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. 2020 Dec 11;15(12):e0243830.
doi: 10.1371/journal.pone.0243830. eCollection 2020.

Quantitative assessment of choriocapillaris flow deficits in diabetic retinopathy: A swept-source optical coherence tomography angiography study

Affiliations

Quantitative assessment of choriocapillaris flow deficits in diabetic retinopathy: A swept-source optical coherence tomography angiography study

Yining Dai et al. PLoS One. .

Abstract

Purpose: To quantitatively assess choriocapillaris (CC) flow deficits in eyes with diabetic retinopathy (DR) using swept-source optical coherence tomography angiography (SS-OCTA).

Methods: Diabetic subjects with different stages of DR and age-matched healthy subjects were recruited and imaged with SS-OCTA. The en face CC blood flow images were generated using previously published and validated algorithms. The percentage of CC flow deficits (FD%) and the mean CC flow deficit size were calculated in a 5-mm-diameter circle centered on the fovea from the 6×6-mm scans.

Results: Forty-five diabetic subjects and 27 control subjects were included in the study. The CC FD% in diabetic eyes was on average 1.4-fold greater than in control eyes (12.34±4.14% vs 8.82±2.61%, P < 0.001). The mean CC FD size in diabetic eyes was on average 1.4-fold larger than in control eyes (2151.3± 650.8μm2 vs 1574.4±255.0 μm2, P < 0.001). No significant difference in CC FD% or mean CC FD size was observed between eyes with nonproliferative DR and eyes with proliferative DR (P = 1.000 and P = 1.000, respectively).

Conclusions: CC perfusion in DR can be objectively and quantitatively assessed with FD% and FD size. In the macular region, both CC FD% and CC FD size are increased in eyes with DR. SS-OCTA provides new insights for the investigations of CC perfusion status in diabetes in vivo.

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Conflict of interest statement

This work is supported in part by Carl Zeiss Meditec Inc, an industry partner. While all other authors do not have competing interests with Carl Zeiss, Dr Wang declare that he is a consultant with Carl Zeiss and holds a patent jointly with Carl Zeiss. However, this relationship does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Example of image processing for the quantification of choriocapillaris flow deficits.
(A) The en face choriocapillaris blood flow image without the removal of artifacts. (B) The en face retinal blood flow image. (C) The large retinal vessel map generated from image B. (D) The en face choriocapillaris structural image. (E) The shadowing artifacts on choriocapillaris image with black pixels corresponding to artifacts caused by retinal lesions. (F) The choriocapillaris flow deficits (green color) overlaid onto the en face choriocapillaris blood flow image (gray) after subtraction of artifacts. (G) The choriocapillaris flow deficit binary map for quantification. All images are from the left eye of a 45-year-old diabetic patient with proliferative diabetic retinopathy. All images are 6×6-mm fields.
Fig 2
Fig 2. Comparisons of CC FD% (left) and mean CC FD size (right) between study groups.
Kruskal-Wallis test with Bonferroni correction was performed in pairwise comparisons of the FD% and the mean FD size, respectively. Brackets indicate statistically significant differences between corresponding study groups. CC, choriocapillaris; FD, flow deficit; FD%, percentage of CC FDs; NPDR, nonproliferative diabetic retinopathy; PDR, proliferative diabetic retinopathy.
Fig 3
Fig 3. Representative illustration of the SS-OCTA images from a control eye and eyes with different stages of diabetic retinopathy.
First column (A, E, and I): The en face retinal blood flow images. Second column (B, F, and J): The en face choriocapillaris blood flow images without removal of the artifacts. Third column (C, G, and K): The corresponding choriocapillaris flow deficits (green color) overlaid onto the en face choriocapillaris blood flow images (gray) after removal of the artifacts. Fourth column (D, H, and L): The choriocapillaris flow deficit binary maps for quantification. (A–D) Images are from the right eye of a 62-year-old healthy subject. (E–H) Images are from the right eye of a 62-year-old patient with nonproliferative diabetic retinopathy. (I–L) Images are from the right eye of a 60-year-old patient with proliferative diabetic retinopathy. All images are 6×6-mm fields).

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