Yidi Lu1, Chia-Yin Wu1,2,3, Shota Hodono1,2, Jin Jin2,4, David Reutens1,2, and Martijn A Cloos1,2
1Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia, 2ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia, 3School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia, 4Siemens Healthcare Pty Ltd, Brisbane, Australia
Synopsis
The standing wave
artefact affects SNR and contrast of the images in Ultra-high
field (UHF) functional magnetic resonance imaging (fMRI). One way to
mitigate this effect is to use parallel transmission (pTx). In this study, we evaluate
the benefits of pTx for studies that investigate large-scale brain networks
involved in motor control. We show that, compared to the standard circularly
polarized (CP) mode, activation patterns in the posterior lobule of the
cerebellum, produced by a coordinated finger flexion-extension task in both
hands, are better captured using subject-specific pTx pulses.
Introduction
Functional
magnetic resonance imaging (fMRI) has been widely used in neuroscience and
behavioural science to study the brain. Ultra-high field (UHF) fMRI provides
images with high specificity1 and signal to noise ratio (SNR)2.
However, the higher frequencies at which these UHF systems operate lead to
shorter radiofrequency (RF) wavelengths, that exacerbate interference effects
and produce inhomogeneous B1+ fields3.
Consequently, when using a standard circularly polarised (CP) transmit coil,
the tissue contrast and SNR in the image vary spatially4. In
particular, the signal drops significantly in the cerebellum, which is involved
in movement planning and motor coordination. One way to address this artefact
is to use parallel transmission (pTx) which allows tailored RF pulses (e.g.,
spokes5 and kT-points6) to be designed to counteract the
inhomogeneous field7. Here, we show preliminary results from a
task-based fMRI experiment to highlight the benefits of pTx for fMRI of large-scale
brain networks involved in fine motor control and coordination, including areas
such as cerebellum.Methods
Paradigm: A block design paradigm was
used for the task. The subject flexed and extended their fingers (~2 Hz) during
the ON block (6s) and the hands remained in a relaxed position during the OFF block
(12s) (Fig 1a). During each run, all fingers in both hands were flexed and extended
either synchronously or asynchronously (Fig 1c). The complete paradigm was measured twice, once
using the CP-mode and once using subject-specific pTx-kT-points pulses6
(8 sub-pulses, duration = 1.18ms). The
task was also performed using only one hand (pTx mode only). A visual cue was
used to instruct the participant when to move (Fig 1b). Additionally, a custom
data glove8, which measures finger joint angles, was worn by the
participant to monitor and record their finger movements during the scan (Fig
1d).
Data acquisition: One subject was scanned on a
7 Tesla whole-body MRI scanner (Siemens Healthineers, Erlangen, Germany) using
an 8-channel transmit/32-channel receive head coil array (Nova Medical, MA,
USA). For calibration, SA2RAGE9 (TR/TE/TD1/TD2
= 2400ms/0.95ms/106ms/1800ms, 4x4x4mm3, iPAT = 2) and a custom 2D
interleaved gradient recalled echo (GRE) (TR/TE = 300ms/3ms, 4×4×4mm3,
iPAT = 3) were used to generate absolute B1+ maps. Additionally,
T2*-weighted images (TR/TE = 1500ms/12ms, 2x2x2mm3, iPAT = 3) were
also obtained to make brain masks in FSL-BET10 (Brain Extraction
Tool) (FMRIB’s software
library, www.fmrib.ox.ac.uk/fsl,
version 6.0.4). An anatomical reference was acquired using an MP2RAGE11
sequence (0.75x0.75x0.75mm3, FOV = 156x225x240mm3, TR/TI1/TI2/TE
= 4300ms/840ms/2450ms/1.99ms). All fMRI data were collected using a 3D gradient
EPI sequence (1.25x1.25x1.25mm3, FOV = 150x220x220mm3, TRvol/TR/TE
= 2035ms/55ms/26ms, flip angle = 12°, number of measurements per run = 150,
total scan time per run = 5min). The study was approved by the local human
research ethics committee in accordance with national guidelines.
Pre-processing: Motion correction
was applied as the first step in SPM12 (Statistical Parametric
Mapping, www.fil.ion.ucl.ac.uk/spm, version 12), then the realigned results
were registered onto the MP2RAGE anatomical images. FSL-BET10 was
used to extract the brain in the registered images. Smoothing (full width at
half maximum = 2.5mm) was applied on the extracted brain images in SPM. Z-score maps were generated in FSL using a canonical hemodynamic response
function (HRF) as a model. Temporal SNR (tSNR) maps were calculated for both pTx and CP-mode
resting-state images by dividing the mean by the standard deviation of the time
series. The mean tSNR in the cerebellum was calculated for both modes.Results & Discussion
In pTx mode, the flip angles
become more uniform (Fig 2) and the tSNR increased (Fig 3), in some locations, by
more than a factor of 2. Mean tSNR in the cerebellum was 1.5 times higher than for
CP-mode. Changes in tSNR and flip angles are well matched because greater flip
angle homogeneity enables higher tSNR4.
Activations for finger
flexion-extension in one hand are shown in Fig 4. The contralateral primary
motor cortex (M1) was activated in both left- and right-hand tasks as expected13,14,15.
The ipsilateral anterior lobule of the cerebellum was also activated as
previously observed16.
Activation patterns in the anterior
cerebellum were similar for the asynchronous task using the pTx and CP-mode
(Fig 5a), whereas activation of the posterior cerebellum, previously
demonstrated for finger flexion-extension14, was only seen with the pTx
acquisition. For the synchronous task, activations close to the primary fissure
and in the posterior cerebellum were only seen in pTx-mode. In the CP-mode data,
these activations were fewer with lower z-scores (Fig 5b). Conclusion
At 7 Tesla, pTx pulses can improve the tSNR across the
brain, especially in the cerebellum. pTx is beneficial when studying
large-scale brain networks involved in fine motor control.Acknowledgements
This work was
supported by ARC Future fellowship grant FT200100329. The authors
acknowledge the facilities of the National Imaging Facility at the Centre for
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