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Determination of Brain Metabolite T 1 Without Interference From Macromolecule Relaxation
Author(s) -
An Li,
Araneta Maria Ferraris,
Victorino Milalynn,
Shen Jun
Publication year - 2020
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.27259
Subject(s) - metabolite , cramér–rao bound , macromolecule , nuclear magnetic resonance , glutamine , chemistry , relaxation (psychology) , analytical chemistry (journal) , medicine , biochemistry , chromatography , algorithm , physics , amino acid , mathematics , estimation theory
Background J‐coupled metabolites are often measured at a predetermined echo time in the presence of macromolecule signals, which complicates the measurement of metabolite T 1 . Purpose To evaluate the feasibility and benefits of measuring metabolite T 1 relaxation times without changing the overlapping macromolecule baseline signals. Study Type Prospective. Subjects Five healthy volunteers (three females and two males; age = 27 ± 7 years). Field Strength/Sequence 7T scanner using a point resolved spectroscopy (PRESS)‐based spectral editing MR spectroscopy (MRS) sequence with inversion recovery (IR). Assessment F‐tests were performed to evaluate if the new approach, which fitted all the spectra together and used the same baselines for the three different IR settings, significantly reduced the variances of the metabolite T 1 values compared to a conventional fitting approach. Statistical Tests Cramer–Rao lower bound (CRLB), within‐subject coefficient of variation, and F‐test. Results The T 1 relaxation times of N‐acetylaspartate (NAA), total creatine (tCr), total choline (tCho), myo‐inositol (mI), and glutamate (Glu) were determined with CRLB values below 6%. Glutamine (Gln) T 1 was determined with a 17% CRLB, and the T 1 of γ‐aminobutyric acid (GABA) was determined with a 34% CRLB. The new approach significantly reduced the variances (F‐test P < 0.05) of NAA, Glu, Gln, tCr, tCho, and mI T 1 s compared to the conventional approach. Data Conclusion Keeping macromolecule signals intact by using only long IR times allowed the use of a single macromolecule spectral model for different IR settings and significantly reduced the variances of NAA, Glu, Gln, tCr, tCho, and mI T 1 s. Level of Evidence 1 Technical Efficacy Stage 1