PFI (MCA): A Cardiac Imaging System

PFI (MCA)：心脏成像系统

• 批准号: 2122299
• 负责人: Pamela Bhatti
• 金额: $ 37.69万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2122299&HistoricalAwards=false
• 关键词: PFI; MCA; Cardiac; Imaging; System

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.

创新伙伴关系-中期职业发展（PFI-MCA）项目的更广泛影响/商业潜力是一个新的系统，以改善心脏（冠状动脉）血管成像，用于检测和监测冠状动脉疾病（CAD）。CAD是最常见的心血管疾病类型，是美国男性和女性死亡的主要原因，占全球死亡人数的30%。冠心病是通过阻塞心脏血管——冠状动脉的血流而进展的。虽然基于导管的冠状动脉造影被认为是评估冠状动脉的金标准，但它是有创的，需要插入导管在动脉内注射造影剂以x线显示血流阻塞。基于导管的冠状动脉造影也是一项昂贵的检查（每次检查57,500美元），而且被过度使用，40%的检查显示的是正常动脉。作为一种替代方法，计算机断层冠状动脉造影是一种低成本、无创的成像方法。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控制，以获得低辐射剂量的诊断质量扫描，即在心脏运动最小时对其进行成像。这一新系统将确保所有患者都能获得安全、高诊断质量的扫描，为冠状动脉成像提供广泛的途径，并消除侵入性的、不必要的、昂贵的手术。拟议的项目通过积极的实时传感器和硬件技术开发，追求心血管成像的前沿研究。该项目将实现最小热运动（心脏静止）的实时预测，从而通过实现人工神经网络和实时硬件原型，实现冠状动脉诊断质量的计算机断层成像。该系统将基于外部心音和个体患者的运动来预测静息，并准备被计算机断层扫描制造商采用。这将比现有的基于心电图的策略产生重大的进步。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。