Dynamic Cardiac SPECT Imaging

描述（由申请人提供）：心脏病是当今美国死亡和残疾的主要原因。单光子发射计算机断层扫描（SPECT）心肌灌注成像（MPI）是目前应用最广泛的冠状动脉疾病（CAD）检测和危险分层的无创方法。假设：与传统MPI SPECT静态图像的视觉解释相比，动态心脏SPECT的冠状动脉血流储备（CFR）参数图像将提供更敏感的梗死、缺血和血流动力学意义边缘病变的测量。该应用的时机与最近引入的新的心脏应激剂，允许更快的冠状动脉充血反应，以及新的专用心脏SPECT系统，能够快速获取动态数据。然而，还没有相应的算法的发展，减少动态获取的数据诊断临床参数。本提案将研究动态SPECT的临床作用，通过使用现有SPECT系统和新的专用心脏SPECT系统，应用算法处理临床研究中获得的动态数据。开发的协议和算法可以在诊所实施，而不需要额外的费用。这是该方法在医疗保健成本高且不断上升的时代的另一个优势。提出的工作应用数学工具来准确和精确地量化动力学参数；通过计算机模拟、模拟实验和临床研究验证这些方法；完善心脏动态SPECT的临床应用。提出的创新方法包括：使用跳动心脏的多分辨率时空力学模型来估计模型参数，这些模型参数描述了示踪剂浓度和心脏变形随时间的变化（5D动态建模）；并开发一个可变形的幻影，以产生更真实的心脏，肺和专利运动数据，以验证运动校正算法。一个独特的方面是我们能够估计动力学模型参数，包括血液输入函数，直接从投影使用缓慢的相机旋转速度，而不需要动脉血液采样。将纠正SPECT与CT之间的不对准。基于示踪剂在器官中的动力学，动力学信息将用于估计来自不同器官的散射成分。这些新算法与新的快速专用心脏SPECT相机的结合将使定量CFR的时间等于目前的定量PET。此外，我们的方法将使动态SPECT在现有扫描仪无法进行快速采集的成像诊所有用。所开发的方法不仅适用于多种灌注和代谢药物的心肌成像，这可能会影响我们对各种心血管适应症的病理生理的理解，而且也将应用于肿瘤和其他器官系统的成像，如肾和脑。

DESCRIPTION (provided by applicant): Heart disease is the leading cause of death and disability in the United States today. Single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is now the most widely applied noninvasive method for the detection and risk stratification of coronary artery disease (CAD). Hypothesis: Parametric images of coronary flow reserve (CFR) from dynamic cardiac SPECT will provide more sensitive measures of infarct, ischemia, and lesions on the margin of hemodynamic significance than visual interpretations of static images of conventional MPI SPECT. This application is well timed with the recent introduction of new cardiac stressing agents that allow faster hyperemic response of coronary arteries, and new dedicated cardiac SPECT systems enabling rapid acquisition of dynamic data. However, there has not been accompanying development of algorithms that reduce dynamically acquired data to diagnostic clinical parameters. This proposal will investigate clinical roles of dynamic SPECT by applying algorithms for processing dynamic data acquired in clinical studies using existing SPECT systems as well as a new dedicated cardiac SPECT systems. The developed protocols and algorithms can be implemented in the clinic without additional costs. This is a further advantage of the method in this time of high and rising healthcare costs. The proposed work applies mathematical tools to accurately and precisely quantify kinetic parameters; validates these methods using computer simulations, phantom experiments, and clinical studies; and will perfect clinical roles for dynamic cardiac SPECT. Innovative methods proposed include: use of multi-resolution spatiotemporal mechanical models of the beating heart to estimate model parameters that delineate changes in tracer concentration and cardiac deformation as a function of time (5D dynamic modeling); and development of a deformable phantom to generate more realistic data of cardiac, lung, and patent motion for validation of motion correction algorithms. An unique aspect is our ability to estimate kinetic model parameters, including the blood input function, directly from projections using slow camera rotation speeds without the need for arterial blood sampling. Misalignment between SPECT and CT will be corrected. Kinetic information will be used to estimate scatter components from different organs based on the kinetics of the tracer in the organ. The incorporation of these new algorithms with the new fast dedicated cardiac SPECT cameras will enable quantitation of CFR in a time equal to that of present quantitative PET. Furthermore, our methods will make dynamic SPECT useful in imaging clinics with existing scanners that cannot perform rapid acquisitions. The methods developed will not only be applicable for imaging the myocardium with a variety of perfusion and metabolic agents, which could impact our understanding of the pathophysiology of a variety of cardiovascular indications, but will also have application for imaging tumors and other organ systems such as the kidney and brain.