The main advantage of hybrid PET-MR imaging systems is the ability to correlate anatomical with metabolic information directly. The bulk of commercially available PET-MR systems are quite large and expensive and mostly used on humans rather than for preclinical animal studies. This has led to a gap of knowledge in PET-MR imaging of small animal models used in preclinical research. Our work takes advantage of a new imaging system developed by Cubresa called 'NuPET'. This device is a MR-compatible PET scanner placed around the subject while they are within the toroidal bore of a MR scanner. With this equipment we are attempting to demonstrate the selective activation of serotonergic neurons in living rodent brains. To specify which neurons are to be activated, we use Designed Receptors Exclusively Activated by Designer Drug (DREADD) technology. These DREADDs are designer G-protein-coupled receptors. Neurons at the site of a stereotactic injection are transfected with a viral vector containing the proteins necessary to force expression of DREADDs in genetically modified rats. These may then be activated by administering the designer drug clozapine-N-oxide (CNO). This technique allows for precise spatiotemporal control of receptor signaling in vivo. Over two experiments (N=5, N=2) we have attempted to image the effect of DREADDs-mediated excitation of 5-HT neurons in rats. Voxel-based analysis of the data thus far show no confirmed statistically significant differences between rats given saline and those given CNO. Numerous methodological issues have been discovered within the experimental design, and are being addressed for a new trial of the technique and technology.

The authors wish to acknowledge funding from NSERC partnership grants, Mitacs, Cubresa, and Research Manitoba.

Multi-modal PET-MR imaging of the selective activation of serotonergic neurons in living rodent brains with DREADD technology

Temporal diffusion spectroscopy (TDS) has been used to infer axon sizes using geometric models that assume axons are cylinders. A celery sample was imaged to test if the importance of other geometric models. The vascular bundles and collenchyma tissue (~20 μm cells) in celery can be modeled as containing cylindrical cells. Whereas the parenchyma cells are rounder and are 3-4 times larger in diameter. Thus we imaged celery to test TDS with oscillating gradient spin echo (OGSE) to see if the spherical cell model and cylindrical cell model infer significantly different cell sizes to determine how important the geometrical model is.
A small section of a celery stalk was cut to fit inside a 15 mL sample tube filled with water. The image slice was chosen to be perpendicular to the length of the celery stalk. The sample was imaged using a 7T Bruker AvanceIII NMR system with Paravision 5.0 and BGA6 gradient set with a maximum gradient strength of 430357 Hz/cm, and a 3.5 cm diameter bird cage RF coil. Each 20 ms apodised cosine gradient pulse ranged from n = 1-20, in steps of 1. Two different gradient strengths were used for each frequency and gradient pulses were separated by 24.52 ms. A 1mm thick slice was acquired with the following imaging parameters: 2 averages, 2.56 cm FOV, TR = 1250 ms, TE = 50 ms, matrix 128 x 128, 200 μm in plane resolution, acquisition time 26.67 minutes per scan (scans performed = 40, 17.78 hours).
The inferred diameters of cells in celery (14±6μm to 20±12μm) were not statistically different when using the two different geometric models. This is the first step toward understanding the importance of geometric models for TDS.
The authors wish to acknowledge funding from NSERC and Mitacs.

Comparison of Cylindrical and Spherical Geometric Models to Infer Cell Sizes in a Celery Sample

M4-2 MR and PET Imaging - Part 2 (DPMB/COMP) / Imagerie RM et TEP - Partie 2 (DPMB/OCPM)

technical paper

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Multi-modal PET-MR imaging of the selective activation of serotonergic neurons in living rodent brains with DREADD technology

Comparison of Cylindrical and Spherical Geometric Models to Infer Cell Sizes in a Celery Sample

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