Saipavitra Murali-Manohar, Helge J. Zöllner, Kathleen E. Hupfeld, Yulu Song, Emily E. Carter, Vivek Yedavalli, Steve C. N. Hui, Dunja Simicic, Aaron T. Gudmundson, Gizeaddis Lamesgin Simegn, Christopher W. Davies-Jenkins, Georg Oeltzschner, Eric C. Porges, Richard A. E. Edden
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引用次数: 0
Abstract
Purpose
To measure T1 relaxation times of metabolites at 3 T in a healthy aging population and investigate age dependence.
Methods
A cohort of 101 healthy adults was recruited with approximately 10 male and 10 female participants in each “decade” band: 18 to 29, 30 to 39, 40 to 49, 50 to 59, and 60+ years old. Inversion-recovery PRESS data (TE/TR: 30/2000 ms) were acquired at 8 inversion times (TIs) (300, 400, 511, 637, 780, 947, 1148, and 1400 ms) from voxels in white-matter-rich centrum semiovale (CSO) and gray-matter-rich posterior cingulate cortex (PCC). Modeling of TI-series spectra was performed in Osprey 2.5.0. Quantified metabolite amplitudes for total N-acetylaspartate (tNAA2.0), total creatine at 3.0 ppm (tCr3.0), and 3.9 ppm (tCr3.9), total choline (tCho), myo-inositol (mI), and the sum of glutamine and glutamate (Glx) were modeled to calculate T1 relaxation times of metabolites.
Results
T1 relaxation times of tNAA2.0 in CSO and tNAA2.0, tCr3.0, mI, and Glx in PCC decreased with age. These correlations remained significant when controlling for cortical atrophy. T1 relaxation times were significantly different between PCC and CSO for all metabolites except tCr3.0. We also propose linear models for predicting metabolite T1s at 3 T to be used in future aging studies.
Conclusion
Metabolite T1 relaxation times change significantly with age, an effect that will be important to consider for accurate quantitative MRS, particularly in studies of aging.
期刊介绍:
Magnetic Resonance in Medicine (Magn Reson Med) is an international journal devoted to the publication of original investigations concerned with all aspects of the development and use of nuclear magnetic resonance and electron paramagnetic resonance techniques for medical applications. Reports of original investigations in the areas of mathematics, computing, engineering, physics, biophysics, chemistry, biochemistry, and physiology directly relevant to magnetic resonance will be accepted, as well as methodology-oriented clinical studies.