Infoscience

Thesis

Biophysical Basis of the Diffusion-Weighted Magnetic Resonance Signal in the Rat Brain

Nuclear magnetic resonance (NMR) can be used in-vivo in a vast array of applications, such as anatomical imaging (magnetic resonance imaging, MRI), localized chemical composition characterization (magnetic resonance spectroscopy, MRS), cellular structure assessment (diffusion tensor imaging, DTI) and cerebral activity mapping (functional imaging, fMRI) for the most important one. This thesis focused on the development of diffusion NMR spectroscopy and imaging methods at ultra-high magnetic field, with the aim of a better characterization of the diffusion mechanism in-vivo. DTI measures the water molecule displacement due to the thermal agitation in the sample. In cellular tissue, the molecules are restrained in compartments delimited by the cell membranes, which mean that DTI can provide information on the cerebral cellular microstructure. DTI is thus widely used to investigate cerebral disorders such as brain ischemia, trauma, and tumors, as well as the structural changes occurring during brain development and normal aging. However, the presence of water molecules in both the intra- and extra-cellular compartments may bias the assessed structural information. On the other hand, the metabolites, measured by 1H-MRS, are mostly localized in the intracellular compartment, which may provide a more precise insight of the cellular structure. With the availability of high magnetic field systems, 1H-MRS allows the measurement of 15 – 20 metabolites in-vivo in localized region in the order of &icro;l in the rodent brain. These metabolites are involved in cell energy management, neurotransmission, neuro-protection, neuronal development and membrane growth, and thus provide a rather complete status of the brain neurochemical profile. In this context, a diffusion tensor spectroscopy pulse sequence (DT-MRS) was implemented and used to investigate the metabolite diffusion properties in specific brain regions in-vivo at ultra-high magnetic field 14.1 T to benefit from the increased sensitivity and spectral resolution at high B0. The diffusion tensor of 5 metabolites were reconstructed in the corpus-callosum, CC, (NAA, Tau, Glu, Ins and Mac) and 8 in the cortex, Cx, (with in addition Cr, PCr, GABA and GSH). Metabolites apparent diffusion coefficients were significantly higher in the CC (0.115 – 0.153 µm2/ms) than in the Cx (0.087 – 0.107 µm2/ms) and so was the fractional anisotropy (0.51 – 0.62 and 0.34 – 0.51 respectively). In addition, the metabolite preferential diffusion directions showed an excellent agreement with the known rat brain structure. The aforementioned DW-MRS pulse sequence was then combined with an inversion recovery module, allowing direct assessment of the macromolecule (MM) signal, which overlaps with metabolites resonances. An inaccurate estimation of the MM baseline may result in a significant bias during the quantification process. At ultra-high magnetic field, the MM spectral shape becomes more complex, and therefore, the previously reported experimental techniques would require post-processing to remove residual metabolite signals. In this study, several metabolite contaminations remaining in the metabolite nulled spectrum were successfully identified and attributed to creatine, myo-inositol, taurine, choline, N-acetylaspartate, glutamine and glutamate. The macromolecule baseline assessed by DW-MRS resulted in a twofold reduction of the metabolite residuals with minimal effect on the macromolecule signal (i.e. < 8% signal reduction). Although at high magnetic field spectral resolution and sensitivity are improved, metabolite diffusion measurements remain very time consuming and challenging due to the low metabolite concentrations in-vivo (1 – 15 mM) compared to water (44 M). Therefore, a fast and robust EPI-based DTI pulse sequence was developed, implemented and validated to investigate the cerebral architecture in-vivo at 14.1 T through water diffusion. Combined with the use of a purpose-built quadrature surface coil and adiabatic RF-pulses, it resulted in images with a full coverage of the rat brain and a total acquisition time of one hour. The rapid signal loss arising from the use of a surface coil for the MRI acquisitions, which was previously in this thesis overcome experimentally, was also addressed in collaboration with the Signal Processing Core of CIBM, by a direct correction applied on reconstructed magnitude images. Based on a low-pass frequency mode; the developed method showed better accuracy in enhancing image intensity compared to standard approaches. In view of a future application of the presented diffusion NMR techniques, investigating structural changes during brain development, a study was performed to characterize different intra-uterine growth retardation (IUGR) models by 1H-MRS. Dexamethasone-treated animals (100 µg/kg/day induced from the day 15 of gestation) showed more severe alterations in cerebral energy metabolism and neurotransmitter action at postnatal day 7 and 21 than the reference IUGR model, caloric restriction (30% food intake of ad libitum fed dams from day 1 of gestation). In a continuation of the IUGR study, the exposure to the estrogen-like molecule (i.e. bisphenol-A, BPA), was investigated. Here, 1H-MRS showed a significant increase of the Glu/Asp ratio in the hippocampus of the BPA-treated group at 20 days old, indicating a possible deviation in the malate-aspartate shuttle. Finally, the diverse NMR techniques used and developed during this thesis have required the implementation of several data processing tools, which were centralized in a framework written in Matlab (Mathworks, Inc). Two principal modules were build: 1. to reconstruct DTI experiments data and 2. to facilitate and standardize the 1H-MRS spectra quantification by LCModel. The proposed NMR data processing framework was used to process most of the data presented in this thesis and has demonstrated good performance. In addition, this framework was tested and used by five external users to analyze for data-analysis in ongoing studies.

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