Jacqueline Chua1, Bingyao Tan2, Mengyuan Ke2, Florian Schwarzhans3, Clemens Vass4, Damon Wong5, Monisha E Nongpiur1, Mae Chui Wei Chua6, Xinwen Yao7, Ching-Yu Cheng8, Tin Aung8, Leopold Schmetterer9. 1. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Academic Clinical Program, Duke-NUS Medical School, Singapore. 2. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore. 3. Center for Medical Statistics Informatics and Intelligent Systems, Section for Medical Information Management and Imaging, Medical University Vienna, Vienna, Austria. 4. Department of Ophthalmology and Optometry, Medical University Vienna, Vienna, Austria. 5. SERI-NTU Advanced Ocular Engineering (STANCE), Singapore; Department of Ophthalmology, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore. 6. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore. 7. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore; Department of Ophthalmology, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore. 8. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Academic Clinical Program, Duke-NUS Medical School, Singapore; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore. 9. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Academic Clinical Program, Duke-NUS Medical School, Singapore; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore; Department of Ophthalmology, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Department of Clinical Pharmacology, Medical University Vienna, Vienna, Austria; Center for Medical Physics and Biomedical Engineering, Medical University Vienna, Vienna, Austria; Institute of Ophthalmology, Basel, Switzerland. Electronic address: leopold.schmetterer@seri.com.sg.
Abstract
PURPOSE: To compare the diagnostic ability of macular intraretinal layer thickness with circumpapillary retinal nerve fiber layer (cpRNFL) thickness, either when used individually or in combination with cpRNFL for detecting early, moderate, and advanced glaucoma. DESIGN: Cross-sectional study. PARTICIPANTS: A total of 423 glaucoma participants and 423 age- and gender-matched normal participants. METHODS: Participants underwent Cirrus spectral-domain OCT (SD-OCT) imaging (Carl Zeiss Meditec, Dublin, CA) using the optic disc and macular scanning protocols. Iowa Reference Algorithms (version 3.8.0) were used for intraretinal layer segmentation, and mean thickness of intraretinal layers was rescaled with magnification correction using axial length value. Thickness measurements of each layer/sector and their corresponding areas under the receiver operating characteristic curve (AUCs) were obtained. Glaucoma eyes were subdivided based on of their visual field severity (early, n = 234; moderate, n = 107; advanced, n = 82). MAIN OUTCOME MEASURES: Intraretinal layers. RESULTS: Some 67% of participants were male, their average ± standard deviation age was 65±9 years. Circumpapillary retinal nerve fiber layer, macular ganglion cell layer (mGCL), and macular inner plexiform layer (mIPL) were significantly thinner in the glaucoma groups (P < 0.0005). The 2 best parameters for detecting normal eyes from early glaucoma was cpRNFL (AUC = 0.861) and mGCL (AUC = 0.842), from moderate glaucoma was mGCL combined with inner plexiform layer (IPL) (AUC = 0.915) and cpRNFL (AUC = 0 .914), and from advanced glaucoma was mGCL-IPL (AUC = 0.984) and cpRNFL (AUC = 0.977). There was no statistical significance between AUCs for the macular parameter and cpRNFL thickness measurement at any of the severities (P > 0.05). Combining macular and cpRNFL parameters improved the diagnostic performance for early glaucoma (AUC = 0.908; P = 0.002) and moderate glaucoma (AUC = 0.944; P = 0.031) but not for advanced glaucoma (AUC = 0.991; P > 0.05). CONCLUSIONS: Single-layer mGCL thickness is comparable to the traditional cpRNFL thickness for the diagnosis of early/moderate glaucoma, whereas cpRNFL thickness remains the most efficient for advanced glaucoma. Combining macular measurements (GCL and GCL-IPL) and cpRNFL improved the discrimination of early/moderate glaucoma but not of advanced glaucoma. For the diagnosis of early glaucoma, both macular and optic disc scans should be used.
