Diagnostic Accuracy of 3D Deep Learning Classifiers for Glaucoma Detection: A Comparison of Cross-Domain and Device-Specific Models.

Purpose: To evaluate the accuracy of a three-dimensional (3D) deep learning (3D DL) and 3D cross domain deep learning (3D CD-DL) classifiers compared to standard macular ganglion cell-inner plexiform layer (GCIPL) thickness measurements for classifying eyes with glaucoma using optical coherence tomography (OCT).

Methods: A total of 502 primary open-angle glaucoma eyes from 295 patients and 119 healthy eyes from 63 individuals were included. Two classifiers were compared: (1) a 3D DL model trained on Spectralis macular OCT and applied to Spectralis macular OCT images and (2) 3D CD-DL model trained on synthetic Spectralis images generated from 3D Cirrus macular OCT using Cycle-consistent adversarial networks (CycleGAN) and applied to real Spectralis macula OCT images.

Glaucoma detection in myopic eyes using deep learning autoencoder-based regions of interest.

Purpose: To evaluate the diagnostic accuracy of a deep learning autoencoder-based model utilizing regions of interest (ROI) from optical coherence tomography (OCT) texture enface images for detecting glaucoma in myopic eyes.

Methods: This cross-sectional study included a total of 453 eyes from 315 participants from the multi-center "Swept-Source OCT (SS-OCT) Myopia and Glaucoma Study", composed of 268 eyes from 168 healthy individuals and 185 eyes from 147 glaucomatous individuals. All participants underwent swept-source optical coherence tomography (SS-OCT) imaging, from which texture enface images were constructed and analyzed.

Longitudinal Measurement of Optic Disc Vessel Density to Detect Glaucoma Progression in High Myopia.

Purpose: To investigate the relationship between optic disc vessel density (ODVD) reduction and visual field (VF) progression in highly myopic glaucomatous eyes.

Design: Retrospective observational case series.

Participants: One hundred and eighteen primary open-angle glaucoma (POAG) eyes with high myopia (axial length [AXL] ≥ 26.

Effect of Deep Optic Nerve Head Morphology on Lamina Cribrosa and Peripapillary Scleral Configurations in Healthy Eyes.

Purpose: The purpose of this study was to investigate the relationship among deep optic nerve head (ONH), lamina cribrosa (LC), and peripapillary sclera (pSc) configurations in healthy eyes.

Methods: This prospective cross-sectional study included 205 healthy eyes of 141 subjects. Multivariable linear mixed models identified factors associated with LC curvature index, prelaminar thickness (PLT), pSc angle, and LC depth (LCD).

Association Between Optic Nerve Head Prelaminar Schisis and Visual Field Progression in Glaucoma.

Purpose: To investigate the association between baseline optic nerve head prelaminar schisis and the rates of visual field mean deviation (VF MD) slopes in glaucoma.

Design: Retrospective clinical cohort study.

Methods: This study included 563 eyes (446 with primary open-angle glaucoma and 117 glaucoma suspect eyes) from 332 patients.

Relationship of 24-2C Central Visual Field Damage to Juxtapapillary Choriocapillaris Dropout in Glaucoma Eyes With or Without Axial Myopia.

Prcis: Larger choriocapillaris microvasculature dropout area and wider angular circumference are significantly associated with 24-2C central visual field damage in primary open angle glaucoma eyes with and without axial myopia.

Purpose: To evaluate the relationship between a juxtapapillary choriocapillaris microvasculature dropout (MvD) and central visual field (VF) damage in primary open angle glaucoma (POAG) patients with or without axial myopia.

Methods: This cross-sectional study included 125 patients with POAG or glaucoma suspects stratified into no axial myopia (axial length (AL) ≤24 mm; 46 eyes), mild axial myopia (24 mm < AL ≤26 mm; 81 eyes), and high axial myopia (AL >26 mm; 59 eyes).

Short-Term Rates of Visual Field Change Predict Glaucoma Progression.

Purpose: To explore the prognostic significance of short-term rates of visual field (VF) mean deviation (MD) change in predicting progression across various levels of glaucoma severity.

Design: Observational cohort.

Participants: A total of 349 eyes from 254 patients followed up to 5 years.

Differential Impact of Central and Global Visual Field Progression on Quality of Life in Glaucoma.

Purpose: To determine the impact of progression of central visual field (VF) and global VF on vision-related quality of life (VRQOL).

Design: Retrospective cohort study.

