The value of contrast-enhanced ultrasonography in predicting stroke occurrence: A prospective study
Yunqian Huang1,2, Chuanjian Chen2, Junni Shi2
1Department of Stroke Center, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu province, China.
Objectives:
This study aimed to investigate the association between contrast-enhanced ultrasound-detected (CEUS) perfusion patterns of carotid plaque and the occurrence of stroke.
Materials And Methods:
This prospective observational study finally enrolled 256 patients (151 of them having undergone CEUS) from 7851 patients who underwent carotid artery ultrasound from May 2019 to December 2019 with the endpoint being the occurrence of stroke. The risk factors and carotid ultrasound fetures was obtained from those patients. Analyze the relationship between these variables and stoke occurrence.
Results:
Patients in the recurrent stroke group and those in the no-recurrent stroke group were statistically different in stenosis rate, plaque echo, fibrous cap integrity, calcification of fibrous cap, hypoechoic area within the plaque, and the pattern of neovascularization perfusion from plaque surface to plaque interior (P < 0.05). Upon adjusting for variables, in all subjects, Cox regression analysis showed that symptoms experienced within the past 6 months (RR = 2.486, 95 % CI: 1.282-4.821), moderate-to-severe carotid stenosis (RR = 2.407, 95 % CI: 1.480-4.593), calcification of fibrous cap (RR = 1.599, 95 % CI: 0.727-3.516) and patchy hypoechoic areas within plaque (RR = 2.486, 95 % CI: 1.107-5.578)independently predicted stroke occurrence across all subjects.; Among subjects underwent CEUS, Cox regression analysis demonstrated that moderate-to-severe carotid artery stenosis (RR = 2.105, 95 % CI: 1.425-4.510) and microbubbles entering the interior of the plaque from its surface (RR = 2.323, 95 % CI: 1.175-4. 594) were independent predictors of stroke occurrence.
Conclusions:
The neovascularization perfusion pattern from the plaque surface to its interior serves as an independent predictor of stroke occurrence, thereby potentially enhancing clinical decision-making.
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