Newer advances in medical management of glaucoma.

The burden of irreversible vision loss from Glaucoma continues to rise. While the disease pathogenesis is not well understood, intraocular pressure (IOP) is the only modifiable risk factor identified to prevent glaucomatous vision loss. Medical management remains the first-line of treatment in most adult glaucomas and the evolution of medical therapy for glaucoma has followed an exponential curve. This review tracks the rapid development of new medications and drug delivery systems in the recent years. Introduction of Rho kinase inhibitors with an entirely new mechanism of action from that of the currently used anti glaucoma medications has been a significant milestone. Latanoprostene Bunod is a novel, single molecule which provides two active metabolites that work through two different pathways for reducing intra ocular pressure. Bimatoprost implants and travoprost punctum plugs attempt to ease chronic medication use in glaucoma patients. Nanotechnology is an evolving route of drug delivery. Role of cannabinoids in medical management of glaucoma remain equivocal. The relatively short term effect on IOP, the risks of developing tolerance and side effects impacting patients' neurocognitive health greatly outweigh the potential benefit. Research on Latrunculin B, Adenosine receptor agonists, Specific gene silencing and Stem cell therapy are poised to make an impact on glaucoma treatment. While there is some evidence to support the role of Brimonidine in neuroprotection, further research is needed to clarify the role of Memantine and Neurotrophins. Evidence for benefit from dietary supplementation with Alpha lipoic acid, Forskolin , and Ginko Biloba is limited.

Evaluating the Viability of a Smartphone-Based Annotation Tool for Faster and Accurate Image Labelling for Artificial Intelligence in Diabetic Retinopathy.

INTRODUCTION: Deep Learning (DL) and Artificial Intelligence (AI) have become widespread due to the advanced technologies and availability of digital data. Supervised learning algorithms have shown human-level performance or even better and are better feature extractor-quantifier than unsupervised learning algorithms. To get huge dataset with good quality control, there is a need of an annotation tool with a customizable feature set. This paper evaluates the viability of having an in house annotation tool which works on a smartphone and can be used in a healthcare setting. METHODS: We developed a smartphone-based grading system to help researchers in grading multiple retinal fundi. The process consisted of designing the flow of user interface (UI) keeping in view feedback from experts. Quantitative and qualitative analysis of change in speed of a grader over time and feature usage statistics was done. The dataset size was approximately 16,000 images with adjudicated labels by a minimum of 2 doctors. Results for an AI model trained on the images graded using this tool and its validation over some public datasets were prepared. RESULTS: We created a DL model and analysed its performance for a binary referrable DR Classification task, whether a retinal image has Referrable DR or not. A total of 32 doctors used the tool for minimum of 20 images each. Data analytics suggested significant portability and flexibility of the tool. Grader variability for images was in favour of agreement on images annotated. Number of images used to assess agreement is 550. Mean of 75.9% was seen in agreement. CONCLUSION: Our aim was to make Annotation of Medical imaging easier and to minimize time taken for annotations without quality degradation. The user feedback and feature usage statistics confirm our hypotheses of incorporation of brightness and contrast variations, green channels and zooming add-ons in correlation to certain disease types. Simulation of multiple review cycles and establishing quality control can boost the accuracy of AI models even further. Although our study aims at developing an annotation tool for diagnosing and classifying diabetic retinopathy fundus images but same concept can be used for fundus images of other ocular diseases as well as other streams of medical science such as radiology where image-based diagnostic applications are utilised.

Posterior capsular rent: Prevention and management.

This review article deals with a potentially sight threatening complication - rupture of the posterior capsule - during cataract surgery. Cataract surgery is the most commonly performed surgical procedure in ophthalmology and despite tremendous technical and technological advancements, posterior capsular rent (PCR) still occurs. PCR occurs both in the hands of experienced senior surgeons and the neophyte surgeons, although with a higher frequency in the latter group. Additionally, certain types of cataracts are prone to this development. If managed properly in a timely manner the eventual outcome may be no different from that of an uncomplicated case. However, improper management may lead to serious complications with a higher incidence of permanent visual disability. The article covers the management of posterior capsular rent from two perspectives: 1. Identifying patients at higher risk and measures to manage such patients by surgical discipline, and 2. Intraoperative management of posterior capsular rent and various case scenarios to minimize long-term complications.This review is written for experienced and not-so-experienced eye surgeons alike to understand and manage PCR.