Construction of vulnerable plaque prediction model based on multimodal vascular ultrasound parameters and clinical risk factors

• Published in: Scientific reports 2024-10, Vol.14 (1), p.24255-12, Article 24255
• Main Authors: Yan, Lei, Ye, Xiaojian, Fu, Liyun, Hou, Wanqing, Lin, Shengnan, Su, Hongda
• Format: Article
• Language: English
• Subjects: 692/308; 692/4019; 692/499; 692/700; Aged; Arteriosclerosis; Body mass index; Calibration; Cardiovascular diseases; Carotid Arteries - diagnostic imaging; Carotid Arteries - pathology; Carotid Stenosis - diagnostic imaging; Carotid Stenosis - pathology; Cerebrovascular diseases; Contrast-enhanced ultrasound; Diabetes mellitus; Endarterectomy, Carotid; Female; Humanities and Social Sciences; Humans; Hypertension; Male; Middle Aged; multidisciplinary; Multimodal; Nomograms; Plaque, Atherosclerotic - diagnostic imaging; Plaque, Atherosclerotic - pathology; Plaques; Prediction model; Prediction models; Regression analysis; Risk Assessment; Risk Factors; ROC Curve; Science; Science (multidisciplinary); Smoking; Statistical analysis; Statistical models; Stenosis; Ultrasonic imaging; Ultrasonography - methods; Ultrasound; Vascular diseases; Vascular ultrasound; Vascularization; Vulnerable plaque
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-75375-4

The rupture of vulnerable plaque (VP) are significant pathogenic factors leading to cardiovascular and cerebrovascular diseases. This study aims to construct a vulnerable plaque prediction model (VPPM) by combining multimodal vascular ultrasound parameters and clinical risk factors, and to validate it. A total of 196 atherosclerotic patients who underwent carotid endarterectomy (CEA) from January 2017 to December 2023 were collected and divided into a modeling group ( n  = 137) and a validation group ( n  = 59). Clinical information including: hypertension, diabetes, smoking history, and body mass index (BMI) was included in the analysis. All patients underwent carotid ultrasound and contrast-enhanced ultrasound (CEUS) examination after admission, with main ultrasound parameters including thickness, echogenicity types, stenosis degree, and CEUS neovascularization grading of plaques. Independent risk factors for VP in CEA patients were screened through binary Logistic regression analysis, and a prediction model was established along with a nomogram. The calibration curve, receiver-operating characteristic curve (ROC), and decision curve analysis (DCA) were employed to assess the calibration, diagnostic efficacy, and clinical utility of the VPPM model. There were no significant statistical differences in multimodal vascular ultrasound parameters and clinical risk factors between the modeling and validation groups ( P  > 0.05). Binary Logistic regression analysis identified plaque thickness, echo type, CEUS neovascularization grading, BMI, and smoking history as 5 variables entering the prediction model. The VPPM model showed good diagnostic efficacy, with an area under the ROC curve of 0.959 (95% CI 0.915–0.999). Using the nomogram with a VPPM risk assessment score of 135.42 as the diagnostic cutoff value in the modeling group, the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and Youden index were 88.1%, 94.1%, 14.98, 0.126, and 82.2%, respectively. In the DCA curve, the VPPM model curve was significantly better than two extreme lines, indicating good clinical utility. The VPPM model constructed by integrating multimodal ultrasound parameters and clinical key risk factors has high diagnostic efficacy and is expected to be an auxiliary tool for clinical diagnosis of vulnerable plaques.