PATIENT MOTION DETECTION AND COMPENSATION IN SPECT

描述（由申请人提供）： 患者运动是可能限制诊断成像准确性的伪影的始终存在的潜在原因。这个问题对于诸如SPECT和PET之类的成像模态尤其重要，这些成像模态需要患者长时间保持不动。完全依赖于发射数据本身的运动补偿策略，尽管是商业上可用的，但对于稳健的临床使用是不够的。拟议调查的目标是确定来自视觉跟踪系统的信息是否将作为迭代重建的一部分为患者运动提供鲁棒补偿。视觉跟踪系统是指处理由光学相机拍摄的立体图像的计算系统，从而提供独立于SPECT系统的运动信息源。胸部和腹部的运动将通过跟踪图案的位置来确定，该图案是缠绕在患者的这些部分周围的弹性服装的一部分。将使用视觉跟踪系统研究补偿的患者运动类型是刚体运动、非刚体运动、呼吸运动、心脏的向上蠕动以及顺序发射和传输、CT或MRI成像之间的运动。基于视觉跟踪系统的补偿的成功的最终测试将是医生-观察者ROC研究，比较接受SPECT灌注成像的患者在有和没有运动补偿的情况下冠状动脉疾病的检测准确性。第一个具体目标是完善视觉跟踪系统，并确定其跟踪刚体运动的精度。第二个具体目标是修改视觉跟踪系统，以包括对呼吸运动和心脏向上蠕动的补偿。第三个具体目标是调查非刚体运动的需要，以及当与来自同一成像床上的多模态成像的个体患者的解剖结构的知识相结合时，服装上的图案中的位置的运动是否可以预测结构的内部运动。第四个具体目标是开发一种运动补偿算法，该算法采用来自视觉跟踪系统的信息来补偿上述运动，作为列表模式迭代重建的一部分。第五个具体目标是确定视觉跟踪系统和motioncompensation算法是否能够提高心脏灌注SPECT成像的诊断准确性，如通过人类观察者ROC研究与临床图像所确定的。

DESCRIPTION (provided by applicant): Patient motion is an ever-present potential cause of artifacts that can limit the accuracy of diagnostic imaging. The problem is especially significant for imaging modalities such as SPECT and PET, which require the patient to remain motionless for protracted periods of time. Compensation strategies for motion that rely exclusively on the emission data itself, although commercially available, are inadequate for robust clinical usage. The goal of the proposed investigations is to determine if information from a visual-tracking-system will provide a robust compensation for patient motion as part of iterative reconstruction. By visual-trackingsystem it is meant a computational system that processes stereo-images taken by optical cameras thereby providing a source of motion information that is independent of the SPECT system. Motion of the chest and abdomen will be determined by tracking the locations of a pattern that is part of a stretchy garment wrapped about these portions of the patient. The types of patient motion for which compensation will be investigated with the visual-tracking-system are rigid-body motion, non-rigid-body motion, respiratory motion, upward-creep of the heart, and motion between sequential emission and transmission, CT or MRI imaging. The ultimate test of the success of the visual-tracking-system based compensation will be physician-observer ROC studies comparing the detection accuracy of coronary artery disease with and without motion compensation for patients undergoing SPECT perfusion imaging. The first specific aim is to perfect the visual-tracking-system and determine its accuracy for tracking rigid-body motion. The second specific aim is to modify the visual-tracking-system to include compensation for respiratory motion, and upward-creep of the heart. The third specific aim is to investigate the need for non-rigid-body motion, and whether the motion of the locations in the pattern on the garment can predict the internal motion of structures when coupled with knowledge of the individual patient's anatomy from multi-modality imaging on the same imaging bed. The fourth specific aim is to develop a motion-compensation algorithm that employs the information from the visual-tracking-system to compensate for the above motions as part of list-mode iterative reconstruction. The fifth specific aim is to determine whether the visual-tracking-system and motioncompensation algorithm are able to improve the diagnostic accuracy of cardiac-perfusion SPECT imaging as determined by human-observer ROC studies with clinical images.