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通过心脏PET成像中的4D呼吸运动补偿增强射血分数测量。

Enhancing ejection fraction measurement through 4D respiratory motion compensation in cardiac PET imaging.

作者信息

Tang Jing, Wang Xinhui, Gao Xiangzhen, Segars W Paul, Lodge Martin A, Rahmim Arman

机构信息

Department of Electrical and Computer Engineering, Oakland University, Rochester, MI, United States of America.

出版信息

Phys Med Biol. 2017 Jun 7;62(11):4496-4513. doi: 10.1088/1361-6560/aa6417. Epub 2017 Mar 2.

Abstract

ECG gated cardiac PET imaging measures functional parameters such as left ventricle (LV) ejection fraction (EF), providing diagnostic and prognostic information for management of patients with coronary artery disease (CAD). Respiratory motion degrades spatial resolution and affects the accuracy in measuring the LV volumes for EF calculation. The goal of this study is to systematically investigate the effect of respiratory motion correction on the estimation of end-diastolic volume (EDV), end-systolic volume (ESV), and EF, especially on the separation of normal and abnormal EFs. We developed a respiratory motion incorporated 4D PET image reconstruction technique which uses all gated-frame data to acquire a motion-suppressed image. Using the standard XCAT phantom and two individual-specific volunteer XCAT phantoms, we simulated dual-gated myocardial perfusion imaging data for normally and abnormally beating hearts. With and without respiratory motion correction, we measured the EDV, ESV, and EF from the cardiac-gated reconstructed images. For all the phantoms, the estimated volumes increased and the biases significantly reduced with motion correction compared with those without. Furthermore, the improvement of ESV measurement in the abnormally beating heart led to better separation of normal and abnormal EFs. The simulation study demonstrated the significant effect of respiratory motion correction on cardiac imaging data with motion amplitude as small as 0.7 cm. The larger the motion amplitude the more improvement respiratory motion correction brought about on the EF measurement. Using data-driven respiratory gating, we also demonstrated the effect of respiratory motion correction on estimating the above functional parameters from list mode patient data. Respiratory motion correction has been shown to improve the accuracy of EF measurement in clinical cardiac PET imaging.

摘要

心电图门控心脏PET成像可测量诸如左心室(LV)射血分数(EF)等功能参数,为冠状动脉疾病(CAD)患者的管理提供诊断和预后信息。呼吸运动降低了空间分辨率,并影响用于计算EF的左心室容积测量的准确性。本研究的目的是系统地研究呼吸运动校正对舒张末期容积(EDV)、收缩末期容积(ESV)和EF估计的影响,特别是对正常和异常EF分离的影响。我们开发了一种结合呼吸运动的4D PET图像重建技术,该技术使用所有门控帧数据来获取运动抑制图像。使用标准XCAT体模和两个个体特异性志愿者XCAT体模,我们模拟了正常和异常跳动心脏的双门控心肌灌注成像数据。在有和没有呼吸运动校正的情况下,我们从心脏门控重建图像中测量EDV、ESV和EF。对于所有体模,与未进行运动校正相比,经运动校正后估计的容积增加,偏差显著减小。此外,在异常跳动心脏中ESV测量的改善导致正常和异常EF的更好分离。模拟研究表明,呼吸运动校正对运动幅度小至0.7 cm的心脏成像数据有显著影响。运动幅度越大,呼吸运动校正对EF测量带来的改善就越大。使用数据驱动的呼吸门控,我们还证明了呼吸运动校正对从列表模式患者数据估计上述功能参数的影响。呼吸运动校正已被证明可提高临床心脏PET成像中EF测量的准确性。

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