Elsevier

NeuroImage

Volume 38, Issue 1, 15 October 2007, Pages 34-42
NeuroImage

A novel approach for imaging brain–behavior relationships in mice reveals unexpected metabolic patterns during seizures in the absence of tissue plasminogen activator

https://doi.org/10.1016/j.neuroimage.2007.06.032Get rights and content

Abstract

Medically refractory seizures cause inflammation and neurodegeneration. Seizure initiation thresholds have been linked in mice to the serine protease tissue plasminogen activator (tPA); mice lacking tPA exhibit resistance to seizure induction, and the ensuing inflammation and neurodegeneration are similarly suppressed. Seizure foci in humans can be examined using PET employing 2-deoxy-2[18F]fluoro-d-glucose (18FDG) as a tracer to visualize metabolic dysfunction. However, there currently exist no such methods in mice to correlate measures of brain activation with behavior. Using a novel method for small animal PET data analysis, we examine patterns of 18FDG uptake in wild-type and tPA−/− mice and find that they correlate with the severity of drug-induced seizure initiation. Furthermore, we report unexpected activations that may underlie the tPA modulation of seizure susceptibility. The methods described here should be applicable to other mouse models of human neurological disease.

Introduction

Increased hippocampal excitability is commonly observed in temporal lobe epilepsy (TLE) (Carne et al., 2004, de Lanerolle et al., 2003) and can be visualized indirectly using metabolic imaging of 2-deoxy-2[18F]fluoro-d-glucose (18FDG) (Diehl et al., 2003, Lamusuo et al., 2001). Small animal imaging using microPET has become an increasingly useful tool in multiple research areas (Schiffer et al., 2005, Schiffer et al., 2006a, Sossi and Ruth, 2005). However, existing image analysis strategies for small animal PET data are targeted toward examining regional changes in 18FDG uptake, as we have shown for an animal model of TLE (Mirrione et al., 2006). Here we describe a way to use statistical parametric mapping (SPM), an advanced image analysis strategy commonly used in human imaging studies, to develop a high-throughput and clinically relevant method to elucidate brain–behavior relationships in animal models of human disease.

We have previously reported that mice deficient in tissue plasminogen activator (tPA−/−) display a higher threshold for seizure onset using an animal model for TLE (Tsirka et al., 1995). tPA is expressed in the central nervous system (CNS) and plays a role in neuronal plasticity (Baranes et al., 1998, Centonze et al., 2002, Madani et al., 1999, Seeds et al., 1995, Zhuo et al., 2000) and seizure susceptibility (Pawlak et al., 2005, Qian et al., 1993, Tsirka et al., 1995, Yepes et al., 2002). In metrazol (PTZ)-induced seizures and kindling, tPA is transcriptionally up-regulated in pyramidal neurons of the hippocampus and thought to contribute to structural changes observed following activity-dependent plasticity (Carroll et al., 1994, Qian et al., 1993). The changes include physiological elongation of mossy fiber axons during late-phase long-term potentiation (LTP) (Baranes et al., 1998, Madani et al., 1999, Zhuo et al., 2000) and aberrant neurite outgrowth (Salles and Strickland, 2002, Wu et al., 2000, Zhang et al., 2005). We have developed a unique method to test the relationship between seizure severity and brain activation and have specifically examined whether tPA−/− mice demonstrate an altered pattern of metabolic activation.

At the core of the method is the necessity for small animal image analysis strategies to keep up with the rapidly expanding role of imaging in animal models of human disease. Small animal MRI, PET and CT systems are now commercially available, and there is a commensurate need for image analysis strategies to take full advantage of these preclinical imaging systems. We describe a high-throughput approach for neurological mouse small animal PET data analysis that includes streamlined spatial preprocessing of imaging data in atlas space and implementation of a voxel-based correlation analysis widely used to elucidate brain–behavior relationships in human functional brain imaging. The voxel-based analysis has been validated using a traditional ROI analysis coupled to behavioral scores with a linear approach we previously described (Mirrione et al., 2006). Our results suggest that the relationships observed between metabolic activity and seizure severity in wild-type mice do not hold in tPA−/− mice. These results provide in vivo evidence of a discord between brain activity and behavior in the genetically modified animals. The integrated approach to experimental design and data analysis can be applied to a broad spectrum of research involving genetically altered mice. We describe tools, including a whole brain mouse ROI template in stereotaxic space (Paxinos and Franklin, 2001), implementation of methods for voxel-based analysis of mouse brain function using the SPM software package, and high-throughput procedures for experimental design using serial studies.

Section snippets

Mouse seizure model

Animal procedures were approved by the Institute for Animal Care and Use Committee (IACUC) at Stony Brook and Brookhaven National Laboratory (BNL). Mice, aged 2–5 months, 24–34 g, were obtained from either Taconic farms or transferred to BNL from Stony Brook University DLAR. All animals received two PET scans, 7 days apart. For the first (baseline) scan each animal underwent 45 min of 18FDG uptake followed by 100 mg/kg of a 10% xylazine, 90% ketamine anesthesia for a 10-min scan. Seizure

Region of interest (ROI) template

The C57Bl/6J (wt) mouse whole brain ex vivo MRI reference template (Ma et al., 2005) was employed for mapping regional changes in 18FDG uptake. This atlas was placed in stereotaxic space (Paxinos and Franklin, 2001) using established methods (Schweinhardt et al., 2003) where several known points spread uniformly around the brain were used to validate its placement. A volumetric ROI template was created based on 20 regions segmented from the MRI template (Ma et al., 2005). In Fig. 1a, this

Discussion

In this study we developed and validated a novel strategy for small animal PET data analysis, and present a novel way to correlate brain activity and behavior. We compare changes in mouse brain 18FDG uptake between baseline conditions and seizures. To our knowledge, this is the first study to streamline whole brain analysis methods using an in-house ROI template with voxel-wise correlations of brain activity and behavior in genetically modified mice. Using voxel-based SPM2, we show that tPA−/−

Conclusions

Here we demonstrate the successful use of 18FDG as a marker for metabolic changes associated with seizure activity. We have demonstrated the potential for correlating behavior and disease symptoms with brain function in vivo. Our data show that the relationship between metabolic activity and behavior is not sustained in tPA−/− animals suggesting that these animals have an altered response to seizure induction. Furthermore, the methods validated here for small animal PET data analysis can be

Acknowledgments

The authors would like to thank the members of the BNL cyclotron facility, Michael Schueller, David J. Schyler, Colleen Shea, and Youwen Xu, for the 18FDG preparation. We would also like to thank Shiva Kothari for assisting in verifying baseline glucose levels between genotypes. This work was supported by the National Science Foundation Integrative Graduate Education and Research Traineeship — Minerals, Metals, Metalloids and Toxicity Program at Stony Brook University (M.M.M), National

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