Functional MRI using super-resolved spatiotemporal encoding

Noam Ben-Eliezer, Ute Goerke, Kamil Ugurbil, Lucio Frydman

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Recently, new ultrafast imaging sequences such as rapid acquisition by sequential excitation and refocusing (RASER) and hybrid spatiotemporal encoding (SPEN) magnetic resonance imaging (MRI) have been proposed, in which the phase encoding of conventional echo planar imaging (EPI) is replaced with a SPEN. In contrast to EPI, SPEN provides significantly higher immunity to frequency heterogeneities including those caused by B0 inhomogeneities and chemical shift offsets. Utilizing the inherent robustness of SPEN, it was previously shown that RASER can be used to successfully perform functional MRI (fMRI) experiments in the orbitofrontal cortex - a task which is challenging using EPI due to strong magnetic susceptibility variation near the air-filled sinuses. Despite this superior performance, systematic analyses have shown that, in its initial implementation, the use of SPEN was penalized by lower signal-to-noise ratio (SNR) and higher radiofrequency power deposition as compared to EPI-based methods. A recently developed reconstruction algorithm based on super-resolution principles is able to alleviate both of these shortcomings; the use of this algorithm is hereby explored within an fMRI context. Specifically, a series of fMRI measurements on the human visual cortex confirmed that the super-resolution algorithm retains the statistical significance of the blood oxygenation level dependent (BOLD) response, while significantly reducing the power deposition associated with SPEN and restoring the SNR to levels that are comparable with those of EPI.

Original languageEnglish (US)
Pages (from-to)1401-1408
Number of pages8
JournalMagnetic Resonance Imaging
Volume30
Issue number10
DOIs
StatePublished - Dec 2012

Bibliographical note

Funding Information:
The authors are grateful to Prof. Michael Garwood for supporting this work and facilitating the collaboration between the two research centers involved, as well as to Dr. Cheryl Olman for providing the visual stimulation software. This research was supported by the Minerva Foundation (Project 710587; Federal German Ministry for Education and Research), ERC Advanced Grant # 246754 , a Helen and Kimmel Award for Innovative Investigation, and the generosity of the Perlman Family Foundation as well as the NIH grants P41 RR008079 (BTRC) and P30 NS057091 (NCC).

Keywords

  • Functional MRI
  • High-field MRI
  • Spatiotemporal encoding
  • Super-resolved processing
  • Visual BOLD activation

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