PURPOSE: To compare the diagnostic ability of macular intraretinal layer thickness with circumpapillary retinal nerve fiber layer (cpRNFL) thickness, either when used individually or in combination with cpRNFL for detecting early, moderate, and advanced glaucoma. DESIGN: Cross-sectional study. PARTICIPANTS: A total of 423 glaucomaparticipants and 423 age- and gender-matched normal participants. METHODS:Participants underwent Cirrus spectral-domain OCT (SD-OCT) imaging (Carl Zeiss Meditec, Dublin, CA) using the optic disc and macular scanning protocols. Iowa Reference Algorithms (version 3.8.0) were used for intraretinal layer segmentation, and mean thickness of intraretinal layers was rescaled with magnification correction using axial length value. Thickness measurements of each layer/sector and their corresponding areas under the receiver operating characteristic curve (AUCs) were obtained. Glaucoma eyes were subdivided based on of their visual field severity (early, n = 234; moderate, n = 107; advanced, n = 82). MAIN OUTCOME MEASURES: Intraretinal layers. RESULTS: Some 67% of participants were male, their average ± standard deviation age was 65±9 years. Circumpapillary retinal nerve fiber layer, macular ganglion cell layer (mGCL), and macular inner plexiform layer (mIPL) were significantly thinner in the glaucoma groups (P < 0.0005). The 2 best parameters for detecting normal eyes from early glaucoma was cpRNFL (AUC = 0.861) and mGCL (AUC = 0.842), from moderate glaucoma was mGCL combined with inner plexiform layer (IPL) (AUC = 0.915) and cpRNFL (AUC = 0 .914), and from advanced glaucoma was mGCL-IPL (AUC = 0.984) and cpRNFL (AUC = 0.977). There was no statistical significance between AUCs for the macular parameter and cpRNFL thickness measurement at any of the severities (P > 0.05). Combining macular and cpRNFL parameters improved the diagnostic performance for early glaucoma (AUC = 0.908; P = 0.002) and moderate glaucoma (AUC = 0.944; P = 0.031) but not for advanced glaucoma (AUC = 0.991; P > 0.05). CONCLUSIONS: Single-layer mGCL thickness is comparable to the traditional cpRNFL thickness for the diagnosis of early/moderate glaucoma, whereas cpRNFL thickness remains the most efficient for advanced glaucoma. Combining macular measurements (GCL and GCL-IPL) and cpRNFL improved the discrimination of early/moderate glaucoma but not of advanced glaucoma. For the diagnosis of early glaucoma, both macular and optic disc scans should be used.
Authors: Ashish Jith Sreejith Kumar; Rachel S Chong; Jonathan G Crowston; Jacqueline Chua; Inna Bujor; Rahat Husain; Eranga N Vithana; Michaël J A Girard; Daniel S W Ting; Ching-Yu Cheng; Tin Aung; Alina Popa-Cherecheanu; Leopold Schmetterer; Damon Wong Journal: JAMA Ophthalmol Date: 2022-10-01 Impact factor: 8.253
Authors: Vahid Mohammadzadeh; Erica Su; Alessandro Rabiolo; Lynn Shi; Sepideh Heydar Zadeh; Simon K Law; Anne L Coleman; Joseph Caprioli; Robert E Weiss; Kouros Nouri-Mahdavi Journal: Am J Ophthalmol Date: 2021-12-21 Impact factor: 5.488
Authors: Katherine Lun; Yin Ci Sim; Rachel Chong; Damon Wong; Bingyao Tan; Rahat Husain; Tin Aung; Chelvin C A Sng; Leopold Schmetterer; Jacqueline Chua Journal: Front Med (Lausanne) Date: 2022-09-21
Authors: Jacqueline Chua; Chi Li; Lucius Kang Hua Ho; Damon Wong; Bingyao Tan; Xinwen Yao; Alfred Gan; Florian Schwarzhans; Gerhard Garhöfer; Chelvin C A Sng; Saima Hilal; Narayanaswamy Venketasubramanian; Carol Y Cheung; Georg Fischer; Clemens Vass; Tien Yin Wong; Christopher Li-Hsian Chen; Leopold Schmetterer Journal: Alzheimers Res Ther Date: 2022-03-10 Impact factor: 6.982