Reproducibility of deep learning based scleral spur localisation and anterior chamber angle measurements from anterior segment optical coherence tomography images.
Liu Peng, Higashita Risa, Guo Philip Yawen, Okamoto Keiichiro, Li Fei, Nguyen Anwell, Sakata Rei, Duan Lixin, Aihara Makoto, Lin Shan
AI Summary
Deep learning accurately localizes the scleral spur and measures anterior chamber angles from AS-OCT images with reproducibility comparable to manual methods, offering a reliable automated tool for glaucoma assessment.
Abstract
Aims
To apply a deep learning model for automatic localisation of the scleral spur (SS) in anterior segment optical coherence tomography (AS-OCT) images and compare the reproducibility of anterior chamber angle (ACA) width between deep learning located SS (DLLSS) and manually plotted SS (MPSS).
Methods
In this multicentre, cross-sectional study, a test dataset comprising 5166 AS-OCT images from 287 eyes (116 healthy eyes with open angles and 171 eyes with primary angle-closure disease (PACD)) of 287 subjects were recruited from four ophthalmology clinics. Each eye was imaged twice by a swept-source AS-OCT (CASIA2, Tomey, Nagoya, Japan) in the same visit and one eye of each patient was randomly selected for measurements of ACA. The agreement between DLLSS and MPSS was assessed using the Euclidean distance (ED). The angle opening distance (AOD) of 750 µm (AOD750) and trabecular-iris space area (TISA) of 750 µm (TISA750) were calculated using the CASIA2 embedded software. The repeatability of ACA width was measured.
Results
The mean age was 60.8±12.3 years (range: 30-85 years) for the normal group and 63.4±10.6 years (range: 40-91 years) for the PACD group. The mean difference in ED for SS localisation between DLLSS and MPSS was 66.50±20.54 µm and 84.78±28.33 µm for the normal group and the PACD group, respectively. The span of 95% limits of agreement between DLLSS and MPSS was 0.064 mm for AOD750 and 0.034 mm 2 for TISA750. The respective repeatability coefficients of AOD750 and TISA750 were 0.049 mm and 0.026 mm 2 for DLLSS, and 0.058 mm and 0.030 mm 2 for MPSS.
Conclusion
DLLSS achieved comparable repeatability compared with MPSS for measurement of ACA.
MeSH Terms
Shields Classification
Key Concepts5
A deep learning model for automatic localization of the scleral spur (SS) in anterior segment optical coherence tomography (AS-OCT) images achieved comparable repeatability for anterior chamber angle (ACA) width measurements (angle opening distance of 750 µm (AOD750) and trabecular-iris space area of 750 µm (TISA750)) compared with manually plotted SS (MPSS).
The mean difference in Euclidean distance (ED) for scleral spur (SS) localization between deep learning located SS (DLLSS) and manually plotted SS (MPSS) was 66.50±20.54 µm for the normal group and 84.78±28.33 µm for the primary angle-closure disease (PACD) group in a multicentre, cross-sectional study.
The span of 95% limits of agreement between deep learning located scleral spur (DLLSS) and manually plotted scleral spur (MPSS) for angle opening distance of 750 µm (AOD750) was 0.064 mm and for trabecular-iris space area of 750 µm (TISA750) was 0.034 mm^2 in a multicentre, cross-sectional study.
The respective repeatability coefficients for angle opening distance of 750 µm (AOD750) and trabecular-iris space area of 750 µm (TISA750) were 0.049 mm and 0.026 mm^2 for deep learning located scleral spur (DLLSS), and 0.058 mm and 0.030 mm^2 for manually plotted scleral spur (MPSS) in a multicentre, cross-sectional study.
A test dataset comprising 5166 anterior segment optical coherence tomography (AS-OCT) images from 287 eyes (116 healthy eyes with open angles and 171 eyes with primary angle-closure disease (PACD)) of 287 subjects was recruited from four ophthalmology clinics for a multicentre, cross-sectional study on scleral spur localization and anterior chamber angle measurements.
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