Christopher Bowd

Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.

Application of GD-CNN to fundus images from different settings and varying image quality demonstrated a high sensitivity, specificity, and generalizability for detecting GON.

Estimating Optical Coherence Tomography Structural Measurement Floors to Improve Detection of Progression in Advanced Glaucoma.

In advanced glaucoma, more GC-IPL tissue remains above the measurement floor compared with other measurements, suggesting GC-IPL thickness is the better candidate for detecting progression. Progression in SDOCT measurements is observable in advanced disease.

Measurement Floors and Dynamic Ranges of OCT and OCT Angiography in Glaucoma.

In late-stage glaucoma, particularly when VF MD is worse than -14 dB, OCTA-measured pfVD is a promising tool for monitoring progression because it does not have a detectable measurement floor.

Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps.

Deep learning models had high accuracy in identifying eyes with GFVD and predicting the severity of functional loss from SD OCT images.

Macular and Optic Nerve Head Vessel Density and Progressive Retinal Nerve Fiber Layer Loss in Glaucoma.

Lower baseline macular and optic nerve head (ONH) vessel density are associated with a faster rate of RNFL progression in mild to moderate glaucoma.

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

A computational approach can identify structural features that improve glaucoma detection and progression prediction.

Ganglion Cell Complex Thickness and Macular Vessel Density Loss in Primary Open-Angle Glaucoma.

Both GCC thinning and macular vessel density decrease were detectable over time in all diagnostic groups.

Association of Macular and Circumpapillary Microvasculature with Visual Field Sensitivity in Advanced Glaucoma.

ONH and macula OCTA VD and thickness are associated with the severity of visual field damage in advanced primary open angle glaucoma.

Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms.

Deep learning glaucoma detection can achieve high accuracy across diverse datasets with appropriate training strategies.

OCT Angiography Artifacts in Glaucoma.

OCTA artifacts associated with poor-quality images are frequent, and their prevalence is affected by ocular and patient characteristics.

Deep Learning Image Analysis of Optical Coherence Tomography Angiography Measured Vessel Density Improves Classification of Healthy and Glaucoma Eyes.

Deep learning en face image analysis improves on feature-based GBC models for classifying healthy and glaucoma eyes.

Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning.

The model's high diagnostic accuracy using OHTS photographs suggests that DL has the potential to standardize and automate POAG determination for clinical trials and management.

Gradient-Boosting Classifiers Combining Vessel Density and Tissue Thickness Measurements for Classifying Early to Moderate Glaucoma.

GBCs that combine OCTA and OCT macula and ONH measurements can improve diagnostic accuracy for glaucoma detection compared to most but not all instrument provided parameters.

Diagnostic Ability of Optical Coherence Tomography Angiography Macula Vessel Density for the Diagnosis of Glaucoma Using Difference Scan Sizes.

The diagnostic accuracy of VD using the 6×6 mm macula OCT-A scan was better than the 3×3 mm scan when differentiating between healthy and mild glaucoma eyes, and similar to the 3×3 mm scan when differentiating between healthy…

Racial Differences in Rate of Change of Spectral-Domain Optical Coherence Tomography-Measured Minimum Rim Width and Retinal Nerve Fiber Layer Thickness.

Race is an important consideration when assessing structural change, particularly minimum rim width, in glaucoma suspect eyes. Differences in rate of structural change may help explain racial disparities in glaucoma susceptibility.

Deep Learning Estimation of 10-2 and 24-2 Visual Field Metrics Based on Thickness Maps from Macula OCT.

Deep learning models improved estimates of functional loss from SD OCT imaging. Accurate estimates can help clinicians to individualize VF testing to patients.

Agreement Between 10-2 and 24-2C Visual Field Test Protocols for Detecting Glaucomatous Central Visual Field Defects.

Substantial agreement for identifying CVFDs using the 24-2C and 10-2 protocols suggests that combining tests by adding central test points to the 24-2 test grid may supplant the need for 2 perimetry regimens for detecting…

Superficial and Deep Macula Vessel Density in Healthy, Glaucoma Suspect, and Glaucoma Eyes.

SCP vessel densities have better diagnostic accuracy for detecting glaucoma than DCP vessel densities. Although the diagnostic accuracy of the macula SCP is relatively modest, it is more informative than the DCP.

A Longitudinal Analysis of Peripapillary Choroidal Thinning in Healthy and Glaucoma Subjects.

The rate of peripapillary choroidal thinning was not significantly different between healthy and glaucoma eyes during this relatively short follow-up period.

Individualized Glaucoma Change Detection Using Deep Learning Auto Encoder-Based Regions of Interest.

