Department of Ultrasound, The First Affiliated Hospital of Fujian Medical University, 20# Chazhong Road, Fuzhou, 350005, Fujian, China.
Department of Ultrasound, Binhai Campus of the First Affiliated Hospital, National Regional Medical Center, Fujian Medical University, Fuzhou, China.
Sci Rep. 2024 Oct 16;14(1):24255. 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.
易损斑块的破裂是导致心脑血管疾病的重要致病因素。本研究旨在通过结合多模态血管超声参数和临床危险因素构建易损斑块预测模型（VPPM），并对其进行验证。
收集了 2017 年 1 月至 2023 年 12 月期间因颈动脉内膜切除术（CEA）而住院的 196 例动脉粥样硬化患者，将其分为建模组（n=137）和验证组（n=59）。分析包括高血压、糖尿病、吸烟史和体重指数（BMI）等临床信息。所有患者入院后均行颈动脉超声和超声造影（CEUS）检查，主要超声参数包括斑块厚度、回声类型、狭窄程度和 CEUS 新生血管分级。通过二元 Logistic 回归分析筛选出 CEA 患者易损斑块的独立危险因素，并建立预测模型及列线图。采用校准曲线、受试者工作特征曲线（ROC）和决策曲线分析（DCA）评估 VPPM 模型的校准、诊断效能和临床实用性。建模组和验证组之间的多模态血管超声参数和临床危险因素无统计学差异（P>0.05）。二元 Logistic 回归分析确定斑块厚度、回声类型、CEUS 新生血管分级、BMI 和吸烟史为进入预测模型的 5 个变量。VPPM 模型显示出良好的诊断效能，ROC 曲线下面积为 0.959（95%CI 0.915-0.999）。在建模组中，使用 VPPM 风险评估评分 135.42 的列线图作为诊断截断值，灵敏度、特异度、阳性似然比、阴性似然比和约登指数分别为 88.1%、94.1%、14.98、0.126 和 82.2%。在 DCA 曲线中，VPPM 模型曲线明显优于两条极端线，表明具有良好的临床实用性。该模型通过整合多模态超声参数和临床关键危险因素，具有较高的诊断效能，有望成为易损斑块临床诊断的辅助工具。
