Also in the News…

Eye care performance reductions. Last week, The Vision Council released their semi-annual Provider inSights report, a research study exploring eye care provider thoughts on the daily operations of their practices, the broader eye care industry, and the US economy. The report highlights that, in comparison to previous years, providers are reporting substantial decreases across all areas of their practice. Link

AI fundus camera. Diagnostics equipment manufacturer, Visionix USA, has released a new fundus camera with automated retinal screening capabilities. Employing artificial intelligence, the VX 610 non-mydriatic fundus camera has been trained to auto-detect 13 early signs of common retinal pathologies, correctly flagging positive results 93 percent of the time. Link

Hyalocytes origins. Seeking to investigate the origin and characteristics of hyalocytes, a type of macrophage found in the vitreous body of the eye, a new Journal of Neuroinflammation study used transgenic mouse models to demonstrate that hyalocytes are already forming during embryonic development. The discovery – highlighted by the inter-university team from Leipzig University, Augsburg University, the University of Freiburg, and Oregon Health & Science University – offers potential new severity-reducing treatment pathways for vitreoretinal diseases, such as diabetic retinopathy. Link

Glaucoma monitoring. A new Ophthalmology Science paper has investigated the discrepancies between retinal nerve fiber layer (RNFL) thickness and Bruch’s membrane opening-minimum rim width (BMO-MRW) measurements in glaucoma patients. The study, conducted by a team based at the University of California at Los Angeles, found that OCT (Optical coherence tomography) mismatches between the two parameters in 8 percent of the measurement sectors were primarily caused by the influence of blood vessels. The findings highlight limitations in current OCT technology, as well as indicating the potential for combined use of both parameters to improve future glaucoma monitoring. Link

Early diagnosis of Parkinson’s. A new TVST study – conducted by a team of researchers from the Duke University School of Medicine, Durham, NC – has developed a convolutional neural network (CNN) to classify Parkinson’s disease (PD) using multimodal retinal imaging. The CNN was trained to analyze images from optical coherence tomography (OCT), OCT angiography (OCTA), and ultra-widefield (UWF) fundus photography. Tested on a dataset of 371 control and 75 PD eyes, the model achieved a high diagnostic accuracy (AUC of 0.918), indicating the potential of using retinal imaging as a non-invasive tool for early PD diagnosis. Link

Nomogram developed for eyelid SC risk. Researchers from various ophthalmology departments across China – including the Shanghai Jiao Tong University School of Medicine – have conducted a multicenter retrospective analysis of 418 patients with eyelid sebaceous carcinoma (SC). The multi-institutional team aimed to identify any predictors of recurrence and develop a personalized prediction model from their analysis. A new predictive model – or nomogram – was developed, which demonstrated better accuracy than the traditional Tumor, Node, Metastasis (TNM) staging system. The authors believe this model could aid future therapeutic decision-making – as well as improve patient outcomes – in managing eyelid SC. Link