Kyung Min Nam1,2,3, Guodong Weng2,3, Nam G Lee4, Edwin Versteeg1, Yeong-Jae Jeon5,6, Arjan Hendriks1, Jannie Wijnen1, Alex Bhogal1, Dennis Klomp1, Maxim Zaitsev7, and Johannes Slotboom2,3
1Department of High Field MR, Centre for Image Sciences, University of Medical Centre Utrecht, Utrecht, Netherlands, 2Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland, 3Translational Imaging Center, sitem-insel AG, Bern, Switzerland, 4Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, 5Lee Gil Ya Cancer & Diabetes Institute, Gachon University, Incheon, Korea, Republic of, 6Department of Health Sciences and Technology, GAIHST, Gachon University, Incheon, Korea, Republic of, 7Department of Radiology, Division of Medical Physics, University Medical Center Freiburg, Freiburg, Germany
Synopsis
Keywords: Data Acquisition, Spectroscopy
An MRSI sequence using a pair of chemically
selective adiabatic 2π refocus pulses, referred to as 2π-CSAP, was implemented using the
open-source Pulseq framework. This sequence enables full coverage of the
frequency spectrum of interest through a shift in carrier frequency, which has
been a limitation in rapid MRSI sequences. In addition, this shifted frequency spectrum also minimizes
signal contaminations from residual water signal after water suppression or
unsuppressed water signal and strong lipid signals, possibly eliminating the
need for additional water suppression pre-pulses. This base sequence can potentially be combined with accelerated acquisition techniques for better scan
efficiency.
Introduction
Magnetic resonance spectroscopic imaging (MRSI)
is a non-invasive technique for measuring and visualizing metabolite level distribution.
It can be used in the brain to provide information about tumour metabolism,
neurodegenerative diseases, and metabolic disorders. However,
residual water signal after water suppression and strong
lipid signals in the brain and skull obscure the accurate quantification of metabolite
signals. Current solutions need a relatively long repetition time (TR), which
particularly limits their applicability to clinical settings, especially when a
high resolution is required. At the high magnetic field, several accelerated MRSI methods have been
proposed1, but
MRI vendors do not provide such methods and implementing these in the vendor's
proprietary sequence programming environment is tedious and complex. In this
work, as a response to the 2023 ISMRM Challenge "Repeat it With Me: Reproducibility Team
Challenge", we reproduce a 2D MRSI sequence using a pair of chemically
selective adiabatic 2π refocusing
pulses (called 2π-CSAP2,3) at
7T using the open-source Pulseq framework4. This
MRSI sequence could be combined with various fast readout strategies such as
EPI used in a recently published SLOW-editing EPSI sequence3.Methods
Sequence design, simulation, data acquisition, and reconstruction
A 2π-CSAP
MRSI sequence (Fig. 1) was
designed in the Pulseq framework. RF, GR, and ADC events were designed based on
the parameters used in SLOW-editing3 full scheme 2. Bloch simulations were performed to
validate the sequence timing and amplitudes of RF and gradient events before deploying
into the scanner. An animation of magnetization evolution (Fig. 2, 3, and 4) during a 2π-CSAP pulse was created with and without the carrier frequency shift (Δf = 0.00 [ppm] and 2.90 [ppm]). A 7T MRI scanner (Magnetom Terra, Siemens Healthineers, Erlangen,
Germany) was used with a 1Tx/32Rx head coil (Nova Medical, USA) using the
built-in gradient system (maximum gradient amplitude of 80 mT/m and maximum
slew rate of 200 mT/m/msec). For the phantom experiment
(BRAINO), imaging parameters were: FA = 65°, bandwidth = 5.5 kHz, and duration = 6 ms for a sinc-Gauss excitation pulse, and nominal FA = 550°, bandwidth = 0.88 kHz, and
duration = 24 ms for a 2π-CSAP pulse, FOV = 240 × 240 mm2,
voxel size = 6 × 6 mm2, TR/TE = 1500/68 ms, spectral bandwidth = 5 kHz,
number of sample points = 2048, readout oversampling factor = 2, number of averages
= 1, and acquisition time = 40 min. An in-house developed script written in
MATLAB was used for reconstruction. Raw data were exported as a TWIX format and converted to the ISMRMRD format5, a vendor-agnostic data format. A noise covariance
matrix for pre-whitening was calculated from noise-only data. A spatial Fourier
transform was performed, and the Roemer equal noise algorithm6,7 was used for channel
combination using coil sensitivity maps8 estimated from the water
reference. Zeroth-order phase correction was applied, and metabolite maps were
generated by calculating the area of each metabolite peak.Results and Discussion
When using the developed 2π-CSAP
sequence in the phantom (Fig. 5), selective excitation could be
performed with minimal artifacts (e.g., residual water and lipid
contamination) by shifting the carrier frequency. Water suppression pre-pulses were
not included in this sequence. Using only 2 low-bandwidth adiabatic RF pulses
reduces SAR and thus enables a relatively short TR. This is advantageous in
acquiring a high resolution in vivo scan in a clinically acceptable scan time
without compromising its ability to avoid the chemical shift displacement
artifact (CSDA). A
full bandwidth coverage is achieved in this sequence by setting the carrier
frequency (Δf) to the center of the frequency band of interest (e.g., Δf = 2.9
[ppm], 1.6 - 4.2 [ppm]). The Pulseq framework based on MATLAB stores RF and gradient
waveforms obtained from a Pulseq file, which enables quick Bloch simulations. This
allows for a deep understanding of existing pulse sequences and possibly provides
insights into a better pulse sequence design.Conclusion
We have
successfully implemented a 2π-CSAP
sequence using an open-source sequence design tool. This
pulse sequence written in Pulseq could be easily shared across different
institutions having different scanners and
scanner software versions. This
sequence provides metabolic information and utilizes its spectral bandwidth by shifting the carrier frequency, and
it avoids strong residual water signal, and lipid signal contamination. Moreover, the use of Pulseq can be easily extended to fast acquisition techniques such as EPI9, concentric ring10, and spiral11 k-space trajectory sequences.Acknowledgements
This project
has received funding from the European Union's Horizon 2020 research and
innovation program under the Marie Sklodowska-Curie grant agreement No 813120.References
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