Sun Jiali, Sui Ying, Chen Yue, Lian Jianxiu, Wang Wei
Department of MRI Room, First Affiliated Hospital of Harbin Medical University, Harbin, China.
Department of Advisory Clinical Scientist C&TS North, Philips Healthcare, Beijing, China.
Front Neurol. 2023 Sep 28;14:1264791. doi: 10.3389/fneur.2023.1264791. eCollection 2023.
Patients with transient ischemic attacks (TIA) have a significant risk of developing acute ischemic strokes (AIS), emphasizing the critical need for hierarchical management. This study aims to develop a clinical-imaging model utilizing multimodal magnetic resonance imaging (mMRI) and the revised Framingham Stroke Risk Profile (FSRP) to predict AIS and achieve early secondary prevention.
mMRI scans were conducted on patients with symptomatic intracranial atherosclerotic disease (ICAD) to assess vascular wall features and cerebral perfusion parameters. Based on diffusion-weighted imaging (DWI), patients were divided into two groups: TIA and AIS. Clinical data were evaluated to calculate the FSRP score. Differences in clinical and imaging characteristics between the groups were analyzed, and a predictive model for AIS probability in patients with ICAD was established.
A total of 112 TIA and AIS patients were included in the study. The results showed that the AIS group had higher proportions of FSRP-high risk, hyperhomocysteinemia, and higher value of low-density lipoprotein (LDL), standardized plaque index (SQI), and enhancement rate (ER) compared to the TIA group ( < 0.05). Mean transit time (MTT) and time to peak (TTP) in the lesion area were significantly longer in the AIS group ( < 0.05). Multivariate analysis identified FSRP-high risk ( = 0.027) and high ER ( = 0.046) as independent risk factors for AIS. The combined clinical and mMRI model produced an area under the curve (AUC) of 0.791 in receiver operating characteristic (ROC) analysis. The constructed nomogram model combining clinical and mMRI features demonstrated favorable clinical net benefits.
FSRP-high risk and high ER were confirmed as independent risk factors for AIS. The combined prediction model utilizing clinical and imaging markers effectively predicts stroke risk in symptomatic ICAD patients.
短暂性脑缺血发作（TIA）患者发生急性缺血性卒中（AIS）的风险显著，这凸显了分层管理的迫切需求。本研究旨在开发一种利用多模态磁共振成像（mMRI）和修订的弗雷明汉卒中风险评估量表（FSRP）的临床影像模型，以预测AIS并实现早期二级预防。
对有症状的颅内动脉粥样硬化疾病（ICAD）患者进行mMRI扫描，以评估血管壁特征和脑灌注参数。根据弥散加权成像（DWI），将患者分为两组：TIA组和AIS组。评估临床数据以计算FSRP评分。分析两组之间临床和影像特征的差异，并建立ICAD患者AIS发生概率的预测模型。
本研究共纳入112例TIA和AIS患者。结果显示，与TIA组相比，AIS组中FSRP高风险、高同型半胱氨酸血症的比例更高，低密度脂蛋白（LDL）、标准化斑块指数（SQI）和强化率（ER）的值更高（<0.05）。AIS组病变区域的平均通过时间（MTT）和达峰时间（TTP）显著更长（<0.05）。多变量分析确定FSRP高风险（=0.027）和高ER（=0.046）为AIS的独立危险因素。在受试者工作特征（ROC）分析中，临床和mMRI联合模型的曲线下面积（AUC）为0.791。构建的结合临床和mMRI特征的列线图模型显示出良好的临床净效益。
FSRP高风险和高ER被确认为AIS的独立危险因素。利用临床和影像标志物的联合预测模型可有效预测有症状ICAD患者的卒中风险。
