Molecular Imaging Center Antwerp, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium.
Biomed Phys Eng Express. 2020 May 6;6(4):045001. doi: 10.1088/2057-1976/ab8c13.
In small animal positron emission tomography (PET) studies, given the spatial resolution of preclinical PET scanners, quantification in small regions can be challenging. Moreover, in scans where animals are placed away from the center of the field of view (CFOV), e.g. in simultaneous scans of multiple animals, quantification accuracy can be compromised due to the loss of spatial resolution towards the edge of the FOV. Here, we implemented a spatially variant resolution model to improve quantification in small regions and to allow simultaneous scanning of multiple animals without compromising quantification accuracy. The scanner's point spread function (PSF) was characterized across the FOV and modelled using a spatially variant and asymmetric Gaussian function. The spatially variant PSF (SVPSF) was then used for resolution modelling in the iterative reconstruction. To assess the image quality, a line source phantom in a cold and warm background, as well as mouse brain [F]FDG scans, were performed. The SVPSF and the vendor's maximum a posteriori (MAP3D) reconstructions produced uniform spatial resolution across the scanner FOV, but MAP3D resulted in lower spatial resolution. The line sources recovery coefficient using SVPSF was similar at the CFOV and at the edge of the FOV. In contrast, the other tested reconstructions produced lower recovery coefficient at the edge of the FOV. In mouse brain reconstructions, less spill-over from hot regions to cold regions, as well as more symmetric regional brain uptake was observed using SVPSF. The contrast in brain images was the highest using SVPSF, in mice scanned at the CFOV and off-center. Incorporation of a spatially variant resolution model for small animal brain PET improves quantification accuracy in small regions and produces consistent image spatial resolution across the FOV. Therefore, simultaneous scanning of multiple animals can benefit by using spatially variant resolution modelling.
在小动物正电子发射断层扫描（PET）研究中，鉴于临床前 PET 扫描仪的空间分辨率，对小区域进行定量可能具有挑战性。此外，在将动物放置在视场（FOV）中心之外的扫描中，例如在同时扫描多个动物的情况下，由于 FOV 边缘处空间分辨率的损失，定量准确性可能会受到影响。在这里，我们实施了一种空间可变分辨率模型，以提高小区域的定量准确性，并允许在不影响定量准确性的情况下同时扫描多个动物。使用空间可变和不对称高斯函数对扫描仪的点扩散函数（PSF）进行了整个 FOV 的特征描述，并对其进行建模。然后，在迭代重建中使用空间可变 PSF（SVPSF）进行分辨率建模。为了评估图像质量，在冷和暖背景下进行了线源体模以及小鼠脑 [F]FDG 扫描。SVPSF 和供应商的最大后验（MAP3D）重建在整个扫描仪 FOV 上产生了均匀的空间分辨率，但 MAP3D 导致了较低的空间分辨率。使用 SVPSF 的线源恢复系数在 FOV 中心和边缘处相似。相比之下，其他测试的重建在 FOV 边缘产生了较低的恢复系数。在小鼠脑重建中，使用 SVPSF 观察到热区到冷区的溢出较少，并且区域脑摄取更对称。使用 SVPSF 观察到对比度在大脑图像中最高，在扫描 CFOV 和偏离中心的小鼠中。在小动物脑 PET 中引入空间可变分辨率模型可提高小区域的定量准确性，并在整个 FOV 中产生一致的图像空间分辨率。因此，使用空间可变分辨率建模可以使同时扫描多个动物受益。
