged from no light perception (NLP) to 6/6. Postoperative visual acuity improved in 11 of the 14 eyes (79%). Until 6 months after surgery, all eyes had attached retina. The median logMAR BCVA was 2.4 at the first visit and 1.19 at the last visit (p = 0.0028). No subject suffered from retinal detachment, endophthalmitis, or other severe complications. Conclusions: Vitrectomy using endoscopy combined with 3D heads-up viewing system allowed early evaluation and intervention in traumatic ocular injuries. Most of our cases showed both anatomical and visual acuity improvements.

Air versus Gas Tamponade for Primary Rhegmatogenous Retinal Detachment: A Systematic Review and Meta-Analysis.

BACKGROUND: Air tamponade's effectiveness in treatment of rhegmatogenous retinal detachment (RRD) remains unclear. OBJECTIVE: We aimed to review the surgical outcomes between air and gas tamponade after vitrectomy for RRD. METHOD: PubMed, Cochrane Library, EMBASE, and Web of Science were reviewed. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO CRD42022342284). The primary outcome was the primary anatomical success after vitrectomy. The secondary outcome was the prevalence of postoperative ocular hypertension. Certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation system. RESULTS: Ten studies involving 2,677 eyes were included. One study was randomized, and the others were non-randomized. The primary anatomical success after vitrectomy was not significantly different between the air and gas groups (odds ratio [OR], 1.00; 95% confidence interval [CI], 0.68-1.48). The risk of ocular hypertension was significantly lower in the air group (OR: 0.14; 95% CI: 0.09-0.24). The certainty of evidence regarding air tamponade having a comparable anatomical outcome and lower frequency of postoperative ocular hypertension in treatment of RRD were low. DISCUSSION: The current evidence base for tamponade selection in treatment of RRD has several major limitations. Further appropriately designed studies are needed to guide tamponade selection.

Application of Artificial Intelligence and Deep Learning for Choroid Segmentation in Myopia.

PURPOSE: To investigate the correlation between choroidal thickness and myopia progression using a deep learning method. METHODS: Two data sets, data set A and data set B, comprising of 123 optical coherence tomography (OCT) volumes, were collected to establish the model and verify its clinical utility. The proposed mask region-based convolutional neural network (R-CNN) model, trained with the pretrained weights from the Common Objects in Context database as well as the manually labeled OCT images from data set A, was used to automatically segment the choroid. To verify its clinical utility, the mask R-CNN model was tested with data set B, and the choroidal thickness estimated by the model was also used to explore its relationship with myopia. RESULTS: Compared with the result of manual segmentation in data set B, the error of the automatic choroidal inner and outer boundary segmentation was 6.72 ± 2.12 and 13.75 ± 7.57 µm, respectively. The mean dice coefficient between the region segmented by automatic and manual methods was 93.87% ± 2.89%. The mean difference in choroidal thickness over the Early Treatment Diabetic Retinopathy Study zone between the two methods was 10.52 µm. Additionally, the choroidal thickness estimated using the proposed model was thinner in high-myopic eyes, and axial length was the most significant predictor. CONCLUSIONS: The mask R-CNN model has excellent performance in choroidal segmentation and quantification. In addition, the choroid of high myopia is significantly thinner than that of nonhigh myopia. TRANSLATIONAL RELEVANCE: This work lays the foundations for mask R-CNN models that could aid in the evaluation of more intricate changes occurring in chorioretinal diseases.

Automatic Segment and Quantify Choroid Layer in Myopic eyes: Deep Learning based Model.

