IEEE Trans Med Imaging. 2020 Jul;39(7):2518-2530. doi: 10.1109/TMI.2019.2962237. Epub 2020 Feb 11.
Recent advances in positron emission tomography (PET) have allowed to perform brain scans of freely moving animals by using rigid motion correction. One of the current challenges in these scans is that, due to the PET scanner spatially variant point spread function (SVPSF), motion corrected images have a motion dependent blurring since animals can move throughout the entire field of view (FOV). We developed a method to calculate the image-based resolution kernels of the motion dependent and spatially variant PSF (MD-SVPSF) to correct the loss of spatial resolution in motion corrected reconstructions. The resolution kernels are calculated for each voxel by sampling and averaging the SVPSF at all positions in the scanner FOV where the moving object was measured. In resolution phantom scans, the use of the MD-SVPSF resolution model improved the spatial resolution in motion corrected reconstructions and corrected the image deformation caused by the parallax effect consistently for all motion patterns, outperforming the use of a motion independent SVPSF or Gaussian kernels. Compared to motion correction in which the SVPSF is applied independently for every pose, our method performed similarly, but with more than two orders of magnitude faster computation time. Importantly, in scans of freely moving mice, brain regional quantification in motion-free and motion corrected images was better correlated when using the MD-SVPSF in comparison with motion independent SVPSF and a Gaussian kernel. The method developed here allows to obtain consistent spatial resolution and quantification in motion corrected images, independently of the motion pattern of the subject.
正电子发射断层扫描（PET）的最新进展使得可以通过使用刚性运动校正来对自由移动的动物进行脑部扫描。这些扫描中的当前挑战之一是，由于 PET 扫描仪的空间变化点扩散函数（SVPSF），运动校正后的图像具有运动相关的模糊，因为动物可以在整个视场（FOV）中移动。我们开发了一种方法来计算运动相关和空间变化 PSF（MD-SVPSF）的基于图像的分辨率核，以校正运动校正重建中的空间分辨率损失。通过在扫描仪 FOV 中所有位置处对 SVPSF 进行采样和平均，为每个体素计算分辨率核，在该位置处测量了移动物体。在分辨率体模扫描中，使用 MD-SVPSF 分辨率模型可改善运动校正重建中的空间分辨率，并一致校正所有运动模式下由于视差效应引起的图像变形，优于使用运动独立的 SVPSF 或高斯核。与独立地为每个姿势应用 SVPSF 的运动校正相比，我们的方法性能相似，但计算时间快两个数量级以上。重要的是，在对自由移动的老鼠进行扫描时，与使用运动独立的 SVPSF 和高斯核相比，在使用 MD-SVPSF 时，在运动和运动校正图像中的大脑区域定量之间具有更好的相关性。与运动独立的 SVPSF 和高斯核相比，与运动独立的 SVPSF 和高斯核相比，使用 MD-SVPSF 可以在不依赖于主体运动模式的情况下，在运动校正图像中获得一致的空间分辨率和定量。
