MICROVASCULAR LEAKAGE IS A POOR PROGNOSTIC FACTOR FOR IDIOPATHIC EPIRETINAL MEMBRANE: A Fluorescein Angiography Study

Effect of topical bromfenac on intraretinal cystoid lesion in simultaneous cataract and idiopathic epiretinal membrane surgery

PURPOSE

To investigate the effect of topical nonsteroidal anti-inflammatory drugs (NSAIDs,) bromfenac on the intraretinal cystic lesions (IRC) when performing simultaneous cataract and idiopathic epiretinal membrane (iERM) surgery.

METHODS

This study included patients with iERM who had been followed up for 6 months after vitrectomy, membrane removal, and concurrent cataract surgery. Eyes were treated with topical bromfenac or not. The baseline fluorescein angiography (FA) was obtained to assess the microvascular leakage (ML). Structural changes of macula, including IRC and central macular thickness (CMT) were assessed using optical coherence tomography (OCT). The main outcome measures were changes in IRCs and best-corrected visual acuity (BCVA) regarding FA findings.

RESULTS

One hundred eighteen eyes were included. IRC and ML were observed in 51 eyes (43.2%) and 63 eyes (53.4%), respectively. The IRC did not show any association with the ML. Of total, 29 eyes (24.6%) were treated with topical bromfenac (Group A). Compared to Group B, topical bromfenac did not show beneficial effects in aspect of preventions for the newly developed IRC and treatment for pre-existed IRC. Whether the ML existed or not, topical bromfenac did not show any different effect on the changes in BCVA and IRC.

CONCLUSION

When performing simultaneous cataract and ERM surgery, topical NSAIDs, bromfenac did not show beneficial effects on the preventions and treatment of IRC in both eyes with and without the ML.

TOPOGRAPHIC ASSESSMENT OF INTRARETINAL CYSTOID SPACE AND ITS PROGNOSTIC VALUES IN IDIOPATHIC EPIRETINAL MEMBRANE

PURPOSE

To assess the topographical distribution of intraretinal cystoid space (IRC) and its prognostic value in idiopathic epiretinal membrane (iERM).

METHODS

One hundred twenty-two eyes of iERM that had been followed up for 6 months after membrane removal were included. Based on the baseline IRC distribution, the eyes were divided into Groups A, B, and C (absence, IRC within 3 mm, and 6 mm from the fovea, respectively). The best-corrected visual acuity (BCVA), central subfield macular thickness (CSMT), ectopic inner foveal layer, and microvascular leakage (ML) were assessed.

RESULTS

Fifty-six eyes (45.9%) had IRC, of which 35 (28.7%) were in Group B and 21 (17.2%) in Group C at baseline. Compared with group B, group C showed worse BCVA, thicker CSMT, and a greater association with ML (OR = 5.415; P = 0.005) at baseline; and also presented with worse BCVA, thicker CSMT, and wider distribution of IRC postoperatively. A wide distribution of IRC was an unfavorable baseline factor in achieving good visual acuity (OR = 2.989; P = 0.031).

CONCLUSION

Widely distributed IRCs were associated with advanced disease phenotype as poor BCVA, thick macula, and baseline ML in iERM and also showed a poor visual outcome after membrane removal.

Retinal vessel geometry in patients with idiopathic epiretinal membrane

We investigated the associations between retinal vascular geometric measurements and idiopathic epiretinal membrane (ERM). Whether changes in retinal vascular geometry are independent of systemic cardiovascular risk factors was also evaluated. This retrospective, cross sectional study included 98 patients with idiopathic ERM, and 99 healthy age-matched controls. Quantitative retinal vascular parameters were measured from digital retinal fundus photographs using a semi-automated computer-assisted program. Multivariate logistic regression analyses were performed to evaluate associations between retinal vascular geometric parameters and the presence of idiopathic ERM after adjusting for systemic cardiovascular risk factors. There was no significant difference in the baseline characteristics of the two groups, except that the ERM group had a higher proportion of females than the control group. In multivariate regression analyses, female sex (odds ratio [OR] 0.402; 95% CI 0.196-0.802; P = 0.011), wider retinal venular caliber (OR 16.852; 95% CI 5.384-58.997; P < 0.001) and decreased total fractal dimension (OR 0.156; 95% CI 0.052-0.440; P = 0.001) were associated with idiopathic ERM. Idiopathic ERM was associated with alterations in global retinal microvascular geometric parameters, wider retinal venules, and less complex vascular branching patterns, independent of cardiovascular risk factors.

Deep-learning-based AI for evaluating estimated nonperfusion areas requiring further examination in ultra-widefield fundus images

We herein propose a PraNet-based deep-learning model for estimating the size of non-perfusion area (NPA) in pseudo-color fundus photos from an ultra-wide-field (UWF) image. We trained the model with focal loss and weighted binary cross-entropy loss to deal with the class-imbalanced dataset, and optimized hyperparameters in order to minimize validation loss. As expected, the resultant PraNet-based deep-learning model outperformed previously published methods. For verification, we used UWF fundus images with NPA and used Bland-Altman plots to compare estimated NPA with the ground truth in FA, which demonstrated that bias between the eNPA and ground truth was smaller than 10% of the confidence limits zone and that the number of outliers was less than 10% of observed paired images. The accuracy of the model was also tested on an external dataset from another institution, which confirmed the generalization of the model. For validation, we employed a contingency table for ROC analysis to judge the sensitivity and specificity of the estimated-NPA (eNPA). The results demonstrated that the sensitivity and specificity ranged from 83.3-87.0% and 79.3-85.7%, respectively. In conclusion, we developed an AI model capable of estimating NPA size from only an UWF image without angiography using PraNet-based deep learning. This is a potentially useful tool in monitoring eyes with ischemic retinal diseases.