Patient Motion Detection and Compensation in SPECT

描述(由申请人提供)：患者运动是一种经常存在的伪影的潜在原因，可能会限制诊断成像的准确性。这个问题对于SPECT和PET等成像方式尤其严重，这些成像方式要求患者在较长时间内保持不动，而在多模式成像中，患者在两种方式之间进行对准是至关重要的。我们的假设是，在迭代重建中结合来自视觉跟踪系统(VTS)的信息和成像方式本身将产生稳健的运动校正策略。我们所说的VTS指的是一种计算系统，它处理患者表面上的反向反射标记的立体图像，以提供独立于临床成像系统的运动信息源(S)。使用这种组合方法进行心肌灌注SPECT成像时，需要研究的患者运动类型包括刚体运动(RBM)、非刚体运动(Non-RBM)、呼吸运动(RM)、心脏向上蠕动(由Rm的变化引起)以及顺序多模式成像检查之间的运动。请注意，我们对身体运动和RM进行了不同的校正，因此我们将它们区分为运动估计的一部分。在这一竞争性更新中，我们建议扩展我们目前的VTS，以包括具有多模式成像、发射数据一致性和基于有限元模型的非RBM校正的应用。志愿者的核磁共振将被用来建立外部标记运动和体内心脏运动之间的关系。MRI还将提供不同运动状态下胸部的高分辨率解剖，并结合测量的标记运动来指导创建逼真的SPECT模拟，以改进算法。最初的临床测试将利用患者-志愿者的重复静息心脏SPECT研究，其中第一个静息成像研究作为判断第二个研究(在此期间患者有意移动)矫正成功的标准。我们假设成功的最终评估将是医生-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对冠状动脉疾病(CAD)的检测准确性，并将心导管检查结果作为“金”标准。我们相信，我们建议的研究的意义不仅在于通过对心脏和非心脏SPECT、PET和多模式成像进行运动校正来提高诊断准确性的可能性，而且还在于提供对患者在成像过程中运动的更好理解。 与公共卫生相关：患者通常在SPECT和PET要求的长时间成像期间移动，以收集统计上足够数量的事件以形成图像，以便做出准确的诊断。这样的运动可能会导致切片中的伪影变化，这可能会误导医生。在多模式成像中，患者还可以在发射成像和用于形成衰减图的成像之间移动，并为发射成像中的功能变化提供解剖学框架。这可能会导致两组图像之间的配准错误，这可能会显著影响临床解释。此外，患者在呼吸时获得的所有图像都会受到被成像结构的呼吸运动模糊的影响。这个项目的目标是开发一种准确和健壮的运动校正方法，用于所有形式的患者运动，最大限度地改变当前的采集协议，以便可以在繁忙的临床中使用。我们为开发这一方法选择的试验台是心脏灌注SPECT成像，它不仅是当今最常用的SPECT成像程序，而且在提供冠状动脉疾病风险评估和分层所需的灌注和功能信息方面发挥着关键作用。一旦心脏SPECT的方法完善，它就可以与其他SPECT和PET成像程序一起使用。这项拟议的研究还将更好地了解患者在医学成像和治疗过程中的运动。

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, and multimodality imaging where patient alignment between the modalities is essential. Our hypothesis is that integrating into iterative reconstruction combined information from a visual-tracking-system (VTS) and the imaging modalities themselves will result in a robust motion-correction strategy. By VTS we mean a computational system that processes stereo-images of retro-reflective markers on the patient surface to provide a source of motion information that is independent of the clinical imaging system(s). The types of patient motion for which compensation will be investigated for cardiac perfusion SPECT imaging with this combined approach are rigid-body motion (RBM), non-rigid-body motion (non-RBM), respiratory motion (RM), cardiac upward creep (which is caused by changes in RM), and motion between sequential multi-modality imaging studies. Note we correct body-motion and RM differently, thus we differentiate between them as part of motion estimation. In this competitive renewal we propose to extend our current VTS to include application with multimodality imaging, emission data-consistency, and finite-element-modeling (FEM) based correction of non-RBM. MRI of volunteers will be employed to establish the relationship between external-marker motion and the motion of the heart within the body. MRI will also provide high-resolution anatomy of the chest at different motion states in combination with measured-marker motion to guide the creation of realistic SPECT simulations for refinement of algorithms. Initial clinical testing will make use of repeat-rest cardiac-SPECT studies in patient-volunteers where the first rest imaging study serves as the standard for judging the success of correction of the second study during which the patients intentionally move. The ultimate assessment of the success of our hypothesis will be physician-observer ROC studies comparing the detection accuracy of coronary artery disease (CAD) with and without motion compensation for patients undergoing SPECT perfusion imaging with the results of cardiac catheterization serving as the "gold" standard. We believe the significance of our proposed investigations lies not only in the potential to improve diagnostic accuracy through motion-correction of both cardiac and non-cardiac SPECT, PET, and multimodality imaging but also in affording a better understanding of patient motion during imaging. PUBLIC HEALTH RELEVANCE: Patients commonly move during the protracted imaging period required by SPECT and PET to collect a statistically sufficient number of events to form images for making an accurate diagnosis. Such motion can cause artifactual changes in the slices which may mislead the physician. In multi-modality imaging patients also may move between emission imaging and imaging used to form attenuation maps and provide an anatomical framework for the functional changes in emission imaging. This can cause a misregistration between the two sets of images which can significantly impact clinical interpretation. Also all images acquired while patients are breathing suffer from respiratory motion blurring of the structures being imaged. The goal of this project is to develop an accurate and robust motion-correction methodology for all forms of patient motion which minimally alters current acquisition protocols so that it can be employed in a busy clinic. The test-bed we have chosen for development of this methodology is cardiac perfusion SPECT imaging which is not only the single most frequent SPECT imaging procedure performed today, but also plays a critical role in providing perfusion and functional information needed for risk assessment and stratification regarding coronary artery disease. Once the methodology is perfected for cardiac SPECT it can be adapted for use with other SPECT and PET imaging procedures. The proposed research will also provide a better understanding of patient motion during medical imaging and treatment.