A non-invasive, automated platform for hemodynamic assessment of patients at risk of heart failure or pulmonary hypertension

用于对有心力衰竭或肺动脉高压风险的患者进行血流动力学评估的无创自动化平台

• 批准号: 10699067
• 负责人: Anthony Arnold
• 金额: $ 60.55万
• 依托单位: SENSYDIA CORPORATION
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-05 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10699067
• 关键词: Acoustics; Activities of Daily Living; Adult; Affect; Agreement; Algorithms; Breakthrough device; Cardiac; Cardiac Catheterization Procedures; Cardiac Output; Cardiology; Cardiovascular system; Caring; Catheterization; Cause of Death; Cessation of life; Chest; Clinic; Clinical; Clinical Research; Collaborations; Computer software; Data; Data Set; Development; Devices; Diagnosis; Disease; EFRAC; Early Diagnosis; Early Intervention; Early treatment; Echocardiography; Effectiveness; Electrocardiogram; Family; Feedback; Freezing; Frequencies; Goals; Gold; Grant; Guidelines; Health Personnel; Healthcare; Healthcare Systems; Heart Abnormalities; Heart failure; Intervention; Left Ventricular Function; Machine Learning; Measurement; Measures; Medical; Medical center; Monitor; Morbidity - disease rate; Operative Surgical Procedures; Participant; Patient Care; Patient Recruitments; Patients; Performance; Perioperative Care; Persons; Phase; Physicians; Procedures; Process; Prospective Studies; Pulmonary Capillary Wedge Pressure; Pulmonary Hypertension; Reporting; Resources; Risk; Risk Factors; Safety; Signal Transduction; Skin; Small Business Technology Transfer Research; Symptoms; System; Techniques; Technology; Testing; Time; Training; Ultrasonography; United States Food and Drug Administration; Universities; Validation; Wedge Pressures; algorithm development; burden of illness; clinical decision support; clinical diagnosis; clinically relevant; commercialization; cost; electronic sensor; experience; heart function; hemodynamics; improved; intracardiac pressure; lung pressure; mortality; patient screening; programs; prospective; prototype; pulmonary arterial pressure; recruit; sensor; skills; software development; standard of care; tool; usability

PROJECT SUMMARY Heart failure (HF) and abnormal heart function directly affects 6 million people in the U.S. and is a leading cause of death. Early intervention is key to reducing mortality and morbidity, yet early diagnosis, particularly for those with asymptomatic disease, is challenging. Effective diagnosis and management of HF and accompanying pulmonary hypertension (PH) requires accurate measurement of four hemodynamic parameters, including ejection fraction (EF), cardiac output (CO), pulmonary artery pressure (PAP), and pulmonary capillary wedge pressure (PCWP). Currently obtained by a combination of echocardiography and cardiac catheterization these assessments can only be performed by skilled medical personnel with specialized training. In addition, cardiac catheterization is highly invasive, requires significant expensive resources, and is associated with risks to the patient. There is an unmet need for an accurate, non-invasive, low cost hemodynamic measurement tool that can be operated without specialized training with accuracy equivalent to cardiac catheterization and sonography. Such a device would enable earlier, safer, and more affordable diagnosis, improved surveillance capabilities, more frequent monitoring of at-risk patients, and better clinical decision support for clinicians in guiding therapies. Non-invasive alternatives to catheterization are not currently available, and there are no technologies that currently exist for simultaneous measurement of EF, CO, PAP and PCWP. Sensydia Corporation is developing a low cost, non-invasive “Cardiac Performance System” (CPS) for hemodynamic measurement with the goal of achieving comparable accuracy to that of gold-standard techniques. CPS acquires and automatically analyzes acoustic and electrocardiogram signals from a set of easily applied sensors to accurately measure EF, CO, PAP, and PCWP. Sensydia has developed fully functioning hardware and prototype software for CPS that uses proprietary algorithms to analyze the acquired signals. Sensydia has been granted 510(k) clearance for measurement of EF; however, further algorithm development and testing are required to achieve a system that can also measure CO, PAP, and PCWP with similar accuracies. In Phase I of this Fast- Track STTR project, PAP and PCWP algorithms will be further refined and tested to meet desired thresholds of accuracy for clinical use using an existing training dataset of CPS and catheterization data obtained by the Sensydia/University of Pittsburgh Medical Center (UPMC) team and will be assessed based on Bland-Altman bias and limits of agreement. In collaboration with a team of experienced cardiologists and anesthesiologists at UPMC, the CO, PAP and PCWP algorithms will then be prospectively validated in a new, independent dataset from patients undergoing cardiac catheterization. Phase II will focus on demonstrating clinical utility and feasibility of routine use in a preoperative clinic setting. Finally, an integrated software application for reporting CPS data and diagnosis based on AHA/ACC guidelines will be developed and assessed in a useability study with UPMC physicians.

项目摘要 心力衰竭 (HF) 和心脏功能异常直接影响美国 600 万人，是导致死亡的主要原因。早期干预是降低死亡率和发病率的关键，但早期诊断（特别是对于无症状疾病的患者）具有挑战性。心力衰竭和伴随的肺动脉高压 (PH) 的有效诊断和治疗需要准确测量四个血流动力学参数，包括射血分数 (EF)、心输出量 (CO)、肺动脉压 (PAP) 和肺毛细血管楔目前，这些评估只能由经过专门培训的熟练医务人员通过超声心动图和心导管检查相结合来进行。此外，心导管检查具有高度侵入性，需要大量昂贵的资源，并且与患者的风险相关。患者对准确、非侵入性、低成本的血流动力学测量工具的需求尚未得到满足，该工具无需专门培训即可进行操作，并且具有与心导管插入术和超声检查相当的精确性，这样的设备将能够实现更早、更安全、更经济的诊断。改进监控能力，更频繁的监控目前尚无导管插入术的非侵入性替代方案，并且目前尚无可同时测量 EF、CO、PAP 和 PCWP 的技术。正在开发一种低成本、非侵入性的“心脏性能系统”(CPS)，用于血流动力学测量，其目标是达到与黄金标准技术相当的精度，CPS 从一组易于应用的信号中获取并自动拼接声学和心电图信号。传感器准确地测量 EF、CO、PAP 和 PCWP 已为 CPS 开发了功能齐全的硬件和原型软件，该软件使用专有算法来分析获取的信号，Sensydia 已获得 EF 测量的 510(k) 许可；需要进行测试以实现能够以类似精度测量 CO、PAP 和 PCWP 的系统。 在该 Fast-Track STTR 项目的第一阶段，将进一步完善和测试 PAP 和 PCWP 算法，以满足所需的阈值。使用 Sensydia/匹兹堡大学医学中心 (UPMC) 团队获得的现有 CPS 训练数据集和导管插入数据的临床使用准确性，并将根据 Bland-Altman 偏差和协议限制与经验丰富的团队合作进行评估。 UPMC 的心脏病专家和麻醉师将在接受心导管插入术的患者的新的独立数据集中对 CO、PAP 和 PCWP 算法进行前瞻性验证，第二阶段将重点展示术前常规使用的临床实用性和可行性。最后，将与 UPMC 医生一起在可用性研究中开发和评估基于 AHA/ACC 指南的 CPS 数据和诊断集成软件应用程序。