Dacryocystitis: Is Dacryocystorhinostomy Always the Solution?

Background/Objectives: The aim of the study was to compare dacryocystectomy (DCT) versus dacryocystorhinostomy (DCR) in patients with dacryocystitis in terms of tearing complaints. Methods: We conducted a retrospective and comparative study on 19 patients. The main outcome measure was defined as an improvement by 1 point of the Munk score postoperatively. Results: A total of 19 patients were included with 10 in the DCR group and 9 in the DCT group. The primary endpoint was reached in 7 (70%) and in 6 (67%) patients in the DCR and DCT groups, respectively (p > 0.999). All DCR procedures were performed under general anesthesia (GA), while almost all DCT procedures were performed under local anesthesia (LA) (p < 0.001). There was a higher need for hospitalization in the DCR group (p < 0.001). Conclusions: Our preliminary results indicate that DCR is not always the solution in the case of dacryocystitis. DCT is a viable surgical procedure, especially in elderly patients without any tearing complaint and with underlying dry eye disease.

DeepAlienorNet: A deep learning model to extract clinical features from colour fundus photography in age-related macular degeneration.

OBJECTIVE: This study aimed to develop a deep learning (DL) model, named 'DeepAlienorNet', to automatically extract clinical signs of age-related macular degeneration (AMD) from colour fundus photography (CFP). METHODS AND ANALYSIS: The ALIENOR Study is a cohort of French individuals 77 years of age or older. A multi-label DL model was developed to grade the presence of 7 clinical signs: large soft drusen (>125 µm), intermediate soft (63-125 µm), large area of soft drusen (total area >500 µm), presence of central soft drusen (large or intermediate), hyperpigmentation, hypopigmentation, and advanced AMD (defined as neovascular or atrophic AMD). Prediction performances were evaluated using cross-validation and the expert human interpretation of the clinical signs as the ground truth. RESULTS: A total of 1178 images were included in the study. Averaging the 7 clinical signs' detection performances, DeepAlienorNet achieved an overall sensitivity, specificity, and AUROC of 0.77, 0.83, and 0.87, respectively. The model demonstrated particularly strong performance in predicting advanced AMD and large areas of soft drusen. It can also generate heatmaps, highlighting the relevant image areas for interpretation. CONCLUSION: DeepAlienorNet demonstrates promising performance in automatically identifying clinical signs of AMD from CFP, offering several notable advantages. Its high interpretability reduces the black box effect, addressing ethical concerns. Additionally, the model can be easily integrated to automate well-established and validated AMD progression scores, and the user-friendly interface further enhances its usability. The main value of DeepAlienorNet lies in its ability to assist in precise severity scoring for further adapted AMD management, all while preserving interpretability.

A Recurrent Orbital Hemorrhage in an Older Adult.

An adult patient in their 70s presented with unilateral painless proptosis and blurred vision of the right eye that resolved with corticosteroid treatment. Magnetic resonance imaging revealed a retrobulbar hemorrhage. Six months later, the hemorrhage and proptosis recurred, with incomplete resolution despite similar treatment. What would you do?