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Purpose: The purpose of this study was to develop a deep learning-based fully automated reconstruction and quantification algorithm which automatically delineates the neurites and somas of retinal ganglion cells (RGCs)., Methods: We trained a deep learning-based multi-task image segmentation model, RGC-Net, that automatically segments the neurites and somas in RGC images. A total of 166 RGC scans with manual annotations from human experts were used to develop this model, whereas 132 scans were used for training, and the remaining 34 scans were reserved as testing data. Post-processing techniques removed speckles or dead cells in soma segmentation results to further improve the robustness of the model. Quantification analyses were also conducted to compare five different metrics obtained by our automated algorithm and manual annotations., Results: Quantitatively, our segmentation model achieves average foreground accuracy, background accuracy, overall accuracy, and dice similarity coefficient of 0.692, 0.999, 0.997, and 0.691 for the neurite segmentation task, and 0.865, 0.999, 0.997, and 0.850 for the soma segmentation task, respectively., Conclusions: The experimental results demonstrate that RGC-Net can accurately and reliably reconstruct neurites and somas in RGC images. We also demonstrate our algorithm is comparable to human manually curated annotations in quantification analyses., Translational Relevance: Our deep learning model provides a new tool that can trace and analyze the RGC neurites and somas efficiently and faster than manual analysis.

Purpose of Review: Glaucoma drainage device (GDD) implantation surgery is commonly performed by glaucoma specialists to treat complex and refractory glaucomas. Relative safety and efficacy data from randomized controlled trials conducted in the last two decades have sparked the interest in GDDs as possible surgical options earlier in the course of the disease than has traditionally been practiced. However, until recently, advances in the design and techniques of GDD surgery have fallen short of this increasing interest., Recent Findings: Most recently, new GDDs that possess novel design features have become available to glaucoma specialists. Two of these new devices are the Ahmed ClearPath and the Paul glaucoma implant. These devices have demonstrated promising outcomes that are comparable to those of traditional implants. Additionally, given their unique respective features, these devices may streamline surgical technique due to ease of insertion and afford better safety and efficacy outcomes in certain patients., Summary: The recent introduction of new GDDs has been long awaited by glaucoma surgeons. Although early results are promising, long-term data and comparison of outcomes to those of traditional filtering surgery and commonly implanted devices are needed before these devices can be the new standard of care in glaucoma tube shunt surgery., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)