Classification algorithms based on anterior segment optical coherence tomography measurements for detection of angle closure

Monisha E. Nongpiur, Benjamin A. Haaland, David S Friedman, Shamira A. Perera, Mingguang He, Li Lian Foo, Mani Baskaran, Lisandro M. Sakata, Tien Y. Wong, Tin Aung

Research output: Contribution to journalArticle

Abstract

Objective: A recent study found that a combination of 6 anterior segment optical coherence tomography (ASOCT) parameters (anterior chamber area, volume, and width [ACA, ACV, ACW], lens vault [LV], iris thickness at 750 μm from the scleral spur, and iris cross-sectional area) explain >80% of the variability in angle width. The aim of this study was to evaluate classification algorithms based on ASOCT measurements for the detection of gonioscopic angle closure. Design: Cross-sectional study. Participants: We included 2047 subjects aged ≥50 years. Methods: Participants underwent gonioscopy and ASOCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters in horizontal ASOCT scans. Six classification algorithms were considered (stepwise logistic regression with Akaike information criterion, Random Forest, multivariate adaptive regression splines, support vector machine, naïve Bayes' classification, and recursive partitioning). The ASOCT-derived parameters were incorporated to generate point and interval estimates of the area under the receiver operating characteristic (AUC) curves for these algorithms using 10-fold cross-validation as well as 50:50 training and validation. Main Outcome Measures: We assessed ASOCT measurements and angle closure. Results: Data on 1368 subjects, including 295 (21.6%) subjects with gonioscopic angle closure were available for analysis. The mean (± standard deviation) age was 62.4±7.5 years and 54.8% were females. Angle closure subjects were older and had smaller ACW, ACA, and ACV; greater LV; and thicker irides (P95% of the time. Financial Disclosure(s): The authors have no proprietary or commercial interest in any of the materials discussed in this article.

Original languageEnglish (US)
Pages (from-to)48-54
Number of pages7
JournalOphthalmology
Volume120
Issue number1
DOIs
StatePublished - Jan 2013

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Optical Coherence Tomography
Iris
Lenses
Gonioscopy
Disclosure
Anterior Chamber
ROC Curve
Area Under Curve
China
Software
Cross-Sectional Studies
Logistic Models
Outcome Assessment (Health Care)

ASJC Scopus subject areas

  • Ophthalmology

Cite this

Classification algorithms based on anterior segment optical coherence tomography measurements for detection of angle closure. / Nongpiur, Monisha E.; Haaland, Benjamin A.; Friedman, David S; Perera, Shamira A.; He, Mingguang; Foo, Li Lian; Baskaran, Mani; Sakata, Lisandro M.; Wong, Tien Y.; Aung, Tin.

In: Ophthalmology, Vol. 120, No. 1, 01.2013, p. 48-54.

Research output: Contribution to journalArticle

Nongpiur, ME, Haaland, BA, Friedman, DS, Perera, SA, He, M, Foo, LL, Baskaran, M, Sakata, LM, Wong, TY & Aung, T 2013, 'Classification algorithms based on anterior segment optical coherence tomography measurements for detection of angle closure', Ophthalmology, vol. 120, no. 1, pp. 48-54. https://doi.org/10.1016/j.ophtha.2012.07.005
Nongpiur, Monisha E. ; Haaland, Benjamin A. ; Friedman, David S ; Perera, Shamira A. ; He, Mingguang ; Foo, Li Lian ; Baskaran, Mani ; Sakata, Lisandro M. ; Wong, Tien Y. ; Aung, Tin. / Classification algorithms based on anterior segment optical coherence tomography measurements for detection of angle closure. In: Ophthalmology. 2013 ; Vol. 120, No. 1. pp. 48-54.
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abstract = "Objective: A recent study found that a combination of 6 anterior segment optical coherence tomography (ASOCT) parameters (anterior chamber area, volume, and width [ACA, ACV, ACW], lens vault [LV], iris thickness at 750 μm from the scleral spur, and iris cross-sectional area) explain >80{\%} of the variability in angle width. The aim of this study was to evaluate classification algorithms based on ASOCT measurements for the detection of gonioscopic angle closure. Design: Cross-sectional study. Participants: We included 2047 subjects aged ≥50 years. Methods: Participants underwent gonioscopy and ASOCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters in horizontal ASOCT scans. Six classification algorithms were considered (stepwise logistic regression with Akaike information criterion, Random Forest, multivariate adaptive regression splines, support vector machine, na{\"i}ve Bayes' classification, and recursive partitioning). The ASOCT-derived parameters were incorporated to generate point and interval estimates of the area under the receiver operating characteristic (AUC) curves for these algorithms using 10-fold cross-validation as well as 50:50 training and validation. Main Outcome Measures: We assessed ASOCT measurements and angle closure. Results: Data on 1368 subjects, including 295 (21.6{\%}) subjects with gonioscopic angle closure were available for analysis. The mean (± standard deviation) age was 62.4±7.5 years and 54.8{\%} were females. Angle closure subjects were older and had smaller ACW, ACA, and ACV; greater LV; and thicker irides (P95{\%} of the time. Financial Disclosure(s): The authors have no proprietary or commercial interest in any of the materials discussed in this article.",
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AU - Nongpiur, Monisha E.

