Macular Vessel Density in Diabetic Retinopathy Patients: How Can We Accurately Measure and What Can It Tell Us?

Pramil, Varsha; Levine, Emily S.; Waheed, Nadia K.

doi:10.2147/opth.s272328

Cited by 16 publications

(16 citation statements)

References 79 publications

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“…There is a wealth of OCTA literature in DR, and numerous studies that have reported reduced VD, SVD, and FD in patients with DR. 2 – 4 , 10 It is also known that older age is associated with decreased VD and SVD. 5 , 19 This is consistent with our findings that PDR and older age were most frequently significantly associated with decreased values of VD, SVD, and FD, which served as somewhat of a positive control in our study to evaluate which combinations of preprocessing and binarization algorithms might be most accurate.…”

Section: Discussionsupporting

confidence: 90%

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The Impact of Image Processing Algorithms on Optical Coherence Tomography Angiography Metrics and Study Conclusions in Diabetic Retinopathy

Freedman

Hui

et al. 2022

Trans. Vis. Sci. Tech.

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Purpose The purpose of this study was to evaluate the impact of image processing on quantitative metrics in optical coherence tomography angiography (OCTA) images and study conclusions in patients with diabetes. Methods This was a single center, retrospective cross-sectional study. OCTA imaging with the Cirrus HD-OCT 5000 AngioPlex of patients with diabetes was performed. The 8 × 8 mm superficial slab images underwent 4 different preprocessing methods (none, background subtraction [BGS], foveal avascular zone brightness adjustment, and contrast limited adaptive histogram equalization [CLAHE]) followed by 4 different binarization algorithms (global Huang, global Otsu, local Niblack, and local Phansalkar) in ImageJ. Vessel density (VD), skeletonized VD (SVD), and fractal dimension (FD) were calculated. Mixed-effect multivariate linear regressions were performed. Results Two hundred eleven scans from 104 patients were included. Of these scans, 67 (31.8%) had no diabetic retinopathy (DR), 99 (46.9%) had nonproliferative DR (NPDR), and 45 (21.3%) had proliferative DR (PDR). Forty-eight of 211 (22.7%) scans had diabetic macular edema (DME). The image processing method used significantly impacted values of VD, SVD, and FD (all P -values < 0.001). On multivariate analysis, the image processing method changed the clinical variables significantly associated with VD, SVD, and FD. However, BGS and CLAHE yielded more consistent significant covariates across multiple binarization algorithms. Conclusions The image processing method can impact the conclusions of any given study analyzing quantitative OCTA metrics. Thus, caution is urged in the interpretation of such studies. Background subtraction or CLAHE may play a role in the standardization of image processing. Translational Relevance This work proposes strategies to achieve robust and consistent analysis of OCTA imaging, which is especially important for clinical trials.

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Section: Discussionsupporting

confidence: 90%

“…The values of these metrics have been shown to be altered in retinal vascular disease, such as diabetic retinopathy (DR). 1 – 5 …”

Section: Introductionmentioning

confidence: 99%

The Impact of Image Processing Algorithms on Optical Coherence Tomography Angiography Metrics and Study Conclusions in Diabetic Retinopathy

Freedman

Hui

et al. 2022

Trans. Vis. Sci. Tech.

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“…There are other OCTA metrics that were reported in the literature, such as vessel or perfusion density, vessel area density, and skeletonized vessel density or vessel length index [19,20,[41][42][43][44][45]. They were evaluated to assess the integrity (i.e.…”

