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.
Highlights
Functional magnetic resonance imaging is a non-invasive imaging tool for detecting brain activity using the blood-oxygen-level-dependent (BOLD) contrast [1, 2]
echo-planar imaging (EPI)-based diffusion-weighted imaging (DWI) can be minimized with a multiplexed sensitivity-encoding (MUSE) algorithm [12], which can be briefly summarized as a 3-step procedure
It can be seen that the point-spread function (PSF) remains sharp in MUSE-produced images, as compared with the theoretical PSF, for different interleaved EPI acquisition schemes
Summary
Functional magnetic resonance imaging (fMRI) is a non-invasive imaging tool for detecting brain activity using the blood-oxygen-level-dependent (BOLD) contrast [1, 2]. Because of the high temporal resolution of single-shot echo-planar imaging (EPI), the majority of fMRI studies were performed with single-shot EPI [3]. It is well known that the spatial resolution and fidelity are limited in single-shot EPI-based fMRI data. The signal decay within the long acquisition window of single-shot EPI broadens the point-spread function (PSF) [6]. It is not always feasible to achieve the optimal echo time (TE) when choosing a large in-plane matrix size for high-resolution fMRI studies [6]
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