Eye-specific ROIs identified using DL-AE analysis of OCT images show promise for improving assessment of glaucomatous progression.

Relationship of Corneal Hysteresis and Anterior Lamina Cribrosa Displacement in Glaucoma.

Lower corneal hysteresis was significantly associated with posterior displacement of the anterior lamina cribrosa over time. These data provide additional support for lower corneal hysteresis being a risk factor for glaucoma progression.

Racial Differences in the Association of Anterior Lamina Cribrosa Surface Depth and Glaucoma Severity in the African Descent and Glaucoma Evaluation Study (ADAGES).

This study demonstrates that a deeper ALCSD, regardless of the ALCSD reference plane used, is associated with more severe glaucoma and higher IOP in the ADAGES cohort, particularly in individuals of AD.

Deep Learning Identifies High-Quality Fundus Photographs and Increases Accuracy in Automated Primary Open Angle Glaucoma Detection.

The DL quality model was able to accurately assess fundus photograph quality. Using automated quality assessment to filter out low-quality photographs increased the accuracy of a DL POAG detection model.

Association Between Lamina Cribrosa Defects and Progressive Retinal Nerve Fiber Layer Loss in Glaucoma.

These data suggest that LC defects are an independent risk factor for RNFL thinning and that glaucoma progression may correspond topographically to the LC defect location.

Estimated Utility of the Short-term Assessment of Glaucoma Progression Model in Clinical Practice.

In this cohort study, results from the STAGE model with reduction of the rate of progression as the end point, frequent testing, and a moderate effect size, suggest that clinical trials to test efficacy of…

A Deep Learning Approach to Improve Retinal Structural Predictions and Aid Glaucoma Neuroprotective Clinical Trial Design.

Our deep learning models were able to accurately estimate both macula GCIPL and ONH RNFL hemiretinal thickness.

Bruch Membrane Opening Detection Accuracy in Healthy Eyes and Eyes With Glaucoma With and Without Axial High Myopia in an American and Korean Cohort.

As BMO location inaccuracy was 2.4 times more likely in eyes with high axial myopia regardless of diagnosis, optical coherence tomography images of high myopes should be reviewed carefully, and when possible, BMO location should…

Diagnostic Accuracy of Macular Thickness Map and Texture En Face Images for Detecting Glaucoma in Eyes With Axial High Myopia.

The current results suggest that our novel en face texture-based analysis method can improve on most investigated macular tissue thickness measurements for discriminating between highly myopic glaucomatous and highly myopic healthy eyes.

Macular Vessel Density in Glaucomatous Eyes With Focal Lamina Cribrosa Defects.

Although OCTA macular vessel density was not significantly different between eyes with and without LC defects, focal GCC loss in eyes with LC defects was different.

Diagnostic Accuracy of Optic Nerve Head and Macula OCT Parameters for Detecting Glaucoma in Eyes With and Without High Axial Myopia.

The diagnostic accuracy for pRNFL and GCIPL was high for high axial myopic eyes and shows promise for glaucoma detection in high myopes.

Impact of Pupil Dilation on Optical Coherence Tomography Angiography Retinal Microvasculature in Healthy Eyes.

Pupil dilation using topical 2.5% phenylephrine and 0.5% tropicamide results in a small but statistically significant reduction in non-HD ONH whole image and cpCD in healthy eyes.

Combined glaucoma and cataract surgery: Comparison of viscocanalostomy, endocyclophotocoagulation, and ab interno trabeculectomy.

All procedures significantly lowered IOP. Phacoemulsification-ab interno trabulectomy resulted in fewest complications and phacoviscocanalostomy led to the largest IOP drop and largest reduction of medications.

Comparison of Peripapillary Capillary Density in Glaucoma Patients of African and European Descent.

Although peripapillary capillary density parameters showed good diagnostic accuracy for detecting glaucoma in ED patients, their diagnostic accuracy was only modest in AD patients.

Multimodal Deep Learning Classifier for Primary Open Angle Glaucoma Diagnosis Using Wide-Field Optic Nerve Head Cube Scans in Eyes With and Without High Myopia.

Combining OCT-based RNFL thickness maps with texture-based en face images showed a better ability to discriminate between healthy and POAG than thickness maps alone, particularly in high axial myopic eyes.

Objective Quantification of Spontaneous Retinal Venous Pulsations Using a Novel Tablet-Based Ophthalmoscope.

Our results suggest that a novel tablet-based ophthalmoscope can aid in documenting and objectively quantifying SVPs in all patients.