AU - Haaland, Benjamin A.

AU - Friedman, David S

AU - Perera, Shamira A.

AU - He, Mingguang

AU - Foo, Li Lian

AU - Baskaran, Mani

AU - Sakata, Lisandro M.

AU - Wong, Tien Y.

AU - Aung, Tin

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N2 - Objective: A recent study found that a combination of 6 anterior segment optical coherence tomography (ASOCT) parameters (anterior chamber area, volume, and width [ACA, ACV, ACW], lens vault [LV], iris thickness at 750 μm from the scleral spur, and iris cross-sectional area) explain >80% of the variability in angle width. The aim of this study was to evaluate classification algorithms based on ASOCT measurements for the detection of gonioscopic angle closure. Design: Cross-sectional study. Participants: We included 2047 subjects aged ≥50 years. Methods: Participants underwent gonioscopy and ASOCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters in horizontal ASOCT scans. Six classification algorithms were considered (stepwise logistic regression with Akaike information criterion, Random Forest, multivariate adaptive regression splines, support vector machine, naïve Bayes' classification, and recursive partitioning). The ASOCT-derived parameters were incorporated to generate point and interval estimates of the area under the receiver operating characteristic (AUC) curves for these algorithms using 10-fold cross-validation as well as 50:50 training and validation. Main Outcome Measures: We assessed ASOCT measurements and angle closure. Results: Data on 1368 subjects, including 295 (21.6%) subjects with gonioscopic angle closure were available for analysis. The mean (± standard deviation) age was 62.4±7.5 years and 54.8% were females. Angle closure subjects were older and had smaller ACW, ACA, and ACV; greater LV; and thicker irides (P95% of the time. Financial Disclosure(s): The authors have no proprietary or commercial interest in any of the materials discussed in this article.

AB - Objective: A recent study found that a combination of 6 anterior segment optical coherence tomography (ASOCT) parameters (anterior chamber area, volume, and width [ACA, ACV, ACW], lens vault [LV], iris thickness at 750 μm from the scleral spur, and iris cross-sectional area) explain >80% of the variability in angle width. The aim of this study was to evaluate classification algorithms based on ASOCT measurements for the detection of gonioscopic angle closure. Design: Cross-sectional study. Participants: We included 2047 subjects aged ≥50 years. Methods: Participants underwent gonioscopy and ASOCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure ASOCT parameters in horizontal ASOCT scans. Six classification algorithms were considered (stepwise logistic regression with Akaike information criterion, Random Forest, multivariate adaptive regression splines, support vector machine, naïve Bayes' classification, and recursive partitioning). The ASOCT-derived parameters were incorporated to generate point and interval estimates of the area under the receiver operating characteristic (AUC) curves for these algorithms using 10-fold cross-validation as well as 50:50 training and validation. Main Outcome Measures: We assessed ASOCT measurements and angle closure. Results: Data on 1368 subjects, including 295 (21.6%) subjects with gonioscopic angle closure were available for analysis. The mean (± standard deviation) age was 62.4±7.5 years and 54.8% were females. Angle closure subjects were older and had smaller ACW, ACA, and ACV; greater LV; and thicker irides (P95% of the time. Financial Disclosure(s): The authors have no proprietary or commercial interest in any of the materials discussed in this article.

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