Literature DB >> 27812696

Visualization of 3 Distinct Retinal Plexuses by Projection-Resolved Optical Coherence Tomography Angiography in Diabetic Retinopathy.

Thomas S Hwang1, Miao Zhang1, Kavita Bhavsar1, Xinbo Zhang1, J Peter Campbell1, Phoebe Lin1, Steven T Bailey1, Christina J Flaxel, Andreas K Lauer1, David J Wilson1, David Huang1, Yali Jia1.   

Abstract

IMPORTANCE: Projection artifacts in optical coherence tomography angiography (OCTA) blur the retinal vascular plexuses together and limit visualization of the individual plexuses.
OBJECTIVE: To describe projection-resolved (PR) OCTA in eyes with diabetic retinopathy (DR) and healthy eyes. DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, patients with DR and healthy controls were enrolled in this observational study from January 26, 2015, to December 4, 2015, at a tertiary academic center. Spectral-domain, 70-kHz OCT obtained 3 × 3-mm macular scans. The PR algorithm suppressed projection artifacts. A semiautomated segmentation algorithm divided PR-OCTA into superficial, intermediate, and deep retinal plexuses. Two masked graders examined 3-layer PR-OCTA and combined angiograms for nonperfusion and abnormal capillaries. MAIN OUTCOMES AND MEASURES: Retinal nonperfusion and capillary abnormalities and the diagnostic accuracy of detecting DR.
RESULTS: Twenty-nine eyes of 15 healthy individuals (mean [SD] age, 36.2 [13.4] years; 11 women) and 47 eyes of 29 patients with DR (mean [SD] age, 55.5 [11.9]; 10 women) underwent imaging. PR-OCTA revealed 3 distinct retinal plexuses in their known anatomical locations in all eyes. The intermediate and deep plexuses of healthy eyes revealed capillary networks of uniform density and caliber, whereas the superficial plexus revealed vessels in the familiar centripetal branching pattern. In eyes with DR, 3-layer PR-OCTA disclosed incongruent areas of nonperfusion and varied vessel caliber and density in the deeper plexuses. Masked grading of capillary nonperfusion on 3-layer PR-OCTA detected DR with 100% sensitivity (95% CI, 90.8%-100%) and 100% specificity (95% CI, 85.4%-100%). With unsegmented retinal angiograms, the sensitivity and specificity were 78.7% (95% CI, 63.9%-88.8%) and 100% (95% CI, 85.4%-100%), respectively (P = .002 for sensitivity). On 3-layer PR-OCTA, sensitivity was 72.2% (95% CI, 54.6%-85.2%) for severe nonproliferative DR and proliferative DR eyes with generalized nonperfusion in 2 or more individual plexuses, but on combined angiogram, sensitivity was 25.0% (95% CI, 12.7%-42.5%) for generalized nonperfusion (P < .001). PR-OCTA disclosed dilated vessels in the intermediate and deep plexuses in 23 eyes (100%) with proliferative DR, 13 eyes (100%) with severe nonproliferative DR, 8 eyes (73%) with mild to moderate nonproliferative DR, and 0 control eyes. CONCLUSIONS AND RELEVANCE: By presenting 3 retinal vascular plexuses distinctly, PR-OCTA reveals capillary abnormalities in deeper layers with clarity and may distinguish DR from healthy eyes and severe DR from mild DR with greater accuracy compared with conventional OCTA.

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Mesh:

Year:  2016        PMID: 27812696      PMCID: PMC5805384          DOI: 10.1001/jamaophthalmol.2016.4272

Source DB:  PubMed          Journal:  JAMA Ophthalmol        ISSN: 2168-6165            Impact factor:   7.389


  28 in total

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Authors:  Li Liu; Simon S Gao; Steven T Bailey; David Huang; Dengwang Li; Yali Jia
Journal:  Biomed Opt Express       Date:  2015-08-25       Impact factor: 3.732

Review 2.  Contemporary retinal imaging techniques in diabetic retinopathy: a review.

Authors:  Emily Dawn Cole; Eduardo Amorim Novais; Ricardo Noguera Louzada; Nadia K Waheed
Journal:  Clin Exp Ophthalmol       Date:  2016-02-25       Impact factor: 4.207

3.  Spectrum of Retinal Vascular Diseases Associated With Paracentral Acute Middle Maculopathy.

Authors:  Xuejing Chen; Ehsan Rahimy; Robert C Sergott; Renata P Nunes; Eduardo C Souza; Netan Choudhry; Nathan E Cutler; Samuel K S Houston; Marion R Munk; Amani A Fawzi; Sonia Mehta; Jean-Pierre Hubschman; Allen C Ho; David Sarraf
Journal:  Am J Ophthalmol       Date:  2015-04-04       Impact factor: 5.258

4.  IN VIVO CHARACTERIZATION OF RETINAL VASCULARIZATION MORPHOLOGY USING OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY.

