Diagnostic accuracy of swept source optical coherence tomography classification algorithms for detection of gonioscopic angle closure

PurposeTo evaluate the performance of swept source optical coherence tomography (SS-OCT) to detect gonioscopic angle closure using different classification algorithms.MethodsThis was a cross-sectional study of 2028 subjects without ophthalmic symptoms recruited from a community-based clinic. All sub...

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Vydané v:British journal of ophthalmology Ročník 106; číslo 12; s. 1716 - 1721
Hlavní autori: Tan, Shayne S, Tun, Tin A, Sultana, Rehena, Tan, Marcus, Quah, Joanne HuiMin, Mani, Baskaran, Allen, John C, Cheng, Ching Yu, Nongpiur, Monisha Esther, Aung, Tin
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: BMA House, Tavistock Square, London, WC1H 9JR BMJ Publishing Group Ltd 01.12.2022
BMJ Publishing Group LTD
Predmet:
Algorithms
angle
anterior chamber
Clinical science
glaucoma
imaging
Medical diagnosis
Ophthalmology
Performance evaluation
Regression analysis
Tomography
ISSN:0007-1161, 1468-2079, 1468-2079
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Shrnutí:PurposeTo evaluate the performance of swept source optical coherence tomography (SS-OCT) to detect gonioscopic angle closure using different classification algorithms.MethodsThis was a cross-sectional study of 2028 subjects without ophthalmic symptoms recruited from a community-based clinic. All subjects underwent gonioscopy and SS-OCT (Casia, Tomey Corporation, Nagoya, Japan) under dark room conditions. For each eye, 8 out of 128 frames (22.5° interval) were selected to measure anterior chamber parameters namely anterior chamber width, depth, area and volume (ACW, ACD, ACA, and ACV), lens vault (LV), iris curvature (IC), iris thickness (IT) from 750 µm and 2000 µm from the scleral spur, iris area and iris volume. Five diagnostic algorithms—stepwise logistic regression, random forest, multivariate adaptive regression splines, recursive partitioning and Naïve Bayes were evaluated for detection of gonioscopic angle closure (defined as ≥2 closed quadrants). The performance of the horizontal frame was compared with that of other meridians.ResultsData from 1988 subjects, including 143 (7.2%) with gonioscopic angle closure, were available for analysis. They were divided into two groups: training (1391, 70%) and validation (597, 30%). The best algorithm for detecting gonioscopic angle closure was stepwise logistic regression with an area under the curve of 0.91 (95% CI 0.88 to 0.93) using all parameters, and 0.88 (95% CI 0.82 to 0.93) using only ACA, LV and IC of the horizontal meridian scan.ConclusionsA stepwise logistic regression model incorporating SS-OCT measurements has a high diagnostic ability to detect gonioscopic angle closure.
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ISSN:0007-1161
1468-2079
1468-2079
DOI:10.1136/bjophthalmol-2021-319165