BME PhD Candidate Daniel Smith will be defending his dissertation:


Mechanical evaluation of structure and function in fibrous soft tissue using MR elastography


  • Location: BPI
  • Room #: 140B
  • Zoom Link:
  • Password: brains
  • Date: February 18th, 2022
  • Time: 11:30 a.m.
  • Committee: Curtis Johnson (Chair), Thomas Buchanan, Fabrizio Sergi, Jeremy Crenshaw


Human soft tissues are highly complex networks comprised of a variety of components that contribute to the overall functionality of the tissue, but these structures can be disrupted through injury or pathology, leading to tissue dysfunction. Magnetic resonance elastography (MRE) is a developing imaging technique that has shown promise in evaluating human soft tissues in-vivo by providing mechanical property estimates that are sensitive to structural changes in these tissues, including sensitivity to pathological changes. While MRE has proved to be an effective technique in much of human soft tissue, fibrous soft tissues, such as brain white matter and skeletal muscle, cause standard assumptions of mechanical isotropy to fail, resulting in data-model mismatches and inaccurate evaluations of tissue integrity and health. In this thesis, we propose to develop and test an MRE method to evaluate the health of fibrous soft tissues by evaluating structural and functional changes from pathology or injury.

The first part of work focuses on the assessing the viability of using a nearly incompressible, transversely isotropic (NITI) material model to accurately estimate the anisotropic material properties of human white matter. This NITI material model uses three independent material parameters to describe tissue response, but the definition of these parameters with MRE requires more information than is typically generated. To generate the necessary data, we utilize a technique called multi-excitation MRE, which uses multiple actuators to generate unique complex waveforms throughout the brain. Through analysis of these waveforms, we show that multiexcitation MRE provides sufficient information to estimate the NITI independent material parameters throughout white matter, ensuring repeatable and reliable parameters measures. Additionally, we estimate these parameters using the recently developed transversely isotropic, nonlinear inversion algorithm (TI-NLI) and combine multiexcitation MRE wave motion data and white matter fiber directions, as defined by diffusion tensor imaging (DTI) data. Using a population of healthy young subjects, we assess the parameter’s sensitivity to structural variances in white matter by quantifying the anisotropic parameters within individual white matter tracts across the population as well as  the heterogeneity within a single tract. By capturing this heterogeneity across WM, this technique indicates an ability to capture structural variances caused by other sources, including degradation from injury or pathology or recovery through applied therapies.

Although structural variations provide can provide significant information about soft tissue health, skeletal muscle has primarily been evaluated through functional measures of health, such as tissue loading. In the second half of this work, we aim to evaluate MRE’s capacity to measure functional outcomes like loading by capturing in-vivo estimates of skeletal muscle tension response and force production. Using multi-muscle MRE (MM-MRE), we provide in-vivo measurements of functional changes through three primary factors: correlation between combined muscle load and shear stiffness parameter outcomes; significant shear stiffness differences between muscles during agonist and antagonist actions; and variation of shear stiffness outcomes with different levels of initial loading due to muscle length. We then applied TI-NLI to skeletal muscle to quantify the anisotropic variations during passive muscle lengthening and isometric contractions and found unique parameter responses between the two conditions. These unique responses indicate anisotropic MRE’s capacity to provide a multifaceted approach to analyzing response to functional measures and provide a valuable tool for evaluating further changes in response due to injury-based or pathological changes to skeletal muscle.