High temporal resolution functional MRI using parallel echo volumar imaging

Abstract

Purpose: To combine parallel imaging with 3D single-shot acquisition (echo volumar imaging, EVI) in order to acquire high temporal resolution volumar functional MRI (fMRI) data. Materials and Methods:An improved EVI sequence was associated with parallel acquisition and field of view reduction in order to acquire a large brain volume in 200 msec. Temporal stability and functional sensitivity were increased through optimization of all imaging parameters and Tikhonov regularization of parallel reconstruction. Two human volunteers were scanned with parallel EVI in a 1.5T whole-body MR system, while submitted to a slow eventrelated auditory paradigm.Results: Thanks to parallel acquisition, the EVI volumes display a low level of geometric distortions and signal losses. After removal of low-frequency drifts and physiological artifacts, activations were detected in the temporal lobes of both volunteers and voxelwise hemodynamic response functions (HRF) could be computed. On these HRF different habituation behaviors in response to sentence repetition could be identified. Conclusion:This work demonstrates the feasibility of high temporal resolution 3D fMRI with parallel EVI. Combined with advanced estimation tools, this acquisition method should prove useful to measure neural activity timing differences or study the nonlinearities and nonstationarities of the BOLD response. UNTIL NOW, functional MRI (fMRI) data were mostly acquired using echo planar imaging (EPI), allowing the acquisition of multislice brain volumes with a spatial resolution of about 3 mm and a temporal resolution of 1-2 seconds. EPI is thus well suited to the detection of cerebral activations and the mapping of activated areas. Nevertheless, with the development of event-related fMRI (1) and the growing interest in the temporal features of the hemodynamic response function (HRF) (2,3), higher scanning rates are called for by neuroscientists.High temporal resolution fMRI is feasible with echo volumar imaging (EVI), a 3D extension of EPI, in which a 3D Fourier space is encoded in a single-shot acquisition. Some applications of EVI have been reported, especially in fMRI (4 -6). As compared with EPI, EVI presents several advantages for fMRI. First, EVI acquisition offers very short TR, on the order of 200 msec. Second, 3D single-shot acquisition makes slicetiming correction unnecessary and reduces the risk of intravolume motion of the subject. Finally, true 3D acquisition is known to reduce vascular inflow effects (7) that often confuse the interpretation of fMRI results (8).Nevertheless, EVI has seldom been used in fMRI, due to its heavy demand on gradient hardware. Actually, because of hardware limitations the echo train duration (ETD) is high in EVI and the voxel bandwidth along the direction of partition (third encoding direction) is very low. Thus, if high spatial resolution and wide brain coverage are required in an EVI acquisition, susceptibility-induced distortions and signal losses due to T2* relaxation dramatically alter image quality. To overcome ...

Three‐dimensional echo planar imaging with controlled aliasing: A sequence for high temporal resolution functional MRI

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Robust Real-Time-Constrained Estimation of Respiratory Motion for Interventional MRI on Mobile Organs

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A wavelet-based regularized reconstruction algorithm for SENSE parallel MRI with applications to neuroimaging☆

“…If one wants to further improve the spatial or temporal resolution, or simply reduce the global imaging time keeping the same acquisition parameters, it would be necessary to increase factor R. To compensate for the intrinsic degradation of the image quality, it is crucial to regularize the reconstruction process which becomes severely ill-posed. To this end, several contributions have been proposed in the recent pMRI literature (Liang et al, 2002;Ying et al, 2004Ying et al, , 2008Lin et al, 2004;Block et al, 2007;Rabrait et al, 2008;Chaâri et al, 2008), most of them operating in the image domain to better estimate full FOV images. For an introductory survey to linear inverse problems with a special emphasis to pMRI reconstruction, the interested reader is referred to Ribes and Schmitt (2008).…”

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