The African Descent and Glaucoma Evaluation Study (ADAGES) III: Contribution of Genotype to Glaucoma Phenotype in African Americans: Study Design and Baseline Data.

Purpose: To describe the study protocol and baseline characteristics of the African Descent and Glaucoma Evaluation Study (ADAGES) III.

Design: Cross-sectional, case-control study.

Participants: Three thousand two hundred sixty-six glaucoma patients and control participants without glaucoma of African or European descent were recruited from 5 study centers in different regions of the United States.

The Association Between Macula and ONH Optical Coherence Tomography Angiography (OCT-A) Vessel Densities in Glaucoma, Glaucoma Suspect, and Healthy Eyes.

Purpose: To evaluate strength of associations between optical coherence tomography (OCT)-angiography vessel density (VD) measurements in the macula and peripapillary region of the optic nerve head (ONH) with standard structural OCT thickness measures.

Materials And Methods: This cross-sectional study included 333 eyes of 219 primary open-angle glaucoma patients, 41 glaucoma suspects, and 73 healthy participants from the Diagnostic Innovations in Glaucoma Study (DIGS) with good quality OCT angiography images. The strength of associations between microvasculature measures in the ONH retinal nerve fiber layer (RNFL) and superficial macula layer was assessed using linear regression models.

Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification.

The inner surface of the retina contains a complex mixture of neurons, glia, and vasculature, including retinal ganglion cells (RGCs), the final output neurons of the retina and primary neurons that are damaged in several blinding diseases. The goal of the current work was two-fold: to assess the feasibility of using computer-assisted detection of nuclei and random forest classification to automate the quantification of RGCs in hematoxylin/eosin (H&E)-stained retinal whole-mounts; and if possible, to use the approach to examine how nuclear size influences disease susceptibility among RGC populations. To achieve this, data from RetFM-J, a semi-automated ImageJ-based module that detects, counts, and collects quantitative data on nuclei of H&E-stained whole-mounted retinas, were used in conjunction with a manually curated set of images to train a random forest classifier.

RetFM-J, an ImageJ-based module for automated counting and quantifying features of nuclei in retinal whole-mounts.

The present article introduces RetFM-J, a semi-automated ImageJ-based module that detects, counts, and collects quantitative data on nuclei of the inner retina from H&E-stained whole-mounted retinas. To illustrate performance, computer-derived outputs were analyzed in inbred C57BL/6J mice. Automated characterization yielded computer-derived outputs that closely matched manual counts.