Transversely-isotropic brain in vivo MR elastography with anisotropic damping.

Dhrubo Jyoti, Matthew McGarry, Diego A Caban-Rivera, Elijah Van Houten, Curtis L Johnson, Keith Paulsen
Author Information
  1. Dhrubo Jyoti: Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA. Electronic address: dhrubo.jyoti@dartmouth.edu.
  2. Matthew McGarry: Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA. Electronic address: matthew.d.mcgarry@dartmouth.edu.
  3. Diego A Caban-Rivera: University of Delaware, Newark, DE, 19716, USA.
  4. Elijah Van Houten: Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada.
  5. Curtis L Johnson: University of Delaware, Newark, DE, 19716, USA.
  6. Keith Paulsen: Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA; Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA.

Abstract

Measuring tissue parameters from increasingly sophisticated mechanical property models may uncover new contrast mechanisms with clinical utility. Building on previous work on in vivo brain MR elastography (MRE) with a transversely-isotropic with isotropic damping (TI-ID) model, we explore a new transversely-isotropic with anisotropic damping (TI-AD) model that involves six independent parameters describing direction-dependent behavior for both stiffness and damping. The direction of mechanical anisotropy is determined by diffusion tensor imaging and we fit three complex-valued moduli distributions across the full brain volume to minimize differences between measured and modeled displacements. We demonstrate spatially accurate property reconstruction in an idealized shell phantom simulation, as well as an ensemble of 20 realistic, randomly-generated simulated brains. We characterize the simulated precisions of all six parameters across major white matter tracts to be high, suggesting that they can be measured independently with acceptable accuracy from MRE data. Finally, we present in vivo anisotropic damping MRE reconstruction data. We perform t-tests on eight repeated MRE brain exams on a single-subject, and find that the three damping parameters are statistically distinct for most tracts, lobes and the whole brain. We also show that population variations in a 17-subject cohort exceed single-subject measurement repeatability for most tracts, lobes and whole brain, for all six parameters. These results suggest that the TI-AD model offers new information that may support differential diagnosis of brain diseases.

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Grants

  1. R01 EB027577/NIBIB NIH HHS

MeSH Term

Humans
Diffusion Tensor Imaging
Magnetic Resonance Imaging
Elasticity Imaging Techniques
Anisotropy
Brain

Word Cloud

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