Ping Ma1, Yanyan Wu2, Julius Oatts3, Jutima Patlidanon3, Yinxi Yu4, Gui-Shuang Ying4, Brad Kline3, Tin A Tun5, Mingguang He6, Tin Aung7, Shuning Li8, Yangfan Yang9, Ying Han10. 1. From the Department of Ophthalmology (P.M., J.O., P.J., K.B., T.A.), University of California, San Francisco, San Francisco, Caliornia, USA; Department of Ophthalmology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China. 2. State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China. 3. From the Department of Ophthalmology (P.M., J.O., P.J., K.B., T.A.), University of California, San Francisco, San Francisco, Caliornia, USA. 4. Center for Preventive Ophthalmology and Biostatistics, Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, USA. 5. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore. 6. State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China;; Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia. 7. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 8. Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Sciences Key Laboratory, Beijing, China. 9. State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China;. Electronic address: yangyangfan23@126.com. 10. From the Department of Ophthalmology (P.M., J.O., P.J., K.B., T.A.), University of California, San Francisco, San Francisco, Caliornia, USA; From the Department of Ophthalmology (P.M., J.O., P.J., K.B., T.A.), University of California, San Francisco, San Francisco, Caliornia, USA; Ophthalmology Section, Surgical Service, San Francisco Veterans Affairs Medical Center, San Francisco, California, USA.. Electronic address: ying.han@ucsf.edu.
Abstract
PURPOSE: To evaluate the diagnostic performance of swept-source anterior segment optical coherence tomography (SS-OCT) in differentiating eyes with primary angle closure disease (PACD) from eyes of control subjects, as well as eyes with PAC and PAC glaucoma (PACG) from eyes with PAC suspect (PACS) disease. DESIGN: Multicenter cross-sectional study. METHODS: Chinese patients were classified into control, PACS, and PAC/PACG groups. The area under the receiving operating characteristic curve (AUC) from logistic regression models was used to evaluate discriminating ability. Sensitivity and specificity were calculated, and performance of the models was validated using an independent dataset. RESULTS: A total of 2928 SS-OCT images from 366 eyes of 260 patients were recruited to develop diagnostic models. The validation dataset included 1176 SS-OCT images from 147 eyes of 143 patients. For distinguishing PACD from control eyes, average anterior chamber depth had the highest AUC (0.94). With a cutoff of 2.2 mm for average anterior chamber depth, the sensitivity and specificity were 90.2% and 85.2% in the training set. For distinguishing PAC/PACG from PACS, a multivariate model had an AUC of 0.83, with sensitivity and specificity of 82.0% and 62.8% in the training set. The validation set confirmed the findings. CONCLUSIONS: SS-OCT of the anterior segment showed excellent diagnostic performance distinguishing PACD from normal eyes and moderate diagnostic ability distinguishing eyes with PAC/PACG from eyes with PACS. ACD alone may provide a simple and effective way to diagnose PACD from control subjects. As ACD can be obtained using other more available modalities, this has implications for the early diagnosis of PACD. Published by Elsevier Inc.
PURPOSE: To evaluate the diagnostic performance of swept-source anterior segment optical coherence tomography (SS-OCT) in differentiating eyes with primary angle closure disease (PACD) from eyes of control subjects, as well as eyes with PAC and PAC glaucoma (PACG) from eyes with PAC suspect (PACS) disease. DESIGN: Multicenter cross-sectional study. METHODS: Chinese patients were classified into control, PACS, and PAC/PACG groups. The area under the receiving operating characteristic curve (AUC) from logistic regression models was used to evaluate discriminating ability. Sensitivity and specificity were calculated, and performance of the models was validated using an independent dataset. RESULTS: A total of 2928 SS-OCT images from 366 eyes of 260 patients were recruited to develop diagnostic models. The validation dataset included 1176 SS-OCT images from 147 eyes of 143 patients. For distinguishing PACD from control eyes, average anterior chamber depth had the highest AUC (0.94). With a cutoff of 2.2 mm for average anterior chamber depth, the sensitivity and specificity were 90.2% and 85.2% in the training set. For distinguishing PAC/PACG from PACS, a multivariate model had an AUC of 0.83, with sensitivity and specificity of 82.0% and 62.8% in the training set. The validation set confirmed the findings. CONCLUSIONS: SS-OCT of the anterior segment showed excellent diagnostic performance distinguishing PACD from normal eyes and moderate diagnostic ability distinguishing eyes with PAC/PACG from eyes with PACS. ACD alone may provide a simple and effective way to diagnose PACD from control subjects. As ACD can be obtained using other more available modalities, this has implications for the early diagnosis of PACD. Published by Elsevier Inc.