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Optical coherence tomography angiography for noninvasive evaluation of angiogenesis in a limb ischemia mouse model.

ABSTRACT: We developed an optical coherence tomography angiography technique by improving the speckle contrast algorithm and the imaging process. This technique, which can achieve angiogenesis imaging in vivo without increasing trauma, was used to evaluate the microvasculature in limb ischemia mice. Sixteen left hindlimb ischemia mice were randomly allocated into CuSO4 and saline groups. Within 7 days after treatment, limb ischemic damage, temperature and histological staining were assessed by traditional methods. In addition, angiogenesis was evaluated using an optical coherence tomography angiography system in vivo. All results were compared. After 7 days of treatment, both the ischemic tissue damage score and temperature ratio of the CuSO4 group were significantly higher than those of the control group (all P?

SUBMITTER: Wang L

PROVIDER: S-EPMC6461622 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Optical coherence tomography angiography for noninvasive evaluation of angiogenesis in a limb ischemia mouse model.

Wang Liwei L Chen Zuoguan Z Li Yongjun Y Yang Jing J Li Yuejie Y

Scientific reports 20190412 1

We developed an optical coherence tomography angiography technique by improving the speckle contrast algorithm and the imaging process. This technique, which can achieve angiogenesis imaging in vivo without increasing trauma, was used to evaluate the microvasculature in limb ischemia mice. Sixteen left hindlimb ischemia mice were randomly allocated into CuSO<sub>4</sub> and saline groups. Within 7 days after treatment, limb ischemic damage, temperature and histological staining were assessed by ...[more]

PMID: 30979948

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Project description:Importance:Whether optical coherence tomography angiography (OCT-A) outperforms OCT to detect glaucoma remains inconclusive. Objective:To compare (1) the diagnostic performance for detection of glaucoma and (2) the structure-function association between inner macular vessel density and inner macular thickness. Design, Setting, and Participants:This cross-sectional study included 115 patients with glaucoma and 35 healthy individuals for measurements of retinal thickness and retinal vessel density, segmented between the anterior boundary of internal limiting membrane and the posterior boundary of the inner plexiform layer, over the 3 × 3-mm2 macula using swept-source OCT. All participants were Chinese. Visual sensitivity corresponding to the 3 × 3-mm2 macular region was expressed in unlogged 1/lambert for investigation of the structure-function associations. Diagnostic performance was evaluated with area under the receiver operating characteristic curves (AUCs). The study was conducted between January 12, 2016, and December 12, 2016. Main Outcomes and Measures:Area under the receiver operating characteristic curve and R2 analysis. Results:Of the 115 patients with glaucoma, 42 (36.5%) were women (mean [SD] age, 53.5 [13.4] years); of the 35 individuals with healthy eyes, 25 (71.4%) were women (age, 60.6 [5.9] years). Inner macular vessel density and thickness were 4.3% (95% CI, 2.4%-6.1%) and 21.1 μm (95% CI, 17.4-24.9 μm) smaller, respectively, in eyes with glaucoma compared with healthy eyes. The AUC of mean inner macular thickness for glaucoma detection was greater than that of mean inner macular vessel density (difference, 0.17; 95% CI, 0.01-0.31; P = .03). At 90% specificity, the sensitivity of mean inner macular thicknesses for detection of glaucoma was greater than that of mean inner macular vessel densities (difference, 29.2%; 95% CI, 11.5%-64.6%; P = .02). The strength of the structure-function association was stronger for mean inner macular thickness than mean inner macular vessel density in the linear (difference in R2 = 0.38; 95% CI, 0.22-0.54; P < .001) and nonlinear (difference in R2 = 0.36; 95% CI, 0.21-0.51; P < .001) regression models. Conclusions and Relevance:In this study, OCT measurement of inner macular thickness shows a higher diagnostic performance to detect glaucoma and a stronger structure-function association than the currently used OCT-A measurement of inner macular vessel density. These findings may suggest that OCT-A of the macula has a limited role in the diagnostic evaluation of glaucoma.

