Task-Based Optimization of Gated Myocardial SPECT

基于任务的门控心肌 SPECT 优化

• 批准号: 6778247
• 负责人: BENJAMIN M. W. TSUI
• 金额: $ 15.97万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-17 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6778247
• 关键词: bioengineering /biomedical engineering; bioimaging /biomedical imaging; computer program /software; computer system design /evaluation; diagnosis design /evaluation; heart imaging /visualization /scanning; heart motion; image enhancement; image processing; mathematical model; phantom model; single photon emission computed tomography; technology /technique development

This proposal develops task-based methods for evaluating and optimizing acquisition, reconstruction, and processing techniques for gated myocardial perfusion SPECT. Gated SPECT yields a series of volume images of the left ventricle, each representing one portion of the cardiac cycle. Several clinical tasks may be performed with the resulting images, including visual observation of motion properties (the detection task). For example, physicians will frequently view animations to assess whether the left ventricular wall appears to move normally. However, reconstruction methods designed for gated SPECT have never been evaluated on such a task, largely due to a lack of appropriate tools. The initial phase of the research involves the development of new tools, including a realistic mathematical phantom that can model a continuum of cardiac motions and an interactive software application for presenting motion images to observers in a controlled experiment. These tools will be used in a series of human observer studies meant to emulate the clinical task of detecting abnormal cardiac motion from animated displays of gated SPECT reconstructions. The initial observer studies will focus on optimizing acquisition parameters, such as the number of gated frames and the presentation frame rate, and on determining whether accurate modeling of physical effects, like attenuation or scatter, has an effect on the detection task. Further observer studies will be used to optimize smoothing parameters for 4D reconstruction and processing methods, and compare these methods to determine if one offers improved performance in the detection task. Lastly, the research proposes to develop a set of computer-based observers, so as to reduce the need for time-consuming human observer studies in the future. The computer-based observers, will incorporate the Channelized Hotelling Observer concept, extending it to the spatiotemporal domain, and will be bases on psychophysical properties of the human visual system. Computer-based observers will be trained and evaluated on the same image detection tasks as in the human observer studies to determine the computer-based observer most likely to emulate human task performance.

该提案开发了基于任务的方法，用于评估和优化门控心肌灌注SPECT的采集、重建和处理技术。 门控SPECT产生左心室的一系列体积图像，每个图像代表心动周期的一部分。 可以利用所得到的图像执行若干临床任务，包括运动特性的视觉观察（检测任务）。例如，医生将频繁地查看动画以评估左心室壁是否看起来正常移动。然而，重建方法设计的门控SPECT从来没有评价这样的任务，主要是由于缺乏适当的工具。 研究的初始阶段涉及新工具的开发，包括可以模拟连续心脏运动的逼真数学模型和在受控实验中向观察者呈现运动图像的交互式软件应用程序。 这些工具将用于一系列人类观察者研究，旨在模拟从门控SPECT重建的动画显示中检测异常心脏运动的临床任务。 最初的观察者研究将侧重于优化采集参数，如门控帧数和呈现帧率，并确定物理效应（如衰减或散射）的准确建模是否对检测任务产生影响。进一步的观察者研究将用于优化4D重建和处理方法的平滑参数，并比较这些方法，以确定是否在检测任务中提供更好的性能。 最后，本研究建议开发一套基于计算机的观察者，以减少未来耗时的人类观察者研究的需要。基于计算机的观察者，将纳入Hotelling观察者的概念，将其扩展到时空域，并将基于人类视觉系统的心理物理特性。 基于计算机的观察者将接受与人类观察者研究相同的图像检测任务的培训和评估，以确定最有可能模仿人类任务性能的基于计算机的观察者。