Diagnostic Utility of Combined 2D Ultrasonography and Contrast-Enhanced Ultrasonography in Evaluation of Carotid Plaque Vulnerability for Predicting Recurrent Ischemic Strokes
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Abstract Objective: To evaluate the sensitivity and specificity of combined 2D ultrasonography (USG) and contrast-enhanced ultrasonography (CEUS) in analyzing the carotid plaque vulnerability for predicting the recurrent ischemic strokes (IS). Methods: One hundred and fifteen patients with first IS were studied by 2D USG and CEUS. The carotid plaques were then classified on the basis of echogenicity (2D USG) and neovascularization (CEUS). The presence or absence of recurrent IS was considered as the dependent variable. Age, gender, body mass index (BMI), hypertension, hyperglycemia, hyperlipidemia, history of smoking and drinking, type of plaque echogenicity, and grade of plaque neovascularization were considered as independent variables. The risk factors of recurrent IS were analyzed by both univariate and multivariate logistic regression analysis. Finally, the sensitivity and specificity of combined 2D USG and CEUS in the diagnosis of recurrent IS was evaluated by receiver operating characteristic curve. Results: Univariate logistic regression analysis revealed that hypertension, echogenicity type, and grade of plaque neovascularization were predictors of recurrent IS. Further, multivariate logistic regression analysis revealed that the echogenicity type (OR=0.282, P=0.012) and grade of plaque neovascularization (OR=7.408, P<0.0001) were independent risk factors for recurrent IS. The sensitivity, specificity, and area under the curve of combined method were 0.865, 0.769, and 0.817, respectively (95%CI: 0.733-0.902, P<0.0001), which were higher than both 2D USG and CEUS.Conclusions: The echogenicity type and grade of plaque neovascularization are independent risk factors for recurrent IS. The combination of two methods has high sensitivity and specificity in predicting the recurrent IS.
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Diagnostic Utility of Combined 2D Ultrasonography and Contrast-Enhanced Ultrasonography in Evaluation of Carotid Plaque Vulnerability for Predicting Recurrent Ischemic Strokes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Diagnostic Utility of Combined 2D Ultrasonography and Contrast-Enhanced Ultrasonography in Evaluation of Carotid Plaque Vulnerability for Predicting Recurrent Ischemic Strokes Fuyong Ye, Yuwen Yang, Yinting Liang, Jianhua Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-535750/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: To evaluate the sensitivity and specificity of combined 2D ultrasonography (USG) and contrast-enhanced ultrasonography (CEUS) in analyzing the carotid plaque vulnerability for predicting the recurrent ischemic strokes (IS). Methods: One hundred and fifteen patients with first IS were studied by 2D USG and CEUS. The carotid plaques were then classified on the basis of echogenicity (2D USG) and neovascularization (CEUS). The presence or absence of recurrent IS was considered as the dependent variable. Age, gender, body mass index (BMI), hypertension, hyperglycemia, hyperlipidemia, history of smoking and drinking, type of plaque echogenicity, and grade of plaque neovascularization were considered as independent variables. The risk factors of recurrent IS were analyzed by both univariate and multivariate logistic regression analysis. Finally, the sensitivity and specificity of combined 2D USG and CEUS in the diagnosis of recurrent IS was evaluated by receiver operating characteristic curve. Results: Univariate logistic regression analysis revealed that hypertension, echogenicity type, and grade of plaque neovascularization were predictors of recurrent IS. Further, multivariate logistic regression analysis revealed that the echogenicity type (OR=0.282, P=0.012) and grade of plaque neovascularization (OR=7.408, P<0.0001) were independent risk factors for recurrent IS. The sensitivity, specificity, and area under the curve of combined method were 0.865, 0.769, and 0.817, respectively (95%CI: 0.733-0.902, P<0.0001), which were higher than both 2D USG and CEUS. Conclusions: The echogenicity type and grade of plaque neovascularization are independent risk factors for recurrent IS. The combination of two methods has high sensitivity and specificity in predicting the recurrent IS. Cardiac & Cardiovascular Systems 2D ultrasonography Carotid plaque Contrast-enhanced ultrasonography Ischemic stroke Recurrence Figures Figure 1 Figure 2 1 | Introduction Amongst strokes, ischemic type is most frequently observed and accounts for 70–80% of the total cases [ 1 ]. Ischemic stroke (IS) is characterized by high rates of incidence, disability, and recurrence. Previous studies evaluating cerebral infarcts have demonstrated a one-year recurrence rate of 32% [ 2 ]. Thus, the prognosis of patients with IS can be significantly improved by effective prevention of recurrent cerebral infarcts. Carotid atherosclerotic plaque has been identified as an independent risk factor for IS [ 3 ]. Histopathological studies have demonstrated that plaque neovascularization is a marker of plaque vulnerability [ 4 ]. Moreover, several researchers have reported that plaque neovascularization is linked to high risk characteristics of plaque [ 5 , 6 ]. Therefore, early identification of plaque neovascularization and evaluation of its vulnerability are of great value in clinical prevention of recurrent strokes. Conventional ultrasonography (CUS) is the most commonly employed imaging method for examination of carotid plaques and can evaluate plaque stability on the basis of echogenicity, shape, size, and integrity of fibrous cap. However, it cannot detect neovascularization in plaques. Contrast enhanced ultrasonography (CEUS) is a novel method to evaluate the stability of carotid plaques. It not only identifies the plaque neovascularization in real time, but can also quantitatively evaluate its density [ 7 ]. In the past, CUS or CEUS was used to evaluate the vulnerability of plaque. However, their combined ability to improve the predictive value of recurrent cerebral infarcts has not been clarified. Thus, the aim of the present study was to assess the combined sensitivity and specificity of two dimensional (2D) ultrasonography (USG) and CEUS for evaluation of carotid plaques in predicting the recurrence of IS. 2 | Materials And Methods 2.1 | Patients One hundred and fifteen cases, including 76 males and 39 females, with acute stroke, hospitalized in the Department of Neurology, Gaozhou People's Hospital between January 2020 and March 2021 were included in the study. The age of the study population ranged from 47 to 91 years, with a mean age of 70.0±10.1 years. In all the patients, computed tomography (CT) or magnetic resonance imaging (MRI) was used to arrive at the diagnosis of atherosclerotic cerebral infarcts. In a calm state, the systolic (SBP) and diastolic (DBP) blood pressure of brachial artery were assessed thrice and the mean values were calculated. In the morning, fasting state venous blood sample (3ml) was collected to evaluate the fasting blood glucose, and lipid profile. The cases belonging to an age group of 18 years or more, with an initial stroke involving carotid artery territory confirmed by MRI or CT, an ultrasonography demonstrating plaques in carotid artery with a size of 2 mm or more, and those willing to follow-up for 15 months were included in the study. While, cases allergic to sulfur hexafluoride, and with contraindication to CEUS were excluded [8, 9]. Moreover, to exclude the influence of stenosis, patients with severe stenosis (70% or more, according to NASCET) of carotid artery were not included. The present study focused on the vulnerability of carotid plaques and the recurrence of cerebral infarct was the end point of the study. The study protocol was reviewed and approved by the Ethics Review Committee, Gaozhou People's Hospital. As per the requirements of the National Legislation and Institutions, the written informed consent from the patients was not required. 