GABA, glutamate and excitatory-inhibitory ratios measured using short-TE STEAM MRS at 7-Tesla: Effects of macromolecule basis sets and baseline parameters - Tomohisa Okada; Hideto Kuribayashi; Yuta Urushibata; Koji Fujimoto; Thai Akasaka; Ravi Teja Seethamraju; Sinyeob Ahn; Tadashi Isa (Heliyon, 2023)
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.