Friday, May 17, 2024
5/17/2024
PROJECT SUMMARY This project includes both the development of advanced MRI sequences to study brain stiffness as well as clinical application of this technique to study brain health in an aging adult population. A sensitive method to establish and reliably detect the point where the progression of Alzheimer’s Disease and other dementias diverge from normal aging is crucial to developing methods for intervention. Early detection is critical in lessening the financial burden of these diseases on the US healthcare system. Magnetic resonance elastography (MRE) is a non-invasive, in vivo, MRI technique which provides information on the mechanical properties of tissues and is uniquely situated to sensitively provide insight into microstructural tissue changes that may occur prior to when structural changes caused by atrophy can be detected. The basis of the MRE technique is that displacements induced in a tissue by an external actuation source can be measured using phase-contrast MRI, and then turned into high-resolution maps of tissue mechanical properties such as stiffness. However, this technique is often difficult to widely implement because it requires use of longer scan times and then further requires specialized equipment to vibrate the tissue. We propose two major improvements to MRE acquisition and processing to remove these barriers based on a novel sampling technique and estimation scheme, EDGE (Elastography with Distributed, Generalized Encoding). EDGE utilizes non-traditional sampling directions implemented in an optimized encoding matrix to collect data much more efficiently, and be used in a novel algorithm to estimate harmonic displacement fields, together allowing room for acceleration of acquisition or redundancies to be built into the data for rejection of bad data in the post-processing step. We also extend this method to intrinsic actuation to capture motion that occurs naturally from pulsatile cerebral blood flow to provide the motion necessary for MRE mechanical property estimation (intEDGE), thus removing the need for external hardware and making the scan similar to any other for the patient experience. We will confirm the validity of these techniques by evaluating differences in brain stiffness between young and older adults using the traditional MRE method and the proposed EDGE and intEDGE methods. Success of this project will result in a novel MRE technique that removes barriers to the wide implementation of MRE as a measure of brain health in aging and aging-related neurological conditions.
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