2.2 Instruments and Methods 2.2.1 Instruments CEUS of the carotid plaque was performed with Esaote MyLab Class C scanner (MyLabClassC Advanced, Esaote, Genova, Italy), equipped with a 12-18 MHz linear transducer. 2.2.2 Ultrasonographic examination The common carotid, internal carotid, external carotid, and vertebral arteries were examined by 2D USG. The stenosis of carotid artery, and the number and distribution of carotid plaques were noted. The thickest carotid plaque was identified and evaluated. The same plaque was studied by both 2D USG and CEUS. The CEUS examination was performed following a bolus injection of SonoVue (Bracco, Milan, Italy). Dynamic images were continuously collected for further offline analysis. 2.2.3 Grading of plaques The plaque echogenicity was interpreted by visual analysis on 2D USG and classified into following 5 types: Type 1 (Uniformly anechoic plaque), Type 2 (Predominantly hypoechoic or anechoic plaque), Type 3 (Predominantly echoic or isoechoic plaque), Type 4 (Uniformly isoechoic or uniformly hyperechoic), and Type 5 (Unclassified calcified plaque) [8, 10]. Obvious hyperechoic (part of Type 4) and calcified plaques (Type 5) which didn`t show contrast were excluded from the present study. CEUS was used to grade the neovascularization of carotid artery plaques and included four grades as follows: Grade 0 (no enhancement of plaques, denoting absence of plaque neovascularization), Grade 1 (Several punctate enhancements within adventitia or tissue surrounding the plaque suggesting limited presence of plaque neovascularization), Grade 2 (Adventitia or shoulder of the plaque was enhanced, suggesting moderate neovascularization, less neovascularization than Grade 3 but more than Grade 1), and Grade 3 (Diffuse enhancement within the plaque suggesting the presence of a pulsatile artery within the plaque) [11]. 2.3 Statistical analysis The continuous data with normal distribution was represented in terms of as mean ± standard deviation (SD), while categorical data was represented in terms of frequency (percentage). The continuous and categorical data were compared with Student's t-test and Chi-Square or Fisher’s exact test, respectively. Univariate and multivariate logistic regression analysis was used to determine the independent risk factors of recurrent cerebral infarcts. Presence or absence of recurrent cerebral infarct was used as a binary dependent variable. The receiver operating characteristic (ROC) curve was used to evaluate the sensitivity and specificity of independent risk factors in predicting the recurrent cerebral infarcts. The data was analysed with SPSS (IBM, Armonk, NY, USA) version 23.0 for windows. A probability (P) of less than 0.05 was considered as statistically significant. 3 | Results The present study involved 115 cases with acute IS, of which 37 (32.2%) had recurrent IS during the study period. Comparison of characteristics between recurrent (n = 37) and non-recurrent (n = 78) groups revealed no significant difference between them in terms of mean age, gender, body mass index (BMI), DBP, fasting plasma glucose (FPG), total cholesterol (TC), triglyceride (TG), and high density lipoprotein-cholesterol (HDL-C) (all P＞0.05), except SBP (P = 0.039) (Table 1). Univariate logistic regression analysis revealed that hypertension (Odd’s ratio (OR) = 0.371, 95% confidence interval (CI): 0.163 – 0.843; P = 0.018), type of echogenicity on 2D USG (OR = 0.247, 95%CI: 0.143 – 0.427; P < 0.0001), and grade of carotid artery plaque neovascularization on CEUS (OR = 10.346, 95%CI: 4.335 – 24.692) were predictors of recurrent IS (Table 2). Further analysis by multivariate logistic regression analysis revealed that type of echogenicity (OR = 0.282, 95%CI: 0.105 – 0.756; P = 0.012) and the grade of carotid artery plaque neovascularization (OR = 7.408, 95%CI: 2.952 – 18.593; P < 0.0001) were markers of recurrent cerebral infarcts (Table 3). Analysis by ROC curve demonstrated that the sensitivity, specificity, and area under the curve (AUC) for predicting the recurrent cerebral infarcts with Type 1 and 2 echogenicity (maximum Youden index: 0.409) were 0.730, 0.679, and 0.705 (95% CI: 0.602-0.807; P < 0.0001), respectively. The corresponding values for CEUS Grade 2 or more (maximum Youden index: 0.474) were 0.730, 0.744, and 0.737 (95% CI: 0.636-0.837, P < 0.0001), respectively. Similarly, the corresponding values for the combination of 2D USG and CEUS (maximum Youden index 0.634) were 0.865, 0.769, and 0.817 (95% CI: 0.733-0.902, P < 0.0001), respectively (Images 1, 2). 4 | Discussion The present study suggest that the type of echogenicity and grade of carotid artery plaque neovascularization were independent risk factors for recurrent IS. The combination of 2D USG and CEUS was found to have a good sensitivity and specificity for predicting the recurrent cerebral infarcts. At present, there are many known risk factors of recurrent cerebral infarcts. Amongst them, age, gender, hypertension, diabetes, hyperlipidemia, and history of smoking have been confirmed to be closely associated with recurrent cerebral infarcts [ 12 , 13 ]. Previous studies have demonstrated that this association is mainly due to the fact that these risk factors have the ability to cause the progression of atherosclerosis and further lead to recurrent cerebral infarcts [ 14 ]. Contrarily, the present study demonstrated no significant difference between the recurrent and non-recurrent groups in terms of mean age, gender, BMI, diabetes, and hyperlipidemia. Thus, it may be suggested that the above risk factors have little value in predicting the recurrent cerebral infarcts. Moreover, these risk factors may be of value in increasing the chances and triggering the events leading to cerebral infarcts. However, they may not have any role in promoting their recurrence. The only risk factor with significant difference between the groups was systolic hypertension. Thus, poorly controlled SBP might have resulted in altered structure of carotid artery wall and induced recurrent IS [ 13 ]. In the present study, univariate and multivariate logistic regression analysis demonstrated that grade of carotid plaque echogenicity was an independent predictor of recurrent cerebral infarcts. In ROC curve analysis, the AUC was 0.705 (95%CI: 0.602–0.807; P = 0.000) for predicting recurrent cerebral infarcts with Type 1 and 2 echogenicity. This finding is consistent with the previous study [ 15 ]. The echogenicity of carotid plaques on 2D USG is an indirect parameter reflecting their vulnerability. Previous studies have confirmed that the echogenicity of carotid plaque is closely associated with the recurrent cerebral infarcts [ 16 ]. The highly vulnerable plaques rich in lipid or those having internal bleeding are mostly hypoechoic, while the less vulnerable plaques rich in fibrous tissue are more hyperechoic [ 16 ]. However, the degree of plaque vulnerability cannot be accurately reflected. Intraplaque neovascularization is closely related to intraplaque hemorrhage, which is the main cause of IS [ 16 – 19 ]. CEUS can accurately reflect the neovascularization in carotid plaques and is an effective parameter to directly reflect their vulnerability [ 4 , 20 ]. CEUS can not only result in significantly improved imaging of blood