MRI with applications in neurological disorders

MRI has developed into one of the most powerful techniques for both experimental and clinical research. Nowadays, it has become the imaging method of choice for modern medical imaging and its success is due to its versatile nature. In addition, it is noninvasive and offers the advantage of imaging at relatively high spatial as well as high temporal resolution. The main advantage of MRI compared with other common imaging techniques such as positron emission tomography and single-photon emission computed tomography is its very high in vivo spatial resolution resulting in clear anatomical information. In addition, it provides an amazingly strong imaging contrast between different soft tissues, which is not feasible with other in vivo imaging modalities. Since magnetic fields and low-energy electro-magnetic waves are used instead of ionizing radiation, no biological damage is caused. Another important advantage is that MRI allows longitudinal studies, since it does not rely on the use of radioactive isotopes. This chapter highlights the most commonly used MRI techniques in both clinical and preclinical practice

Cholinergic and serotonergic modulations differentially affect large-scale functional networks in the mouse brain

Resting-state functional MRI (rsfMRI) is a widely implemented technique used to investigate large-scale topology in the human brain during health and disease. Studies in mice provide additional advantages, including the possibility to flexibly modulate the brain by pharmacological or genetic manipulations in combination with high-throughput functional connectivity (FC) investigations. Pharmacological modulations that target specific neurotransmitter systems, partly mimicking the effect of pathological events, could allow discriminating the effect of specific systems on functional network disruptions. The current study investigated the effect of cholinergic and serotonergic antagonists on large-scale brain networks in mice. The cholinergic system is involved in cognitive functions and is impaired in, e.g., Alzheimer’s disease, while the serotonergic system is involved in emotional and introspective functions and is impaired in, e.g., Alzheimer’s disease, depression and autism. Specific interest goes to the default-mode-network (DMN), which is studied extensively in humans and is affected in many neurological disorders. The results show that both cholinergic and serotonergic antagonists impaired the mouse DMN-like network similarly, except that cholinergic modulation additionally affected the retrosplenial cortex. This suggests that both neurotransmitter systems are involved in maintaining integrity of FC within the DMN-like network in mice. Cholinergic and serotonergic modulations also affected other functional networks, however, serotonergic modulation impaired the frontal and thalamus networks more extensively. In conclusion, this study demonstrates the utility of pharmacological rsfMRI in animal models to provide insights into the role of specific neurotransmitter systems on functional networks in neurological disorders

More accurate estimation of diffusion tensor parameters using diffusion kurtosis imaging

With diffusion tensor imaging, the diffusion of water molecules through brain structures is quantified by parameters, which are estimated assuming monoexponential diffusion-weighted signal attenuation. The estimated diffusion parameters, however, depend on the diffusion weighting strength, the b-value, which hampers the interpretation and comparison of various diffusion tensor imaging studies. In this study, a likelihood ratio test is used to show that the diffusion kurtosis imaging model provides a more accurate parameterization of both the Gaussian and non-Gaussian diffusion component compared with diffusion tensor imaging. As a result, the diffusion kurtosis imaging model provides a b-value-independent estimation of the widely used diffusion tensor parameters as demonstrated with diffusion-weighted rat data, which was acquired with eight different b-values, uniformly distributed in a range of [0,2800 sec/mm(2)]. In addition, the diffusion parameter values are significantly increased in comparison to the values estimated with the diffusion tensor imaging model in all major rat brain structures. As incorrectly assuming additive Gaussian noise on the diffusion-weighted data will result in an overestimated degree of non-Gaussian diffusion and a b-value-dependent underestimation of diffusivity measures, a Rician noise model was used in this study. Magn Reson Med 65:138-145, 2011. (c) 2010 Wiley-Liss, Inc

Diffusion tensor imaging in a rat model of Parkinson's disease after lesioning of the nigrostriatal tract

Parkinson's disease (PD) is characterised by degeneration of the nigrostrial connection causing dramatic changes in the dopaminergic pathway underlying clinical pathology. Till now, no MRI tools were available to follow up any specific PD-related neurodegeneration. However, recently, diffusion tensor imaging (DTI) has received considerable attention as a new and potential in vivo diagnostic tool for various neurodegenerative diseases. To assess this in PD, we performed DTI in the acute 6-hydroxydopamine (6-OHDA) rat model of PD to evaluate diffusion properties in the degenerating nigrostriatal pathway and its connecting structures. Injection of a neurotoxin in the striatum causes retrograde neurodegeneration of the nigrostriatal tract, and selective degeneration of nigral neurons. The advantage of this model is that the lesion size is well controllable by the injected dose of the toxin. The degree of functional impairment was evaluated in vivo using the amphetamine rotation test and microPET imaging of the dopamine transporter (DAT). Despite a nearly complete lesion of the nigrostriatal tract, DTI changes were limited to the ipsilateral substantia nigra (SN). In this study we demonstrate, using voxel-based statistics (VBS), an increase in fractional anisotropy (FA), whereas all eigenvalues were significantly decreased. VBS enabled us to visualise neurodegeneration of a cluster of neurons but failed to detect degeneration of more diffuse microstructures such as the nigrostriatal fibres or the dopaminergic endings in the striatum. VBS without a priori information proved to be better than manual segmentation of brain structures as it does not suffer from volume averaging and is not susceptible to erroneous segmentations of brain regions that show very little contrast on MRI images such as SN.status: publishe