Abstract:
Non-uniform muscle deformation has become a frequent finding in biomechanics research, using imaging modalities operating at different resolution levels from sarcom eres to fascicles. Mainly due to technical limitations, interpretations of these findings are detached from a theoretical foundation that considers the muscle with mechanical links to its surrounding. To enable this vital consideration, this thesis aims at devel oping and testing the validity of a multimodal MRI method that bridges the under standing between non-uniform mechanical deformations and their myofascial origins, in-vivo. 1) Supplemented with DTI tractography, registration-based fiber direction deformations and principal strains on NVTs characterized the myofascial loads in re lation to the strain heterogeneity pattern in active muscle (proximally shortened (up to 22%), distally lengthened (up to 108%) fascicles). Inter-subject deviations from the general pattern were in agreement with subject specific anatomy. 2) A multiverse analysis was performed on the tuning parameters of the demons registration algorithm to assess the validity of strain distribution pattern against algorithmic choices. Results showed that the overall deformation pattern was immune to such perturbations, yet the strains amplitudes underwent significant changes. 3) To add orthogonal information to the myofascial origin assessment and validation of strain distributions, quantitative and velocimetry MRI were used. T1 mapping showed promising results in associating microstructural content with the strain distribution pattern. SR patterns from 2D VE PC showed weak similarities with registration-based principal strains, whereas those from compressed sensing 4D-PC showed much better agreement. Collectively, these studies show a way forward for the understanding of in-vivo muscle structure function relationship with implications for muscle physiology in health and disease. NOTE Keywords : Magnetic Resonance Imaging (MRI); Diffusion Tensor Imaging (DTI); Myofascial loads; quantitative MRI; Velocimetry; Validation.
