Grootjans Willem, Kok Peter, Butter Jurrian, Aarntzen Erik
Department of Radiology, Leiden University Medical Centre;
Department of Radiology and Nuclear Medicine, Radboud University Medical Centre.
J Vis Exp. 2020 Jul 23(161). doi: 10.3791/60258.
Positron emission tomography (PET) combined with X-ray computed tomography (CT) is an important molecular imaging platform that is required for accurate diagnosis and clinical staging of a variety of diseases. The advantage of PET imaging is the ability to visualize and quantify a myriad of biological processes in vivo with high sensitivity and accuracy. However, there are multiple factors that determine image quality and quantitative accuracy of PET images. One of the foremost factors influencing image quality in PET imaging of the thorax and upper abdomen is respiratory motion, resulting in respiration-induced motion blurring of anatomical structures. Correction of these artefacts is required for providing optimal image quality and quantitative accuracy of PET images. Several respiratory gating techniques have been developed, typically relying on acquisition of a respiratory signal simultaneously with PET data. Based on the respiratory signal acquired, PET data is selected for reconstruction of a motion-free image. Although these methods have been shown to effectively remove respiratory motion artefacts from PET images, the performance is dependent on the quality of the respiratory signal being acquired. In this study, the use of an amplitude-based optimal respiratory gating (ORG) algorithm is discussed. In contrast to many other respiratory gating algorithms, ORG permits the user to have control over image quality versus the amount of rejected motion in the reconstructed PET images. This is achieved by calculating an optimal amplitude range based on the acquired surrogate signal and a user-specified duty cycle (the percentage of PET data used for image reconstruction). The optimal amplitude range is defined as the smallest amplitude range still containing the amount of PET data required for image reconstruction. It was shown that ORG results in effective removal of respiration-induced image blurring in PET imaging of the thorax and upper abdomen, resulting in improved image quality and quantitative accuracy.
正电子发射断层扫描(PET)与X射线计算机断层扫描(CT)相结合是一种重要的分子成像平台,是多种疾病准确诊断和临床分期所必需的。PET成像的优势在于能够在体内以高灵敏度和准确性可视化和量化无数生物过程。然而,有多个因素决定PET图像的质量和定量准确性。影响胸部和上腹部PET成像图像质量的首要因素之一是呼吸运动,导致解剖结构出现呼吸诱导的运动模糊。为了提供最佳的PET图像质量和定量准确性,需要校正这些伪影。已经开发了几种呼吸门控技术,通常依赖于与PET数据同时采集呼吸信号。基于采集到的呼吸信号,选择PET数据来重建无运动图像。虽然这些方法已被证明能有效去除PET图像中的呼吸运动伪影,但其性能取决于所采集呼吸信号的质量。在本研究中,讨论了基于幅度的最优呼吸门控(ORG)算法的应用。与许多其他呼吸门控算法不同,ORG允许用户控制重建PET图像中的图像质量与剔除的运动量。这是通过根据采集到的替代信号和用户指定的占空比(用于图像重建的PET数据百分比)计算最优幅度范围来实现的。最优幅度范围被定义为仍包含图像重建所需PET数据量的最小幅度范围。结果表明,ORG能有效消除胸部和上腹部PET成像中呼吸诱导的图像模糊,从而提高图像质量和定量准确性。