K-space data processing for magnetic resonance elastography (MRE)

MAGMA. 2017 Apr;30(2):203-213. doi: 10.1007/s10334-016-0594-8. Epub 2016 Nov 7.

Abstract

Objective: Magnetic resonance elastography (MRE) requires substantial data processing based on phase image reconstruction, wave enhancement, and inverse problem solving. The objective of this study is to propose a new, fast MRE method based on MR raw data processing, particularly adapted to applications requiring fast MRE measurement or high elastogram update rate.

Materials and methods: The proposed method allows measuring tissue elasticity directly from raw data without prior phase image reconstruction and without phase unwrapping. Experimental feasibility is assessed both in a gelatin phantom and in the liver of a porcine model in vivo. Elastograms are reconstructed with the raw MRE method and compared to those obtained using conventional MRE. In a third experiment, changes in elasticity are monitored in real-time in a gelatin phantom during its solidification by using both conventional MRE and raw MRE.

Results: The raw MRE method shows promising results by providing similar elasticity values to the ones obtained with conventional MRE methods while decreasing the number of processing steps and circumventing the delicate step of phase unwrapping. Limitations of the proposed method are the influence of the magnitude on the elastogram and the requirement for a minimum number of phase offsets.

Conclusion: This study demonstrates the feasibility of directly reconstructing elastograms from raw data.

Keywords: Elasticity imaging techniques; Interventional; Magnetic resonance imaging; Radiology.

MeSH terms

  • Algorithms
  • Animals
  • Elasticity Imaging Techniques*
  • Image Processing, Computer-Assisted*
  • Liver / diagnostic imaging*
  • Magnetic Resonance Imaging
  • Models, Statistical
  • Phantoms, Imaging*
  • Swine