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Wright, P., Mougin, O., Totman, J., Peters, A., Brookes, M., Coxon, R., Morris, P., Clemence, M., Francis, S., Bowtell, R. and Gowland, P. (2008) Water Proton T1 Measurements in Brain Tissue at 7, 3, and 1.5T Using IR-EPI, IR-TSE, and MPRAGE: Results and Optimization. Magnetic Resonance Materials in Physics, Biology and Medicine, 21, 121-130.

has been cited by the following article:

• TITLE: Assessment of Mechanical Properties of Muscles from Multi-Parametric Magnetic Resonance Imaging

  AUTHORS: Renaud Grenier, Delphine Périé, Guillaume Gilbert, Gilles Beaudoin, Daniel Curnier

  KEYWORDS: Muscles, Mechanical Properties, Multi-Parametric MRI, Multiple Regressions, Principal Component Analysis

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.7 No.8, June 26, 2014

  ABSTRACT: We hypothesized that a relationship existed between the mechanical properties and the magnetic resonance imaging (MRI) parameters of muscles, as already demonstrated in cartilaginous tissues. The aim was to develop an indirect evaluation tool of the mechanical properties of degenerated muscles. Leg and arm muscles of adult rabbits were dissected, and tested 12 hours post mortem, in a state of rigor mortis, or 72 hours post mortem, in a state of post-rigor mortis. The tests consisted of a multi-parametric MRI acquisition followed by a uniaxial tensile test until failure. The statistical analysis consisted of multiple linear regressions and principal component analysis. Significant differences existed between the rigor mortis and post-rigor mortis groups for E but not for the MRI parameters. 78%, 60% or 33% of the Young’s modulus could be explained by the MRI parameters in the post-rigor mortis group, rigor mortis group or both groups respectively. These relationships were confirmed by the principal component analysis. The proposed multi-parametric MRI protocol associated to principal component analysis is a promising tool for the indirect evaluation of muscle mechanical properties and should be useful to find biomarkers and predictive factors of the evolution of the pathologies.