Suhyung Park1,2, Sugil Kim3, Hankyeol Lee4, Seulgi Eun4, Seong-Gi Kim4,5, and David Feinberg6,7
1Department of Computer Engineering, Chonnam National University, Gwangju, Korea, Republic of, 2Department of ICT Convergence System Engineering, Chonnam National University, Gwangju, Korea, Republic of, 3Siemens-Healthineers, Seoul, Korea, Republic of, 4Center for Neuroscience Imaging Research (CNIR), Institute for Basic Science (IBS), Suwon, Korea, Republic of, 5Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea, Republic of, 6University of California, Berkeley, Berkeley, CA, United States, 7Advanced MRI Technologies, Sebastopol, CA, United States
Synopsis
With ultra-high fields, 3D
EPI has been used by improving imaging efficiency. Nevertheless, there have been some limitations: 1) the regular sampling limits
the use of temporal structure in the data and 2) parallel imaging allows up to 6-fold acceleration in 3D acquisition. Here, we developed an accelerated 3D EPI using VD-CAPI sampling with temporal random walk. Experimental studies
confirm advantages in acceleration, SNR, and sensitivity of the proposed method: 1) temporal random walk allows extra
spatial encoding across time, 2) temporal prior provides high SNR, and 3) the temporal incoherent sampling and high SNR result in higher BOLD activations.
Introduction
With ultra-high
magnetic fields, functional MRI (fMRI) achieves increased signal-to-noise ratio
(SNR) and sensitivity to BOLD contrast at sub-millimeter resolutions, and hence
holds great potential for columnar and layer imaging1-4. In pursuit of
sub-millimeter resolution fMRI with a short TR per volume, application of 2D
CAIPI sampling to multi-shot 3D EPI was recently proposed5-7, improving
acquisition efficiency with reduced g-factor penalty during reconstruction. Nevertheless, 3D EPI acquisitions have some disadvantages in that 1) the regular sampling with
the EPI sequence limits the use of temporal structure in the data and 2) parallel
imaging typically allows up to 6-fold acceleration in 3D acquisition even with
32 receiver channels8-9. In this work, we developed a novel highly accelerated 3D
EPI using variable density (VD) 2D CAPI sampling with temporal random walk. Experimental
studies confirm advantages in acceleration, SNR, and sensitivity of the proposed
new sampling scheme coupled with 3D EPI: 1) temporal random walk in 3D EPI allows
extra spatial encoding by exploiting the temporal redundancy, 2) temporally constrained
reconstruction provides high SNR efficiency, and 3) the incoherent time-varying
sampling and high SNR efficiency result in higher BOLD sensitivity in the
expected primary visual areas.Methods
3D Spatiotemporal Encoding:
The design of the spatiotemporal sampling in 3D EPI
is important in estimating missing signals from highly undersampled data. In
order to design an optimized random encoding for fMRI, we introduce a temporal random
walk into 2D VD-CAIPI sampling under the framework of 3D EPI sequence. Fig. 1A
shows an example of the temporal random walk. For the spatial encoding, CAIPI-based
sampling repeats for all TRs by evenly distributing the aliasing between both
of the phase encoding axes. In each TR, the CAIPI sampling itself randomly jumps
to neighboring sites of the lattice within a ky -kz block (the bock size is
the undersmapled factor for each axis) to achieve a complementary random encoding
across time while keeping the coherence on the spatial axes. Additionally, we
incorporate the VD concept along the partition axis into 2D CAIPI sampling to
include more central k-space data without changing EPI blip size along phase
axis (as shown in Fig. 1B).
Reconstruction: For spatiotemporal joint reconstruction, SENSE is applied
to the spatial axes while low rank and sparsity priors
are applied to temporal axis under the assumption that parallel imaging is more
effective with the regular sampling while the above temporal priors well
performed with incoherent acquisition10-11.
Experiments:
All experiments were conducted using a 7T
whole-body scanner (MAGNETOM, Terra, Siemens Healthineers, Erlangen, Germany)
equipped with a 32-channel head coil. Institutional review board and informed
consent was obtained for all subjects. All data were acquired using accelerated
3D EPI with 1) Skipped-CAIPI and 2) VD-CAIPI+Random Walk. The imaging parameters are summarized in table 1.
Stimulation paradigm:
Functional activation was assessed by
performing a flickering checkerboard pattern with 6.25 Hz frequency in blocks of
19.2s on/off for visual stimulation. The cycle was repeated 8 times per scan for
a total task duration of 5.44 minutes. Results
Fig. 2 shows an example of reconstructed images
(displaying 6 out of 60 slices) acquired using skipped CAIPI (6-fold acceleration) and proposed VD-CAIPI+Random
Walk (8-fold acceleration). The skipped CAIPI yields aliasing in frontal area and signal loss around
slab boundary. On the other hand, the proposed method substantially suppresses
image noises and aliasing artifacts over the entire brain. Fig. 3 and 4 compares functional activation
maps of primary visual cortex using multiplanar reformatting for each sequence.
Note that skipped CAIPI introduces a smearing of BOLD information, while the
proposed method can better delineate cortical gray matter area with higher BOLD sensitivity. Conclusions
We
demonstrated that multi-shot 3D EPI combined with a new sampling scheme (VD-CAIPI+Random
Walk) has significant improvement over the current skipped CAIPI 3D EPI sequence in terms of
net acceleration, reconstruction quality, and functional activation. Unlike the
current sequence that operates in a time-independent manner for reconstruction,
the proposed method is able to exploit temporal redundancy while keeping normal
EPI framework unchanged, thus improving statistical power in measuring
functional activation. In the near future, we plan to incorporate the new 3D sequence readout with CBV-based VASO sequences12. Acknowledgements
This work has been supported by the National Institute of Biomedical
Imaging and Bio-engineering, and the National Institute for Mental Health of the
National Institutes of Health and the BRAIN Initiative under award numbers: U01EB025162 and 1R01MH111444References
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