As 81 million 'baby boomers' living in the US enter old age, the fact that 50 percent of adults over the age of 85 are afflicted with Alzheimer's disease presents a looming crisis. Early diagnosis or the hope of developing an effective neuroprotective or regenerative intervention requires a deeper understanding of how the healthy human brain ages normally. A novel noninvasive elastography method based on magnetic resonance imaging has allowed high-resolution measurements of local mechanical properties of the living brain, which reveal that brain stiffness decreases with age. This award focuses on the development of fundamental knowledge to connect brain tissue microstructure with local mechanical properties measured noninvasively. Employing imaging technology available in the local clinic, mechanical maps of the brain can then be generated and used as a baseline to determine the stage of age-related brain degeneration, or to monitor the efficacy of an intervention. This award will enhance the outreach efforts of both principal investigators towards continuing to attract engineers from traditionally underrepresented groups interested in the intersection of computational mechanics, soft-tissue mechanics, image processing, and neuroscience. In addition to the enrichment of the mechanics-related curriculum and training of future engineers in research aligned with the national healthy brain initiatives, this project is expected to directly impact the broader medical communities at the two institutions.
Two important technical advances have provided insight into the development and degeneration of brain neurons: cell-level mechanobiology and high-resolution in vivo magnetic resonance elastography. The challenge is to unify these two levels of analysis in order to obtain a rigorous biomechanical view of the white matter of the human brain during normal aging. This award supports the development of hierarchical multiscale models of white matter micromechanics based on medical imaging and published histological data. These models will enable the interpretation of the magnetic resonance elastography data in terms of certain parameters in axon microstructure. Local viscoelastic properties will be spatially correlated with architectural metrics of the axonal network, so that the biomechanical properties of the brain can be investigated across subjects and age groups. The main outcome of this multiscale modeling effort is to relate the structural integrity of the axons to locally averaged functional properties quantified by magnetic resonance imaging. This will help explain how the age-related changes in the brain white matter are related to alterations in connectivity and mechanical coupling between neurons and glial cells as they age.
