Tobias Wech1,2, Tina Urbanek1,3, Andreas Max Weng1, Daniel Stäb4, Peter Speier5, Thorsten Alexander Bley1, and Herbert Köstler1,2
1Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany, 2Comprehensive Heart Failure Centre, University Hospital Würzburg, Würzburg, Germany, 3Fakultät Ingenieurwissenschaften, Hochschule für Technik und Wirtschaft des Saarlandes, Saarbrücken, Germany, 4The Centre for Advanced Imaging, The University of Queensland, Brisbane, Germany, 5Magnetic Resonance, Siemens Healthcare GmbH, Erlangen, Germany
Synopsis
MS-CAIPIRINHA is a valuable
technique to extend the anatomical coverage in myocardial first-pass perfusion
imaging. In our previous studies, dual-band excitation was applied in
conjunction with three SR-prepared acquisition blocks per RR interval to obtain
six 2D-slices with a temporal resolution of one heartbeat. Especially in obese
patients, however, the SNR occasionally turned out to be marginal, ultimately
complicating the assessment of perfusion defects. In this work, an according
approach using tri-band RF excitation was tested with respect to potential SNR
benefits.
Target audience
Clinicians interested in cardiac perfusion and
MR physicists interested in using MS-CAIPIRINHA.Purpose
MS-CAIPIRINHA is a valuable means to extend the
anatomical coverage in first-pass myocardial perfusion imaging [1, 2, 3]. In
earlier studies [4, 5], three saturation-recovery (SR) preparations were used
per RR-interval, each followed by an undersampled dual-slice MS-CAIPIRINHA
acquisition. The parallel imaging (PI) reconstruction then yielded six 2D-slices with a temporal resolution
of one RR-interval. Especially in obese patients, however, the SNR occasionally
turned out to be marginal for a robust diagnosis of perfusion defects.
In this work, the technique was compared to an
alternative approach: Two SR preparations were performed per RR-interval and
each was followed by an undersampled MS-CAIPIRINHA with tri-band excitation. Aim
of the study was to evaluate whether the new approach results in a higher
signal-to-noise-ratio (SNR).Methods
The TurboFLASH-based MS-CAIPIRINHA prototype (see above,
[4]) utilized dual-band RF pulses to excite two slices at the same time. The
simultaneously excited slices were shifted with respect to each other by ½ FOV
by toggling the RF phase in the second slice between 0 and π.
In this work, tri-band RF pulses were implemented in
order to excite three slices at the same time. The RF phases in the three
slices were varied according to
$$$\phi_1(j)=0$$$, $$$\phi_2(j)=\frac{2\pi}{3}j$$$ and $$$\phi_2(j)=\frac{4\pi}{3}j$$$ with the excitation index $$$j$$$, in order to shift the
slices by ⅓ FOV with respect to each other and equally distribute the slice
aliasing along the phase encoding direction. Two SR-preparations were applied
per RR-interval to obtain six slices, in accordance with the dual-band
approach.
First, both techniques were compared in a first-pass
perfusion investigation of a patient with primary hyperaldosteronism. Data were
acquired on a 3T whole-body MR-scanner (MAGNETOM Skyra, Siemens Healthcare,
Erlangen, Germany) equipped with a body and spine phase array coil using 34
elements in total. For each measurement, a 10 ml bolus of gadoterate meglumine
(Dotarem, Guerbet, Aulnay-sous-Bois, France) was injected and observed over 60
RR-intervals. The overall PI acceleration factor corresponded to 5 (RCAIPI =
2, RInPlane = 2.5) for dual-band and to 4 (RCAIPI = 3, RInPlane = 1.3) for
tri-band excitation. TGRAPPA [6] was used for offline image reconstruction in
MATLAB (MathWorks, Natick, MA, USA). The remaining imaging parameters included:
Spatial resolution = 3.1 mm x 2.5 mm, TE=1.06, TR = 2.33, FA = 10°, slice
thickness = 8mm, phase encoding steps (PES) / RR-interval = 135 for the dual-band and: Spatial
resolution = 3.1 mm x 2.5 mm, TE=1.38, TR = 2.65, FA = 10°, slice thickness =
8mm, PES / RR-interval = 168 for the tri-band acquisition.
An
SNR study was then performed for a quantitative comparison of the dual- and the
tri-band techniques. Phantom data were acquired on the same scanner. For an objective comparison, the total number
of PES was kept equal for both acquisitions. The dual-band
MS-CAIPIRINHA measurement was performed using three SR preparations, each
followed by 45 phase-encoding steps (135 PES in total, Rtotal=5), while the tri-band
acquisition featured two SR-preparations, each followed by 68 phase-encoding
steps (136 PES in total, Rtotal=4). A measurement of the noise amplitude and
correlation in the 34-channel phased-array receiver coil was performed for both
approaches and the method described in [7] was used to obtain SNR maps.
Remaining imaging parameters were adjusted as follows: spatial resolution = 2.3
mm x 1.9 mm; TE = 1.49; TR = 2.79; flip angle =10°.
Results
The results of the first-pass perfusion
acquisitions are depicted in Fig. 1. Both techniques resulted in an overall
good image quality. No considerable differences in artifact level and image
sharpness are apparent throughout all frames of the image series. The maps in
Fig. 2 reveal an overall higher SNR for the dual-band approach. The average SNR
across all pixels of all slices was 27±13 for the tri-band and 41 ± 16 for the
dual-band pulse.Discussion & Conclusion
The
simulations performed in our study compared dual- and tri-band MS-CAIPIRINHA
with respect to their usability in first-pass myocardial perfusion imaging.
Both techniques yielded six slices with a temporal resolution of one
RR-interval, however, the SNR was significantly lower for the tri-band
excitation. This is most likely due to the comparably small slice distances in
cardiac MRI, which result in a limited variation of the coil sensitivities and
ultimately in an elevation of the g-factor.
The dual-band acquisition with
three SR preparations is therefore the method of choice. This is also justified
by a shorter acquisition window for each multi-slice time frame, which comes
with less cardiac motion and less signal variation due to the ongoing recovery
of the magnetization.Acknowledgements
Funding: DFG (KO 2938/4-1), Siemens Healthcare
References
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et al., ISMRM 2015 #2686 [5] Wech et al., ISMRM 2016 #2607 [6] Breuer FA, Magn
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