flow and vascular wall, but also depict microvasculature. Moreover, even a single microbubble can be displayed at the capillary level [ 21 ]. For homogeneous fibrous tissue and mixed plaques, CEUS can also accurately evaluate their vulnerability [ 22 ]. The guidelines and recommendations of the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) have clearly proposed that CEUS can evaluate the stability of carotid plaques by detecting neovascularization [ 7 ]. In addition to the plaque neovascularization, CEUS can also detect ulceration on the surface of carotid plaques, and accurately display the shape, size, depth, and other characteristics of ulceration [ 23 , 24 ]. In the present study, CEUS had better sensitivity and specificity than 2D USG in predicting recurrent cerebral infarcts. It was found to be an independent risk predictor and closely associated with the recurrent cerebral infarcts. In multivariate logistic regression analysis, the OR of ECUS in predicting recurrent IS was much higher than that of 2D USG (7.408 vs 0.282). This could be due to the exclusion of hyperechoic and calcified plaques. However, in some cases, such as those with fresh thrombosis-associated carotid plaque, or vulnerable plaques without neovascularization, the reference value of 2D USG was greater than that of CEUS. The combination and cross reference of the both the methods can greatly improve the accuracy of diagnosis. The present study combined the two techniques to evaluate the carotid plaques, and provided a more reliable basis for judging their stability. The ROC curve analysis of the combined method resulted in an AUC of 0.817 (95%CI: 0.733–0.902; P < 0.0001), which was larger than that of 2D USG (AUC = 0.705; 95%CI: 0.602–0.807; P = 0.000) and CEUS (AUC = 0.737; 95%CI: 0.636–0.837; P < 0.0001). 5 | Limitations In the present study, the thickest plaque rather than plaque which caused the recurrence of IS was evaluated. However, previous studies have reported that the stability of the largest plaque is significantly related to the occurrence of cerebral infarcts [ 25 , 26 ]. Moreover, the present study was retrospective in nature and whether the conclusions drawn hold the same significance in the prospective study needs to be evaluated further. 6 | Conclusion The 2D USG-based echogenicity classification and CEUS-based grade of carotid plaque neovascularization were found to be the independent risk factors for recurrence of IS. The combination of the two methods had high sensitivity and specificity in predicting the recurrence of IS, which has clinical importance. Declarations Availability of data and materials The regarding raw data and material of this manuscript can be available through the corresponding author by [email protected] if required. Acknowledgements The authors would like to thank Medjaden Bioscience Limited for assistance with language editing. Funding No funding was received Author information Fuyong Ye 1,2 , Yuwen Yang 1,3 , Yinting Liang 2 , Jianhua Liu 1,3 1 The First Affiliated Hospital of Jinan University, Guangzhou, China. 2 Department of Medical Ultrasound, Gaozhou People’s Hospital, Gaozhou, Guangdong, China. 3 Department of Medical Ultrasound, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, China. Fuyong Ye and Yuwen Yang contributed equally to this work. *Correspondence to Jianhua Liu, Department of Medical Ultrasound, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, China. Tel: +86 20 81048075, Fax: +86 20 81048075, Email: [email protected] Contributions Fuyong Ye and Yuwen Yang enrolled patients, directed the researches, carried out statistical analysis, and wrote the manuscript. Xiaofang Li, Fei Lin and Yinting Liang acquired and analyzed echocardiographic images. Jianhua Liu conceived, instructed, reviewed, and revised the manuscript. All authors read and approved the final manuscript. Ethics declarations The study protocol was approved by the ethics committee of Gaozhou People’s Hospital ( Guangdong, China). Written informed consent was obtained from all participants. Consent for publication Not applicable. Competing interests None. 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Characteristics of Two Groups Characteristic Recurrent group (n=37) Non- recurrent group (n=78) t/X 2 value p value Age(y) 69.5±10.4 70.2±10.0 -0.303 0.762 Male gender 26 (70.3%) 50 (64.1%) 0.426 0.514 BMI (KG/M2) 23.9±2.5 23.0±3.0 0.301 0.764 SBP (mmHg) 138.6±17.5 133.8±15.6 2.084 0.039 DBP (mmHg) 84.4±9.6 82.1±8.9 -0.445 0.657 FPG (mmol/L) 6.55±1.77 6.07±1.60 1.650 0.102 TC (mmol/L) 4.66±1.30 4.29±1.03 1.469 0.145 TG (mmol/L) 1.62±0.88 1.39±1.01 -1.008 0.316 HDL-C (mmol/L) 1.12±0.69 1.24±0.71 -0.482 0.631 BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglyceride; HDL-C, high density lipoprotein-cholesterol. Table 2. Univariate Logistic Regression Analysis of Predictors of Recurrence Risk of Ischemic Stroke Parameter B SE. Wals P OR (95% CI) Age -0.006 0.020 0.093 0.760 0.994 (0.956~1.033) Gender -0.280 0.430 0.425 0.515 0.755 (0.325~1.756) BMI 0.020 0.067 0.092 0.762 1.021 (0.895~1.164) Hypertension -0.992 0.419 5.606 0.018 0.371 (0.163~0.843) Hyperglycemia -0.727 0.419 3.012 0.083 0.484 (0.213~1.099) Hyperlipidemia -0.323 0.402 0.647 0.421 0.724 (0.329~1.591) History of drinking 0.735 0.435 2.859 0.091 2.086 (0.890~4.893) History of smoking -0.148 0.402 0.135 0.713 0.863 (0.393~1.896) 2D ultrasound -1.398 0.279 25.071 0.000 0.247 (0.143~0.427) CEUS 2.337 0.444 27.713 0.000 10.346 (4.335~24.692) 2D, two dimension; CEUS, contrast enhanced ultrasound Table 3. Multivariate Logistic Regression Analysis of Predictors of Recurrence Risk of Ischemic Stroke Parameter B SE. Wals P OR (95% CI) Hypertension -0.278 0.542 0.262 0.609 0.758 (0.262~2.192) 2D ultrasound -1.266 0.503 6.336 0.012 0.282 (0.105~0.756) CEUS 2.003 0.469 18.196 0.000 7.408 (2.952~18.593) Constant -1.752 1.135 2.384 0.123 0.173 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-535750","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":28108767,"identity":"6c962bcb-7635-4e27-b9bf-2517553b996c","order_by":0,"name":"Fuyong Ye","email":"","orcid":"","institution":"Jinan University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fuyong","middleName":"","lastName":"Ye","suffix":""},{"id":28108768,"identity":"a606251a-daa9-483b-9cb7-97ef8358b899","order_by":1,"name":"Yuwen Yang","email":"","orcid":"","institution":"Jinan University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuwen","middleName":"","lastName":"Yang","suffix":""},{"id":28108769,"identity":"97af0616-2518-428c-95a9-b70e093e2bf7","order_by":2,"name":"Yinting Liang","email":"","orcid":"","institution":"Gaozhou People's Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yinting","middleName":"","lastName":"Liang","suffix":""},{"id":28108770,"identity":"c560482f-172a-41df-95c7-e521550967ff","order_by":3,"name":"Jianhua Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYBACPmYGBoMEBgYgYj744EOFhJw8IS1sCC1syYYzzlgYGzYQ0gKlgVp4zIQ52yoSGQ4Q0sLOY1DwoOZOnsHxA2bMjPMkEhgbmB8+uoHXYTwGBgnHnhUbnElIe1y4TSKPnYHN2DiHoBa2w4kbDiQcN565TaKYsYGHTZqwln9ALecftknzzpFIbDhAjJbENqCWG8ls0rwNRGlhKzBI7DucOPPGM2bDGcckjA2bCfiFn//wNsMf3w4n9p3P//jgQ02dnDx788PH+LSALDJA5TPjVw5W8oCwmlEwCkbBKBjRAAD+YkwUrSuQjwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-0200-8482","institution":"Jinan University First Affiliated Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jianhua","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2021-05-17 17:48:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-535750/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-535750/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":9934213,"identity":"2f674e39-5726-4c7a-a626-38fbc8e1ee2c","added_by":"auto","created_at":"2021-06-03 12:53:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1356765,"visible":true,"origin":"","legend":"A~D. The carotid artery plaque neovascularization was graded from 0 to 3 by CEUS. A: Grade 0; B: Grade 1; C: Grade 2; D: Grade 3. ","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-535750/v1/322031e1a1124714e7399000.png"},{"id":9934212,"identity":"6dc6a7aa-f406-434d-8506-a61364169048","added_by":"auto","created_at":"2021-06-03 12:53:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":201216,"visible":true,"origin":"","legend":"The ROC curve of 2D ultrasound, CEUS and combination of two methods in predicting recurrence of ischemic stroke","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-535750/v1/51bc3a2252ca521d2c4d21ec.png"},{"id":17359110,"identity":"a3c99994-c9e8-4a5d-aa90-34af1c8d3fcd","added_by":"auto","created_at":"2022-01-16 16:43:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2354831,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-535750/v1/f45fca7b-61d0-4001-9e4c-4e2de96504ed.