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Updated: May 3, 2026
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Multiparametric Aging Study Across Adulthood in the Leg Through Quantitative MR Imaging, 1H Spectroscopy, and 31P
Alfredo L Lopez Kolkovsky1, Beatrice Matot1, Pierre-Yves Baudin1
1NMR Laboratory, Neuromuscular Investigation Center, Institute of Myology, Paris, France.
Background:
Improved characterization of healthy muscle aging is needed to establish early biomarkers in age-related diseases.
Purpose:
To quantify age-related changes on multiple MRI and clinical variables evaluated in the same cohort and identify correlations among them.
Study Type:
Prospective.
Population:
70 healthy subjects (30 men) from 20 to 81 years old.
Field Strength/Sequence:
3T/water T2 (multiecho SE, multi-TE STEAM), water T1 (GRE MR Fingerprinting), fat-fraction (multiecho GRE, multi-TE STEAM), carnosine (PRESS), multicomponent water T2 (ISIS-CPMG SE train), and 31P pulse-acquire spectroscopy.
Assessment:
Age- and sex-related changes on: Imaging: fat-fraction (FFMRI), water T1 (T1-H2O), and T2 (T2-H2O-MRI) and their heterogeneities ΔT1-H2O and ΔT2-H2O-MRI in the posterior compartment (PC) and anterior compartment (AC) of the leg. 1H spectroscopy: Carnosine concentration, pH, water T2 components (T2-H2O-CPMG), fat-fraction (FFMRS), and water T2 (T2-H2O-MRS) in the gastrocnemius medialis. 31P spectroscopy: Phosphodiesters (PDE), phosphomonoesters, inorganic phosphates (Pi), and phosphocreatine (PCr) normalized to adenosine triphosphate (ATP) and pH in the calf. Clinical evaluation: Body-mass index (BMI), gait speed (GS), plantar flexion strength, handgrip strength (HS), HS normalized to wrist circumference (HSnorm), physical activity assessment.
Statistical Tests:
Multilinear regressions with sex and age as fixed factors. Spearman correlations calculated between variables. Benjamini-Hochberg procedure for false positives reduction (5% rate). A P < 0.05 significance level was used.
Results:
Significant age-related increases were found for BMI (ρAge = 0.04), HSnorm (ρAge = -0.01), PDE/ATP (ρAge = 2.8 × 10-3), Pi/ATP (ρAge = 2.0 × 10-3), Pi/PCr (ρAge = 0.3 × 10-3), T2-H2O-MRS (ρAge = 0.051 msec), FFMRS (ρAge = 0.036) the intermediate T2-H2O-CPMG component time (ρAge = 0.112 msec), and fraction (ρAge = -0.3 × 10-3); and in both compartments for FFMRI (ρAge = 0.06, PC; ρAge = 0.06, AC), T2-H2O-MRI (ρAge = 0.05, PC; ρAge = 0.05, AC; msec), ΔT2-H2O-MRI (ρAge = 0.02, PC; ρAge = 0.02, AC; msec), T1-H2O (ρAge = 1.08, PC; ρAge = 1.06, AC; msec), and ΔT1-H2O (ρAge = 0.22, PC; ρAge = 0.37, AC; msec). The best age predictors, accounting for sex-related differences, were HSnorm (R2 = 0.52) and PDE/ATP (R2 = 0.44). In both leg compartments, the imaging measures and HSnorm were intercorrelated. In PC, T2-H2O-MRS and FFMRS also showed numerous correlations to the imaging measures. PDE/ATP correlated to T1-H2O, T2-H2O-MRI, ΔT2-H2O-MRI, FFMRI, FFMRS, the intermediate T2-H2O-CPMG, BMI, Pi/PCr, and HSnorm.
Data Conclusion:
Our multiparametric MRI approach provided an integrative view of age-related changes in the leg and revealed multiple correlations between these parameters and the normalized HS.
Level Of Evidence:
1 TECHNICAL EFFICACY: Stage 3.
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