As a noninvasive method for measuring concentration and distribution of chemicals in the living brain MRS is an important tool for studying brain function and disorders. However, robust measurement of MRS signals requires highly sophisticated design, implementation and maintenance of various MRS techniques. MRS technology has been a very active research area, attracting major effort from top magnetic resonance research centers around the world. Clinical magnetic resonance imaging scanners optimized for performing structural and functional imaging studies also present daunting obstacles for MRS technical development. Most of the MRS protocols at NIH were developed and implemented by the MRS core under protocol no. 05-M-0144 (NCT# 00109174) and protocol no. 11-M-0045 (NCT# 01266577). 1) Correction of baseline in short echo time proton MRS. To capture the entire metabolic profile of brain visible to proton MRS, data acquisition at short echo time is needed. At the same time the broad macromolecule baseline was also acquired. The macromolecule baselien contributes to Cremer Rao Lower Bound of the metabolite signals. To accurately quantify this effect in clinical short echo time MRS we have recently developed a method for determining the smoothness of baseline based on mean squared error of the baseline, leading to more objective and reliable determinatin of metabolite signals (Zhang et al, Magn Reson Med, in press, 2014). 2) Automatic correction of magnetic field inhomogeneity. It is essential to optimize the homogeneity of magnetic field for all MRS experiments because field inhomogeneity can easily destroy the critical separation of different chemicals. More importantly, an inhomogeneous field makes effective suppression of tissue water signal difficult, therefore making reliable detection of more dilute chemicals impossible. This is particularly the case for anatomical regions of interest to psychiatric research. We have optimized an automatic shimming method based on fastmap which consistently out-performs the automatic shimming methods provided by MRI scanner manufacturers. It has already greatly improved the quality of clinical MRS data acquried at NIH. 3) Multislice chemcial shift imaging of NAA, creatine and choline-containing compounds. The MRS core maintains a chemical shift imaging techique for mapping distribution of the neuronal marker N-acetylaspartate at 3 Tesla. This method simultaneously generates images of N-acetylaspartate, creatine, and choline-containing compounds. 4) Glutathione detection. Glutathione is a marker for oxidative stress. Many psychiatric and neurological disoders (such as schizophrenia, Alzheimer's disease and stroke) are associated with abnormal glutathione levels. In collaboration with Steven Warach (NINDS) a glutathione editing method was developed on the Philip 3 Tesla scanner at the Suburban Hospital for studying stroke patients using adaptive linefitting. We have also developed a single-shot methdo for measuring glutathione at 7 Tesla. 5) Carbon-13 MRS. By using carbon-13 labeled glucose or the glial-specific substrate acetate, brain energetics and glutamate and glutamine cycling flux can be measured. Previously we invented a method for carbon-13 MRS by combining low power stochastic decoupling and intravenous infusion of glucose with a carbon-13 label at the C2 position. This strategy makes it possible to perform viable carbon-13 MRS on single channel clincial MRI scanners. Using this strategy, we have acquired high quality carbon-13 MRS data from both the occipital and frontal lobes of healthy subjects and showed that it is possible to simultaneously detect two labeling pathways in the human brain. Recently, we have succeeded in implementing this strategy on the 7 Tesla scanner with enhanced sensitivity and spectral resolution. In particular, we are the first to detect GABA turnover in the human brain. 6) Proton glutamate editing. Previously we implmented a single-voxel glutamate editing method with correction of eddy current effects for measuring glutamate concentration at 3 Tesla. Recently, we have developed a new glutamate editing method which needs a single echo time to isolate the glutamate H4 signal at 7 Tesla. 7) GABA editing. Previously we implemented and refined a method for measuring GABA. Similar to N-acetylaspartate imaging, patient movements can lead to difficulty in accurate determination of GABA. A navigator strategy based on residual water was used to track and correct for patient movement. Special data processing software was also developed to correct for phase changes because of patient motion. The improvements of the corrections have been quantified and applied to studies of human subjects. Currently, we are quantifying glutamate concentration using GABA-edited spectral data. Teh goal of this effort is to simultaneously measure both GABA and glutamate. 8) NAAG editing. We have successfully developed MRS methods for measuring the dipeptide neurotransmitter N-acetylaspartylglutamate (NAAG) which plays an important role in glutamate signaling. Our methods use regularized lineshape deconvolution based on the L-curve method and Wiener filtering to reliably measure NAAG.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Scientific Cores Intramural Research (ZIC)
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Li, Shizhe; An, Li; Yu, Shao et al. (2016) (13)C MRS of human brain at 7 Tesla using [2-(13)C]glucose infusion and low power broadband stochastic proton decoupling. Magn Reson Med 75:954-61
Zhang, Yan; Shen, Jun (2016) Simultaneous quantification of glutamate and glutamine by J-modulated spectroscopy at 3 Tesla. Magn Reson Med 76:725-32
Marenco, Stefano; Meyer, Christian; Kuo, Susan et al. (2016) Prefrontal GABA Levels Measured With Magnetic Resonance Spectroscopy in Patients With Psychosis and Unaffected Siblings. Am J Psychiatry 173:527-34
Lally, Níall; An, Li; Banerjee, Dipavo et al. (2016) Reliability of 7T (1) H-MRS measured human prefrontal cortex glutamate, glutamine, and glutathione signals using an adapted echo time optimized PRESS sequence: A between- and within-sessions investigation. J Magn Reson Imaging 43:88-98
Zhang, Yan; Shen, Jun (2015) Regional and tissue-specific differences in brain glutamate concentration measured by in vivo single voxel MRS. J Neurosci Methods 239:94-9
An, Li; Shen, Jun (2015) Image-guided spatial localization of heterogeneous compartments for magnetic resonance. Med Phys 42:5278-86
Preuss, Nora; Salehi, Basira; van der Veen, Jan Willem et al. (2013) Associations between prefrontal γ-aminobutyric acid concentration and the tryptophan hydroxylase isoform 2 gene, a panic disorder risk allele in women. Int J Neuropsychopharmacol 16:1707-17
Salehi, Basira; Preuss, Nora; van der Veen, Jan Willem et al. (2013) Age-modulated association between prefrontal NAA and the BDNF gene. Int J Neuropsychopharmacol 16:1185-93
Zhang, Yan; Shen, Jun (2013) Soft constraints in nonlinear spectral fitting with regularized lineshape deconvolution. Magn Reson Med 69:912-9
van der Veen, Jan Willem; Shen, Jun (2013) Regional difference in GABA levels between medial prefrontal and occipital cortices. J Magn Reson Imaging 38:745-50

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