evaluation and optimisation of magnetic resonance elastography of the liver.

Magnetic resonance elastography (MRE) is widely adopted as a biomarker of liver fibrosis. However,MRE accuracy is difficult to assess.Finite element model (FEM) simulation was employed to evaluate liver MRE accuracy and inform methodological optimisation. MRE data was simulated in a 3D FEM of the human torso including the liver, and compared with spin-echo echo-planar imaging MRE acquisitions. The simulated MRE results were compared with the ground truth magnitude of the complex shear modulus (∣*∣) for varying: (1) ground truth liver ∣*∣; (2) simulated imaging resolution; (3) added noise; (4) data smoothing. Motion and strain-based signal-to-noise (SNR) metrics were evaluated on the simulated data as a means to select higher-quality voxels for preparation of acquired MRE summary statistics of ∣*∣.The simulated MRE accuracy for a given ground truth ∣*∣ was found to be a function of imaging resolution, motion-SNR and smoothing. At typical imaging resolutions, it was found that due to under-sampling of the MRE wave-field, combined with motion-related noise, the reconstructed simulated ∣*∣ could contain errors on the scale of the difference between liver fibrosis stages, e.g. 54% error for ground truth ∣*∣ = 1 kPa. Optimum imaging resolutions were identified for given ground truth ∣*∣ and motion-SNR levels.This study provides important knowledge on the accuracy and optimisation of liver MRE. For example, for motion-SNR ≤ 5, to distinguish between liver ∣*∣ of 2 and 3 kPa (i.e. early-stage liver fibrosis) it was predicted that the optimum isotropic voxel size is 4-6 mm.