Stress field within biological tissues from multiparametric Magnetic Resonance Imaging

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Biological tissues remodeling is largely due to the mechanical stresses withstood by the cells. In many diseases, tissue mechanical damage is associated to a perturbed mechanical stress distribution that triggers biological changes. These biological changes produce structural changes that in turn modify the mechanical properties and stress distribution, resulting in a "vicious cycle". I believe that the evaluation of the mechanical stresses within biological tissues is a cornerstone in understanding of fundamental processes in humans and would enable defining new strategies to break this "vicious cycle". The long-term objective of my research program is to provide new diagnostic imaging and modeling technologies for the robust in vivo mechanical stresses evaluation within musculoskeletal or cardiac tissues for further prediction of human tissues degradation and regeneration.***The short-term objectives are 1) the development of algorithms to measure tissue strain maps from velocity encoded in phase MRI images and wave propagation in the heart and intervertebral discs; 2) the comprehensive anisotropy evolution quantification during heart failure and intervertebral disc degeneration from MRI diffusion imaging; 3) the development of new algorithms to infer mechanical stresses from inverse materials parameters identification strategies.***The robust mechanical stress estimation is of growing interest for 1) biomedical researchers developing mathematical models for which validation is purely geometrical, due to lack of in vivo mechanical stresses data; and 2) mechanical researchers developing solutions to the inverse problem of mechanical properties identification from displacements for hyperelastic or viscoelastic materials. The early detection of subtle mechanical changes within biological tissues with the proposed diagnostic imaging and modeling technologies is of growing interest for the clinicians to anticipate pathology progression and provide early damage biomarkers. This knowledge transfer to pediatric orthopaedists, cardiologists and oncologists should pave the way for longitudinal studies assessing many disease conditions. There is a potential for future commercial application by generating automated diagnostic algorithms applicable in medical imaging equipment that would initiate an important technology transfer to industry.**