Improving MRI's slice selectivity in the presence of strong, metal-derived inhomogeneities

Gil Farkash, Gilad Liberman, Ricardo P. Martinho, Lucio Frydman

Research output: Contribution to journalArticlepeer-review


Purpose: To develop schemes that deliver faithful 2D slices near field heterogeneities of the kind arising from non-ferromagnetic metal implants, with reduced artifacts and shorter scan times. Methods: An excitation scheme relying on cross-term spatio-temporal encoding (xSPEN) was used as basis for developing the new inhomogeneity-insensitive, slice-selective pulse scheme. The resulting Fully refOCUSED cross-term SPatiotemporal ENcoding (FOCUSED-xSPEN) approach involved four adiabatic sweeps. The method was evaluated in silico, in vitro and in vivo using mice models, and compared against a number of existing and of novel alternatives based on both conventional and swept RF pulses, including an analogous method based on LASER's selectivity spatial selectivity. Results: Calculations and experiments confirmed that multi-sweep derivatives of xSPEN and LASER can deliver localized excitation profiles, centered at the intended positions and endowed with enhanced immunity to B 0 and B 1 distortions. This, however, is achieved at the expense of higher SAR than non-swept counterparts. Furthermore, single-shot FOCUSED-xSPEN and LASER profiles covered limited off-resonance ranges. This could be extended to bands covering arbitrary off-resonance values with uniform slice widths, by looping the experiments over a number of scans possessing suitable transmission and reception offsets. Conclusions: A series of novel approaches were introduced to select slices near metals, delivering robustness against B o and B 1 + field inhomogeneities.

Original languageEnglish
Pages (from-to)71-80
Number of pages10
JournalMagnetic Resonance Imaging
Early online date13 Mar 2020
StatePublished - Jun 2020

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


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