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eDiagnostic Utility of Combined 2D Ultrasonography and Contrast-Enhanced Ultrasonography in Evaluation of Carotid Plaque Vulnerability for Predicting Recurrent Ischemic Strokes\u003c/p\u003e","fulltext":[{"header":"1 | Introduction","content":" \u003cp\u003eAmongst strokes, ischemic type is most frequently observed and accounts for 70\u0026ndash;80% of the total cases [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Ischemic stroke (IS) is characterized by high rates of incidence, disability, and recurrence. Previous studies evaluating cerebral infarcts have demonstrated a one-year recurrence rate of 32% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Thus, the prognosis of patients with IS can be significantly improved by effective prevention of recurrent cerebral infarcts.\u003c/p\u003e \u003cp\u003eCarotid atherosclerotic plaque has been identified as an independent risk factor for IS [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Histopathological studies have demonstrated that plaque neovascularization is a marker of plaque vulnerability [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, several researchers have reported that plaque neovascularization is linked to high risk characteristics of plaque [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, early identification of plaque neovascularization and evaluation of its vulnerability are of great value in clinical prevention of recurrent strokes.\u003c/p\u003e \u003cp\u003eConventional ultrasonography (CUS) is the most commonly employed imaging method for examination of carotid plaques and can evaluate plaque stability on the basis of echogenicity, shape, size, and integrity of fibrous cap. However, it cannot detect neovascularization in plaques. Contrast enhanced ultrasonography (CEUS) is a novel method to evaluate the stability of carotid plaques. It not only identifies the plaque neovascularization in real time, but can also quantitatively evaluate its density [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the past, CUS or CEUS was used to evaluate the vulnerability of plaque. However, their combined ability to improve the predictive value of recurrent cerebral infarcts has not been clarified. Thus, the aim of the present study was to assess the combined sensitivity and specificity of two dimensional (2D) ultrasonography (USG) and CEUS for evaluation of carotid plaques in predicting the recurrence of IS.\u003c/p\u003e "},{"header":"2 | Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 | Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne hundred and fifteen cases, including 76 males and 39 females, with acute stroke, hospitalized in the Department of Neurology, Gaozhou People's Hospital between January 2020 and March 2021 were included in the study. The age of the study population ranged from 47 to 91 years, with a mean age of 70.0\u0026plusmn;10.1 years. In all the patients, computed tomography (CT) or magnetic resonance imaging (MRI) was used to arrive at the diagnosis of atherosclerotic cerebral infarcts. In a calm state, the systolic (SBP) and diastolic (DBP) blood pressure of brachial artery were assessed thrice and the mean values were calculated. In the morning, fasting state venous blood sample (3ml) was collected to evaluate the fasting blood glucose, and lipid profile.\u003c/p\u003e\n\u003cp\u003eThe cases belonging to an age group of 18 years or more, with an initial stroke involving carotid artery territory confirmed by MRI or CT, an ultrasonography demonstrating plaques in carotid artery with a size of 2 mm or more, and those willing to follow-up for 15 months were included in the study. While, cases allergic to sulfur hexafluoride, and with contraindication to CEUS were excluded [8, 9]. Moreover, to exclude the influence of stenosis, patients with severe stenosis (70% or more, according to NASCET) of carotid artery were not included. The present study focused on the vulnerability of carotid plaques and the recurrence of cerebral infarct was the end point of the study.\u003c/p\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by the Ethics Review Committee, Gaozhou People's Hospital. As per the requirements of the National Legislation and Institutions, the written informed consent from the patients was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Instruments and Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.1 Instruments\u003c/strong\u003e CEUS of the carotid plaque was performed with Esaote MyLab Class C scanner (MyLabClassC Advanced, Esaote, Genova, Italy), equipped with a 12-18 MHz linear transducer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.2 Ultrasonographic examination \u003c/strong\u003eThe common carotid, internal carotid, external carotid, and vertebral arteries were examined by 2D USG. The stenosis of carotid artery, and the number and distribution of carotid plaques were noted. The thickest carotid plaque was identified and evaluated. The same plaque was studied by both 2D USG and CEUS. The CEUS examination was performed following a bolus injection of\u0026nbsp;SonoVue\u0026nbsp;(Bracco, Milan, Italy). Dynamic images were continuously collected for further offline analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.3 Grading of plaques\u003c/strong\u003e The plaque echogenicity was interpreted by visual analysis on 2D USG and classified into following 5 types: Type 1 (Uniformly anechoic plaque), Type 2 (Predominantly hypoechoic or anechoic plaque), Type 3 (Predominantly echoic or isoechoic plaque), Type 4 (Uniformly isoechoic or uniformly hyperechoic), and Type 5 (Unclassified calcified plaque) [8, 10]. Obvious hyperechoic (part of Type 4) and calcified plaques (Type 5) which didn`t show contrast were excluded from the present study.\u003c/p\u003e\n\u003cp\u003eCEUS was used to grade the neovascularization of carotid artery plaques and included four grades as follows: Grade 0 (no enhancement of plaques, denoting absence of plaque neovascularization), Grade 1 (Several punctate enhancements within adventitia or tissue surrounding the plaque suggesting limited presence of plaque neovascularization), Grade 2 (Adventitia or shoulder of the plaque was enhanced, suggesting moderate neovascularization, less neovascularization than Grade 3 but more than Grade 1), and Grade 3 (Diffuse enhancement within the plaque suggesting the presence of a pulsatile artery within the plaque) [11].