ArticleTranslational vision science & technology2021
Focal Loss Analysis of Nerve Fiber Layer Reflectance for Glaucoma Diagnosis.
Article in Translational vision science & technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 1 citations in OpenAlex.
- Prediction of primary glaucoma: development and validation of multiple machine learning models.Scientific reports · 2026Article
- Eccentricity-Dependent Reflectivity Rates-of-Change Across the Retina in Intermediate Age-Related Macular Degeneration.Investigative ophthalmology & visual science · 2026Article
- Inner Retinal Reflectivity Loss and Concurrent Thickening Predict Short-Term Conversion to Neovascular AMD.Investigative ophthalmology & visual science · 2026Article
- Artificial Intelligence-Driven Detection of LASIK Using Corneal Optical Coherence Tomography Maps.Translational vision science & technology · 2025Article
- Guidelines for glaucoma imaging classification, annotation, and quality control for artificial intelligence applications.International journal of ophthalmology · 2025Article
- Glaucoma Detection through a Novel Hyperspectral Imaging Band Selection and Vision Transformer Integration.Diagnostics (Basel, Switzerland) · 2024Article
- Article
- Predicting perimetric defects from en face maps of retinal nerve fibre layer reflectance.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2024Article
- Structure-function assessment in glaucoma based on perimetric sensitivity and en face optical coherence tomography images of retinal nerve fiber bundles.Scientific reports · 2023Article
- Adaptive IoU Thresholding for Improving Small Object Detection: A Proof-of-Concept Study of Hand Erosions Classification of Patients with Rheumatic Arthritis on X-ray Images.Diagnostics (Basel, Switzerland) · 2022Article
- Within-eye and between-subject variability for reflectance of the retinal nerve fibre layer.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2022Article
- Literature Review on Artificial Intelligence Methods for Glaucoma Screening, Segmentation, and Classification.Journal of imaging · 2022Review
- Enhanced Objective Detection of Retinal Nerve Fiber Bundle Defects in Glaucoma With a Novel Method for En Face OCT Slab Image Construction and Analysis.Translational vision science & technology · 2021Article
- A Simple Subjective Evaluation of Enface OCT Reflectance Images Distinguishes Glaucoma From Healthy Eyes.Translational vision science & technology · 2021Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
Purpose: To evaluate nerve fiber layer (NFL) reflectance for glaucoma diagnosis. Methods: Participants were imaged with 4.5 × 4.5 mm volumetric disc scans using spectral-domain optical coherence tomography. The normalized NFL reflectance map was processed by an azimuthal filter to reduce directional reflectance bias caused by variation of beam incidence angle. The peripapillary area of the map was divided into 160 superpixels. Average reflectance was the mean of superpixel reflectance. Low-reflectance superpixels were identified as those with NFL reflectance below the fifth percentile normative cutoff. Focal reflectance loss was measured by summing loss in low-reflectance superpixels. Results: Thirty-five normal, 30 preperimetric, and 35 perimetric glaucoma participants were enrolled. Azimuthal filtering improved the repeatability of the normalized NFL reflectance, as measured by the pooled superpixel standard deviation (SD), from 0.73 to 0.57 dB (P < 0.001, paired t-test) and reduced the population SD from 2.14 to 1.78 dB (P < 0.001, t-test). Most glaucomatous reflectance maps showed characteristic patterns of contiguous wedge or diffuse defects. Focal NFL reflectance loss had significantly higher diagnostic sensitivity than the best NFL thickness parameter (from map or profile): 77% versus 55% (P < 0.001) in glaucoma eyes with the specificity fixed at 99%. Conclusions: Azimuthal filtering reduces the variability of NFL reflectance measurements. Focal NFL reflectance loss has excellent glaucoma diagnostic accuracy compared to the standard NFL thickness parameters. The reflectance map may be useful for localizing NFL defects. Translational Relevance: The high diagnostic accuracy of NFL reflectance may make population-based screening feasible.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.