Project description:PurposeUsing retinal optical coherence tomography angiography (OCTA), we aimed to investigate the changes in important indicators of cerebral microcirculatory disorders, such as the properties of the radial peripapillary capillaries, vascular complexes, and the retinal nerve fiber layer, caused by carotid stenosis and postoperative reperfusion.MethodsIn this prospective longitudinal cohort study, we recruited 40 carotid stenosis patients and 89 healthy volunteers in the First Affiliated Hospital of Harbin Medical University (Harbin, China). Eyes with ipsilateral carotid stenosis constituted the experimental group, while the fellow eyes constituted the contralateral eye group. Digital subtraction angiography, CT perfusion imaging (CTP), and OCTA examinations were performed in all subjects. The vessel density of the radial peripapillary capillaries (RPC), superficial retinal vascular complexes (SVC), deep vascular complexes (DVC), choriocapillaris (CC), and the thickness of the retinal nerve fiber layer (RNFL) were assessed. Propensity-matched analysis was undertaken to adjust for covariate imbalances. Intergroup comparative analysis was conducted, and the paired sample t-test was used to evaluate the preoperative and postoperative changes in OCTA variables.ResultsThe ocular vessel density in the experimental group was significantly lower than that in the control group (RPC: 55.95 vs. 57.24, P = 0.0161; SVC: 48.65 vs. 52.22, P = 0.0006; DVC: 49.65 vs. 57.50, P < 0.0001). Participants with severe carotid stenosis have reduced contralateral ocular vessel density (RPC 54.30; SVC 48.50; DVC 50.80). Unilateral stenosis removal resulted in an increase in vessel density on both sides, which was detected by OCTA on the 4th day (RPC, P < 0.0001; SVC, P = 0.0104; DVC, P = 0.0104). Moreover, the ocular perfusion was consistent with that established by CTP.ConclusionOCTA can be used for sensitive detection and accurate evaluation of decreased ocular perfusion caused by carotid stenosis and may thus have the potential for application in noninvasive detection of cerebral microcirculation disorders. This trial is registered with NCT04326842.

Project description:PurposeTo examine whether deep-learning denoised optical coherence tomography angiography (OCTA) images could enhance automated macular ischemia quantification in branch retinal vein occlusion (BRVO).MethodsThis retrospective, single-center, cross-sectional study enrolled 74 patients with BRVO and 46 age-matched healthy subjects. The severity of macular ischemia was graded as mild, moderate, or severe. Denoised OCTA images were produced using a neural network model. Quantitative parameters derived from denoised images, including vessel density and nonperfusion area, were compared with those derived from the OCTA machine. The main outcome measures were correlations between quantitative parameters, and areas under receiver operating characteristic curves (AUCs) in classifying the severity of the macular ischemia.ResultsThe vessel density and nonperfusion area from denoised images were correlated strongly with the corresponding parameters from machine-derived images in control eyes and BRVO eyes with mild or moderate macular ischemia (all P < 0.001). However, no such correlation was found in eyes with severe macular ischemia. The vessel density and nonperfusion area from denoised images had significantly larger area under receiver operating characteristic curve than those derived from the original images in classifying moderate versus severe macular ischemia (0.927 vs 0.802 [P = 0.042] and 0.946 vs 0.797, [P = 0.022], respectively). There were no significant differences in the areas under receiver operating characteristic curve between the denoised images and the machine-derived parameters in classifying control versus BRVO, and mild versus moderate macular ischemia.ConclusionsA neural network model is useful for removing speckle noise on OCTA images and facilitating the automated grading of macular ischemia in eyes with BRVO.Translational relevanceDeep-learning denoised optical coherence tomography angiography images could enhance automated macular ischemia quantification.

Dataset Information

Optical coherence tomography angiography for noninvasive evaluation of angiogenesis in a limb ischemia mouse model.

Publications

Optical coherence tomography angiography for noninvasive evaluation of angiogenesis in a limb ischemia mouse model.

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