PURPOSE: To report a rapid and accurate method based upon deep learning for automatic segmentation and measurement of the choroidal thickness (CT) in myopic eyes, and to determine the relationship between refractive error (RE) and CT. METHODS: Fifty-four healthy subjects 20-39 years of age were retrospectively reviewed. Data reviewed included age, gender, laterality, visual acuity, RE, and Enhanced Depth Imaging Optical Coherence Tomography (EDI-OCT) images. The choroid layer was labeled by manual and automatic method using EDI-OCT. A Mask Region-convolutional Neural Network (Mask R-CNN) model, using deep Residual Network (ResNet) and Feature Pyramid Networks (FPN) as a backbone network, was trained to automatically outline and quantify the choroid layer. RESULTS: ResNet 50 model was adopted for its 90% accuracy rate and 6.97 s average execution time. CT determined by the manual method had a mean thickness of 258.75 ± 66.11 µm, a positive correlation with RE (r = 0.596, p < .01) and significant association with gender (p = .011) and RE (p < .001) in multivariable linear regression analysis. Meanwhile, CT determined by deep learning presented a mean thickness of 226.39 ± 54.65 µm, a positive correlation with RE (r = 0.546, p < .01) and significant association with gender (p = .043) and RE (p < .001) in multivariable linear regression analysis. Both methods revealed that CT decreased with the increase in myopic RE. CONCLUSIONS: This deep learning method using Mask-RCNN was able to successfully determine the relationship between RE and CT in an accurate and rapid way. It could eliminate the need for manual process, while demonstrating a feasible clinical application.

Efficacy of Combined Vitrectomy with Intravitreal Corticosteroid Injection for Idiopathic Epiretinal Membrane Removal on Anatomical and Functional Outcomes: A Meta-Analysis.

BACKGROUND: Macular edema can be a cause of visual loss in eyes undergoing vitrectomy with epiretinal membrane (ERM) peeling. OBJECTIVE: The objective of this study was to evaluate the efficacy of combined vitrectomy with intravitreal corticosteroid injection for ERM. METHODS: We conducted a systematic literature review by searching PubMed, Embase, and Medline up to December 2020 for studies that evaluated the effect of intravitreal corticosteroid injection during vitrectomy for ERM. Follow-up data on postoperative best corrected visual acuity (BCVA) and central macular thickness (CMT) were collected and pooled using the standard mean deviation (SMD) with the corresponding 95% confidence interval (CI). Heterogeneity was statistically quantified using I2 statistics, and a meta-analysis was performed using a random-effects model. RESULTS: Eight studies provided data on a total sample of 443 eyes. The meta-analysis revealed that concomitant intravitreal corticosteroid administration during vitrectomy contributed to a significant reduction in CMT than vitrectomy alone at 3 months after operation (pooled SMD = -0.353; 95% CI: -0.594 to -0.111; p = 0.004). However, between the two groups, no significant difference was found in CMT reduction at 1 and 6 months after operation and in postoperative BCVA improvement at 1, 3, and 6 months after operation. CONCLUSION: Combined treatment with vitrectomy and intravitreal corticosteroid injection may accelerate CMT reduction 3 months after ERM surgery. However, it did not result in a significant change in CMT and BCVA compared with vitrectomy alone at the end of follow-up.

Surgical outcomes and prognostic factors in traumatic retinal detachment following closed-globe injuries.

PURPOSE: To evaluate the anatomical and functional results of retinal detachment (RD) surgery following closed-globe injuries (CGI). METHODS: Patients treated with vitreoretinal surgeries due to RD following CGI from 2014 to 2020 were retrospectively reviewed. Data included demographics, mechanism of injury, preoperative evaluation, and surgical intervention. Outcome measurements included anatomic success, best corrected visual acuity (BCVA), and possible prognostic factors. RESULTS: A total of 67 eyes from 64 patients (49 males; mean age 52.84 years) were included. The most common causes of the CGI were work-related injury (22.4%) and traffic accidents (23.9%). The primary and final anatomic success rates were 80.6% (54/67) and 89.6% (60/67), respectively. In the multivariable analysis of the logistic regression models, the poor prognostic factor was proliferative vitreoretinopathy (PVR) (P = 0.009) for primary anatomic success. The median preoperative and final BCVA were logMAR 0.7 (IQR, 0.3-1.6) and logMAR 0.5 (IQR, 0.1-1.1), respectively (P = 0.077). Poorly presenting BCVA (counting fingers or worse) and giant tear were associated with poor visual outcomes. CONCLUSION: Work-related injuries and traffic accidents are the prevalent causes of RD following CGI. The anatomic outcomes were favorable, but visual outcomes varied. Poor prognostic factors included PVR and poorly presenting BCVA, highlighting the importance of a careful initial evaluation.