Brain Magnetic Resonance Elastography based on Rayleigh damping material model
Thesis DisciplineMechanical Engineering
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosophy
Magnetic Resonance Elastography (MRE) is an emerging medical imaging modality that allows quantification of the mechanical properties of biological tissues in vivo. MRE typically involves time-harmonic tissue excitation followed by the displacement measurements within the tissue obtained by phase-contrast Magnetic Resonance Imaging (MRI) techniques. MRE is believed to have great potential in the detection of wide variety of pathologies, diseases and cancer formations, especially tumors.
This thesis concentrates on a thorough assessment and full rheological evaluation of the Rayleigh damping (RD) material model applied to MRE. The feasibility of the RD model to accurately reconstruct viscoelastic and damping properties was assessed. The goal is to obtain accurate quantitative estimates of the mechanical properties for the in vivo healthy brain via the subzone optimization based nonlinear image reconstruction algorithm.
The RD model allows reconstruction of not only stiffness distribution of the tissue, but also energy attenuation mechanisms proportionally related to both elastic and inertial effects. The latter allows calculation of the concomitant damping properties of the material. The initial hypothesis behind this research is that accurate reconstruction of the Rayleigh damping parameters may bring additional diagnostic potential with regards to differentiation of various tissue types and more accurate characterisation of certain pathological diseases based on different energy absorbing mechanisms. Therefore, the RD model offers reconstruction of three additional material properties that might be of clinical diagnostic merit and can enhance characterisation of cancer tumors within the brain.
A pneumatic-based actuator was specifically developed for in vivo human brain MRE experiments. Performance of the actuator was investigated and the results showed that the actuator produces average displacement in the range of 300 µmicrons and is well suited for generation of shear waves if applied to the human head. Unique features of the the actuator are patient comfort and safety, MRI compatibility, flexible design and good displacement characteristics.
In this research, a 3D finite element (FE) subzone-based non-linear reconstruction algorithm using the RD material model has been applied and rigorously assessed to investigate the performance of elastographic based reconstruction to accurately recover mechanical properties and a concomitant damping behaviour of the material. A number of experiments were performed on a variety of homogenous and heterogeneous tissue-simulating damping phantoms comprising a set of materials that mimic range of mechanical properties expected in the brain. The result showed consistent effect of a poor reconstruction accuracy of the RD parameters which suggested the nonidentifiable nature of the RD model.
A structural model identifiability analysis further supported the nonidentifiabilty of the RD parameters at a single frequency. Therefore, two approaches were developed to overcome the fundamental identifiability issue. The first one involved application of multiple frequencies over a broad range. The second one was based on parametrisation techniques, where one of the damping parameters was globally defined throughout the reconstruction domain allowing reconstruction of the two remaining parameters.
Based on the findings of this research, multi-frequency (MF) elastography was performed on the tissue-simulating phantoms to investigate improvement of the elastographic reconstruction accuracy. Dispersion characteristics of the materials as well as RD changes across different frequencies in various materials were also studied. Simultaneous multi-frequency inversion was undertaken where two models were evaluated: a zero-order model and a power-law model. Furthermore, parametric-based RD reconstruction was carried out to evaluate enhancement of accurate identification of the reconstructed parameters. The results showed that parametric-based RD reconstruction, compared to MF-based RD results, allowed better material characterisation on the reconstructed shear modulus image. Also, significant improvement in material differentiation on the remaining damping parameter image was also observed if the fixed damping parameter was adjusted appropriately.
In application to in vivo brain imaging, six repetitive MRE examinations of the in vivo healthy brain demonstrated promising ability of the RD MRE to resolve local variations in mechanical properties of different brain tissue types. Preliminary results to date show that reconstructed real shear modulus and overall damping levels correlate well with the brain anatomical features. Quantified shear stiffness estimates for white and gray matter were found to be 3 kPa and 2.1 kPa, respectively. Due to the non-identifiability of the model at a single frequency, reconstructed RD based parameters limit any physical meaning. Therefore, MF-based and parametric-based cerebral RD elastography was also performed.