Normal aging is associated with neuro-axonal changes reflected by metabolic and volumetric changes. The aim of this cross-sectional study was to investigate the influence of aging on the neural network system by quantifying the whole-brain N-acetylaspartate (WBNAA) concentration (which reflects neuronal health and density) and brain volume.
METHOD AND MATERIALS
Proton density and T2-weighted FSE (TE1/TE2/TR: 16/80/2500 ms) MRI were performed in 81 healthy controls (35 male, 46 female) of mean age 39 (range: 16-86) years. A non-localizing, non-echo, proton MR spectroscopy (1H-MRS) followed to obtain the whole head NAA signal. This was converted into an absolute level using phantom-replacement with a reference 3 L sphere of 15 millimoles NAA in water. To account for inter individual variations in head size, the absolute NAA amount was divided by the brain volume,obtained with the 3DVIEWNIX software package, and each brain volume was expressed as its percent of the total intracranial volume (PBV). Least square regression was used to examine the functional nature of the relationships between WBNAA, PBV and age, adjusting for differences between genders
The average level and the annual, cross-sectional rate of change of WBNAA exhibited age-dependence (p<0.045) without gender differences, increasing with age from 11.4 mM at age 16 to 12.6 mM at age 50 with a subsequent decline at an increasing rate, reaching 11.4 again at age 80. PBV exhibited a significant continuous cross-sectional decline with age (p<0.018) without gender differences. The average PBV was 88% at age 16, 85% at age 50 and 76% at age 80.
WBNAA and atrophy both provide in vivo, non-invasive information about the dynamics of normal brain aging, with the latter reflecting tissue loss and the former indicating the quality of the remaining tissue. The gradual increase of WBNAA suggests a continual remodeling of neurons and neuropil which reach the maximum level at age 50. Obtaining both enables to distinguish and quantify age-related structural and metabolic brain tissue changes, important in detecting and monitoring abnormal changes in subjects at risk to develop degenerative diseases.