Unbalanced SSFP for super-resolution in MRI

Magn Reson Med. 2021 May;85(5):2477-2489. doi: 10.1002/mrm.28593. Epub 2020 Nov 17.

Abstract

Purpose: To achieve rapid, low specific absorption rate (SAR) super-resolution imaging by exploiting the characteristic magnetization off-resonance profile in SSFP.

Theory and methods: In the presented technique, low flip angle unbalanced SSFP imaging is used to acquire a series of images at a low nominal resolution that are then combined in a super-resolution strategy analogous to non-linear structured illumination microscopy. This is demonstrated in principle via Bloch simulations and synthetic phantoms, and the performance is quantified in terms of point-spread function (PSF) and SNR for gray and white matter from field strengths of 0.35T to 9.4T. A k-space reconstruction approach is proposed to account for B0 effects. This was applied to reconstruct super-resolution images from a test object at 9.4T.

Results: Artifact-free super-resolution images were produced after incorporating sufficient preparation time for the magnetization to approach the steady state. High-resolution images of a test object were obtained at 9.4T, in the presence of considerable B0 inhomogeneity. For gray matter, the highest achievable resolution ranges from 3% of the acquired voxel dimension at 0.35T, to 9% at 9.4T. For white matter, this corresponds to 3% and 10%, respectively. Compared to an equivalent segmented gradient echo acquisition at the optimal flip angle, with a fixed TR of 8 ms, gray matter has up to 34% of the SNR at 9.4T while using a ×10 smaller flip angle. For white matter, this corresponds to 29% with a ×11 smaller flip angle.

Conclusion: This approach achieves high degrees of super-resolution enhancement with minimal RF power requirements.

Keywords: SSFP; spatial encoding; structured illumination microscopy; super-resolution.

Publication types

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

MeSH terms

  • Artifacts*
  • Magnetic Resonance Imaging*
  • Phantoms, Imaging