Concentration and effective T2 relaxation times of macromolecules at 3T

• Published in: Magnetic resonance in medicine Vol. 84; no. 5; pp. 2327 - 2337
• Main Authors: Landheer, Karl, Gajdošík, Martin, Treacy, Michael, Juchem, Christoph
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 01.11.2020
• Subjects: Cortex (frontal); Gender; Learning algorithms; Machine learning; Macromolecules; magnetic resonance spectroscopy; Metabolites; Occipital lobe; Optimization; Relaxation time; short TE; sLASER
• ISSN: 0740-3194; 1522-2594; 1522-2594
• DOI: 10.1002/mrm.28282

Purpose We aimed to investigate the concentration and effective T2 relaxation time of macromolecules assessed with an ultra‐short TE sLASER sequence in 2 brain regions, the occipital and frontal cortex, in both genders at 3T. Methods An optimized sLASER sequence was used in conjunction with a double‐inversion preparation module to null the metabolites. Eight equally spaced TEs were chosen from 20.1 to 62.1 ms, and the macromolecules were modeled by 10 line broadened singlets. The amplitude of each of the macromolecule signals was extracted at each TE and fit to a monoexponential function to extract the respective effective T2 values. Absolute quantification of the macromolecule resonances was performed using water signal as a reference. A total of 10 young healthy adult subjects (5 females) were scanned, with spectra being obtained from both the frontal and occipital cortex. Differences in the effective T2 relaxation times and concentrations were investigated between both regions and genders. Results A wide disparity was observed between the effective T2 values of the individual resonances; however, no significant differences between gender or region for any of the measured macromolecule concentration or effective T2 values were found. Conclusion The effective T2 relaxation times and concentration of 10 different macromolecule resonances were measured and found to be well represented by the monoexponential model. These results will be useful for absolute quantification of macromolecules in future studies, or in the generation of synthetic basis sets for optimization or machine learning.