The principal aim of this thesis was to investigate human brain energy metabolism during physiological activation using proton (1H) magnetic resonance spectroscopy (MRS) at 7 Tesla (T). High magnetic fields (≥ 7 T) provide several advantages in human brain imaging and spectroscopy. In particular, signal-to-noise ratio (SNR) and chemical shift dispersion increase at higher magnetic fields, allowing for improved accuracy and precision of metabolite quantification. To take profit of the benefits of MRS at high field, one needs to provide an advanced methodology including hardware, pulse sequences experimental setup and data analysis. Each of these aspects was thoroughly explored in this thesis. In the field of functional studies, functional MRS (fMRS) has recently been used as a research tool to investigate the neuroenergetic and metabolic basis of physiologic brain activation. It provides direct insight into brain metabolism by non-invasively determining concentrations of metabolites. This is critical for the basic understanding of overall brain function, and potentially of the pathogenesis of many neurodegenerative diseases. In general, an optimized MR system and accurate acquisition methodology are required for high sensitivity and reliable metabolite quantification. The metabolites of interest for fMRS studies (e.g. lactate, glucose) are present in low concentration and metabolite changes are small under activation. Hence, studies of metabolite changes, in particular lactate, have led to inconsistent reports in the literature over the last decades. To address these challenges, it was essential to develop a robust MR protocol for the quantitative measurement of metabolite changes. A fMRS study was performed to investigate metabolite changes during visual stimulation using the enhanced sensitivity of the SPin ECho full Intensity Acquired Localized (SPECIAL) sequence. Small but significant increases of lactate (19 ± 4 %, P < 0.05) and glutamate (4 ± 1 %, P < 0.001) were observed using a small number of subjects (n = 6). With the exception of glucose (12 ± 5 %, P < 0.001), no other significant metabolite concentration changes beyond experimental error were observed. Based on this successful fMRS study, we further investigated brain energy metabolism. A subsequent fMRS study was performed to determine metabolite changes occurring during motor activation in the human brain. This second study demonstrated that increases in lactate (17 ± 5 %, P < 0.001) and glutamate (2 ± 1 %, P < 0.005) during motor stimulation were small, but similar to those observed during visual stimulation. These metabolite changes were further analyzed, and they supported the hypothesis of an increase in the change of cerebral metabolic rate of oxygen, ∆CMRO2, that is transiently lower than that of glucose, ∆CMRGlc, during the first one to two minutes of stimulation. Finally, we hypothesized that the observed glutamate and lactate increases were a general manifestation of the blood-oxygenation level dependent effect. The accuracy and the reliability of metabolite quantification is particularly challenging at short echo times due to the presence of broad underlying resonances overlapping with those of metabolite. Such resonances arise from macromolecules, which are characterized by short T1 and T2 relaxation times. Two studies were performed at 3 T and 7 T to investigate the characteristics of the macromolecule signal. An important finding was that the mathematical approximation (spline baseline) was a sufficient estimation of the macromolecule contribution to 1H spectra at 3 T compared to the experimentally measured macromolecule signal for healthy subjects. As a caveat, small, but significant, differences in the quantification may need to be taken into account when comparing metabolite concentrations obtained with these two different approaches, such as for glutamate and for γ-amino-butyric, which were more reliably quantified when using the measured macromolecule baseline. In addition, a study on the tissue-specificity of the macromolecule signal in the healthy human occipital lobe at 7 T reported that a general average macromolecule signal ensured reliable metabolite quantification. In general, these studies helped to set up a robust and reliable methodology in order to investigate human brain metabolism with improved accuracy. Despite their great potential for MRS, high main magnetic fields also compose challenges. In particular, the wavelength of the proton spin resonance becomes comparable to the size of a human head (at 7 T, λ = 11 cm). The phase variation across the brain produces signal addition (constructive interference, central bright spot) and signal cancellation (destructive interference, signal drop). Transceive arrays have been developed to address this issue. In this study, we designed, tested, and built an eight-channel transceive array, which was used to acquire images of the human head at 7 T (297 MHz). The design aimed for a low mutual coupling between the microstrip elements (> -15 dB), a relatively large penetration depth in the loading sample, reduced radiation losses and load-invariant tuning and matching. Electromagnetic simulations were run using Microwave Studio (CST, Darmstadt, Germany) for design optimization. The model was further demonstrated with the construction of the transceive array. Finally, the resulting array coil was shown to be handling, stable and also suited for techniques in which the transmission signals from all channels with different amplitudes and phases are combined. To conclude, this thesis provided complementary and new metabolic information about cerebral energy metabolism during physiological activation. Furthermore, the macromolecule studies and the building of the transceive array allowed to improve the accuracy and sensitivity of NMR measurements.
EPFL2013