Methods: This study included 364 eyes of 235 primary open-angle glaucoma participants who had at least five 24-2 VF tests over a minimum of 2-year follow-up.

Impact of Physical Activity Levels on Visual Field Progression in Individuals With Glaucoma.

Prcis: Higher self-reported physical activity level was associated with a slower rate of visual field mean deviation loss in patients with primary open angle glaucoma.

Purpose: To determine the impact of physical activity (PA) on visual field (VF) progression rates in patients with primary open angle glaucoma (POAG).

Methods: In this longitudinal study, POAG patients were included who had ≥5 visits, ≥2 years of follow-up VFs and underwent PA questionnaire at the baseline.

Gap Analysis of Standard Automated Perimetry Concept Representation in Medical Terminologies.

Prcis: In this multi-institutional effort, we identified gaps in SAP data elements within medical terminologies. We proposed new concepts to LOINC to enhance SAP data standards and big data representation and improve interoperability across health care systems.

Purpose: To identify gaps in the representation of Standard Automated Perimetry (SAP) data elements in Logical Observation Identifiers Names and Codes (LOINC) and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) and propose solutions for those gaps.

Relationships between distance from the fovea to the disc and macular retinal layer thickness differ between normal and glaucomatous eyes.

A multicenter cross-sectional study was conducted to investigate the magnification-corrected association between fovea-disc distance (FDD) and optical coherence tomography (OCT)-measured macular retinal layer thickness in eyes with and without primary open-angle glaucoma (POAG). A 12.0 × 9.

Effects of a single osteopathic manipulative treatment on intraocular pressure reduction: a pilot study.

Context: Research on the effects of osteopathic manipulative treatment (OMT) on visual functions and conditions is very limited. This study continues the exploration on the application of OMT with the intent of lowering intraocular pressure (IOP).

Objectives: A pilot randomized clinical trial was conducted to assess the impact of one OMT session on patients diagnosed with suspected ocular hypertension (OHT) or glaucoma.

Deep Learning Approach Predicts Longitudinal Retinal Nerve Fiber Layer Thickness Changes.

This study aims to develop deep learning (DL) models to predict the retinal nerve fiber layer (RNFL) thickness changes in glaucoma, facilitating the early diagnosis and monitoring of disease progression. Using the longitudinal data from two glaucoma studies (Diagnostic Innovations in Glaucoma Study (DIGS) and African Descent and Glaucoma Evaluation Study (ADAGES)), we constructed models using optical coherence tomography (OCT) scans from 251 participants (437 eyes). The models were trained to predict the RNFL thickness at a future visit based on previous scans.

Optic Disc Size and Circumpapillary Retinal Nerve Fiber Layer Thinning in Glaucoma.

Purpose: To investigate the association between optic disc size and circumpapillary retinal nerve fiber layer (cpRNFL) thinning in eyes with preperimetric glaucoma and glaucoma.

Design: Observational cohort.

Participants: A total of 841 eyes (554 primary open angle glaucoma and 287 preperimetric glaucoma) from 553 patients who had at least 4 visits and 2 years of follow-up using OCT.

Risk of Falls, Fear of Falling, and Rates of Visual Field Progression in Glaucoma in the African Descent and Glaucoma Evaluation Study.

Purpose: To assess the relationships between rates of glaucomatous visual field (VF) progression, fear of falling (FoF), history of falls, and ancestry.

Design: Prospective, multicenter, longitudinal cohort.

Subjects: Patients followed in the multisite African Descent and Glaucoma Evaluation Study with primary open-angle glaucoma and who completed a validated fear of falling questionnaire along with a self-reported history of falls in the past year were enrolled.

Optic Disc Microvasculature Reduction and Visual Field Progression in Primary Open-Angle Glaucoma.

Purpose: To investigate the relationship between optic disc vessel density (ODVD) reduction and visual field (VF) progression in primary open-angle glaucoma (POAG) patients.

Design: Retrospective case series.

Methods: A total of 187 POAG eyes underwent ≥5 consecutive VF, spectral-domain optical coherence tomography, and swept-source OCT angiography imaging sessions during ≥3 years of follow-up.

Cross-sectional design and protocol for Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI).

Introduction: Artificial Intelligence Ready and Equitable for Diabetes Insights (AI-READI) is a data collection project on type 2 diabetes mellitus (T2DM) to facilitate the widespread use of artificial intelligence and machine learning (AI/ML) approaches to study salutogenesis (transitioning from T2DM to health resilience). The fundamental rationale for promoting health resilience in T2DM stems from its high prevalence of 10.5% of the world's adult population and its contribution to many adverse health events.

