Establishment and Comparison of Algorithms for Detection of Primary Angle Closure Suspect Based on Static and Dynamic Anterior Segment Parameters

Thomas

et al. 2021

Acta Ophthalmologica

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Purpose To investigate the development of angle closure from baseline open angle and associated risk factors in a rural Chinese population through a longitudinal study over a 5‐year period. Methods Subjects aged ≥30 years and older with bilateral open angles at baseline of the Handan Eye Study who participated in the follow‐up and had undergone both baseline and follow‐up gonioscopic examinations were included. Subjects with any form of angle closure, glaucoma, incisional ocular surgery or other conditions that could influence the results were excluded. The development of angle closure was defined as the presence of primary angle closure suspect (PACS) or primary angle closure (PAC)/primary angle closure glaucoma (PACG) during the follow‐up in normal subjects with baseline bilateral open angles. Logistic regression was performed to identify the baseline risk factors for the development of angle closure. Results A total of 457 subjects with bilateral open angles at baseline aged 53.0 (45.5, 58.0) years were enrolled. 94.7% of the included cases developed PACS, 5.3% developed PAC and no one developed PACG after 5 years. In logistic regression, significant risk factors for the development of angle closure were shallower central anterior chamber depth (ACD) (p = 0.002) and narrower mean angle width (p < 0.001). Conclusions This study reports the development from baseline open angle to angle closure after a 5‐year follow‐up. We confirm that the mean angle width and central ACD were independent predictive risk factors for the development of any form of angle closure.

Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

Development of angle closure and associated risk factors: The Handan eye study

Thomas

et al. 2021

Acta Ophthalmologica

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“…Zhang et al 26 , 27 have developed several algorithms for detecting PAC using AS-OCT by mechanisms of angle closure: pupillary block, plateau iris configuration, thick peripheral iris roll, and all three mechanisms. The authors measured 12 anterior segment parameters twice under different lighting conditions.…”

Section: Discussionmentioning

confidence: 99%

“… Lens vault seems to increase with a larger pupil, which also seems to happen in the real eye but with a lesser magnitude. 24 , 26 …”

Section: Discussionmentioning

confidence: 99%

Development of a β-Variational Autoencoder for Disentangled Latent Space Representation of Anterior Segment Optical Coherence Tomography Images

Shon

Sung

Kwak

et al. 2022

Trans. Vis. Sci. Tech.

Purpose To investigate the feasibility of extracting a low-dimensional latent structure of anterior segment optical coherence tomography (AS-OCT) images by use of a β-variational autoencoder (β-VAE). Methods We retrospectively collected 2111 AS-OCT images from 2111 eyes of 1261 participants from the ongoing Asan Glaucoma Progression Study. After hyperparameter optimization, the images were analyzed with β-VAE. Results The mean participant age was 64.4 years, with mean values of visual field index and mean deviation of 86.4% and −5.33 dB, respectively. After experiments, a latent space size of 6 and β value of 5 3 were selected for latent space analysis with β-VAE. Latent variables were successfully disentangled, showing readily interpretable distinct characteristics, such as the overall depth and area of the anterior chamber (η1), pupil diameter (η2), iris profile (η3 and η4), and corneal curvature (η5). Conclusions β-VAE can successfully be applied for disentangled latent space representation of AS-OCT images, revealing the high possibility of applying unsupervised learning in the medical image analysis. Translational Relevance This study demonstrates that a deep learning–based latent space model can be applied for the analysis of AS-OCT images.

“…In a previous study, we had investigated algorithms for detection of PACS by combining static and dynamic ASOCT parameters and found that the three algorithms including BLR, NBC and NN failed to meet the requirements for population‐based screening of PACS; NN had the largest AUC of 0.844 (Zhang et al 2020 ). The current investigation shows potential for the development of an image‐based non‐contact method to screen for PACS, which is the ASOCT examinations under both light and dark conditions.…”

Section: Discussionmentioning

confidence: 99%

Detection of primary angleclosure suspect with different mechanisms of angle closure using multivariate prediction models

Dong

et al. 2020

Acta Ophthalmologica

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Purpose We had found that a multivariate prediction model used for the detection of primary angle‐closure suspects (PACS) by combining multiple static and dynamic anterior segment optical coherence tomography (ASOCT) parameters had an area under the receiver operating characteristic curve (AUC) of 0.844. We undertook this study to evaluate this method in screening of PACS with different dominant mechanisms of angle closure (AC). Methods The right eyes of subjects aged ≥40 years who participated in the 5‐year follow‐up of the Handan Eye Study and had undergone gonioscopy and ASOCT examinations under light and dark conditions were included. All ASOCT images were analysed by the Zhongshan Angle Assessment Program. The dominant AC mechanism in each eye was determined to be pupillary block (PB), plateau iris configuration (PIC) or thick peripheral iris roll (TPIR). Backward logistic regression (LR) was used for inclusion of variables in the prediction models. LR, Naïve Bayes’ classification (NBC) and neural network (NN) were evaluated and compared using the AUC. Results Data from 796 subjects (413 PACS and 383 normal eyes) were analysed. The AUCs of LR, NBC and NN in the PB group were 0.920, 0.918 and 0.917. The AUCs of LR, NBC and NN in the PIC group were 0.715, 0.708 and 0.707. The AUCs of LR, NBC and NN in TPIR group were 0.867, 0.833 and 0.886. Conclusions Prediction models showed the best performance for detection of PACS with PB mechanism for AC and have potential for screening of PACS.