Multimodal Actuation in Magnetic Resonance Elastography Experiments

Biological skeletal muscle tissue is subject to different modifications: as a matter of fact, its mechanical properties may be subject to changes correlated with diseases, such as Duchenne’s dystrophy and spasticity, or aging processes. These changes, especially those arising in the stiffness of the material, must be evaluated over time, in order to monitor the time-course of severe conditions and their potential response to therapeutic interventions. In recent years, scientists have developed new methods based on imaging techniques commonly used during diagnosis. These methods, named “elastographic”, are based on ultrasonic, optical and magnetic resonance imaging. Our research will focus on the Magnetic Resonance Elastography technique, which is often referred to as a “remote palpation technique”, able to give insights on the mechanical properties of a sample or tissue without being invasive. This method relies on the creation of MRI phase images following induced wave propagation in the tissue through mechanical excitation. Mechanical tissue properties can then be reconstructed with the use of mathematical inversion algorithms. This technique has been previously put to a test acquiring images resulting from geometrically focused (converging) out-of-imaging-plane (axial) excitation of the sample by means of a piezoelectric actuator. This research study aims to use the same MRE technique to identify changes in tissue mechanical properties under (in-plane) torsional deformations as well and to gain insight into the material properties variation from the comparison between the two kinds of actuation on the same sample. In the most innovative scenario, actuation of the sample, mimicking skeletal muscle tissue, will be achieved with the use of a stepper motor device, able to rotate on its axis thus transmitting torsional waves to the sample under examination. Images mapping the displacement field in a cross-sectional slice of the sample will be acquired by means of a Matlab sequence, able to trigger the acquisition process and to tune various parameters and filtering tools in order to obtain the so called “wave images”. Finally, an inversion algorithm named “Transformation Elastography” will be used to obtain stiffness values for the tissue both for the axial and the torsional excitation. We anticipate that the shape of wave images acquired through the stepper motor device will be substantially different from those that have already been acquired with excitation given by the piezo. These measures could prove to be useful in improving accuracy and efficiency of diagnosis, given the fact that they provide information about directional mechanical properties of the material that have not yet been examined (since they are provided by a novel type of actuation).