Literature DB >> 33528650

Quantification of retinal microvascular parameters by severity of diabetic retinopathy using wide-field swept-source optical coherence tomography angiography.

Kiyoung Kim1, Jong In You1, Jang Ryul Park2, Eung Suk Kim1, Wang-Yuhl Oh2, Seung-Young Yu3.   

Abstract

PURPOSE: To investigate the diagnostic utility of microvascular parameters for grading the severity of diabetic retinopathy (DR) with a range of views using wide-field swept-source optical coherence tomography angiography (SS-OCTA).
METHODS: This retrospective study grouped 235 eyes with diabetes into the five grades: diabetes without retinopathy (no-DR), mild non-proliferative DR (NPDR), moderate NPDR, severe NPDR, and proliferative DR (PDR). Foveal avascular zone (FAZ) metrics, vessel density (VD), and the capillary nonperfusion area (NPA) were quantified with a customized, semiautomatic software algorithm. Regions of interest were selected from three rectangular fields of different sizes (i.e., 3 × 3 mm2, 6 × 6 mm2, and 10 × 10 mm2), perpendicular to the fovea-optic disc axis.
RESULTS: NPA obtained from the 6 × 6mm2 and 10 × 10mm2 areas was the only discriminating parameter for the three NPDR stages. ROC curve analysis revealed that NPA from the 10 × 10mm2 field exhibited the best performance for grading DR into five stages. The NPA cutoff values were 3.7% (area under the curve (AUC): 0.91), 4.7% (AUC: 0.94), 9.3% (AUC: 0.94), and 21.4% (AUC: 0.90) for grading no-DR, mild from moderate NPDR, moderate from severe NPDR, and severe NPDR from PDR, respectively.
CONCLUSIONS: Increasing DR severity as assessed by conventional grading systems is accompanied with increasing retinal ischemia on SS-OCTA. NPA measured from the larger 10 × 10 mm2 scan area showed the highest sensitivity for determining five-grade DR severity. In the future, the addition of quantitative NPA may provide a more clinically feasible DR grading system.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.

Entities:  

Keywords:  Capillary nonperfusion area; Diabetic retinopathy; Swept-source optical coherence tomography angiography

Year:  2021        PMID: 33528650     DOI: 10.1007/s00417-021-05099-y

Source DB:  PubMed          Journal:  Graefes Arch Clin Exp Ophthalmol        ISSN: 0721-832X            Impact factor:   3.117


  1 in total

1.  Early signs of diabetic retinopathy by fluorescein angiography.

Authors:  Y Yamana; Y Ohnishi; Y Taniguchi; M Ikeda
Journal:  Jpn J Ophthalmol       Date:  1983       Impact factor: 2.447

  1 in total
  4 in total

1.  A Deep Learning Algorithm for Classifying Diabetic Retinopathy Using Optical Coherence Tomography Angiography.

Authors:  Gahyung Ryu; Kyungmin Lee; Donggeun Park; Inhye Kim; Sang Hyun Park; Min Sagong
Journal:  Transl Vis Sci Technol       Date:  2022-02-01       Impact factor: 3.048

2.  Nonperfusion Area and Other Vascular Metrics by Wider Field Swept-Source OCT Angiography as Biomarkers of Diabetic Retinopathy Severity.

Authors:  Itika Garg; Chibuike Uwakwe; Rongrong Le; Edward S Lu; Ying Cui; Karen M Wai; Raviv Katz; Ying Zhu; Jade Y Moon; Chloe Y Li; Inês Laíns; Dean Eliott; Tobias Elze; Leo A Kim; David M Wu; Joan W Miller; Deeba Husain; Demetrios G Vavvas; John B Miller
Journal:  Ophthalmol Sci       Date:  2022-03-18

3.  Vascular Analysis of Type 1, 2, and 3 Macular Neovascularization in Age-Related Macular Degeneration Using Swept-Source Optical Coherence Tomography Angiography Shows New Insights into Differences of Pathologic Vasculature and May Lead to a More Personalized Understanding.

Authors:  Henrik Faatz; Kai Rothaus; Martin Ziegler; Marius Book; Britta Heimes-Bussmann; Daniel Pauleikhoff; Albrecht Lommatzsch
Journal:  Biomedicines       Date:  2022-03-17

4.  Automated Diagnosis of Optical Coherence Tomography Angiography (OCTA) Based on Machine Learning Techniques.

Authors:  Ibrahim Yasser; Fahmi Khalifa; Hisham Abdeltawab; Mohammed Ghazal; Harpal Singh Sandhu; Ayman El-Baz
Journal:  Sensors (Basel)       Date:  2022-03-18       Impact factor: 3.576

  4 in total

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