Submillimeter resolution positron emission tomography for high-sensitivity mouse brain imaging

Positron emission tomography (PET) is a powerful molecular imaging technique that can provide functional information of living objects. However, the spatial resolution of PET imaging has been limited to around 1 mm which makes it difficult to visualize mouse brain functions in detail. Here we report an ultrahigh resolution small animal PET scanner we developed that can provide a resolution approaching 0.6 mm to visualize the mouse brain functions with unprecedented detail. Methods: The ultrahigh resolution small animal PET scanner had 52.5 mm inner diameter and 51.5 mm axial coverage. The PET scanner consisted of 4 rings each of which had 16 DOI detectors. Each DOI detector consisted of a 3-layer staggered LYSO crystal array with a pitch of 1 mm and 4×4 SiPM array. The physical performance was evaluated in accordance with the NEMA NU4 protocol. The spatial resolution was evaluated with various resolution phantoms. In vivo glucose metabolism imaging of mouse brain was performed. Results: The peak absolute sensitivity was 2.84% with an energy window of 400-600 keV. The 0.55 mm rod structure of a resolution phantom was resolved using the iterative algorithm. The in vivo mouse brain imaging with ¹⁸F-FDG showed clear identification of cortex, thalamus, and hypothalamus which were barely distinguishable in a commercial preclinical PET scanner that we used for imaging comparison. Conclusion: The developed ultrahigh resolution small animal PET scanner is a promising molecular imaging tool for neuroscience research using rodent models.

Left, right, or bilateral amygdala activation? How effects of smoothing and motion correction on ultra-high field, high-resolution functional magnetic resonance imaging (fMRI) data alter inferences

Given the amygdala's role in survival mechanisms, and its pivotal contributions to psychological processes, it is no surprise that it is one of the most well-studied brain regions. One of the common methods for understanding the functional role of the amygdala is the use of functional magnetic resonance imaging (fMRI). However, fMRI tends to be acquired using resolutions that are not optimal for smaller brain structures. Furthermore, standard processing includes spatial smoothing and motion correction which further degrade the resolution of the data. Inferentially, this may be detrimental when determining if the amygdalae are active during a task. Indeed, studies using the same task may show differential amygdala(e) activation. Here, we examine the effects of well-accepted preprocessing steps on whole-brain submillimeter fMRI data to determine the impact on activation patterns associated with a robust task known to activate the amygdala(e). We analyzed 7T fMRI data from 30 healthy individuals collected at sub-millimeter in-plane resolution and used a field standard preprocessing pipeline with different combinations of smoothing kernels and motion correction options. Resultant amygdalae activation patterns were altered depending on which combination of smoothing and motion correction were performed, indicating that whole-brain preprocessing steps have a significant impact on the inferences that can be drawn about smaller, subcortical structures like the amygdala.