PFI (MCA): A Cardiac Imaging System

该创新伙伴关系-中期职业发展（PFI-MCA）项目的更广泛影响/商业潜力是一种改进心脏（冠状动脉）血管成像以检测和监测冠状动脉疾病（CAD）的新系统。CAD是最常见的心血管疾病类型，是美国男性和女性的主要死亡原因，占全球死亡人数的30%。CAD通过阻塞心脏血管-冠状动脉中的血流而进展。虽然基于导管的冠状动脉造影术被认为是评估冠状动脉的黄金标准，但它是侵入性的，需要插入导管进行动脉内造影剂注射，以便对血流阻塞进行X射线可视化。基于导管的冠状动脉造影术也是一种昂贵的（每次手术57，500美元），并且过度使用的检查，40%的检查显示正常动脉。作为替代，计算机断层扫描冠状动脉造影术是一种低成本和非侵入性成像方法。然而，在美国广泛使用的计算机断层摄影系统必须被有效地控制以获取具有低辐射剂量的诊断质量扫描，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都能进行安全、诊断质量的扫描，提供广泛的冠状动脉成像服务，并消除侵入性、不必要和昂贵的程序。拟议项目通过积极开发实时传感器和硬件技术，追求心血管成像领域的前沿研究。该项目将通过实施人工神经网络和实时硬件原型，实现对最小热运动（心脏静止）的实时预测，从而实现冠状动脉血管的诊断质量计算机断层扫描成像。该系统将基于外部心音和逐搏基础上的个体患者的运动来前瞻性地预测静止，以供计算机断层扫描制造商采用。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值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.