Jin Hui, Hou Jie, Qin Xue, Du Xingyue, Zheng Guangying, Meng Yu, Shu Zhenyu, Wei Yuguo, Gong Xiangyang
Department of Radiology, Center for Rehabilitation Medicine, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Bengbu Medical College, Bengbu, China.
Front Aging Neurosci. 2023 Nov 10;15:1256228. doi: 10.3389/fnagi.2023.1256228. eCollection 2023.
Coronary artery disease (CAD) usually coexists with subclinical cerebrovascular diseases given the systematic nature of atherosclerosis. In this study, our objective was to predict the progression of white matter hyperintensity (WMH) and find its risk factors in CAD patients using the coronary artery calcium (CAC) score. We also investigated the relationship between the CAC score and the WMH volume in different brain regions.
We evaluated 137 CAD patients with WMH who underwent coronary computed tomography angiography (CCTA) and two magnetic resonance imaging (MRI) scans from March 2018 to February 2023. Patients were categorized into progressive ( = 66) and nonprogressive groups ( = 71) by the change in WMH volume from the first to the second MRI. We collected demographic, clinical, and imaging data for analysis. Independent risk factors for WMH progression were identified using logistic regression. Three models predicting WMH progression were developed and assessed. Finally, patients were divided into groups based on their total CAC score (0 to <100, 100 to 400, and > 400) to compare their WMH changes in nine brain regions.
Alcohol abuse, maximum pericoronary fat attenuation index (pFAI), CT-fractional flow reserve (CT-FFR), and CAC risk grade independently predicted WMH progression ( < 0.05). The logistic regression model with all four variables performed best (training: AUC = 0.878, 95% CI: 0.790, 0.938; validation: AUC = 0.845, 95% CI: 0.734, 0.953). An increased CAC risk grade came with significantly higher WMH volume in the total brain, corpus callosum, and frontal, parietal and occipital lobes ( < 0.05).
This study demonstrated the application of the CCTA-derived CAC score to predict WMH progression in elderly people (≥60 years) with CAD.
鉴于动脉粥样硬化的系统性，冠状动脉疾病（CAD）通常与亚临床脑血管疾病共存。在本研究中，我们的目的是使用冠状动脉钙化（CAC）评分预测CAD患者白质高信号（WMH）的进展并找出其危险因素。我们还研究了CAC评分与不同脑区WMH体积之间的关系。
我们评估了137例患有WMH的CAD患者，这些患者在2018年3月至2023年2月期间接受了冠状动脉计算机断层扫描血管造影（CCTA）和两次磁共振成像（MRI）扫描。根据第一次和第二次MRI扫描时WMH体积的变化，将患者分为进展组（n = 66）和非进展组（n = 71）。我们收集了人口统计学、临床和影像学数据进行分析。使用逻辑回归确定WMH进展的独立危险因素。开发并评估了三种预测WMH进展的模型。最后，根据患者的总CAC评分（0至<100、100至400和>400）将患者分组，以比较他们在九个脑区的WMH变化。
酗酒、最大冠状动脉周围脂肪衰减指数（pFAI）、CT分数血流储备（CT-FFR）和CAC风险等级独立预测WMH进展（P<0.05）。包含所有四个变量的逻辑回归模型表现最佳（训练：AUC = 0.878，95%CI：0.790，0.938；验证：AUC = 0.845，95%CI：0.734，0.953）。总脑、胼胝体以及额叶、顶叶和枕叶的WMH体积随着CAC风险等级的增加而显著增加（P<0.05）。
本研究证明了基于CCTA得出的CAC评分在预测老年（≥60岁）CAD患者WMH进展方面的应用。
