Quantitative Imaging for Personalized Cancer Medicine (QIPCM)-Techna Institute, University Health Network, Toronto, ON M5G 2C4, Canada.
Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada.
Tomography. 2022 Mar 21;8(2):842-857. doi: 10.3390/tomography8020069.
Dynamic PET (dPET) imaging can be utilized to perform kinetic modelling of various physiologic processes, which are exploited by the constantly expanding range of targeted radiopharmaceuticals. To date, dPET remains primarily in the research realm due to a number of technical challenges, not least of which is addressing partial volume effects (PVE) in the input function. We propose a series of equations for the correction of PVE in the input function and present the results of a validation study, based on a purpose built phantom. F-dPET experiments were performed using the phantom on a set of flow tubes representing large arteries, such as the aorta (1" 2.54 cm ID), down to smaller vessels, such as the iliac arteries and veins (1/4" 0.635 cm ID). When applied to the dPET experimental images, the PVE correction equations were able to successfully correct the image-derived input functions by as much as 59 ± 35% in the presence of background, which resulted in image-derived area under the curve (AUC) values within 8 ± 9% of ground truth AUC. The peak heights were similarly well corrected to within 9 ± 10% of the scaled DCE-CT curves. The same equations were then successfully applied to correct patient input functions in the aorta and internal iliac artery/vein. These straightforward algorithms can be applied to dPET images from any PET-CT scanner to restore the input function back to a more clinically representative value, without the need for high-end Time of Flight systems or Point Spread Function correction algorithms.
动态 PET(dPET)成像可用于对各种生理过程进行动力学建模,这些生理过程被不断扩展的靶向放射性药物所利用。迄今为止,由于存在许多技术挑战,dPET 主要仍处于研究领域,其中最主要的是解决输入函数中的部分容积效应(PVE)。我们提出了一系列用于校正输入函数中 PVE 的方程,并基于专用的体模展示了验证研究的结果。在一组代表大动脉(如主动脉,内径 1" 2.54 cm)的流管上,使用体模进行了 F-dPET 实验,直到较小的血管(如髂动脉和静脉,内径 1/4" 0.635 cm)。当将这些方程应用于 dPET 实验图像时,PVE 校正方程能够成功地校正图像衍生的输入函数,校正程度高达 59 ± 35%,在存在背景的情况下,图像衍生的曲线下面积(AUC)值与真实 AUC 值的差异在 8 ± 9%以内。峰值高度也得到了类似的校正,校正值与缩放后的 DCE-CT 曲线在 9 ± 10%以内。然后,这些相同的方程成功地应用于校正主动脉和髂内动脉/静脉中的患者输入函数。这些简单的算法可应用于任何 PET-CT 扫描仪的 dPET 图像,以将输入函数恢复到更具临床代表性的值,而无需使用高端时间飞行系统或点扩散函数校正算法。