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe continuous data with normal distribution was represented in terms of as mean \u0026plusmn; standard deviation (SD), while categorical data was represented in terms of frequency (percentage). The continuous and categorical data were compared with Student's t-test and Chi-Square or Fisher\u0026rsquo;s exact test, respectively. Univariate and multivariate logistic regression analysis was used to determine the independent risk factors of recurrent cerebral infarcts. Presence or absence of recurrent cerebral infarct was used as a binary dependent variable. The receiver operating characteristic (ROC) curve was used to evaluate the sensitivity and specificity of independent risk factors in predicting the recurrent cerebral infarcts. The data was analysed with SPSS (IBM, Armonk, NY, USA) version 23.0 for windows. A probability (P) of less than 0.05 was considered as statistically significant.\u003c/p\u003e"},{"header":"3 | Results","content":"\u003cp\u003eThe present study involved 115 cases with acute IS, of which 37 (32.2%) had recurrent IS during the study period.\u003c/p\u003e\n\u003cp\u003eComparison of characteristics between recurrent (n = 37) and non-recurrent (n = 78) groups revealed no significant difference between them in terms of mean age, gender, body mass index (BMI), DBP, fasting plasma glucose (FPG), total cholesterol (TC), triglyceride (TG), and high density lipoprotein-cholesterol (HDL-C) (all P＞0.05), except SBP (P = 0.039) (Table 1).\u003c/p\u003e\n\u003cp\u003eUnivariate logistic regression analysis revealed that hypertension (Odd\u0026rsquo;s ratio (OR) = 0.371, 95% confidence interval (CI): 0.163 \u0026ndash; 0.843; P = 0.018), type of echogenicity on 2D USG (OR = 0.247, 95%CI: 0.143 \u0026ndash; 0.427; P \u0026lt; 0.0001), and grade of carotid artery plaque neovascularization on CEUS (OR = 10.346, 95%CI: 4.335 \u0026ndash; 24.692) were predictors of recurrent IS (Table 2). Further analysis by multivariate logistic regression analysis revealed that type of echogenicity (OR = 0.282, 95%CI: 0.105 \u0026ndash; 0.756; P = 0.012) and the grade of carotid artery plaque neovascularization (OR = 7.408, 95%CI: 2.952 \u0026ndash; 18.593; P \u0026lt; 0.0001) were markers of recurrent cerebral infarcts (Table 3).\u003c/p\u003e\n\u003cp\u003eAnalysis by ROC curve demonstrated that the sensitivity, specificity, and area under the curve (AUC) for predicting the recurrent cerebral infarcts with Type 1 and 2 echogenicity (maximum Youden index: 0.409) were 0.730, 0.679, and 0.705 (95% CI: 0.602-0.807; P \u0026lt; 0.0001), respectively. The corresponding values for CEUS Grade 2 or more (maximum Youden index: 0.474) were 0.730, 0.744, and 0.737 (95% CI: 0.636-0.837, P \u0026lt; 0.0001), respectively. Similarly, the corresponding values for the combination of 2D USG and CEUS (maximum Youden index 0.634) were 0.865, 0.769, and 0.817 (95% CI: 0.733-0.902, P \u0026lt; 0.0001), respectively (Images 1, 2).\u003c/p\u003e"},{"header":"4 | Discussion","content":" \u003cp\u003eThe present study suggest that the type of echogenicity and grade of carotid artery plaque neovascularization were independent risk factors for recurrent IS. The combination of 2D USG and CEUS was found to have a good sensitivity and specificity for predicting the recurrent cerebral infarcts.\u003c/p\u003e \u003cp\u003eAt present, there are many known risk factors of recurrent cerebral infarcts. Amongst them, age, gender, hypertension, diabetes, hyperlipidemia, and history of smoking have been confirmed to be closely associated with recurrent cerebral infarcts [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Previous studies have demonstrated that this association is mainly due to the fact that these risk factors have the ability to cause the progression of atherosclerosis and further lead to recurrent cerebral infarcts [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eContrarily, the present study demonstrated no significant difference between the recurrent and non-recurrent groups in terms of mean age, gender, BMI, diabetes, and hyperlipidemia. Thus, it may be suggested that the above risk factors have little value in predicting the recurrent cerebral infarcts. Moreover, these risk factors may be of value in increasing the chances and triggering the events leading to cerebral infarcts. However, they may not have any role in promoting their recurrence. The only risk factor with significant difference between the groups was systolic hypertension. Thus, poorly controlled SBP might have resulted in altered structure of carotid artery wall and induced recurrent IS [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, univariate and multivariate logistic regression analysis demonstrated that grade of carotid plaque echogenicity was an independent predictor of recurrent cerebral infarcts. In ROC curve analysis, the AUC was 0.705 (95%CI: 0.602\u0026ndash;0.807; P\u0026thinsp;=\u0026thinsp;0.000) for predicting recurrent cerebral infarcts with Type 1 and 2 echogenicity. This finding is consistent with the previous study [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe echogenicity of carotid plaques on 2D USG is an indirect parameter reflecting their vulnerability. Previous studies have confirmed that the echogenicity of carotid plaque is closely associated with the recurrent cerebral infarcts [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The highly vulnerable plaques rich in lipid or those having internal bleeding are mostly hypoechoic, while the less vulnerable plaques rich in fibrous tissue are more hyperechoic [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, the degree of plaque vulnerability cannot be accurately reflected. Intraplaque neovascularization is closely related to intraplaque hemorrhage, which is the main cause of IS [\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. CEUS can accurately reflect the neovascularization in carotid plaques and is an effective parameter to directly reflect their vulnerability [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. CEUS can not only result in significantly improved imaging of blood flow and vascular wall, but also depict microvasculature. Moreover, even a single microbubble can be displayed at the capillary level [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For homogeneous fibrous tissue and mixed plaques, CEUS can also accurately evaluate their vulnerability [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The guidelines and recommendations of the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) have clearly proposed that CEUS can evaluate the stability of carotid plaques by detecting neovascularization [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to the plaque neovascularization, CEUS can also detect ulceration on the surface of carotid plaques, and accurately display the shape, size, depth, and other characteristics of ulceration [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, CEUS had better sensitivity and specificity than 2D USG in predicting recurrent cerebral infarcts. It was found to be an independent risk predictor and closely associated with the recurrent cerebral infarcts. In multivariate logistic regression analysis, the OR of ECUS in predicting recurrent IS was much higher than that of 2D USG (7.408 vs 0.282). This could be due to the exclusion of hyperechoic and calcified plaques.