Age-dependent macromolecule signals in the human motor cortex and thalamus: implications for metabolites
Xinyu Liu1,2, Gianna Nossa2,3,4, Ying Xiao1,2
1Laboratory for functional and metabolic imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Objective:
Macromolecular (MM) signals overlap with metabolite signals, but MM content differences across age and brain region and their influences on brain metabolites quantification have remained elusive. While most studies assume universal MM content when assessing neurochemical levels, region- and age-related MM differences could result in inaccurate quantification of metabolites. This study assesses MM differences linked to specific brain regions and age by analyzing their influence on metabolite signal quantification in the primary motor cortex (M1) and thalamus.
Materials And Methods:
We created age- and region-specific MM basis sets measured using an inversion-recovery protocol at 7 T. In addition, we acquired short echo time (TE) spectra from M1 and thalamus in a separate cohort, and differences in the metabolite quantification results that arose from using age- or region-matched and unmatched basis sets were evaluated. Comparisons were made between a young group (22-34 years) and an elderly group (64-79 years) and across M1 or thalamus.
Results:
We found significant differences in metabolite signals when using basis sets created from matched versus unmatched macromolecule spectra by age or region. Specifically, in M1, substituting the alternate same-region basis set significantly changed 7/12 metabolite signals in elderly spectra and 6/12 in young spectra. The effect was more evident when fitting young thalamic spectra with the elderly thalamic basis, where 11/12 metabolites signals changed. When the thalamic MM basis set was applied to M1 spectra, 11/12 metabolites signals shifted significantly in the young-M1 and 7/12 in the elderly-M1.
Discussion:
Our study demonstrated the importance of age-specific and region-specific MM basis sets for accurate metabolite quantification.


