High-Performance Automated System For Analysis of Cardiac SPECT

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。它是美国男性和女性死亡的唯一最大原因，占所有死亡人数的20%。虽然CAD有有效的医学和侵入性治疗，但其适当使用取决于对疾病的准确检测和对个体患者心脏风险的评估。门控心肌灌注SPECT（MRS）在这一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，美国有超过800万例患者接受了MRS。目前，MRS解释的标准方法是在应激和静息时局部心肌灌注摄取的主观视觉评分。这种视觉方法是耗时的，遭受观察者之间的变化，并且在异常的检测和其幅度的估计中可能是次优的。我们的目标是开发一个全自动的MRS计算机系统，在诊断CAD和预测心脏事件方面将超过有经验的人类读者的表现。这一高水平的性能将通过应用新的图像处理技术、提高图像质量和对所有现有图像数据进行自动区域整合来实现。具体而言，我们的目标是：1）开发用于灌注量化的增强技术，2）开发用于量化衰减校正的MRS的新技术，以及3）通过与大型多中心研究中多位专家的视觉评估进行比较，诊断性验证最终集成系统的性能，并通过回顾性分析来验证最终集成系统的性能。大型结果数据库。新系统将有能力区分真正的异常和成像伪影，并将检测到细微的缺陷。我们假设，新系统将能够检测CAD和预测结果，如心源性死亡比最好的可达到的视觉分析。这种发展将产生深远和直接的影响，因为MRS的这种新的准确性和自动化水平可以在国内和国际上广泛复制。这项工作将提高MRS检测的效率，并由于更准确的CAD诊断和更好地选择适当的治疗而节省大量成本。静息和应激状态下的心肌灌注（心肌血流）成像使医生能够检测疾病并预测美国每年数百万患者的风险，但目前它受到视觉解释需求的限制，这取决于医生的经验。研究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，该系统在解释这些图像方面甚至优于经验丰富的医生，从而通过更好地选择需要治疗的患者来挽救更多的生命，并节省时间和成本。

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.