PFI (MCA): A Cardiac Imaging System

这一创新伙伴关系-职业发展中期(PFI-MCA)项目的更广泛的影响/商业潜力是一个新的系统，用于改善心脏(冠状动脉)血管的成像，用于检测和监测冠状动脉疾病(CAD)。冠心病是最常见的心血管疾病，是美国男性和女性的主要死亡原因，占全球死亡人数的30%。冠心病的进展是通过阻塞心脏血管--冠状动脉中的血液流动来进行的。尽管基于导管的冠状动脉造影术被认为是评估冠状动脉的金标准，但它是有创的，需要插入导管进行动脉内对比剂注射，以X射线显示血流受阻。基于导管的冠状动脉造影术也是一种昂贵的检查(每个程序57500美元)，而且过度使用，40%的检查显示正常的动脉。作为一种替代方法，CT冠状动脉成像是一种低成本和非侵入性的成像方法。然而，在美国广泛使用的计算机断层扫描系统必须得到有效的控制，以获得低辐射剂量的诊断性扫描，即在心脏运动最小时对其成像。这一新系统将确保所有患者的安全、诊断质量的扫描，提供广泛的冠状动脉成像途径，并消除侵入性、不必要的、昂贵的程序。拟议的项目通过积极发展实时传感器和硬件的技术，追求心血管成像领域的尖端研究。该项目将能够实时预测最小热运动(心脏静止)，从而通过实施人工神经网络和实时硬件原型，从而能够对冠状动脉进行诊断性质量的计算机断层成像。该系统将根据外部心音和运动对个体患者的心跳进行前瞻性预测，准备好供计算机断层扫描制造商采用。这将比现有的基于心电图仪的策略有很大的进步。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Partnerships for Innovation – Mid Career Advancement (PFI-MCA) project is a new system to improve imaging of heart (coronary) vessels for the detection and monitoring of coronary artery disease (CAD). CAD, the most common type of cardiovascular disease, is the leading cause of death in the U.S. for both men and women and responsible for 30% of deaths globally. CAD progresses by obstructing blood flow in heart vessels—coronary arteries. While catheter-based coronary angiography is considered the gold standard for assessing coronary arteries it is invasive, requiring insertion of a catheter for intra-arterial contrast agent injection for X-ray visualization of obstruction to blood flow. Catheter-based coronary angiography is also a costly ($57,500 per procedure), and over-utilized exam, with 40% of exams revealing normal arteries. As an alternative, computed tomography coronary angiography is a low cost and non-invasive imaging approach. However, computed tomography systems that are widely available in the U.S. must be effectively controlled to acquire diagnostic-quality scans with low radiation dose, i.e., image the heart when its motion is minimal. This new system will ensure safe, diagnostic-quality scans in all patients, providing widespread access to coronary imaging and eliminate invasive, unnecessary, costly procedures.The proposed project pursues cutting-edge research in cardiovascular imaging via aggressive technology development of real-time sensors and hardware. The project will enable real-time prediction of minimal heat motion (cardiac quiescence) thereby enabling diagnostic-quality computed tomography imaging of coronary vessels arteries by implementing an artificial neural network and a real-time hardware prototype. The system will prospectively predict quiescence based on external heart sounds and motion for individual patients on a beat-by-beat basis ready for adoption by computed tomography manufacturers. This will yield a significant advancement over existing strategies based on the electrocardiogram.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.