New spatiotemporal approaches for fully refocused, multislice ultrafast 2D MRI

Magn Reson Med. 2014 Feb;71(2):711-22. doi: 10.1002/mrm.24714.

Abstract

Purpose: Single-scan multislice acquisition schemes play key roles in magnetic resonance imaging. Central among these "ultrafast" experiments stands echo-planar imaging, a technique that although of optimal sampling is challenged by T2* artifacts. Recent studies described alternatives based on spatiotemporal encoding (SPEN), which are particularly robust if implemented in a "full-refocusing" mode. This work extends this modality from the single-slice acquisitions in which it has hitherto been implemented, by introducing a variety of multislice schemes scanning 3D volumes.

Methods: Multislice SPEN employing either inversion or stimulated echo pulses and timed to fulfill the demands of full refocusing, are demonstrated. The performance of the ensuing methods was examined in "Hybrid" modalities encoding data in k- and direct-space, in low-specific absorption rate stimulated-echo approaches, and in direct-space SPEN approaches.

Results: When applied in phantoms and in in vivo systems, the ensuing single-shot sequences evidenced similar robustness, sensitivity, and resolution qualities as previously discussed 2D single-slice schemes, while enabling a rapid sampling of the third dimension via multislicing.

Conclusion: The unique benefits deriving from fully refocused, multislice, single-scan SPEN sequences were corroborated by phantom tests, as well as by in vivo scans at 3 and 7 T. Low specific absorption rate multislice SPEN variants compatible with human studies were demonstrated.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Artifacts*
  • Brain / anatomy & histology*
  • Humans
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Information Storage and Retrieval / methods*
  • Magnetic Resonance Imaging / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Spatio-Temporal Analysis