Local and Interregional Neurochemical Associations Measured by Magnetic Resonance Spectroscopy for Studying Brain Functions and Psychiatric Disorders

Shen, Jun; Shenkar, Dina; Liu, An; Tomar, Jyoti

doi:10.3389/fpsyt.2020.00802

Cited by 5 publications

(3 citation statements)

References 135 publications

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“…The results of this study indicate that metabolite concentrations measured by short‐TE MRS are in general correlated in a significant and complex way. These results underscore the importance of continuing to develop spectral editing and/or high magnetic field MRS techniques 24–30 in order to spectrally isolate signals of interest such that the signals of interest are free from the undesirable correlations with other metabolites, MM, and the background baseline. Although spectral editing of certain metabolites is difficult or impossible, de facto statistical independence in the presence of severe spectral overlap may also be achievable by altering the spectral pattern for the purpose of minimizing the undesirable correlations.…”

Section: Discussionmentioning

confidence: 92%

Neurochemical correlations in short echo time proton magnetic resonance spectroscopy

Hong

Shen

2023

NMR in Biomedicine

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Neurochemical concentrations determined by magnetic resonance spectroscopy (MRS) have been treated as statistically independent measurements in various clinical MRS studies. However, spectral overlap, independent of any biological effects, could lead to significant correlations between neurochemical concentrations extracted from spectral fitting of MRS data, confounding determination of correlations of biological origin. Short echo time (TE) proton MRS spectra are very crowded because of the comparatively narrow chemical shift dispersion of proton nuclear spins. In this study, the complex neurochemical correlations of spectral origin in short‐TE MRS spectra were quantified. The effects of macromolecules and the background spectral baseline on metabolite–metabolite correlations were also analyzed. Our results demonstrate the importance of factoring in spectral correlations when correlating overlapping metabolite signals in short‐TE spectra with clinical parameters.

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Section: Discussionmentioning

confidence: 92%

Neurochemical correlations in short echo time proton magnetic resonance spectroscopy

Hong

Shen

2023

NMR in Biomedicine

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“…Although 7 T magnets have become more widely available for research, the majority of MRI systems use 3 T for neuroimaging applications at present. At 1.5 T magnetic field strength, the ability to distinguish metabolites is particularly challenging due to the poorer separation of resonances in the spectra than at 3 or 7 T. This condensed spectrum can lead to overlaps in peaks, which can result in miscalculation of metabolite concentration (60). Most notably, the standard LCModel method of analysis (see section A Model for Changes in MRS Measured Glutamate, GABA, and Glutamine Levels During the Progression of ALS) depends on both separation of metabolites with resonances that overlap as separation of metabolites from broad baseline resonances of macromolecules.…”

Section: Pulse Sequence and Magnetic Field Strength Methodologymentioning

confidence: 99%

1H Magnetic Resonance Spectroscopy to Understand the Biological Basis of ALS, Diagnose Patients Earlier, and Monitor Disease Progression

Caldwell

Rothman

2021

Front. Neurol.

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At present, limited biomarkers exist to reliably understand, diagnose, and monitor the progression of amyotrophic lateral sclerosis (ALS), a fatal neurological disease characterized by motor neuron death. Standard MRI technology can only be used to exclude a diagnosis of ALS, but 1H-MRS technology, which measures neurochemical composition, may provide the unique ability to reveal biomarkers that are specific to ALS and sensitive enough to diagnose patients at early stages in disease progression. In this review, we present a summary of current theories of how mitochondrial energetics and an altered glutamate/GABA neurotransmitter flux balance play a role in the pathogenesis of ALS. The theories are synthesized into a model that predicts how pathogenesis impacts glutamate and GABA concentrations. When compared with the results of all MRS studies published to date that measure the absolute concentrations of these neurochemicals in ALS patients, results were variable. However, when normalized for neuronal volume using the MRS biomarker N-acetyl aspartate (NAA), there is clear evidence for an elevation of neuronal glutamate in nine out of thirteen studies reviewed, an observation consistent with the predictions of the model of increased activity of glutamatergic neurons and excitotoxicity. We propose that this increase in neuronal glutamate concentration, in combination with decreased neuronal volume, is specific to the pathology of ALS. In addition, when normalized to glutamate levels, there is clear evidence for a decrease in neuronal GABA in three out of four possible studies reviewed, a finding consistent with a loss of inhibitory regulation contributing to excessive neuronal excitability. The combination of a decreased GABA/Glx ratio with an elevated Glx/NAA ratio may enhance the specificity for 1H-MRS detection of ALS and ability to monitor glutamatergic and GABAergic targeted therapeutics. Additional longitudinal studies calculating the exact value of these ratios are needed to test these hypotheses and understand how ratios may change over the course of disease progression. Proposed modifications to the experimental design of the reviewed 1H MRS studies may also increase the sensitivity of the technology to changes in these neurochemicals, particularly in early stages of disease progression.

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“…In the clinical 31 P MRS literature, concentrations of 31 P-contaning metabolites measured by 31 P MRS have been treated as statistically independent variables in their correlations with clinical metrics. However, spectral overlap can present as an intervening variable that may unfortunately reduce the likelihood of the intended statistical precision and extrapolation of the clinical findings under investigation, unless correlations of metabolites can be parsed correctly [ 13 , 14 ]. When two peaks of the same polarity overlap each other, overdetermination (underdetermination) of one peak is correlated with the underdetermination (overdetermination) of the other, leading to a negative correlation between the two signals [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Magnetic Field Dependence of Spectral Correlations between 31P-Containing Metabolites in Brain

Hong

Shen

2023

Metabolites

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Spectral correlations between metabolites in 31P magnetic resonance spectroscopy (MRS) spectra of human brain were compared at 3 and 7 Tesla, the two commonly used magnetic field strengths for clinical research. It was found that at both field strengths, there are significant correlations between 31P-containing metabolites arising from spectral overlap, and their downfield correlations are markedly altered by the background spectral baseline. Overall, the spectral correlations between 31P-containing metabolites are markedly reduced at 7 Tesla with the increased chemical shift dispersion and the decreased membrane phospholipid signal. The findings provide the quantitative landscape of pre-existing correlations in 31P MRS spectra due to overlapping signals. Detailed procedures for quantifying the pre-existing correlations between 31P-containing metabolites are presented to facilitate incorporation of spectral correlations into statistical modeling in clinical correlation studies.

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Local and Interregional Neurochemical Associations Measured by Magnetic Resonance Spectroscopy for Studying Brain Functions and Psychiatric Disorders

Cited by 5 publications

References 135 publications

Neurochemical correlations in short echo time proton magnetic resonance spectroscopy

Neurochemical correlations in short echo time proton magnetic resonance spectroscopy

1H Magnetic Resonance Spectroscopy to Understand the Biological Basis of ALS, Diagnose Patients Earlier, and Monitor Disease Progression

Magnetic Field Dependence of Spectral Correlations between 31P-Containing Metabolites in Brain

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