Subgrouping of primary angle-closure suspects based on anterior segment optical coherence tomography parameters.

PURPOSE To identify subgroups of primary angle-closure suspects (PACS) based on anterior segment optical coherence tomography (AS-OCT) and biometric parameters. DESIGN Cross-sectional study. PARTICIPANTS We evaluated 243 PACS subjects in the primary group and 165 subjects in the validation group. METHODS Participants underwent gonioscopy and AS-OCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou, China) was used to measure AS-OCT parameters. An agglomerative hierarchical clustering method was first used to determine the optimum number of parameters to be included in the determination of subgroups. The best number of subgroups was then determined using Akaike Information Criterion (AIC) and Gaussian Mixture Model (GMM) methods. MAIN OUTCOME MEASURES Subgroups of PACS. RESULTS The mean age of the subjects was 64.8 years, and 65.02% were female. After hierarchical clustering, 1 or 2 parameters from each cluster were chosen to ensure representativeness of the parameters and yet keep a minimum of redundancy. The parameters included were iris area, anterior chamber depth (ACD), anterior chamber width (ACW), and lens vault (LV). With the use of GMM, the optimal number of subgroups as given by AIC was 3. Subgroup 1 was characterized by a large iris area, subgroup 2 was characterized by a large LV and a shallow ACD, and subgroup 3 was characterized by elements of both subgroups 1 and 2. The results were replicated in a second independent group of 165 PACS subjects. CONCLUSIONS Clustering analysis identified 3 distinct subgroups of PACS subjects based on AS-OCT and biometric parameters. These findings may be relevant for understanding angle-closure pathogenesis and management.

[1]  D. Friedman,et al.  Quantitative iris parameters and association with narrow angles. , 2010, Ophthalmology.

[2]  Clifford M. Hurvich,et al.  Regression and time series model selection in small samples , 1989 .

[3]  S. Sawaguchi,et al.  Uveal effusion in primary angle-closure glaucoma. , 2005, Ophthalmology.

[4]  N. Congdon,et al.  Screening techniques for angle-closure glaucoma in rural Taiwan. , 2009, Acta ophthalmologica Scandinavica.

[5]  N. Congdon,et al.  Age, gender, biometry, refractive error, and the anterior chamber angle among Alaskan Eskimos. , 2003, Ophthalmology.

[6]  Mingguang He,et al.  Iris Cross-sectional Area Decreases With Pupil Dilation and its Dynamic Behavior is a Risk Factor in Angle Closure , 2009, Journal of glaucoma.

[7]  Tin Aung,et al.  Changes in anterior segment morphology after laser peripheral iridotomy: an anterior segment optical coherence tomography study. , 2012, Ophthalmology.

[8]  Philippe Denis,et al.  Optical coherence tomography quantitative analysis of iris volume changes after pharmacologic mydriasis. , 2010, Ophthalmology.

[9]  D. Friedman,et al.  Lens vault, thickness, and position in Chinese subjects with angle closure. , 2011, Ophthalmology.

[10]  Tin Aung,et al.  Association of narrow angles with anterior chamber area and volume measured with anterior-segment optical coherence tomography. , 2011, Archives of ophthalmology.

[11]  Geoffrey J. McLachlan,et al.  Finite Mixture Models , 2019, Annual Review of Statistics and Its Application.

[12]  S. K. Seah,et al.  Screening for narrow angles in the singapore population: evaluation of new noncontact screening methods. , 2008, Ophthalmology.

[13]  S. K. Seah,et al.  Determinants of angle closure in older Singaporeans. , 2008, Archives of ophthalmology.

[14]  D. Friedman,et al.  Quantitative analysis of anterior segment optical coherence tomography images: the Zhongshan Angle Assessment Program , 2008, British Journal of Ophthalmology.

[15]  D. Friedman,et al.  Determinants of angle width in Chinese Singaporeans. , 2012, Ophthalmology.

[16]  Tien Yin Wong,et al.  Novel association of smaller anterior chamber width with angle closure in Singaporeans. , 2010, Ophthalmology.

[17]  H. Quigley,et al.  The number of people with glaucoma worldwide in 2010 and 2020 , 2006, British Journal of Ophthalmology.

[18]  Tin Aung,et al.  Increased lens vault as a risk factor for angle closure: confirmation in a Japanese population , 2012, Graefe's Archive for Clinical and Experimental Ophthalmology.

[19]  S. K. Seah,et al.  Anterior chamber depth and the risk of primary angle closure in 2 East Asian populations. , 2005, Archives of ophthalmology.

[20]  Kyung Rim Sung,et al.  A hierarchical cluster analysis of primary angle closure classification using anterior segment optical coherence tomography parameters. , 2013, Investigative ophthalmology & visual science.

[21]  P. Foster,et al.  The definition and classification of glaucoma in prevalence surveys , 2002, The British journal of ophthalmology.

[22]  N. Congdon,et al.  Possible mechanisms of primary angle-closure and malignant glaucoma. , 2003, Journal of glaucoma.

[23]  Philip Chan,et al.  Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms , 2004, 16th IEEE International Conference on Tools with Artificial Intelligence.

[24]  J. H. Ward Hierarchical Grouping to Optimize an Objective Function , 1963 .

[25]  Geoffrey J. McLachlan,et al.  Multivariate Normal Mixtures , 2005 .