High-Performance Automated System For Analysis of Cardiac SPECT

用于心脏 SPECT 分析的高性能自动化系统

• 批准号: 8089330
• 负责人: Piotr J Slomka
• 金额: $ 35.78万
• 依托单位: CEDARS-SINAI MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-18 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8089330
• 关键词: Accounting; Algorithms; Automation; Baptist Church; Blood flow; Cardiac; Cardiac Death; Cardiology; Cardiovascular system; Cause of Death; Cessation of life; Clinical; Collaborations; Collection; Computer Systems; Computer software; Consensus; Coronary Arteriosclerosis; Cost Savings; Data; Data Set; Databases; Defect; Detection; Development; Diagnosis; Diagnostic; Diagnostic tests; Disease; Evaluation; Event; Generations; Goals; Grant; Heart; Hospitals; Human; Hybrids; Image; Image Analysis; Individual; Institutes; Institution; Interobserver Variability; Japan; Left; Medical; Medical center; Methods; Modeling; Morphologic artifacts; Motion; Myocardial; Myocardial perfusion; Myocardium; Normalcy; Nuclear; Oregon; Outcome; Patient Selection; Patients; Performance; Perfusion; Physicians; Play; Positioning Attribute; Process; Protocols documentation; Public Health; Qualifying; Reader; Reading; Reproducibility; Research Personnel; Resources; Rest; Risk; Role; Specific qualifier value; Specificity; Stress; System; Techniques; Testing; Time; Universities; Validation; Ventricular; Ventricular Function; Visual; Woman; Work; attenuation; cost; experience; image processing; improved; men; next generation; novel; prognostic; single photon emission computed tomography; tool; tool development; uptake

DESCRIPTION (provided by applicant): Coronary artery disease (CAD) continues to be a major public health problem. It is the single greatest cause of death for men and women in the US, accounting for 20% of all deaths. While there are effective medical and invasive therapies for CAD, their appropriate use is dependent on accurate detection of the disease and evaluation of cardiac risk in individual patients. Gated myocardial perfusion SPECT (MRS) has played a critical role in this process, providing key information about myocardial perfusion and ventricular function. Over 8 million patients underwent MRS in the US in 2005. Currently, the standard method for MRS interpretation is subjective visual scoring of regional myocardial uptake of perfusion at stress and rest. This visual approach is time-consuming, suffers from inter-observer variability, and is potentially sub-optimal in the detection of abnormalities and estimation of their magnitude. We aim to develop a fully automated computer system for MRS that will surpass the performance of experienced human readers in diagnosing CAD and in predicting cardiac events. This high level of performance will be accomplished by the application of new image processing techniques, improvement of image quality, and automatic regional integration of all available image data. Specifically, we aim to: 1) develop enhanced techniques for perfusion quantification, 2) develop new techniques for quantification of attenuation corrected MRS, and 3) validate performance of the final integrated system diagnostically by comparison to the visual evaluation by multiple experts in a large multi-center study and prognostically by retrospective analysis of a large outcome database. The new system will have the ability to distinguish true abnormalities from imaging artifacts and will detect subtle defects. We hypothesize that the new system will be able to detect CAD and predict outcomes such as cardiac death better than the best attainable visual analysis. Such development will have far-reaching and immediate consequences since this new level of accuracy and automation for MRS can be widely reproduced nationally and internationally. This work will result in increased efficiency of MRS testing and large cost savings due to more accurate diagnosis of CAD and better selection of appropriate treatment. Imaging of myocardial perfusion (heart muscle blood flow) at rest and stress allows physicians to detect disease and predict risk in millions of patients in the US each year, but it is currently limited by the need of visual interpretation, which is dependent on doctor's experience. The investigators propose to develop and validate an automated, highly-accurate and objective computer system which will outperform even experienced physicians in interpreting these images and consequently allow a greater number of lives saved by better selection of patients needing treatment and also resulting in time- and cost-savings.

描述（由申请人提供）：冠状动脉疾病（CAD）仍然是一个主要的公共卫生问题。这是美国男性和女性的最大死亡原因，占所有死亡的20％。尽管有有效的医疗和侵入性CAD疗法，但它们的适当使用取决于对疾病的准确检测和对个别患者心脏风险的评估。门控心肌灌注SPECT（MRS）在此过程中发挥了关键作用，提供了有关心肌灌注和心室功能的关键信息。 2005年，超过800万患者在美国接受了MRS。目前，MRS解释的标准方法是在压力和休息下进行灌注的区域心肌摄取的主观视觉评分。这种视觉方法是耗时的，患有观察者间的变异性，并且在异常检测和幅度的估计中可能是最佳的。我们旨在为MRS开发全自动的计算机系统，该系统将超过经验丰富的人类读者在诊断CAD和预测心脏事件方面的表现。这种高度的性能将通过应用新的图像处理技术，改进图像质量以及所有可用图像数据的区域集成来实现。具体而言，我们的目的是：1）开发用于灌注定量的增强技术，2）开发用于量化衰减校正的MRS的新技术，以及3）通过比较大型多中心研究中的多个专家的视觉评估，通过对大型成果数据的回顾性分析进行大型专家的视觉评估来验证最终集成系统的性能。新系统将具有区分真实异常与成像伪像的能力，并将检测到细微的缺陷。我们假设新系统将能够检测CAD并预测诸如心脏死亡之类的结果，而不是最佳可达到的视觉分析。这种发展将带来深远的影响和直接的后果，因为这种新的准确性和自动化的MRS可以在国内和国际上广泛繁殖。这项工作将导致MRS测试效率提高，并且由于更准确地诊断了CAD和更好地选择适当的治疗，因此可以提高效率。静止和压力下心肌灌注（心肌血流）的成像使医生每年都能检测到美国数百万患者的疾病并预测疾病的风险，但目前受到视觉解释的需要，这取决于医生的经验。调查人员建议开发和验证一种自动化，高度准确和客观的计算机系统，该系统甚至在解释这些图像方面甚至会超越经验丰富的医生，因此允许通过更好地选择需要治疗的患者挽救的生命，并导致时间和成本节省。