We have established an innovative approach to brain magnetic resonance elastography (MRE) based on encoding of endogenous low frequency (~1Hz) motion resulting from blood pulsation through the cerebrovascular system that is reconstructed with a poroelastic mechanical model to produce three- dimensional (3D), spatially-resolved mechanical and hydrodynamical property images. Our poroelastic MRE (pMRE) methods have produced promising preliminary data in phantoms, animals, and humans. In parallel, we have advanced substantially our viscoelastic MRE (vMRE) methods based on external high frequency (50- 100Hz) actuation, and preliminary data from our latest vMRE studies in phantoms, animals and humans are also very impressive because of the spatially-resolved mechanical property information that can be obtained. Indeed, we have evidence to suggest that vMRE and pMRE are complementary - namely that vMRE is the method of choice at externally-actuated high frequencies where the viscous damping effects of brain parenchyma are more dominant, whereas pMRE is the best choice at intrinsically-actuated low frequencies where the hydrodynamic fluid effects become more important. Our overall objective in this project is to unify and optimize our pMRE and vMRE methods in order to evaluate them across the frequency spectrum of interest (~1-100Hz) in a series of phantom and animal model systems which will identify the conditions under which they provide superior, comparable and/or complementary images and data. Specifically, we will (1) develop a unified framework and platform through which we will advance and optimize our pMRE and vMRE image reconstruction methods, (2) use actuation and phantom systems for comparative evaluations across the frequency range of interest, and (3) complete experiments in three large animal models with controllable parameters and experimental conditions under which comparative evaluations will occur in vivo. Evidence already exists to support the potential of brain MRE to inform clinical identification and management of multiple neurological disorders. We hypothesize that brain MRE has much more to offer - specifically, that 3D, spectrally-optimized, spatially-resolved maps of tissue mechanical and hydrodynamical properties should be the standard - not the whole/regional brain mechanical property averages that have largely been reported to date. External and intrinsic brain actuation both have merit, as do pMRE and vMRE;hence, a focused and sustained effort to optimize, evaluate and compare these approaches across the available frequency range is needed to identify the methods of choice under selected and prevailing conditions of interest.

Public Health Relevance

We will advance, evaluate and compare magnetic resonance elastography (MRE) methods for brain imaging based on poroelastic and viscoelastic models of response to externally and intrinsically induced motion in the head. Evidence already exists to suggest that brain MRE can help clinicians identify and manage neurological disorders such as hydrocephalus, multiple sclerosis, and Alzheimer's disease. We believe that brain MRE has much more to offer - specifically, that 3D, spectrally-optimized, spatially-resolved maps of tissue mechanical and hydrodynamical properties should be the standard - not the whole/regional brain property averages that have largely been reported to date. Our proposed poroelastic and viscoelastic MRE methods are designed to produce this information.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
5R01EB018230-02
Application #
8738671
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Liu, Guoying
Project Start
Project End
Budget Start
Budget End
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Dartmouth College
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
City
Hanover
State
NH
Country
United States
Zip Code
03755
Pattison, Adam J; McGarry, Matthew; Weaver, John B et al. (2014) Spatially-resolved hydraulic conductivity estimation via poroelastic magnetic resonance elastography. IEEE Trans Med Imaging 33:1373-80