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Quantification of Nonperfusion Area in Montaged Widefield OCT Angiography Using Deep Learning in Diabetic Retinopathy

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作者：
Guo Yukun[1] * ; Hormel Tristan T[1] ; Gao Liqin[1,2] ; You Qisheng[1] ; Wang Bingjie[1] ; Flaxel Christina J[1] ; Bailey Steven T[1] ; Choi Dongseok[1,3] ; Huang David[1] ; Hwang Thomas S[1] ; Jia Yali[1,4,*1] ;
机构： [1]Casey Eye Institute, Oregon Health & Science University, Portland, Oregon. [2]Beijing Tongren Eye Center, Beijing Key Laboratory of Ophthalmology and Visual Science, Beijing Tongren Hospital, Capital Medical University, Beijing, China. [3]Oregon Health & Science UniversityePortland State University School of Public Health, Oregon Health & Science University, Portland, Oregon. [4]Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon.
出处：
DOI： 10.1016/j.xops.2021.100027
ISSN：

关键词： Deep learning Diabetic retinopathy Nonperfusion area Widefield OCTA

摘要：
To examine the efficacy of a deep learning-based algorithm to quantify the nonperfusion area (NPA) on montaged widefield OCT angiography (OCTA) for assessment of diabetic retinopathy (DR) severity.Cross-sectional study.One hundred thirty-seven participants with a full range of DR severity and 26 healthy participants.A deep learning-based algorithm was developed for detecting and quantifying NPA in the superficial vascular complex on widefield OCTA comprising 3 horizontally montaged 6 × 6-mm OCTA scans from the nasal, macular, and temporal regions. We trained the algorithm on 978 volumetric OCTA scans from all participants using 5-fold cross-validation. The algorithm can distinguish NPA from shadow artifacts. The F1 score evaluated segmentation accuracy. The area under the receiver operating characteristic curve and sensitivity with specificity fixed at 95% quantified network performance to distinguish patients with diabetes from healthy control participants, referable DR from nonreferable DR (nonproliferative DR [NPDR] less than moderate severity), and severe DR (severe NPDR, proliferative DR, or DR with edema) from nonsevere DR (mild to moderate NPDR).Widefield OCTA NPA, visual acuity (VA), and DR severities.Automatically segmented NPA showed high agreement with the manually delineated ground truth, with a mean ± standard deviation F1 score of 0.78 ± 0.05 in nasal, 0.82 ± 0.07 in macular, and 0.78 ± 0.05 in temporal scans. The extrafoveal avascular area (EAA) in the macular scan showed the best sensitivity at 54% for differentiating those with diabetes from healthy control participants, whereas montaged widefield OCTA scan showed significantly higher sensitivity than macular scans (P < 0.0001, McNemar's test) for detecting eyes with DR at 66%, referable DR at 63%, and severe DR at 62%. Montaged widefield OCTA showed the highest correlation (Spearman ρ = 0.74; P < 0.0001) between EAA and DR severity. The macular scan showed the strongest negative correlation (Pearson ρ = -0.42; P < 0.0001) between EAA and best-corrected VA.A deep learning-based algorithm for montaged widefield OCTA can detect NPA accurately and can improve the detection of clinically important DR.© 2021 by the American Academy of Ophthalmology.

基金：
National Institutes of Health, Bethesda, Maryland (grant nos.: R01 EY027833, R01 EY024544, R01EY031394, P30 EY010572, and T32 EY023211); Research to Prevent Blindness, Inc, New York, New York (William & Mary Greve Special Scholar Award and unrestricted departmental grant); and the Bright Focus Foundation, United States (grant no: G2020168).
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出版当年[2020]版：
无
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大类 | 3 区 医学
小类 | 2 区 眼科学
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出版当年[2019]版：
无
最新[2023]版：
Q1 OPHTHALMOLOGY

影响因子： 最新[2023版] 最新五年平均 出版当年[2019版] 出版当年五年平均 出版前一年[2018版]

第一作者：
第一作者机构： [1]Casey Eye Institute, Oregon Health & Science University, Portland, Oregon.
通讯作者：
通讯机构： [1]Casey Eye Institute, Oregon Health & Science University, Portland, Oregon. [4]Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon. [*1]Casey Eye Institute, Oregon Health and Science University, 515 SW Campus Drive, Portland, OR 97239
推荐引用方式(GB/T 7714)：
Guo Yukun,Hormel Tristan T,Gao Liqin,et al.Quantification of Nonperfusion Area in Montaged Widefield OCT Angiography Using Deep Learning in Diabetic Retinopathy[J].OPHTHALMOLOGY SCIENCE.2021,1(2):100027.doi:10.1016/j.xops.2021.100027.
APA：
Guo Yukun,Hormel Tristan T,Gao Liqin,You Qisheng,Wang Bingjie...&Jia Yali.(2021).Quantification of Nonperfusion Area in Montaged Widefield OCT Angiography Using Deep Learning in Diabetic Retinopathy.OPHTHALMOLOGY SCIENCE,1,(2)
MLA：
Guo Yukun,et al."Quantification of Nonperfusion Area in Montaged Widefield OCT Angiography Using Deep Learning in Diabetic Retinopathy".OPHTHALMOLOGY SCIENCE 1..2(2021):100027

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