Glaucoma Detection and Feature Identification via GPT-4V Fundus Image Analysis.

Purpose: The aim is to assess GPT-4V's (OpenAI) diagnostic accuracy and its capability to identify glaucoma-related features compared to expert evaluations.

Design: Evaluation of multimodal large language models for reviewing fundus images in glaucoma.

Subjects: A total of 300 fundus images from 3 public datasets (ACRIMA, ORIGA, and RIM-One v3) that included 139 glaucomatous and 161 nonglaucomatous cases were analyzed.

Longitudinal Changes of Retinal Nerve Fiber Layer and Ganglion Cell-Inner Plexiform Layer in Highly Myopic Glaucoma: A 3-Year Cohort Study.

Purpose: To describe the longitudinal changes in peripapillary retinal nerve fiber layer (pRNFL) and macular ganglion cell-inner plexiform layer (mGC-IPL) thicknesses in highly myopic eyes with and without glaucoma and to investigate the effects of high myopia (HM) on the sectoral patterns of pRNFL and mGC-IPL thinning.

Design: Longitudinal cohort study.

Participants: A total of 243 eyes from 243 individuals with 3-year follow-up were included in this study: 109 eyes in the HM group, 64 eyes in the open-angle glaucoma (OAG) group, and 70 eyes in the highly myopic glaucoma (HMG) group.

Evaluating glaucoma in myopic eyes: Challenges and opportunities.

The increasing global prevalence of myopia presents a significant public health concern, and growing evidence has demonstrated that myopia is a major risk factor for the development of open-angle glaucoma. Therefore, timely detection and management of glaucoma in myopic patients are crucial; however, identifying the structural alterations of glaucoma in the optic nerve head (ONH) and retinal tissues of myopic eyes using standard diagnostic tools such as fundus photography, optical coherence tomography (OCT), and OCT angiography (OCTA) presents challenges. Additionally, myopia-related perimetric defects can be confounded with glaucoma-related defects.

Number of macula optical coherence tomography scans needed to detect glaucoma progression.

Background: To evaluate the impact of testing frequency on the time required to detect statistically significant glaucoma progression for ganglion cell complex (GCC) with optical coherence tomography (OCT).

Materials And Methods: From multicentre glaucoma registries, 332 eyes of 201 glaucoma patients were enrolled over an average of 4.4 years.

Evaluating a Foundation Artificial Intelligence Model for Glaucoma Detection Using Color Fundus Photographs.

Purpose: To evaluate RETFound, a foundation artificial intelligence model, using a diverse clinical research dataset to assess its accuracy in detecting glaucoma using optic disc photographs. The model's accuracy for glaucoma detection was evaluated across race, age, glaucoma severity, and various training cycles (epochs) and dataset sample sizes.

Design: Evaluation of a diagnostic technology.

The Development and Validation of a Glaucoma Health Score for Glaucoma Screening Based on Clinical Parameters and Optical Coherence Tomography Metrics.

This study aims to develop and validate a Glaucoma Health Score (GHS) that incorporates multiple individual glaucoma risk factors to enhance glaucoma detection in screening environments. The GHS was developed using a retrospective dataset from two clinical sites, including both eyes of glaucoma patients and controls. The model incorporated age, central corneal thickness, intraocular pressure, pattern standard deviation from a visual field threshold 24-2 test, and two parameters from an optical coherence tomography (OCT) test: the average circumpapillary retinal nerve fiber layer thickness and the minimum thickness of the six sectors of the macular ganglion cell plus the inner plexiform layer.

Longitudinal OCTA vessel density loss in macula and optic nerve head in healthy, glaucoma suspect and established glaucoma eyes.

Background/aims: To examine longitudinal optical coherence tomography angiography (OCTA) changes in macula and optic nerve head (ONH) in healthy, glaucoma suspect (GS) and primary open-angle glaucoma (POAG) eyes.

Methods: Healthy, GS and POAG eyes from Diagnostic Innovations in Glaucoma Study with ≥2 years follow-up and four visits of macular/ONH OCTA imaging were included. Rates of macular wiVD (whole-image vessel density) and ONH wiCD (whole-image capillary density) changes were calculated for each diagnosis group using join mixed-effect modelling.