Use of pattern recognition for unaliasing simultaneously acquired slices in simultaneous multislice MR fingerprinting

Magn Reson Med. 2017 Nov;78(5):1870-1876. doi: 10.1002/mrm.26572. Epub 2016 Dec 26.

Abstract

Purpose: The purpose of this study is to accelerate an MR fingerprinting (MRF) acquisition by using a simultaneous multislice method.

Methods: A multiband radiofrequency (RF) pulse was designed to excite two slices with different flip angles and phases. The signals of two slices were driven to be as orthogonal as possible. The mixed and undersampled MRF signal was matched to two dictionaries to retrieve T1 and T2 maps of each slice. Quantitative results from the proposed method were validated with the gold-standard spin echo methods in a phantom. T1 and T2 maps of in vivo human brain from two simultaneously acquired slices were also compared to the results of fast imaging with steady-state precession based MRF method (MRF-FISP) with a single-band RF excitation.

Results: The phantom results showed that the simultaneous multislice imaging MRF-FISP method quantified the relaxation properties accurately compared to the gold-standard spin echo methods. T1 and T2 values of in vivo brain from the proposed method also matched the results from the normal MRF-FISP acquisition.

Conclusion: T1 and T2 values can be quantified at a multiband acceleration factor of two using our proposed acquisition even in a single-channel receive coil. Further acceleration could be achieved by combining this method with parallel imaging or iterative reconstruction. Magn Reson Med 78:1870-1876, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Keywords: MR fingerprinting; pattern recognition; quantitative imaging; relaxation time; simultaneous multislice.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Brain / diagnostic imaging
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / methods*
  • Pattern Recognition, Automated / methods*
  • Phantoms, Imaging