Dynamic Cardiac SPECT Imaging

描述(申请人提供)：心脏病是当今美国导致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无创方法，用于冠心病(CAD)的检测和危险分层。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脑梗塞、缺血和血流动力学边缘病变的测量。这一应用的时机恰到好处，因为最近推出了新的心脏应激剂，使冠状动脉的充血反应更快，以及新的专用心脏SPECT系统能够快速获取动态数据。然而，还没有伴随着将动态获取的数据减少到诊断性临床参数的算法的开发。这项提议将通过应用算法来处理使用现有SPECT系统以及新的专用心脏SPECT系统在临床研究中获得的动态数据，来研究动态SPECT的临床作用。所开发的协议和算法可以在不增加成本的情况下在临床上实施。在医疗成本居高不下且不断上升的情况下，这是该方法的进一步优势。这项拟议的工作应用数学工具来准确和精确地量化动力学参数；使用计算机模拟、模体实验和临床研究来验证这些方法；并将完善动态心脏SPECT的临床作用。提出的创新方法包括：使用心脏跳动的多分辨率时空力学模型来估计描述示踪剂浓度和心脏变形随时间变化的模型参数(5D动态建模)；以及开发可变形的体模以生成更真实的心脏、肺和专利运动的数据，以验证运动校正算法。一个独特的方面是我们能够使用低相机转速直接根据投影估计动力学模型参数，包括血液输入函数，而不需要动脉采血。SPECT和CT之间的错位将得到纠正。动力学信息将被用于根据示踪剂在器官中的动力学来估计来自不同器官的散射成分。将这些新算法与新的快速专用心脏SPECT相机相结合，将能够在与目前定量PET相同的时间内对CFR进行定量。此外，我们的方法将使动态SPECT在现有扫描仪无法执行快速采集的成像临床中有用。所开发的方法不仅适用于使用各种灌注剂和代谢剂进行心肌成像，这可能会影响我们对各种心血管适应症的病理生理学的理解，而且还将应用于肿瘤和其他器官系统的成像，如肾脏和脑。

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.