Novel methods for earlier detection of coronary artery calcium using CT

项目总结/摘要 冠心病（CHD）是最常见的心脏病形式，是全世界死亡的主要原因。 传统的风险预测工具，如Fragrance风险评分，使用临床生物标志物来识别个体 不良CHD事件风险较高，因此可从预防性降低LDL-C中获益的患者 疗法然而，这些工具发现很少有年轻人处于增加的风险中，尽管事实上， 较低LDL-C的累积暴露时间越长，对CHD事件的保护作用越强。冠状动脉 通过CT测量的钙（CAC）是CHD事件的最佳新预测因子， 在年轻人中。最近更新的指南建议在患有任何 可检测的CAC。冠状动脉钙化随着年龄的增长而进展，因此扫描所有年轻人将导致 阳性检出率极低。需要确定与年龄无关的风险因素，如遗传风险， 哪些年轻人将从早期钙筛查中获益最多。此外，当前CAC评分 方法是基于过时的技术，有一个关键需要了解扫描敏感性，以非 零CAC检测。CAC检测是斑块大小和钙密度两者的函数，并且 运动引入了额外的技术挑战。本工作的重点是开发新颖的图像扫描 和重建方法，用于使用CT进行早期CAC检测，并将创新的风险预测工具应用于 制定成功的CAC筛选策略。这项工作将确定每个人的适当年龄， 开始CAC筛查与CT使用年龄无关的风险因素的性别和遗传学。另夕h 将通过优化扫描采集评估和改善CT可检测到的CAC最小质量， 重建方法最后，新的图像分析技术，发现非零CAC的标准 将导出具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 用于CAC检测的采集、图像重建和风险预测工具，将改善CAC测量 作为冠心病的筛查策略。这些发展将允许在年轻个体中早期检测CAC 之前被误认为无病的人

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 Additionally, current CAC scoring methods are based on outdated technology, and there is a critical need to understand scan sensitivity to non- zero CAC detection.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.