\u003c/p\u003e \u003cp\u003eHowever, in some cases, such as those with fresh thrombosis-associated carotid plaque, or vulnerable plaques without neovascularization, the reference value of 2D USG was greater than that of CEUS. The combination and cross reference of the both the methods can greatly improve the accuracy of diagnosis. The present study combined the two techniques to evaluate the carotid plaques, and provided a more reliable basis for judging their stability. The ROC curve analysis of the combined method resulted in an AUC of 0.817 (95%CI: 0.733\u0026ndash;0.902; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), which was larger than that of 2D USG (AUC\u0026thinsp;=\u0026thinsp;0.705; 95%CI: 0.602\u0026ndash;0.807; P\u0026thinsp;=\u0026thinsp;0.000) and CEUS (AUC\u0026thinsp;=\u0026thinsp;0.737; 95%CI: 0.636\u0026ndash;0.837; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e "},{"header":"5 | Limitations","content":" \u003cp\u003eIn the present study, the thickest plaque rather than plaque which caused the recurrence of IS was evaluated. However, previous studies have reported that the stability of the largest plaque is significantly related to the occurrence of cerebral infarcts [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Moreover, the present study was retrospective in nature and whether the conclusions drawn hold the same significance in the prospective study needs to be evaluated further.\u003c/p\u003e "},{"header":"6 | Conclusion","content":" \u003cp\u003eThe 2D USG-based echogenicity classification and CEUS-based grade of carotid plaque neovascularization were found to be the independent risk factors for recurrence of IS. The combination of the two methods had high sensitivity and specificity in predicting the recurrence of IS, which has clinical importance.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regarding raw data and material of this manuscript can be available through the corresponding author by [email protected] if required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Medjaden Bioscience Limited for assistance with language editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFuyong Ye\u003csup\u003e1,2\u003c/sup\u003e, Yuwen Yang\u003csup\u003e1,3\u003c/sup\u003e, Yinting Liang\u003csup\u003e2\u003c/sup\u003e, Jianhua Liu\u003csup\u003e1,3\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1 The First Affiliated Hospital of Jinan University, Guangzhou, China.\u003c/p\u003e\n\u003cp\u003e2 Department of Medical Ultrasound, Gaozhou People\u0026rsquo;s Hospital, Gaozhou, Guangdong, China.\u003c/p\u003e\n\u003cp\u003e3 Department of Medical Ultrasound, Guangzhou First People\u0026rsquo;s Hospital, School of Medicine, South China University of Technology, Guangzhou, China.\u003c/p\u003e\n\u003cp\u003eFuyong Ye and Yuwen Yang contributed equally to this work.\u003c/p\u003e\n\u003cp\u003e*Correspondence to Jianhua Liu, Department of Medical Ultrasound, Guangzhou First People\u0026rsquo;s Hospital, School of Medicine, South China University of Technology, Guangzhou, China.\u003c/p\u003e\n\u003cp\u003eTel: +86 20 81048075, Fax: +86 20 81048075, Email: \u003ca href=\"mailto:[email protected]\"\[email protected]\u003c/a\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFuyong Ye and Yuwen Yang enrolled patients, directed the researches, carried out statistical analysis, and wrote the manuscript. Xiaofang Li, Fei Lin and Yinting Liang acquired and analyzed echocardiographic images. Jianhua Liu conceived, instructed, reviewed, and revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the ethics committee of Gaozhou People\u0026rsquo;s Hospital ( Guangdong, China). Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMeschia JF, Bushnell C, Boden-Albala B, Braun LT, Bravata DM, Chaturvedi S, Creager MA, Eckel RH, Elkind MS, Fornage M\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eGuidelines for the primary prevention of stroke: a statement for healthcare professionals from the American Heart Association/American Stroke Association\u003c/strong\u003e. \u003cem\u003eStroke \u003c/em\u003e2014, \u003cstrong\u003e45\u003c/strong\u003e(12):3754-3832.\u003c/li\u003e\n\u003cli\u003eOza R, Rundell K, Garcellano M: \u003cstrong\u003eRecurrent Ischemic Stroke: Strategies for Prevention\u003c/strong\u003e. \u003cem\u003eAm Fam Physician \u003c/em\u003e2017, \u003cstrong\u003e96\u003c/strong\u003e(7):436-440.\u003c/li\u003e\n\u003cli\u003eBaradaran H, Al-Dasuqi K, Knight-Greenfield A, Giambrone A, Delgado D, Ebani EJ, Kamel H, Gupta A: \u003cstrong\u003eAssociation between Carotid Plaque Features on CTA and Cerebrovascular Ischemia: A Systematic Review and Meta-Analysis\u003c/strong\u003e. \u003cem\u003eAJNR Am J Neuroradiol \u003c/em\u003e2017, \u003cstrong\u003e38\u003c/strong\u003e(12):2321-2326.\u003c/li\u003e\n\u003cli\u003eCamps-Renom P, Prats-Sanchez L, Casoni F, Gonzalez-de-Echavarri JM, Marrero-Gonzalez P, Castrillon I, Marin R, Jimenez-Xarrie E, Delgado-Mederos R, Martinez-Domeno A\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePlaque neovascularization detected with contrast-enhanced ultrasound predicts ischaemic stroke recurrence in patients with carotid atherosclerosis\u003c/strong\u003e. \u003cem\u003eEur J Neurol \u003c/em\u003e2020, \u003cstrong\u003e27\u003c/strong\u003e(5):809-816.\u003c/li\u003e\n\u003cli\u003eMoreno PR, Purushothaman KR, Fuster V, Echeverri D, Truszczynska H, Sharma SK, Badimon JJ, O'Connor WN: \u003cstrong\u003ePlaque neovascularization is increased in ruptured atherosclerotic lesions of human aorta: implications for plaque vulnerability\u003c/strong\u003e. \u003cem\u003eCirculation \u003c/em\u003e2004, \u003cstrong\u003e110\u003c/strong\u003e(14):2032-2038.\u003c/li\u003e\n\u003cli\u003eWang J, Chen H, Sun J, Hippe DS, Zhang H, Yu S, Cai J, Xie L, Cui B, Yuan C\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eDynamic contrast-enhanced MR imaging of carotid vasa vasorum in relation to coronary and cerebrovascular events\u003c/strong\u003e. \u003cem\u003eAtherosclerosis \u003c/em\u003e2017, \u003cstrong\u003e263\u003c/strong\u003e:420-426.\u003c/li\u003e\n\u003cli\u003eSidhu PS, Cantisani V, Dietrich CF, Gilja OH, Saftoiu A, Bartels E, Bertolotto M, Calliada F, Clevert DA, Cosgrove 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review\u003c/strong\u003e. \u003cem\u003eInt J Stroke \u003c/em\u003e2012, \u003cstrong\u003e7\u003c/strong\u003e(3):243-247.\u003c/li\u003e\n\u003cli\u003eYamauchi H, Kagawa S, Kishibe Y, Takahashi M, Higashi T: \u003cstrong\u003eMisery perfusion, blood pressure control, and 5-year stroke risk in symptomatic major cerebral artery disease\u003c/strong\u003e. \u003cem\u003eStroke \u003c/em\u003e2015, \u003cstrong\u003e46\u003c/strong\u003e(1):265-268.\u003c/li\u003e\n\u003cli\u003eSingh AS, Atam V, Jain N, Yathish BE, Patil MR, Das L: \u003cstrong\u003eAssociation of carotid plaque echogenicity with recurrence of ischemic stroke\u003c/strong\u003e. \u003cem\u003eN Am J Med Sci \u003c/em\u003e2013, \u003cstrong\u003e5\u003c/strong\u003e(6):371-376.\u003c/li\u003e\n\u003cli\u003eSedding DG, Boyle EC, Demandt JAF, Sluimer JC, Dutzmann J, Haverich A, Bauersachs J: \u003cstrong\u003eVasa Vasorum Angiogenesis: Key Player in the Initiation and Progression of Atherosclerosis and Potential Target for the Treatment of Cardiovascular Disease\u003c/strong\u003e. \u003cem\u003eFront Immunol \u003c/em\u003e2018, \u003cstrong\u003e9\u003c/strong\u003e:706.\u003c/li\u003e\n\u003cli\u003eSztajzel R, Momjian S, Momjian-Mayor I, Murith N, Djebaili K, Boissard G, Comelli M, Pizolatto G: \u003cstrong\u003eStratified gray-scale median analysis and color mapping of the carotid plaque: correlation with endarterectomy specimen histology of 28 patients\u003c/strong\u003e. \u003cem\u003eStroke \u003c/em\u003e2005, \u003cstrong\u003e36\u003c/strong\u003e(4):741-745.\u003c/li\u003e\n\u003cli\u003eBredahl K, Mestre XM, Coll RV, Ghulam QM, Sillesen H, Eiberg J: \u003cstrong\u003eContrast-Enhanced Ultrasound in Vascular Surgery: Review and Update\u003c/strong\u003e. \u003cem\u003eAnn Vasc Surg \u003c/em\u003e2017, \u003cstrong\u003e45\u003c/strong\u003e:287-293.