Patient motion effects on the quantification of regional myocardial blood flow with dynamic PET imaging
Patient motion effects on the quantification of regional myocardial blood flow with dynamic PET imaging
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DOI：
10.1118/1.4943565
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发表时间：
2016-04-01
期刊：
影响因子：
3.8
通讯作者：
deKemp, Robert A.
中科院分区：
文献类型：
--
作者：
Hunter, Chad R. R. N.;Klein, Ran;deKemp, Robert A.
目的：患者运动是动态正电子发射断层扫描（PET）定量心肌血流量（MBF）过程中的常见问题。本研究的目的是量化的患病率在临床环境中的身体运动和评估与现实的幻影的影响，运动对血流定量，包括CT衰减校正（CTAC）伪影，PET-CT misalignment.Methods的结果：一个队列的236个连续的患者进行了分析，由两个独立的观察者在休息和峰值应力条件下的患者运动。记录运动的存在、受影响的时间范围和运动方向;观察员之间的差异通过共识审查解决。基于这些结果，患者身体运动对MBF量化的影响使用基于数字化的心脏躯干体模进行表征，特征时间活动曲线（TAC）分配给心脏壁（心肌）和血液区域。对模拟投影数据进行衰减校正，并使用滤波反投影进行重建。所有模拟进行无噪声添加，和一个单一的CT图像用于衰减校正和对齐的早期或后期帧PET images.Results：在患者队列中，轻度运动0.5 +/- 0.1厘米发生在24%和中度运动1.0 +/- 0.3厘米发生在38%的患者。上级/下级方向的运动占所有检测到的运动的45%，其中30%在上级方向。前/后运动以向后方向为主（29%）。24%的病例发生左/右运动，左右方向的比例相似。计算机模拟研究表明，MBF的错误可以接近500%的扫描与严重的患者运动（高达2厘米）。最大的误差发生在心壁向左移向相邻肺区域时，导致心壁衰减严重校正不足。模拟还表明，由上级/下级和前/后方向运动引起的MBF误差幅度相似（高达250%）。对于更高分辨率的PET成像（2 mm与10 mm半高全宽）以及在中晚期时间范围内发生的运动，身体运动效应更为有害。重建的动态图像系列的运动校正导致MBF误差的显著减少，但没有考虑到残留的PET-CTAC未对准伪影。MBF偏差进一步减少使用全球部分容积校正，并使用动态对准的PET投影数据的CT扫描准确的衰减校正在图像reconstruction.Conclusions：病人的身体运动可以产生MBF估计误差高达500%。为了减少这些误差，新的运动校正算法必须有效地识别左/右方向上的运动，并且在中晚期时间帧中，因为这些条件在MBF中产生最大的误差，特别是对于高分辨率PET成像。理想情况下，应在图像重建之前或重建期间进行运动校正，以消除PET-CTAC未对准伪影。(C)2016年美国医学物理学家协会。
Purpose: Patient motion is a common problem during dynamic positron emission tomography (PET) scans for quantification of myocardial blood flow (MBF). The purpose of this study was to quantify the prevalence of body motion in a clinical setting and evaluate with realistic phantoms the effects of motion on blood flow quantification, including CT attenuation correction (CTAC) artifacts that result from PET-CT misalignment.Methods: A cohort of 236 sequential patients was analyzed for patient motion under resting and peak stress conditions by two independent observers. The presence of motion, affected time-frames, and direction of motion was recorded; discrepancy between observers was resolved by consensus review. Based on these results, patient body motion effects on MBF quantification were characterized using the digital NURBS-based cardiac-torso phantom, with characteristic time activity curves (TACs) assigned to the heart wall (myocardium) and blood regions. Simulated projection data were corrected for attenuation and reconstructed using filtered back-projection. All simulations were performed without noise added, and a single CT image was used for attenuation correction and aligned to the early-or late-frame PET images.Results: In the patient cohort, mild motion of 0.5 +/- 0.1 cm occurred in 24% and moderate motion of 1.0 +/- 0.3 cm occurred in 38% of patients. Motion in the superior/inferior direction accounted for 45% of all detected motion, with 30% in the superior direction. Anterior/posterior motion was predominant (29%) in the posterior direction. Left/right motion occurred in 24% of cases, with similar proportions in the left and right directions. Computer simulation studies indicated that errors in MBF can approach 500% for scans with severe patient motion (up to 2 cm). The largest errors occurred when the heart wall was shifted left toward the adjacent lung region, resulting in a severe undercorrection for attenuation of the heart wall. Simulations also indicated that the magnitude of MBF errors resulting from motion in the superior/inferior and anterior/posterior directions was similar (up to 250%). Body motion effects were more detrimental for higher resolution PET imaging (2 vs 10 mm full-width at half-maximum), and for motion occurring during the mid-to-late time-frames. Motion correction of the reconstructed dynamic image series resulted in significant reduction in MBF errors, but did not account for the residual PET-CTAC misalignment artifacts. MBF bias was reduced further using global partial-volume correction, and using dynamic alignment of the PET projection data to the CT scan for accurate attenuation correction during image reconstruction.Conclusions: Patient body motion can produce MBF estimation errors up to 500%. To reduce these errors, new motion correction algorithms must be effective in identifying motion in the left/right direction, and in the mid-to-late time-frames, since these conditions produce the largest errors in MBF, particularly for high resolution PET imaging. Ideally, motion correction should be done before or during image reconstruction to eliminate PET-CTAC misalignment artifacts. (C) 2016 American Association of Physicists in Medicine.