GABA, glutamate and excitatory-inhibitory ratios measured using short-TE STEAM MRS at 7-Tesla: Effects of macromolecule basis sets and baseline parameters

Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured...

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Published inHeliyon Vol. 9; no. 7; p. e18357
Main Authors Okada, Tomohisa, Kuribayashi, Hideto, Urushibata, Yuta, Fujimoto, Koji, Akasaka, Thai, Seethamraju, Ravi Teja, Ahn, Sinyeob, Isa, Tadashi
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 01.07.2023
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Abstract Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated. Twenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV). CRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2–3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR. Neurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.
AbstractList Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated. Twenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV). CRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2–3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR. Neurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.
Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated.Rationale and objectivesMacromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated.Twenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV).Materials and methodsTwenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV).CRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2-3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR.ResultsCRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2-3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR.Neurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.ConclusionNeurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.
Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated. Twenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV). CRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2–3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR. Neurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.
Rationale and objectives: Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated. Materials and methods: Twenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV). Results: CRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2–3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR. Conclusion: Neurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.
ArticleNumber e18357
Author Kuribayashi, Hideto
Okada, Tomohisa
Akasaka, Thai
Seethamraju, Ravi Teja
Urushibata, Yuta
Fujimoto, Koji
Isa, Tadashi
Ahn, Sinyeob
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Issue 7
Keywords Magnetic resonance spectroscopy
7-Tesla
Gamma-aminobutyric acid
Excitatory-inhibitory ratio
Glutamate
Stimulated echo acquisition mode
Language English
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2023 Published by Elsevier Ltd.
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Snippet Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly...
Rationale and objectives: Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured...
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StartPage e18357
SubjectTerms 7-Tesla
Excitatory-inhibitory ratio
Gamma-aminobutyric acid
Glutamate
glutamic acid
Magnetic resonance spectroscopy
magnetism
spectroscopy
Stimulated echo acquisition mode
Title GABA, glutamate and excitatory-inhibitory ratios measured using short-TE STEAM MRS at 7-Tesla: Effects of macromolecule basis sets and baseline parameters
URI https://dx.doi.org/10.1016/j.heliyon.2023.e18357
https://www.ncbi.nlm.nih.gov/pubmed/37539101
https://www.proquest.com/docview/2846928388
https://www.proquest.com/docview/3153737291
https://pubmed.ncbi.nlm.nih.gov/PMC10393741
https://doaj.org/article/5e5e2f7cc89944faa51a11cfa09bf9f7
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