title: Interleaved EPI based fMRI improved by multiplexed sensitivity encoding (MUSE) and simultaneous multi-band imaging.
abstract: Functional magnetic resonance imaging (fMRI) is a non-invasive and powerful imaging tool for detecting brain activities. The majority of fMRI studies are performed with single-shot echo-planar imaging (EPI) due to its high temporal resolution. Recent studies have demonstrated that, by increasing the spatial-resolution of fMRI, previously unidentified neuronal networks can be measured. However, it is challenging to improve the spatial resolution of conventional single-shot EPI based fMRI. Although multi-shot interleaved EPI is superior to single-shot EPI in terms of the improved spatial-resolution, reduced geometric distortions, and sharper point spread function (PSF), interleaved EPI based fMRI has two main limitations: 1) the imaging throughput is lower in interleaved EPI; 2) the magnitude and phase signal variations among EPI segments (due to physiological noise, subject motion, and B0 drift) are translated to significant in-plane aliasing artifact across the field of view (FOV). Here we report a method that integrates multiple approaches to address the technical limitations of interleaved EPI-based fMRI. Firstly, the multiplexed sensitivity-encoding (MUSE) post-processing algorithm is used to suppress in-plane aliasing artifacts resulting from time-domain signal instabilities during dynamic scans. Secondly, a simultaneous multi-band interleaved EPI pulse sequence, with a controlled aliasing scheme incorporated, is implemented to increase the imaging throughput. Thirdly, the MUSE algorithm is then generalized to accommodate fMRI data obtained with our multi-band interleaved EPI pulse sequence, suppressing both in-plane and through-plane aliasing artifacts. The blood-oxygenation-level-dependent (BOLD) signal detectability and the scan throughput can be significantly improved for interleaved EPI-based fMRI. Our human fMRI data obtained from 3 Tesla systems demonstrate the effectiveness of the developed methods. It is expected that future fMRI studies requiring high spatial-resolvability and fidelity will largely benefit from the reported techniques.
authors.affiliation: Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, United States of America.
authors.forename: Hing-Chiu
authors.initials: HC
authors.lastname: Chang
authors.affiliation: Department of Chemical and Physical Biology, Vanderbilt University, Nashville, TN, United States of America; Vanderbilt University Institute of Imaging Science, Nashville, TN, United States of America.
authors.forename: Pooja
authors.initials: P
authors.lastname: Gaur
authors.affiliation: Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, United States of America; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, United States of America.
authors.forename: Ying-hui
authors.initials: YH
authors.lastname: Chou
authors.affiliation: Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, United States of America; Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
authors.forename: Mei-Lan
authors.initials: ML
authors.lastname: Chu
authors.affiliation: Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, United States of America.
authors.forename: Nan-kuei
authors.initials: NK
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D017352:Echo-Planar Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D012680:Sensitivity and Specificity