ArticleBMJ open ophthalmology2020
Macular hole morphology and measurement using an automated three-dimensional image segmentation algorithm.
Article in BMJ open ophthalmology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Stage-Specific Morphofunctional Evaluation of Idiopathic Macular Holes Using En Face OCT Imaging.Ophthalmology science · 2026Article
- Automated measurement of the minimum macular hole diameter based on optical coherence tomography images.BMC ophthalmology · 2026Article
- Quantifying Explainability in OCT Segmentation of Macular Holes and Cysts: A SHAP-Based Coverage and Factor Contribution Analysis.Diagnostics (Basel, Switzerland) · 2025Article
- Volumetric Optical Coherence Tomography Analysis of Visual and Surgical Outcomes in Patients With Full-Thickness Macular Hole.Journal of vitreoretinal diseases · 2025Article
- Analysing the translatability of macular hole size measurements between high-density horizontal and radial OCT scan patterns.BMJ open ophthalmology · 2025Article
- Idiopathic Macular Hole Area to Foveal Avascular Zone Ratio and Its Effects on Visual Acuity Before and After Surgery.Translational vision science & technology · 2025Article
- Factors influencing the reliability of measurements in eyes with full-thickness macular holes: are we measuring incorrectly?BMJ open ophthalmology · 2024Observational
- Application of CT images for reconstruction of adigital model of the sacral nerve canal.American journal of translational research · 2024Article
- Surgical classification for large macular hole: based on different surgical techniques results: the CLOSE study group.International journal of retina and vitreous · 2023Article
- Automatic Determination of the Center of Macular Hole Using Optical Coherence Tomography En Face Images.Journal of clinical medicine · 2022Article
- A Tool for High-Resolution Volumetric Optical Coherence Tomography by Compounding Radial-and Linear Acquired B-Scans Using Registration.Sensors (Basel, Switzerland) · 2022Article
- Internal limiting membrane peeling for large macular hole: Tailoring the rhexis to the shape of the hole.Indian journal of ophthalmology · 2022Article
- Defining a Cutoff for Progression of Macular Holes.Translational vision science & technology · 2021Article
- Repeatability and Reproducibility of Macular Hole Size Measurements Using Optical Coherence Tomography.Journal of clinical medicine · 2021Article
- Predicting Postoperative Vision for Macular Hole with Automated Image Analysis.Ophthalmology. Retina · 2020Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveFull-thickness macular holes (MH) are classified principally by size, which is one of the strongest predictors of anatomical and visual success. Using a three-dimensional (3D) automated image processing algorithm, we analysed optical coherence tomography (OCT) images of 104 MH of patients, comparing MH dimensions and morphology with clinician-acquired two-dimensional measurements. METHODS AND ANALYSIS: All patients underwent a high-density central horizontal scanning OCT protocol. Two independent clinicians measured the minimum linear diameter (MLD) and maximum base diameter. OCT images were also analysed using an automated 3D segmentation algorithm which produced key parameters including the respective maximum and minimum diameter of the minimum area (MA) of the MH, as well as volume and surface area.
resultsUsing the algorithm-derived values, MH were found to have significant asymmetry in all dimensions. The minima of the MA were typically approximately 90° to the horizontal, and differed from their maxima by 55 μm. The minima of the MA differed from the human-measured MLD by a mean of nearly 50 μm, with significant interobserver variability. The resultant differences led to reclassification using the International Vitreomacular Traction Study Group classification in a quarter of the patients (p=0.07).
conclusionMH are complex shapes with significant asymmetry in all dimensions. We have shown how 3D automated analysis of MH describes their dimensions more accurately and repeatably than human assessment. This could be used in future studies investigating hole progression and outcome to help guide optimum treatments.
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