Kovalski Gil, Israel Ora, Keidar Zohar, Frenkel Alex, Sachs Jonathan, Azhari Haim
Faculty of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel.
J Nucl Med. 2007 Apr;48(4):630-6. doi: 10.2967/jnumed.106.037390.
Several studies have described nonuniform blurring of myocardial perfusion imaging (MPI) due to respiration. This article describes a technique for correcting the respiration effect and assesses its effectiveness in clinical studies.
Simulated phantoms, physical phantoms, and patient scans were used in this study. A heart phantom, which oscillated back and forth, was used to simulate respiration. The motion was measured on a gamma-camera supporting list-mode functionality synchronized with an external respiratory strap or resistor sensor. Eight clinical scans were performed using a 1-d (99m)Tc-sestamibi protocol while recording the respiratory signal. The list-mode capability along with the strap or sensor signals was used to generate respiratory bin projection sets. A segmentation process was used to detect the shift between the respiratory bins. This shift was further projected to the acquired projection images for correction of the respiratory motion. The process was applied to the phantom and patient studies, and the rate of success of the correction was assessed using the conventional bull's eye maps.
The algorithm provided a good correction for the phantom studies. The shift after the correction, measured by a fitted ellipsoid, was <1 mm in the axial direction. The average motion due to respiration in the clinical studies was 9.1 mm in the axial direction. The average shift between the respiratory phases was reduced to 0.5 mm after correction. The maximal change in the bull's eye map for the clinical scans after the correction was 6%, with a mean of 3.75%. The postcorrection clinical summed perfusion images were more uniform, consistent, and, for some patients, clinically significant when compared with the images before correction for respiration.
Myocardial motion generated by respiration during MPI SPECT affects perfusion image quality and accuracy. Motion introduced by respiration can be corrected using the proposed method. The degree of correction depends on the patient respiratory pattern and can be of clinical significance in certain cases.
多项研究描述了由于呼吸导致的心肌灌注成像（MPI）不均匀模糊。本文描述了一种校正呼吸效应的技术，并在临床研究中评估了其有效性。
本研究使用了模拟体模、物理体模和患者扫描。使用一个来回摆动的心脏体模来模拟呼吸。运动在支持列表模式功能并与外部呼吸带或电阻传感器同步的γ相机上进行测量。使用1日（99m）Tc-司他米比方案进行了8次临床扫描，同时记录呼吸信号。列表模式功能以及带或传感器信号用于生成呼吸分箱投影集。使用分割过程检测呼吸分箱之间的偏移。该偏移进一步投影到采集的投影图像上以校正呼吸运动。该过程应用于体模和患者研究，并使用传统的靶心图评估校正的成功率。
该算法对体模研究提供了良好的校正。校正后通过拟合椭圆体测量的轴向偏移<1毫米。临床研究中呼吸引起的平均运动在轴向为9.1毫米。校正后呼吸相位之间的平均偏移减少到0.5毫米。校正后临床扫描的靶心图最大变化为6%，平均为3.75%。与校正呼吸前的图像相比，校正后的临床总灌注图像更均匀、一致，并且对于一些患者具有临床意义。
MPI SPECT期间呼吸产生的心肌运动影响灌注图像质量和准确性。可以使用所提出的方法校正呼吸引入的运动。校正程度取决于患者的呼吸模式，在某些情况下可能具有临床意义。
