title: Concurrent 3D acquisition of diffusion tensor imaging and magnetic resonance elastography displacement data (DTI-MRE): Theory and in vivo application.
abstract: To introduce a newly developed technique (DTI-MRE) for the simultaneous acquisition of diffusion tensor imaging (DTI) and 3D-vector field magnetic resonance elastography (MRE) data, and to demonstrate its feasibility when applied in vivo to the mouse brain.
  
  
  
  In DTI-MRE, simultaneous encoding is achieved by using a series of diffusion/motion-sensitizing gradients (dMSGs) with specific timing and directions. By adjusting the duration of the dMSGs with the diffusion time and with the mechanical vibration frequency, the shear wave motion and diffusion are encoded into the MR phase and MR magnitude signals, respectively. The dMSGs are applied in a noncollinear and noncoplanar manner that optimizes the capture of both the DTI signal attenuation and the three-dimensional MRE displacements. In this work, the feasibility of the DTI-MRE technique was demonstrated on in vivo mouse brains (n=3) using a 9.4T animal MRI scanner. The DTI-MRE derived parameters (MD, mean diffusivity; FA, fractional anisotropy; MRE displacement fields; and shear modulus |G|) were compared with those acquired using conventional, separate MRE and diffusion methods.
  
  
  
  The averaged (MD, FA, and |G|) values for three mice are (0.580 ± 0.050 µm2/ms, 0.43 ± 0.02, and 4.80 ± 0.06 kPa) and (0.583 ± 0.035 µm2/ms, 0.46 ± 0.02, and 4.91 ± 0.19 kPa) for DTI-MRE, and conventional DTI and 3D-vector field MRE measurements, respectively. All derived parameters (MD, FA, |G|, and displacement) obtained using the combined DTI-MRE method and conventional methods were significantly correlated with P < 0.05.
  
  
  
  Simultaneous acquisition of DTI and 3D-vector field MRE is feasible in vivo and reduces the scan time by up to 50% compared with conventional, separate acquisitions, while providing an immediate co-registration of maps of diffusion properties and stiffness. Magn Reson Med 77:273-284, 2017. © 2016 Wiley Periodicals, Inc.
authors.affiliation: Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: Ziying
authors.initials: Z
authors.lastname: Yin
authors.affiliation: Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: Steven P
authors.initials: SP
authors.lastname: Kearney
authors.affiliation: Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: Richard L
authors.initials: RL
authors.lastname: Magin
authors.affiliation: Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: Dieter
authors.initials: D
authors.lastname: Klatt
mesh_terms: D000465:Algorithms; D000818:Animals; D016880:Anisotropy; D001921:Brain; D056324:Diffusion Tensor Imaging / Q000295:instrumentation / Q000379:methods*; D055119:Elastic Modulus; D054459:Elasticity Imaging Techniques / Q000295:instrumentation / Q000379:methods*; D004867:Equipment Design; D005260:Female; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D051379:Mice; D008810:Mice, Inbred C57BL
keywords: diffusion; elastography; fractional anisotropy; imaging; mean diffusivity; shear modulus; stiffness