University of Rochester Receives NIH Grant for Advanced Brain OCT Elastography
University of Rochester Receives a 2020 NIH Grant for $421,880 for Advanced Brain OCT Elastography. The principal investigator is Kevin Parker. Below is a summary of the proposed work.
Changes in the local and global mechanical properties of brain tissue associated with aging and neurodegenerative diseases has not been extensively studied and quantified. Pathology and autopsy case studies have provided some qualitative insight, and magnetic resonance elastography (MRE) studies have demonstrated some general patterns. However, current techniques require technical refinement and much remains to be elucidated about the relationship between the evolution of brain biomechanics and these complex processes. There are several approaches that employ optical coherence tomography (OCT), a high-resolution imaging modality, to obtain the mechanical properties of biological tissues. These techniques are generally referred to as optical coherence elastography (OCE), and have demonstrated promising applications with studies in cornea, breast, muscle, heart, and skin. In this project, brain OCE will be performed in mice ex vivo/in situ and in vivo to study the aging process and Alzheimer’s disease. Mechanical waves are introduced into the tissue via transducers, and an OCT imaging system captures volumetric data with lateral and axial resolutions of a few microns. Variations in the softness and stiffness of cortical brain tissue with respect to time will be quantified. Specifically, the use of reverberant shear wave fields for elastography, which takes advantage of inevitable reflections from boundaries and tissue inhomogeneities, allow for estimation of the shear wave speed, which is directly related to the elastic modulus of soft tissues, along with other key properties of the brain including viscosity, dispersion, and anisotropy. The goal of this project is to quantify how shear wave speeds (related to stiffness of tissues) change with aging or the onset and progression of Alzheimer’s disease using mice models, informing basic science, creating useful biomarkers, and guiding clinical measurements in humans.