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Updated: Jan 20, 2026

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Inter-Individual Differences in T1, T2, and Proton Density Using Quantitative Synthetic Imaging for 1H-MRS
Samantha A Leech1,2,3,4, Sarah L Manske2, Paul G Mullins5
1Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada.
Purpose:
Metabolite concentrations can be determined from proton magnetic resonance spectroscopy (1H-MRS) data using water as an internal reference. This calculation requires tissue-specific water T1 and T2 relaxation constants and proton density (PD). Although literature values are commonly used, these vary with age and within clinical conditions, potentially introducing variability or masking metabolite effects. The introduction of rapid multi-dynamic multi-echo (MDME) imaging to generate multiparametric maps allows fast measurement of these parameters for each individual within a single acquisition.
Methods:
1H-MRS and MDME data were collected from 26 healthy volunteers (aged 18-40 years). The agreement between metabolite concentrations derived using individually measured T1, T2 and PD values and literature-based values was assessed. A sensitivity analysis was also used to determine the impact of extended value ranges on metabolite concentrations.
Results:
Using a MDME sequence to determine individually measured T1, T2, and PD values for tissue correction was successful. Strong agreement between metabolite concentrations calculated using literature and measured values was seen, although concentrations calculated using literature values tended to be slightly higher than when using measured values. The sensitivity analysis showed T1 relaxation contributed most strongly to the calculated concentration variability.
Conclusion:
This study demonstrates the feasibility of using a MDME acquisition to acquire individual- specific parameter values for tissue correction. This provides a fast, effective method to acquire individual relaxation parameters, which will be highly relevant for populations where these parameters will vary (such as the elderly, pediatrics or with clinical diagnoses).
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