\u003c/li\u003e\n\u003cli\u003eHjelmgren O, Johansson L, Prahl U, Schmidt C, Bergstrom GML: \u003cstrong\u003eInverse association between size of the lipid-rich necrotic core and vascularization in human carotid plaques\u003c/strong\u003e. \u003cem\u003eClin Physiol Funct Imaging \u003c/em\u003e2018, \u003cstrong\u003e38\u003c/strong\u003e(2):326-331.\u003c/li\u003e\n\u003cli\u003eSaba L, Saam T, Jager HR, Yuan C, Hatsukami TS, Saloner D, Wasserman BA, Bonati LH, Wintermark M: \u003cstrong\u003eImaging biomarkers of vulnerable carotid plaques for stroke risk prediction and their potential clinical implications\u003c/strong\u003e. \u003cem\u003eLancet Neurol \u003c/em\u003e2019, \u003cstrong\u003e18\u003c/strong\u003e(6):559-572.\u003c/li\u003e\n\u003cli\u003eSchinkel AFL, Bosch JG, Staub D, Adam D, Feinstein SB: \u003cstrong\u003eContrast-Enhanced Ultrasound to Assess Carotid Intraplaque Neovascularization\u003c/strong\u003e. \u003cem\u003eUltrasound Med Biol \u003c/em\u003e2020, \u003cstrong\u003e46\u003c/strong\u003e(3):466-478.\u003c/li\u003e\n\u003cli\u003eRafailidis V, Huang DY, Yusuf GT, Sidhu PS: \u003cstrong\u003eGeneral principles and overview of vascular contrast-enhanced ultrasonography\u003c/strong\u003e. \u003cem\u003eUltrasonography \u003c/em\u003e2020, \u003cstrong\u003e39\u003c/strong\u003e(1):22-42.\u003c/li\u003e\n\u003cli\u003eHamada O, Sakata N, Ogata T, Shimada H, Inoue T: \u003cstrong\u003eContrast-enhanced ultrasonography for detecting histological carotid plaque rupture: Quantitative analysis of ulcer\u003c/strong\u003e. \u003cem\u003eInt J Stroke \u003c/em\u003e2016, \u003cstrong\u003e11\u003c/strong\u003e(7):791-798.\u003c/li\u003e\n\u003cli\u003eRafailidis V, Chryssogonidis I, Tegos T, Kouskouras K, Charitanti-Kouridou A: \u003cstrong\u003eImaging of the ulcerated carotid atherosclerotic plaque: a review of the literature\u003c/strong\u003e. \u003cem\u003eInsights Imaging \u003c/em\u003e2017, \u003cstrong\u003e8\u003c/strong\u003e(2):213-225.\u003c/li\u003e\n\u003cli\u003eten Kate GL, van Dijk AC, van den Oord SC, Hussain B, Verhagen HJ, Sijbrands EJ, van der Steen AF, van der Lugt A, Schinkel AF: \u003cstrong\u003eUsefulness of contrast-enhanced ultrasound for detection of carotid plaque ulceration in patients with symptomatic carotid atherosclerosis\u003c/strong\u003e. \u003cem\u003eAm J Cardiol \u003c/em\u003e2013, \u003cstrong\u003e112\u003c/strong\u003e(2):292-298.\u003c/li\u003e\n\u003cli\u003eChen J, Zhang YM, Song ZZ, Fu YF, Geng Y: \u003cstrong\u003eThe inter-observer agreement in the assessment of carotid plaque neovascularization by contrast-enhanced ultrasonography: The impact of plaque thickness\u003c/strong\u003e. \u003cem\u003eJ Clin Ultrasound \u003c/em\u003e2018, \u003cstrong\u003e46\u003c/strong\u003e(6):403-407.\u003c/li\u003e\n\u003cli\u003eSpence JD: \u003cstrong\u003eCoronary calcium is not all we need: Carotid plaque burden measured by ultrasound is better\u003c/strong\u003e. \u003cem\u003eAtherosclerosis \u003c/em\u003e2019, \u003cstrong\u003e287\u003c/strong\u003e:179-180.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Characteristics of Two Groups\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eCharacteristic\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003eRecurrent group (n=37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eNon- recurrent group (n=78)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003et/X\u003csup\u003e2\u003c/sup\u003e value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eAge(y)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e69.5\u0026plusmn;10.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e70.2\u0026plusmn;10.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e-0.303\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0.762\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eMale gender\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e26 (70.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e50 (64.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.426\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0.514\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eBMI (KG/M2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e23.9\u0026plusmn;2.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e23.0\u0026plusmn;3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.301\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0.764\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eSBP (mmHg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e138.6\u0026plusmn;17.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e133.8\u0026plusmn;15.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e2.084\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0.039\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eDBP (mmHg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e84.4\u0026plusmn;9.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e82.1\u0026plusmn;8.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e-0.445\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0.657\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eFPG (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e6.55\u0026plusmn;1.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e6.07\u0026plusmn;1.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e1.650\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0.102\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eTC (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e4.66\u0026plusmn;1.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e4.29\u0026plusmn;1.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e1.469\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0.145\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eTG (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e1.62\u0026plusmn;0.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e1.39\u0026plusmn;1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e-1.008\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0.316\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eHDL-C (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e1.12\u0026plusmn;0.69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e1.24\u0026plusmn;0.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e-0.482\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e0.631\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglyceride; HDL-C, high density lipoprotein-cholesterol.\u003c/p\u003e\n\u003cp\u003eTable 2. Univariate Logistic Regression Analysis of Predictors of Recurrence Risk of Ischemic Stroke\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eParameter\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003eB\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003eSE.