Department of Biomechanics, University of Nebraska at Omaha, Omaha, Nebraska.
Department of Surgery, University of Nebraska Medical Center, Omaha, Nebraska.
Am J Physiol Heart Circ Physiol. 2021 Jun 1;320(6):H2313-H2323. doi: 10.1152/ajpheart.00040.2021. Epub 2021 May 7.
Vascular calcification is associated with a higher incidence of cardiovascular events, but its prevalence in different vascular zones and the influence of demographics, risk factors, and morphometry remain insufficiently understood. Computerized tomography angiography scans from 211 subjects 5-93 yr old (mean age 47 ± 24 yr, 127 M/84 F) were used to build 3D vascular reconstructions and measure arterial diameters, tortuosity, and calcification volumes in six vascular zones spanning from the ascending thoracic aorta to the pelvic arteries. A machine learning random forest algorithm was used to determine the associations between calcification in each zone with demographics, risk factors, and vascular morphometry. Calcification appeared during the fourth decade of life and was present in all subjects after 65 yr. The abdominal aorta and the iliofemoral segment were the first to develop calcification, whereas the ascending thoracic aorta was the last. Demographics and risk factors explained 33-59% of the variation in calcification. Age, creatinine level, body mass index, coronary artery disease, and hypertension were the strongest contributors, whereas the effects of sex, race, tobacco use, diabetes, dyslipidemia, and alcohol and substance use disorders on calcification were small. Vascular morphometry did not directly and independently affect calcium burden. Vascular zones develop calcification asynchronously, with distal segments calcifying first. Understanding the influence of demographics and risk factors on calcium prevalence can help better understand the disease pathophysiology and may help with the early identification of patients that are at higher risk of cardiovascular events. We investigated the prevalence of vascular calcification in different zones of the aorta and pelvic arteries using computerized tomography angiography reconstructions and have applied machine learning to determine how calcification is affected by demographics, risk factors, and morphometry. The presented data can help identify patients at higher risk of developing vascular calcification that may lead to cardiovascular events.
血管钙化与心血管事件的发生率较高有关，但不同血管区域的患病率以及人口统计学、风险因素和形态学的影响仍了解不足。使用计算机断层血管造影扫描 211 名 5-93 岁（平均年龄 47 ± 24 岁，127 名男性/84 名女性）的受试者的扫描图像来构建 3D 血管重建，并测量六个血管区域（从升主动脉到骨盆动脉）的动脉直径、迂曲度和钙化体积。使用机器学习随机森林算法确定每个区域的钙化与人口统计学、风险因素和血管形态学之间的关联。钙化在 40 岁出头时出现，并且在 65 岁后所有受试者中都存在。腹部主动脉和髂股段是最早发生钙化的部位，而升主动脉是最后一个发生钙化的部位。人口统计学和风险因素解释了钙化变化的 33-59%。年龄、肌酐水平、体重指数、冠心病和高血压是最强的影响因素，而性别、种族、吸烟、糖尿病、血脂异常以及酒精和物质使用障碍对钙化的影响较小。血管形态学并没有直接和独立地影响钙负荷。血管区域的钙化是不同步发展的，远端节段先发生钙化。了解人口统计学和风险因素对钙患病率的影响有助于更好地了解疾病的病理生理学，并可能有助于早期识别发生心血管事件风险较高的患者。我们使用计算机断层血管造影重建来研究不同主动脉和骨盆动脉区域的血管钙化的患病率，并应用机器学习来确定钙化如何受人口统计学、风险因素和形态学的影响。所提供的数据有助于识别发生血管钙化风险较高的患者，这可能导致心血管事件。
