Abstract
Echo planar imaging (EPI) is an MRI technique of particular value to neuroscience, with its use for virtually all functional MRI (fMRI) and diffusion imaging of fiber connections in the human brain. EPI generates a single 2D image in a fraction of a second; however, it requires 2–3 seconds to acquire multi-slice whole brain coverage for fMRI and even longer for diffusion imaging. Here we report on a large reduction in EPI whole brain scan time at 3 and 7 Tesla, without significantly sacrificing spatial resolution, and while gaining functional sensitivity. The multiplexed-EPI (M-EPI) pulse sequence combines two forms of multiplexing: temporal multiplexing (m) utilizing simultaneous echo refocused (SIR) EPI and spatial multiplexing (n) with multibanded RF pulses (MB) to achieve m×n images in an EPI echo train instead of the normal single image. This resulted in an unprecedented reduction in EPI scan time for whole brain fMRI performed at 3 Tesla, permitting TRs of 400 ms and 800 ms compared to a more conventional 2.5 sec TR, and 2–4 times reductions in scan time for HARDI imaging of neuronal fibertracks. The simultaneous SE refocusing of SIR imaging at 7 Tesla advantageously reduced SAR by using fewer RF refocusing pulses and by shifting fat signal out of the image plane so that fat suppression pulses were not required. In preliminary studies of resting state functional networks identified through independent component analysis, the 6-fold higher sampling rate increased the peak functional sensitivity by 60%. The novel M-EPI pulse sequence resulted in a significantly increased temporal resolution for whole brain fMRI, and as such, this new methodology can be used for studying non-stationarity in networks and generally for expanding and enriching the functional information.
Highlights
In the last two decades, magnetic resonance imaging (MRI) techniques such as functional magnetic resonance imaging [1,2] and diffusion weighted imaging for neuronal fiber tractography [3,4,5] have revolutionized our ability to investigate the human brain
These techniques mostly rely on echo planar imaging (EPI) [6] for spatial encoding of the magnetic resonance image because of its fast scan time, enabling rapid volumetric coverage over the brain reducing temporal instabilities associated with multi-excitation techniques (e.g. [7,8])
Acquisition times have targeted reducing the number of refocused echoes needed for spatial encoding to form an image. These approaches decrease scan time for spatial encoding in EPI, with many consequent benefits, they do not necessarily reduce image acquisitions time significantly. This is because a physiological contrast preparation period must precede the spatial encoding period for each slice and this contrast preparation period can equal or exceed the time employed for collecting the EPI echo train. 3D echo volume (EVI) [14] avoids the repetition of the contrast encoding time by following a single contrast preparation period with subsequent 3D volume coverage in a single echo train
Summary
In the last two decades, magnetic resonance imaging (MRI) techniques such as functional magnetic resonance imaging (fMRI) [1,2] and diffusion weighted imaging for neuronal fiber tractography [3,4,5] have revolutionized our ability to investigate the human brain. These approaches decrease scan time for spatial encoding in EPI, with many consequent benefits, they do not necessarily reduce image acquisitions time significantly This is because a physiological contrast preparation period (i.e. for neuronal activity or water diffusion) must precede the spatial encoding period for each slice and this contrast preparation period can equal or exceed the time employed for collecting the EPI echo train. PRESTO [18,19], increase volume coverage efficiency in fMRI by taking advantage of TE delays to apply additional RF pulses, but are SNR limited and run into restrictions at higher magnetic fields when T2 and T2* become inherently short Another approach to reducing the scan time per volume in fMRI uses UNFOLD [20]to reconstruct images from undersampled, 3D kspace [21]. The method and resulting images are presented together with preliminary data on the application of this approach to resting state fMRI (R-fMRI) and diffusion imaging based tractography
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