Section: Discussionmentioning

confidence: 99%

“…These methods cover automatic or semi-automatic segmentation algorithms designed on both the macro and micro macula's vasculature levels. Some researchers suggested extending the OCTA segmentation tasks by producing quantification parameters [17,19,20,[41][42][43][44][45], such as OCTA vessels' length, area density, and diameters. Some studies moved beyond the segmentation and quantitative analysis toward exploring the use of Artificial Intelligence (AI) techniques such as Deep Learning [21-23, 46, 48] and Machine Learning [24,47] to classify the delineated vasculature regions into normal or abnormal.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction and Visualization of 5μm Sectional Coronal Views for Macula Vasculature in OptoVue OCTA

et al. 2023

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A Computerized Medical Image Processing (CMIP) method is proposed to address the current challenges of optical coherence tomography angiography (OCTA): (1) the need for observing the macula vasculature concerning natural curvature of the macula region; (2) the need for generating OCTA frames at successive small depths in all macula layers; and (3) the need for enhancing the visibility of blood vessels, particularly below the outer retina region. The proposed CMIP method involves image preprocessing, reconstruction, and enhancement stages. Twenty subjects were obtained from the OCTA500 dataset, which was obtained from the OptoVue OCTA machine. The 20 subjects comprise the two OCTA fields of view (FOV), right and left eyes (OD and OS), and five common macula disorders. The sequential enface OCTA images at 5µm macula depths were displayed. The presentation of the macula vasculature was enhanced at all depths. The resulting new ophthalmic views enable: (1) avoiding the superimposition of macula vasculature into a projection map; (2) enhancing the OCTA presentation of blood vessels; and (3) inspecting the macula's 3D oval-shaped. The proposed CMIP method can generate sectional macula coronal views (MCV) for every 5µm depth, clarifying the macula's curvature in a way that has not been presented in OCTA machines. Therefore, "tracking" the 3D propagation of the blood vessel network at all macula depths becomes possible. Furthermore, the blood vessels' display at all macula depths, including the deep choroid layers, is enhanced. The method yields futuristic ophthalmic advantages that would allow the physician to precisely inspect the 3D localization and diffusion of the macula disorders. The method is invariant to the OCTA's FOVs, macula disorder, and OD or OS eye.

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“…Vascular length density (VLD) index was calculated as the area of pixels occupied with skeletonized vessels divided by the total area of the image. In skeletonization, reducing the width of each vessel to a single pixel results in uniform contribution of the large and small vasculature in density measurements 19 .…”

Section: Methodsmentioning

confidence: 99%

Differentiating features of OCT angiography in diabetic macular edema

Mirshahi

Riazi-Esfahani

Pour

et al. 2021

Sci Rep

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The purpose of current study was to evaluate different optical coherence tomography angiography (OCTA) metrics in eyes with diabetic retinopathy with and without diabetic macular edema (DME). In this retrospective study, macular OCTA images of eyes with non-proliferative or proliferative diabetic retinopathy were evaluated. Vascular density, vascular complexity and non-perfusion densities were compared between eyes with and without DME. One-hundred-thirty-eight eyes of 92 diabetic patients including 49 eyes with DME were included. In multivariate analysis, the presence of DME was positively associated with geometric perfusion deficit (GPD) in superficial capillary plexus (SCP), capillary non-perfusion (CNP) of SCP, and GPD in deep capillary plexus (DCP) (all P < 0.05). In eyes with DME, central foveal thickness was associated with VD ratio (SCP/DCP) (P = 0.001) and FAZ area (P = 0.001). In conclusion, in eyes with diabetic retinopathy, the presence of DME was associated with more extensive capillary non-perfusion compared to those with no macular edema.

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Macular Vessel Density in Diabetic Retinopathy Patients: How Can We Accurately Measure and What Can It Tell Us?

Cited by 16 publications

References 79 publications

The Impact of Image Processing Algorithms on Optical Coherence Tomography Angiography Metrics and Study Conclusions in Diabetic Retinopathy

The Impact of Image Processing Algorithms on Optical Coherence Tomography Angiography Metrics and Study Conclusions in Diabetic Retinopathy

Reconstruction and Visualization of 5μm Sectional Coronal Views for Macula Vasculature in OptoVue OCTA

Differentiating features of OCT angiography in diabetic macular edema

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