Application of parallel imaging to fMRI at 7 Tesla utilizing a high 1D reduction factor

Area of Science:

• Neuroimaging
• Magnetic Resonance Imaging (MRI)

Background:

• Blood oxygenation level-dependent (BOLD) functional MRI (fMRI) is crucial for mapping brain activity.
• Ultrahigh field strength (7 Tesla) offers increased signal-to-noise ratio (SNR) but also heightened physiological noise.
• Parallel imaging (PI) is a technique to accelerate MRI acquisition by undersampling k-space.

Purpose of the Study:

• To demonstrate the efficacy of gradient-echo EPI fMRI using parallel imaging (PI) at 7 Tesla.
• To compare the performance of PI with conventional segmented full field of view (FOV) acquisition.
• To assess the impact of PI on activation detection and statistical significance in fMRI.

Main Methods:

• Gradient-echo EPI fMRI at 7 Tesla using a 16-channel coil.
• Implementation of parallel imaging (PI) with a 1D reduction factor (R) of 4 and maximal aliasing.
• Comparison with segmented acquisition covering the full FOV of k-space.

Main Results:

• Robust activation detection in finger-tapping fMRI studies using PI, consistent with expected patterns.
• Functional maps acquired with PI outperformed segmented full-FOV coverage.
• PI-based fMRI activation showed higher statistical significance (up to 1.6-fold) compared to segmented data.

Conclusions:

• Parallel imaging (PI) is highly beneficial for fMRI at 7 Tesla.
• PI improves statistical significance and activation detection, outperforming conventional methods.
• The advantages of PI are pronounced at ultrahigh fields due to high intrinsic SNR and physiological noise levels.