Tellmann Lutz, Fulton Roger, Pietrzyk Uwe, Nickel Ingo, Stangier Isabelle, Winz Oliver, Herzog Hans
Institute of Medicine, Forschungszentrum Juelich, D-52425 Juelich, Germany.
Z Med Phys. 2006;16(1):67-74. doi: 10.1078/0939-3889-00293.
The long acquisition times (up to hours) in PET brain imaging bear a high risk of head motion, which results in artefacts like blurred images and may even lead to misinterpretation and useless data. With the increased resolution of high performance PET scanners, the influence of head movements becomes more and more relevant. Especially in the analysis of small brain structures, e.g. during ROI-analysis, head motion results in inaccuracies of quantified data. This may also influence the kinetic analysis and generate artifacts in parametric images calculated from a motion-affected image sequence. This work presents the feasibility of head motion registration using an external motion tracking system. The implementation of the multi acquisition frame method and an event-by-event method to correct PET data for motion are described. The effects of motion correction are demonstrated on the basis of phantom measurements and patient data. The influence of motion correction on parametric imaging is described in a receptor study.
PET脑成像中较长的采集时间(长达数小时)带来了头部运动的高风险,这会导致诸如图像模糊等伪影,甚至可能导致误解和无用的数据。随着高性能PET扫描仪分辨率的提高,头部运动的影响变得越来越显著。特别是在分析小脑结构时,例如在感兴趣区分析期间,头部运动会导致量化数据不准确。这也可能影响动力学分析,并在从受运动影响的图像序列计算出的参数图像中产生伪影。这项工作展示了使用外部运动跟踪系统进行头部运动配准的可行性。描述了多采集帧方法和逐事件方法用于校正PET数据运动的实现。基于体模测量和患者数据展示了运动校正的效果。在一项受体研究中描述了运动校正对参数成像的影响。