METHOD FOR PET QUANTIFICATION OF MYOCARDIAL PERFUSION

心肌灌注 PET 定量方法

• 批准号: 2637999
• 负责人: PING-CHUN CHIAO
• 金额: $ 11.87万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-01-01 至 1998-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2637999
• 关键词: body movement; diagnosis quality /standard; dogs; heart circulation; heart disorder diagnosis; heart motion; method development; noninvasive diagnosis; nuclear medicine; positron emission tomography; radiotracer

On-going research activities have focused on advancing PET from a qualitative to a quantitative imaging modality for the non-invasive characterization of coronary artery disease (CAD). Since CAD causes 1.5 million myocardial infarctions and 520,000 deaths per year (one-third to one-half deaths between the ages of 35 and 64) in the United States, it is critically important to define its severity for cardiologists to decide objectively among dietary control and therapeutic interventions (such as thrombolytic therapy, balloon angioplasty, and bypass surgery) and for assessment of effects of these treatments. Over the years, PET has been proven as a highly sensitive and specific diagnostic tool for the detection of CAD. At the present time, PET represents the most promising non-invasive means to quantify regional blood flow and coronary reserve, which has been shown to provide a sensitive marker for the functional significance of coronary artery stenosis. Intensive research has been devoted to developing or validating kinetic models for PET perfusion agents such as N-13 ammonia, O-15 water, and rubidium-82. However, accurate quantification of myocardial perfusion using PET is difficult to achieve because of difficulties in analyzing degraded image data (due to finite spatial resolution, counting noise, accidental coincidence, instrument deadtime, and patient motion) and limitations on myocardial boundary delineation. To overcome such difficulties and limitations, we propose an integrated approach in which a 3D measurement model characterizes the imagine degradation factors, relates perfusion, myocardial boundary parameters, blood pool concentration (input function) and spatial positions of the heart (for patient motion correction) to the projection data, and allows joint estimation of these parameters directly from the projection data based on maximum likelihood criteria. The long term goal of this research is to develop and validate more accurate methods for simultaneously estimating myocardial perfusion and boundaries from gated dynamic PET data. The aim of this proposal is to prove a hypothesis that the model-based method will provide more accurate perfusion estimates even in unaged situations. To prove our hypothesis, we will develop a 3D measurement model and will construct a 3D digital dog-thorax phantom to refine the model and to develop methods for body movement correction. We will then conduct dog heart perfusion studies using N-13 ammonia, analyze data based on the refined model and simulation experience, and evaluate the performance of perfusion estimation against conventional methods and a gold standard. We will perform preliminary trials on N-13 ammonia patient data.

正在进行的研究活动集中在推进PET从一个 定性到定量成像模式， 冠状动脉疾病（CAD）的特征。 由于CAD导致1.5 每年有100万人心肌梗死和520，000人死亡（三分之一至 在美国，35岁至64岁之间的死亡人数占一半， 对于心脏病专家来说，确定其严重程度至关重要， 在饮食控制和治疗干预之间做出客观的决定 (such如溶栓治疗、球囊血管成形术和旁路手术） 并评估这些治疗的效果。 多年来，PET 已被证明是一种高度敏感和特异性的诊断工具， CAD的检测。 目前，PET代表了 有前途的非侵入性手段，以量化局部血流和冠状动脉 储备，这已被证明是一个敏感的标志， 冠状动脉狭窄的功能意义。 密集调研 一直致力于开发或验证PET的动力学模型 灌注剂如N-13氨、O-15水和铷-82。 然而，使用PET对心肌灌注进行精确定量是不可能的。 难以实现，因为难以分析退化图像 数据（由于有限的空间分辨率、计数噪声、偶然的 重合、仪器死区时间和患者运动）以及 心肌边界勾画 为了克服这些困难和局限性，我们提出了一个综合的 一种3D测量模型表征图像的方法 降解因子，涉及灌注，心肌边界参数， 血池浓度（输入函数）和空间位置 心脏（用于患者运动校正）到投影数据，并允许 直接从投影数据联合估计这些参数 基于最大似然准则。 长期目标是 研究的目的是开发和验证更准确的方法， 同时估计心肌灌注和边界从门控 动态PET数据。 这个提议的目的是证明一个假设， 基于模型的方法将提供更精确的灌注估计 即使是在未成年的情况下。 为了证明我们的假设，我们将开发一个3D测量模型， 构建3D数字化犬胸体模，以细化模型， 开发身体运动校正方法。 然后我们将进行狗 使用N-13氨的心脏灌注研究，基于 完善的模型和模拟经验，并评估性能， 与常规方法和金标准相比的灌注估计。 我们将对N-13氨患者数据进行初步试验。