Comparing optical coherence tomography radial and cube scan patterns for measuring Bruch's membrane opening minimum rim width (BMO-MRW) in glaucoma and healthy eyes: cross-sectional and longitudinal analysis.

Although the cube scan-based BMO-MRW was significantly smaller than the radial scan-based BMO-MRW, we found no significant difference between the two scan patterns for detecting glaucoma, identifying BMO location and measuring the rate of BMO-MRW change.

Racial Differences in the Rate of Change in Anterior Lamina Cribrosa Surface Depth in the African Descent and Glaucoma Evaluation Study.

Glaucomatous remodeling of the lamina cribrosa differs between AD and ED patients with glaucoma.

Capillary Density Measured by Optical Coherence Tomography Angiography in Glaucomatous Optic Disc Phenotypes.

OCTA-measured vessel density differs among optic disc phenotypes. Clinicians should be aware that the performance of OCTA for glaucoma diagnosis may be influenced by the optic disc phenotype.

The Association Between Regional Macula Vessel Density and Central Visual Field Damage in Advanced Glaucoma Eyes.

Given a stronger MVD-central 10-degree VF association compared with GCC, as well as stronger GCC-central 5-degree VF association compared with MVD, MVD and GCC are complementary measurements in eyes with advanced glaucoma.

Racial Differences in Diagnostic Accuracy of Retinal Nerve Fiber Layer Thickness in Primary Open-Angle Glaucoma.

OCT-RNFLT has lower diagnostic accuracy in eyes of AD compared to those of ED.

OCT-Angiography Face Mask-Associated Artifacts During the COVID-19 Pandemic.

Face mask wearing had no significant effect on area of artifacts or vessel density measurements. OCT-A vessel density measurements can be acquired reliably with face mask wear during the pandemic.

Agreement between Compass Fundus Perimeter New Grid and 10-2 Testing Protocols for Detecting Central Visual Field Defects.

Although the Compass NG detected fewer CVFDs than the 10-2 test protocol, it did detect CVFDs that were not observed in the Compass 24-2 test in patients with early glaucoma.

Performance of General-Purpose Vision Language Models and Ophthalmology Foundation Models in Glaucoma Detection and Function Prediction.

Fine-tuned VLMs demonstrated high performance in glaucoma detection and VF MD prediction, matching or exceeding specialized foundation models and traditional convolutional neural network (CNN)-based methods.

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

The 3D DL classifier showed significantly higher diagnostic accuracy than global GCIPL thickness but was similar in performance to the 3D CD-DL classifier.

Wide-Field Optical Coherence Tomography Imaging Improves Rate of Change Detection in Progressing Glaucomatous Eyes Compared With Standard-Field Imaging.

In this cohort that includes eyes with and without high axial myopia, the mean rate of retinal nerve fiber layer thinning measured using SWF images was faster in eyes with progressing glaucoma than in eyes with nonprogressing glaucoma.

Structural Change Can Be Detected in Advanced-Glaucoma Eyes.

Ganglion cell-inner plexiform layer and 3D volume BKDS show promise for identifying change in severely advanced glaucoma.

African Descent and Glaucoma Evaluation Study (ADAGES): Racial Differences in Optic Disc Hemorrhage and Beta-Zone Parapapillary Atrophy.

Subjects of ED are at higher risk for developing DH compared with AD subjects, whereas AD subjects have greater prevalence of βPPA.

Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields.

GEM-POP was significantly more sensitive to PGON than PoPLR and linear regression of MD and VFI in our sample, while providing localized progression information.

Rate and Pattern of Rim Area Loss in Healthy and Progressing Glaucoma Eyes.

Compared with healthy eyes, the mean rate of global rim area loss was 3.7 times faster and the mean rate of global percentage rim area loss was 5.4 times faster in progressing glaucoma eyes.

Does the Location of Bruch's Membrane Opening Change Over Time? Longitudinal Analysis Using San Diego Automated Layer Segmentation Algorithm (SALSA).

Bruch's membrane opening location was stable in normal and progressing glaucoma eyes with follow-up between 3 and 4 years indicating that it can be used as reference point in monitoring glaucoma progression.

The African Descent and Glaucoma Evaluation Study (ADAGES): predictors of visual field damage in glaucoma suspects.

In this cohort of glaucoma suspects with similar access to treatment, multivariate analysis revealed that at higher mean IOP during follow-up, individuals of African descent were more likely to develop VF damage than individuals of…

Response to comment on the article entitled "effect of improper scan alignment on retinal nerve fiber layer thickness measurements using stratus optical coherence tomograph" by Vizzeri G, et al published in J Glaucoma. 2008;17: 341-349.