Neovascularization in carotid atherosclerotic plaques can be effectively evaluated by superb microvascular imaging (SMI): Initial experience
The objective of this study was to investigate the correlation between the amount of blood flow in the area of neovascularization within a carotid atherosclerotic plaque by superb microvascular imaging (SMI) and the microvessel density (MVD) determined by histopathological staining. Twenty-eight car...
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Veröffentlicht in: | Vascular medicine (London, England) England), 2020-08, Vol.25 (4), p.328-333 |
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Sprache: | eng |
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Zusammenfassung: | The objective of this study was to investigate the correlation between the amount of blood flow in the area of neovascularization within a carotid atherosclerotic plaque by superb microvascular imaging (SMI) and the microvessel density (MVD) determined by histopathological staining. Twenty-eight carotid atherosclerotic plaques were detected by SMI in 28 patients who underwent carotid endarterectomy. SMI was graded according to the visual methods as follows: grade I: no appearance of neovascularization within the plaque; grade II: punctate neovascularization; grade III: one or two linear neovascularizations within the plaque; and grade IV: multiple (> 2) linear neovascularizations throughout the plaque. The neovascularization density was determined by the CD31 complex staining method. There was a significant correlation between the density of neovascularization in histopathologic plaques and the blood flow grade found by SMI (r = 0.788, p < 0.001). A significant difference was observed in SMI blood flow grade between the symptomatic and asymptomatic groups (χ2 = 2.634, p = 0.036). The MVD of plaques in the symptomatic group was significantly higher than that in the asymptomatic group (t = 2.530, p = 0.018). The SMI-based classification was positively correlated with plaque thickness. SMI, which is a new nonultrasound contrast-enhanced imaging method, can effectively evaluate neovascularization in carotid atherosclerotic plaques and can be used as a novel method for the clinical prediction of stroke risk. |
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ISSN: | 1358-863X 1477-0377 |
DOI: | 10.1177/1358863X20909992 |