We developed a statistical model based on quantitative characteristics of drusen to estimate the likelihood of conversion from early and intermediate age-related macular degeneration (AMD) to its advanced exudative form (AMD progression) in the short term (less than 5 years), a crucial task to enable early intervention and improve outcomes. Image features of drusen quantifying their number, morphology, and reflectivity properties, as well as the longitudinal evolution in these characteristics, were automatically extracted from 2146 spectral-domain optical coherence tomography (SD-OCT) scans of 330 AMD eyes in 244 patients collected over a period of 5 years, with 36 eyes showing progression during clinical follow-up. We developed and evaluated a statistical model to predict the likelihood of progression at predetermined times using clinical and image features as predictors. Area, volume, height, and reflectivity of drusen were informative features distinguishing between progressing and nonprogressing cases. Discerning progression at follow-up (mean, 6.16 months) resulted in a mean area under the receiver operating characteristic curve (AUC) of 0.74 (95% confidence interval [CI], 0.58, 0.85). The maximum predictive performance was observed at 11 months after a patient's first early AMD diagnosis, with mean AUC 0.92 (95% CI, 0.83, 0.98). Those eyes predicted to progress showed a much higher progression rate than those predicted not to progress at any given time from the initial visit. Our results demonstrate the potential ability of our model to identify those AMD patients at risk of progressing to exudative AMD from an early or intermediate stage.

We describe the use of chick chorioallantoic membrane (CAM) as a model system for the study of the precision and safety of vitreoretinal microsurgical instruments and techniques. The CAM was prepared for experimentation with and without its inner shell membrane (ISM) attached for in vivo and in vitro experiments that simulated medical and surgical interventions on the retina. The CAM’s ease of use, low cost, and anatomic structure make it a convenient model for surgical retinal and retinal vascular modeling. While CAM has been used extensively in the past for ocular angiogenesis studies, we describe the tissue as a useful tool for a variety of other applications, including (1) testing of novel surgical tools and techniques for cutting and coagulating retina and its vasculature, (2) testing vessel cannulation and injection techniques, (3) angiographic studies, and (4) endoscopic surgery.

We propose a hybrid sequential prediction model called “Deep Sequence”, integrating radiomics-engineered imaging features, demographic, and visual factors, with a recursive neural network (RNN) model in the same platform to predict the risk of exudation within a future time-frame in non-exudative AMD eyes. The proposed model provides scores associated with risk of exudation in the short term (within 3 months) and long term (within 21 months), handling challenges related to variability of OCT scan characteristics and the size of the training cohort. We used a retrospective clinical trial dataset that includes 671 AMD fellow eyes with 13,954 observations before any signs of exudation for training and validation in a tenfold cross validation setting. Deep Sequence achieved high performance for the prediction of exudation within 3 months (0.96 ± 0.02 AUCROC) and within 21 months (0.97 ± 0.02 AUCROC) on cross-validation. Training the proposed model on this clinical trial dataset and testing it on an external real-world clinical dataset showed high performance for the prediction within 3-months (0.82 AUCROC) but a clear decrease in performance for the prediction within 21-months (0.68 AUCROC). While performance differences at longer time intervals may be derived from dataset differences, we believe that the high performance and generalizability achieved in short-term predictions may have a high clinical impact allowing for optimal patient follow-up, adding the possibility of more frequent, detailed screening and tailored treatments for those patients with imminent risk of exudation.