Macular hole morphology and measurement using an automated three dimensional image segmentation algorithm
| Autor: | Amar Vijai Nasrulloh, Caspar Geenen, Boguslaw Obara, Yunzi Chen, David H. W. Steel, Maged Habib, Ian J. Wilson |
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| Rok vydání: | 2020 |
| Předmět: |
retina
Morphology (linguistics) anatomy medicine.diagnostic_test imaging Image processing Vitreomacular traction medicine.disease Maxima and minima 03 medical and health sciences Ophthalmology diagnostic tests/investigation 0302 clinical medicine Optical coherence tomography 030221 ophthalmology & optometry medicine Image segmentation algorithm macula Maxima Macular hole 030217 neurology & neurosurgery Mathematics Biomedical engineering Original Research |
| Zdroj: | BMJ open ophthalmology, 2020, Vol.5(1), pp.e000404 [Peer Reviewed Journal] BMJ Open Ophthalmology |
| Popis: | 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 AnalysisAll 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. |
| Databáze: | OpenAIRE |
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