Novel methods for earlier detection of coronary artery calcium using CT

项目摘要/摘要 冠心病(CHD)是最常见的心脏病形式，是全球主要的死亡原因。 传统的风险预测工具，如Framingham Risk Score，使用临床生物标志物来识别个体 谁是冠心病不良事件的高危人群，因此将从预防性降低低密度脂蛋白中受益 心理治疗。然而，这些工具识别出风险增加的年轻人很少，尽管事实是 长期接触较低的低密度脂蛋白胆固醇表明，对CHD事件的保护作用增强。冠状动脉 通过CT测量的钙(CAC)是预测冠心病事件的最佳新指标，也是预测冠心病事件的最新指标 在年轻的个体中。最近的指南更新建议对患有任何 可检测的CAC。冠状动脉钙化会随着年龄的增长而发展，所以扫描所有年轻的人将导致 检测的阳性率很低。年龄无关的风险因素，如遗传风险，需要确定 哪些年轻人将从早期钙筛查中受益最大。此外，当前的CAC评分 这些方法都基于过时的技术，因此迫切需要了解扫描对非 零CAC检测。CAC检测是斑块大小和钙密度的函数，并且 Motion带来了一个额外的技术挑战。这项工作的重点是开发新型的图像扫描 和重建方法，用于使用CT进行早期CAC检测，并应用创新的风险预测工具 制定成功的CAC筛查策略。这项工作将确定每个人的适当年龄 使用与年龄无关的性别和遗传危险因素，通过CT开始CAC筛查。此外， 将通过优化扫描采集和优化来评估和改进CT对CAC的最小可检测质量 重建方法。最后，新的图像分析技术用于发现标准CAC中的非零CAC 将得到带有运动伪影的螺旋胸部CT扫描。拟议的项目将建立新的扫描 CAC检测的采集、图像重建和风险预测工具将改进CAC测量 作为冠心病的筛查策略。这些进展将使年轻人能够更早地检测到CAC 他们之前被错误地归类为无疾病。

Project Summary/Abstract Coronary heart disease (CHD) is the most common form of heart disease, the leading cause of death worldwide. Traditional risk prediction tools such as the Framingham Risk Score use clinical biomarkers to identify individuals who are of higher risk for an adverse CHD event and would therefore benefit from preventive LDL-C lowering therapy. However, these tools identify very few younger individuals who are at increased risk, despite the fact that longer cumulative exposure to lower LDL-C shows increased protection from CHD events. Coronary artery calcium (CAC) measured via CT is the best novel predictor of CHD events and is predictive of CHD events among young individuals. Recent guideline updates recommend LDL-C lowering therapy in individuals with any detectable CAC. Coronary calcification progresses with age, so scanning all younger individuals will result in a very low positive rate of detection. Age independent risk factors, such as genetic risk, are needed to determine which younger individuals will benefit the most from early calcium screening. Additionally, current CAC scoring methods are based on outdated technology, and there is a critical need to understand scan sensitivity to non- zero CAC detection. CAC detection is a function of both plaque size and calcium density, and the influence of motion introduces an additional technical challenge. The focus of this work is to develop novel image scanning and reconstruction methods for earlier CAC detection using CT and to apply innovative risk prediction tools to develop a successful CAC screening strategy. This work will identify the appropriate age for each individual to begin CAC screening with CT using the age independent risk factors of sex and genetics. Additionally, the minimum detectable mass of CAC by CT will be assessed and improved by optimizing scan acquisition and reconstruction methods. Finally, new image analysis techniques for discovery of non-zero CAC in standard helical chest CT scans with motion artifact will be derived. The proposed project will establish novel scan acquisition, image reconstruction, and risk prediction tools for CAC detection that will improve CAC measurement as a screening strategy for CHD. These developments will permit earlier detection of CAC in young individuals who have previously been misclassified as disease free.