No abstract

No abstract

Many human neural or neurodegenerative diseases strongly affect the ocular and retinal environment showing peculiar alterations which can be employed as specific disease biomarkers. The noninvasive optical accessibility of the retina makes the ocular investigation a potentially competitive strategy for screening, thus the development of retinal biomarkers is rapidly growing. Nevertheless, a tool to study and image biomarkers or biological samples in a human-like eye environment is still missing. Here we report on a modular and versatile eye model designed to host biological samples, such as retinal cultures differentiated from human induced pluripotent stem cells and ex-vivo retinal tissue, but also suited to host any kind of retinal biomarkers. We characterized the imaging performance of this eye model on standard biomarkers such as Alexa Fluor 532 and Alexa Fluor 594.

Purpose Lens opacification is a common complication after pars plana vitrectomy (PPV) and knowing its progression would facilitate consulting patients. The purpose of this study was to evaluate a quantitative model for lens-status-monitoring after PPV with C3F8 gas. Our model was evaluated in rhegmatogenous retinal detachment (RRD) patients of various age and lens densitometry (LD). Methods Data between March 2018 and March 2020 were evaluated retrospectively. LD measurements of the PentacamHR® Nucleus Staging mode (PNS) were used to quantify lens opacification over time. A mixed-effect regression model was designed, to enable LD predictions at any time postoperatively. Calculations were based on patient’s age and baseline LD as dependent variables. Six patients were randomly excluded during model development, to be used for testing its power afterwards. Results 34 patients (male 19 [55.9%], female 15 [44.1%]) matched the inclusion criteria. Average age was 58.5 years (32–77;±4.3) and average follow-up was 7.2 months (3,4–23.1;±1,8). Mean baseline LD of the treated and fellow eye before surgery were 10.9% (8.7%-14.8%;±0.8) and 10.7% (8.5%-14.1%;±0.6), respectively. Using our prediction model, LD values for the six pre-selected patients closely match the observed data with an average deviation of 1.07%. Conclusions Evaluation of age and baseline LD using a mixed-effect regression model might predict cataract progression in RRD patients treated with PPV and C3F8-gas. Such a tool could be considered during cataract surgery consultation in these patients.