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003eWals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e-0.006\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e0.093\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.760\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e0.994 (0.956~1.033)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eGender\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e-0.280\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.430\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e0.425\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.515\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e0.755 (0.325~1.756)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e0.020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.067\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e0.092\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.762\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e1.021 (0.895~1.164)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e-0.992\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.419\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e5.606\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e0.371 (0.163~0.843)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eHyperglycemia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e-0.727\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.419\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e3.012\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.083\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e0.484 (0.213~1.099)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eHyperlipidemia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e-0.323\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.402\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e0.647\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.421\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e0.724 (0.329~1.591)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eHistory of drinking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e0.735\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.435\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e2.859\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.091\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e2.086 (0.890~4.893)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eHistory of smoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e-0.148\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.402\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e0.135\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.713\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e0.863 (0.393~1.896)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e2D ultrasound\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e-1.398\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.279\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e25.071\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e0.247 (0.143~0.427)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003eCEUS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e2.337\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.444\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"56\"\u003e\n\u003cp\u003e27.713\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"251\"\u003e\n\u003cp\u003e10.346 (4.335~24.692)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e2D, two dimension; CEUS, contrast enhanced ultrasound\u003c/p\u003e\n\u003cp\u003eTable 3. Multivariate Logistic Regression Analysis of Predictors of Recurrence Risk of Ischemic Stroke\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003eParameter\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003eB\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003eSE.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"83\"\u003e\n\u003cp\u003eWals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"169\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e-0.278\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e0.542\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"83\"\u003e\n\u003cp\u003e0.262\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e0.609\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"169\"\u003e\n\u003cp\u003e0.758 (0.262~2.192)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e2D ultrasound\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e-1.266\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e0.503\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"83\"\u003e\n\u003cp\u003e6.336\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e0.012\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"169\"\u003e\n\u003cp\u003e0.282 (0.105~0.756)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003eCEUS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e2.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e0.469\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"83\"\u003e\n\u003cp\u003e18.196\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"169\"\u003e\n\u003cp\u003e7.408 (2.952~18.593)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003eConstant\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"89\"\u003e\n\u003cp\u003e-1.752\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e1.135\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"83\"\u003e\n\u003cp\u003e2.384\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"64\"\u003e\n\u003cp\u003e0.123\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"169\"\u003e\n\u003cp\u003e0.173\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"2D ultrasonography, Carotid plaque, Contrast-enhanced ultrasonography, Ischemic stroke, Recurrence","lastPublishedDoi":"10.21203/rs.3.rs-535750/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-535750/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To evaluate the sensitivity and specificity of combined 2D ultrasonography (USG) and contrast-enhanced ultrasonography (CEUS) in analyzing the carotid plaque vulnerability for predicting the recurrent ischemic strokes (IS). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eOne hundred and fifteen patients with first IS were studied by 2D USG and CEUS. The carotid plaques were then classified on the basis of echogenicity (2D USG) and neovascularization (CEUS). The presence or absence of recurrent IS was considered as the dependent variable. Age, gender, body mass index (BMI), hypertension, hyperglycemia, hyperlipidemia, history of smoking and drinking, type of plaque echogenicity, and grade of plaque neovascularization were considered as independent variables. The risk factors of recurrent IS were analyzed by both univariate and multivariate logistic regression analysis. Finally, the sensitivity and specificity of combined 2D USG and CEUS in the diagnosis of recurrent IS was evaluated by receiver operating characteristic curve. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eUnivariate logistic regression analysis revealed that hypertension, echogenicity type, and grade of plaque neovascularization were predictors of recurrent IS. Further, multivariate logistic regression analysis revealed that the echogenicity type (OR=0.282, P=0.012) and grade of plaque neovascularization (OR=7.408, P\u0026lt;0.0001) were independent risk factors for recurrent IS. The sensitivity, specificity, and area under the curve of combined method were 0.865, 0.769, and 0.817, respectively (95%CI: 0.733-0.902, P\u0026lt;0.0001), which were higher than both 2D USG and CEUS.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThe echogenicity type and grade of plaque neovascularization are independent risk factors for recurrent IS. The combination of two methods has high sensitivity and specificity in predicting the recurrent IS.\u003c/p\u003e","manuscriptTitle":"Diagnostic Utility of Combined 2D Ultrasonography and Contrast-Enhanced Ultrasonography in Evaluation of Carotid Plaque Vulnerability for Predicting Recurrent Ischemic Strokes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-06-03 12:53:39","doi":"10.21203/rs.3.rs-535750/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1102247a-58f8-48ea-ae47-8aa0b98b6616","owner":[],"postedDate":"June 3rd, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":4585317,"name":"Cardiac \u0026 Cardiovascular Systems"}],"tags":[],"updatedAt":"2022-01-16T16:43:42+00:00","versionOfRecord":[],"versionCreatedAt":"2021-06-03 12:53:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-535750","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-535750","identity":"rs-535750","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
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