Authors:  Maria Cristina Savastano; Bruno Lumbroso; Marco Rispoli
Journal:  Retina       Date:  2015-11       Impact factor: 4.256

5.  Optical Coherence Tomography Angiography in Diabetic Retinopathy: A Prospective Pilot Study.

Authors:  Akihiro Ishibazawa; Taiji Nagaoka; Atsushi Takahashi; Tsuneaki Omae; Tomofumi Tani; Kenji Sogawa; Harumasa Yokota; Akitoshi Yoshida
Journal:  Am J Ophthalmol       Date:  2015-04-18       Impact factor: 5.258

6.  Paracentral acute middle maculopathy in nonischemic central retinal vein occlusion.

Authors:  Ehsan Rahimy; David Sarraf; Michael L Dollin; John D Pitcher; Allen C Ho
Journal:  Am J Ophthalmol       Date:  2014-05-01       Impact factor: 5.258

7.  Using ultrahigh sensitive optical microangiography to achieve comprehensive depth resolved microvasculature mapping for human retina.

Authors:  Lin An; Tueng T Shen; Ruikang K Wang
Journal:  J Biomed Opt       Date:  2011-10       Impact factor: 3.170

8.  CHARACTERIZATION OF THE MIDDLE CAPILLARY PLEXUS USING OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IN HEALTHY AND DIABETIC EYES.

Authors:  Justin J Park; Brian T Soetikno; Amani A Fawzi
Journal:  Retina       Date:  2016-11       Impact factor: 4.256

9.  OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY FEATURES OF DIABETIC RETINOPATHY.

Authors:  Thomas S Hwang; Yali Jia; Simon S Gao; Steven T Bailey; Andreas K Lauer; Christina J Flaxel; David J Wilson; David Huang
Journal:  Retina       Date:  2015-11       Impact factor: 4.256

10.  Retinal vasculature of the fovea of the squirrel monkey, Saimiri sciureus: three-dimensional architecture, visual screening, and relationships to the neuronal layers.

Authors:  D M Snodderly; R S Weinhaus
Journal:  J Comp Neurol       Date:  1990-07-01       Impact factor: 3.215

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  74 in total

1.  Automated segmentation of peripapillary retinal boundaries in OCT combining a convolutional neural network and a multi-weights graph search.

Authors:  Pengxiao Zang; Jie Wang; Tristan T Hormel; Liang Liu; David Huang; Yali Jia
Journal:  Biomed Opt Express       Date:  2019-08-01       Impact factor: 3.732

2.  Development and validation of a deep learning algorithm for distinguishing the nonperfusion area from signal reduction artifacts on OCT angiography.

Authors:  Yukun Guo; Tristan T Hormel; Honglian Xiong; Bingjie Wang; Acner Camino; Jie Wang; David Huang; Thomas S Hwang; Yali Jia
Journal:  Biomed Opt Express       Date:  2019-06-12       Impact factor: 3.732

3.  Automated detection of shadow artifacts in optical coherence tomography angiography.

Authors:  Acner Camino; Yali Jia; Jeffrey Yu; Jie Wang; Liang Liu; David Huang
Journal:  Biomed Opt Express       Date:  2019-02-28       Impact factor: 3.732

4.  Maximum value projection produces better en face OCT angiograms than mean value projection.

Authors:  Tristan T Hormel; Jie Wang; Steven T Bailey; Thomas S Hwang; David Huang; Yali Jia
Journal:  Biomed Opt Express       Date:  2018-11-26       Impact factor: 3.732

5.  Automated detection of dilated capillaries on optical coherence tomography angiography.

Authors:  Changlei Dongye; Miao Zhang; Thomas S Hwang; Jie Wang; Simon S Gao; Liang Liu; David Huang; David J Wilson; Yali Jia
Journal:  Biomed Opt Express       Date:  2017-01-25       Impact factor: 3.732

6.  Reflectance-based projection-resolved optical coherence tomography angiography [Invited].

Authors:  Jie Wang; Miao Zhang; Thomas S Hwang; Steven T Bailey; David Huang; David J Wilson; Yali Jia
Journal:  Biomed Opt Express       Date:  2017-02-15       Impact factor: 3.732

7.  Automated boundary detection of the optic disc and layer segmentation of the peripapillary retina in volumetric structural and angiographic optical coherence tomography.

Authors:  Pengxiao Zang; Simon S Gao; Thomas S Hwang; Christina J Flaxel; David J Wilson; John C Morrison; David Huang; Dengwang Li; Yali Jia
Journal:  Biomed Opt Express       Date:  2017-02-01       Impact factor: 3.732

8.  Robust non-perfusion area detection in three retinal plexuses using convolutional neural network in OCT angiography.

Authors:  Jie Wang; Tristan T Hormel; Qisheng You; Yukun Guo; Xiaogang Wang; Liu Chen; Thomas S Hwang; Yali Jia
Journal:  Biomed Opt Express       Date:  2019-12-18       Impact factor: 3.732

9.  Vascular Density of Deep, Intermediate and Superficial Vascular Plexuses Are Differentially Affected by Diabetic Retinopathy Severity.

Authors:  Mohamed Ashraf; Konstantina Sampani; Allen Clermont; Omar Abu-Qamar; Jae Rhee; Paolo S Silva; Lloyd Paul Aiello; Jennifer K Sun
Journal:  Invest Ophthalmol Vis Sci       Date:  2020-08-03       Impact factor: 4.799

10.  Automated Quantification of Nonperfusion Areas in 3 Vascular Plexuses With Optical Coherence Tomography Angiography in Eyes of Patients With Diabetes.

Authors:  Thomas S Hwang; Ahmed M Hagag; Jie Wang; Miao Zhang; Andrew Smith; David J Wilson; David Huang; Yali Jia
Journal:  JAMA Ophthalmol       Date:  2018-08-01       Impact factor: 7.389

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