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Evaluation of Automatically Quantified Foveal Avascular Zone Metrics for Diagnosis of Diabetic Retinopathy Using Optical Coherence Tomography Angiography.
Invest Ophthalmol Vis Sci. 2018 05 01; 59(6):2212-2221.IO

Abstract

Purpose

To describe an automated algorithm to quantify the foveal avascular zone (FAZ), using optical coherence tomography angiography (OCTA), and to compare its performance for diagnosis of diabetic retinopathy (DR) and association with best-corrected visual acuity (BCVA) to that of extrafoveal avascular area (EAA).

Methods

We obtained 3 × 3-mm macular OCTA scans in diabetic patients with various levels of DR and healthy controls. An algorithm based on a generalized gradient vector flow (GGVF) snake model detected the FAZ, and metrics assessing FAZ size and irregularity were calculated. We compared the automated FAZ segmentation to manual delineation and tested the within-visit repeatability of FAZ metrics. The correlations of two conventional FAZ metrics, two novel FAZ metrics, and EAA with DR severity and BCVA, as determined by Early Treatment Diabetic Retinopathy Study (ETDRS) charts, were assessed.

Results

Sixty-six eyes from 66 diabetic patients and 19 control eyes from 19 healthy participants were included. The agreement between manual and automated FAZ delineation had a Jaccard index > 0.82, and the repeatability of automated FAZ detection was excellent in eyes at all levels of DR severity. FAZ metrics that incorporated both FAZ size and shape irregularity had the strongest correlation with clinical DR grade and BCVA. Of all the tested OCTA metrics, EAA had the greatest sensitivity in differentiating diabetic eyes without clinical evidence of retinopathy, mild to moderate nonproliferative DR (NPDR), and severe NPDR to proliferative DR from healthy controls.

Conclusions

The GGVF snake algorithm tested in this study can accurately and reliably detect the FAZ, using OCTA data at all DR severity grades, and may be used to obtain clinically useful information from OCTA data regarding macular ischemia in patients with diabetes. While FAZ metrics can provide clinically useful information regarding macular ischemia, and possibly visual acuity potential, EAA measurements may be a better biomarker for DR.

Authors+Show Affiliations

Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States. Shandong Province Key Laboratory of Medical Physics and Image Processing Technology, Institute of Biomedical Sciences, School of Physics and Electronics, Shandong Normal University, Jinan, China.Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States.Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States.Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States. Optovue, Inc., Fremont, California, United States.Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States.Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States.Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States.Shandong Province Key Laboratory of Medical Physics and Image Processing Technology, Institute of Biomedical Sciences, School of Physics and Electronics, Shandong Normal University, Jinan, China.Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, United States.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

29715365

Citation

Lu, Yansha, et al. "Evaluation of Automatically Quantified Foveal Avascular Zone Metrics for Diagnosis of Diabetic Retinopathy Using Optical Coherence Tomography Angiography." Investigative Ophthalmology & Visual Science, vol. 59, no. 6, 2018, pp. 2212-2221.
Lu Y, Simonett JM, Wang J, et al. Evaluation of Automatically Quantified Foveal Avascular Zone Metrics for Diagnosis of Diabetic Retinopathy Using Optical Coherence Tomography Angiography. Invest Ophthalmol Vis Sci. 2018;59(6):2212-2221.
Lu, Y., Simonett, J. M., Wang, J., Zhang, M., Hwang, T., Hagag, A. M., Huang, D., Li, D., & Jia, Y. (2018). Evaluation of Automatically Quantified Foveal Avascular Zone Metrics for Diagnosis of Diabetic Retinopathy Using Optical Coherence Tomography Angiography. Investigative Ophthalmology & Visual Science, 59(6), 2212-2221. https://doi.org/10.1167/iovs.17-23498
Lu Y, et al. Evaluation of Automatically Quantified Foveal Avascular Zone Metrics for Diagnosis of Diabetic Retinopathy Using Optical Coherence Tomography Angiography. Invest Ophthalmol Vis Sci. 2018 05 1;59(6):2212-2221. PubMed PMID: 29715365.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Evaluation of Automatically Quantified Foveal Avascular Zone Metrics for Diagnosis of Diabetic Retinopathy Using Optical Coherence Tomography Angiography. AU - Lu,Yansha, AU - Simonett,Joseph M, AU - Wang,Jie, AU - Zhang,Miao, AU - Hwang,Thomas, AU - Hagag,Ahmed M, AU - Huang,David, AU - Li,Dengwang, AU - Jia,Yali, PY - 2018/5/2/entrez PY - 2018/5/2/pubmed PY - 2019/2/16/medline SP - 2212 EP - 2221 JF - Investigative ophthalmology & visual science JO - Invest Ophthalmol Vis Sci VL - 59 IS - 6 N2 - Purpose: To describe an automated algorithm to quantify the foveal avascular zone (FAZ), using optical coherence tomography angiography (OCTA), and to compare its performance for diagnosis of diabetic retinopathy (DR) and association with best-corrected visual acuity (BCVA) to that of extrafoveal avascular area (EAA). Methods: We obtained 3 × 3-mm macular OCTA scans in diabetic patients with various levels of DR and healthy controls. An algorithm based on a generalized gradient vector flow (GGVF) snake model detected the FAZ, and metrics assessing FAZ size and irregularity were calculated. We compared the automated FAZ segmentation to manual delineation and tested the within-visit repeatability of FAZ metrics. The correlations of two conventional FAZ metrics, two novel FAZ metrics, and EAA with DR severity and BCVA, as determined by Early Treatment Diabetic Retinopathy Study (ETDRS) charts, were assessed. Results: Sixty-six eyes from 66 diabetic patients and 19 control eyes from 19 healthy participants were included. The agreement between manual and automated FAZ delineation had a Jaccard index > 0.82, and the repeatability of automated FAZ detection was excellent in eyes at all levels of DR severity. FAZ metrics that incorporated both FAZ size and shape irregularity had the strongest correlation with clinical DR grade and BCVA. Of all the tested OCTA metrics, EAA had the greatest sensitivity in differentiating diabetic eyes without clinical evidence of retinopathy, mild to moderate nonproliferative DR (NPDR), and severe NPDR to proliferative DR from healthy controls. Conclusions: The GGVF snake algorithm tested in this study can accurately and reliably detect the FAZ, using OCTA data at all DR severity grades, and may be used to obtain clinically useful information from OCTA data regarding macular ischemia in patients with diabetes. While FAZ metrics can provide clinically useful information regarding macular ischemia, and possibly visual acuity potential, EAA measurements may be a better biomarker for DR. SN - 1552-5783 UR - https://www.unboundmedicine.com/medline/citation/29715365/Evaluation_of_Automatically_Quantified_Foveal_Avascular_Zone_Metrics_for_Diagnosis_of_Diabetic_Retinopathy_Using_Optical_Coherence_Tomography_Angiography_ L2 - https://iovs.arvojournals.org/article.aspx?doi=10.1167/iovs.17-23498 DB - PRIME DP - Unbound Medicine ER -