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

Abstract

Purpose: In this work, we combine three-dimensional echo planar imaging (3D-EPI) with controlled aliasing to substantially increase temporal resolution in whole-brain functional MRI (fMRI) while minimizing geometry-factor (g-factor) losses. Theory and Methods: The study was performed on a 7 Tesla scanner equipped with a 32-channel receive coil. The proposed 3D-EPI-CAIPI sequence was evaluated for: (i) image quality, compared with a conventionally undersampled parallel imaging acquisition; (ii) temporal resolution, the ability to sample and remove physiological signal fluctuations from the fMRI signal of interest and (iii) the ability to distinguish small changes in hemodynamic responses in an event-related fMRI experiment. Results: Whole-brain fMRI data with a voxel size of 2 Â 2 Â 2 mm 3 and temporal resolution of 371 ms could be acquired with acceptable image quality. Ten-fold parallel imaging accelerated 3D-EPI-CAIPI data were shown to lower the maximum g-factor losses up to 62% with respect to a 10-fold accelerated 3D-EPI dataset. FMRI with 400 ms temporal resolution allowed the detection of time-to-peak variations in functional responses due to multisensory facilitation in temporal, occipital and frontal cortices. Conclusion: 3D-EPI-CAIPI allows increased temporal resolution that enables better characterization of physiological noise, thus improving sensitivity to signal changes of interest. Furthermore, subtle changes in hemodynamic response dynamics can be studied in shorter scan times by avoiding the need for jittering.

The multisensory function of the human primary visual cortex

“…Specifically, for the multisensory as compared to either unisensory condition within primary visual cortices (and primary auditory cortices) the BOLD signal peaked earlier (following also a steeper slope). Importantly, these latency effects were not a result of a simple amplitude/latency trade-off (see Table 1 in Martuzzi et al, 2007, for detailed statistics; see also Narsude et al, 2015 for a recent replication at 7T). A pressing issue that will require additional research is resolving the neurophysiologic mechanisms underlying modulations of the BOLD signal latency.…”

How to choose the right MR sequence for your research question at 7 T and above?

“…With maximum gradients strengths and slew rates of 80mT/m and 333mT/m/ms available in head gradient set (and hence a higher slew rate than for whole body coils), it is possible to use EPI to, for example, to encode the whole brain slice/plane at 2mm in plane resolution in 44ms without the use of in-plane acceleration (Narsude et al, 2016) or at 1mm in plane resolution in 48ms using 6/8 partial Fourier and an in-plane acceleration of 2 (Setsompop et al, 2012). This has not come at the expense of BOLD contrast as also the T 2 *(which is the optimum echo time for GE BOLD contrast) decreases with increasing magnetic field.…”

“…3D EPI can be accelerated using parallel imaging along the two phase-encoding axes. The g-factor in 3D EPI can be reduced by application of the CAIPI technique (Narsude et al, 2016) making the gfactor noise penalty comparable to what can be obtained using blipped-CAIPI SMS (Zahneisen et al, 2014). The first publication on the use of accelerated 3D EPI for fMRI showed comparable or better performance to standard 2D EPI (Poser et al, 2010), yet 3D EPI acquisitions with volume TRs that are greater than about one second will suffer from the combined effects of physiological noise and motion which increase with the number of segments used to construct the 3D volume (van Der Zwaag et al, 2012).…”

Accurate modeling of temporal correlations in rapidly sampled fMRI time series

“…The emergence of advanced MRI acquisition strategies such as parallel (Griswold et al, 2002; Pruessmann, Weiger, Scheidegger, & Boesiger, 1999) and multiband (or simultaneous multi‐slice) imaging (Breuer et al, 2005; Larkman et al, 2001; Setsompop et al, 2012) have enabled sampling rates to be greatly increased by reducing the time taken to acquire a single volume. Reducing the volume acquisition time not only allows the acquisition of more samples within the same total duration but also reduces sensitivity to intravolume motion and improves the sampling of physiological noise, which can then be more effectively removed by low‐pass filtering the time series (Narsude, Gallichan, van der Zwaag, Gruetter, & Marques, 2016; Todd et al, 2017). …”