Yiming Wang1, Limin Zhou1, Marco C. Pinho1,2, Ivan Pedrosa1,2,3, Joseph A. Maldjian1,2, and Ananth J. Madhuranthakam1,2
1Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States, 2Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States, 3Department of Urology, UT Southwestern Medical Center, Dallas, TX, United States
Synopsis
Arterial spin labeled (ASL) MRI is
often acquired at reduced spatial resolution due to lower signal to noise (SNR),
although higher spatial resolution within clinically feasible scan times is
desired. In this study, we applied Compressed Sensing–Sensitivity Encoding
(CS-SENSE) to 3D Cartesian TSE with Variable Density (VD) sampling to achieve
higher spatial resolution ASL-MRI without prolonging acquisition time. Perfusion
images acquired with CS-SENSE showed good SNR and image quality in both brains
and kidneys, without introducing bias to perfusion quantification. This may be particularly
useful to measure perfusion changes in small-sized lesions in both brains and
kidneys.
Introduction
Arterial
spin labeled (ASL) MRI is often acquired at reduced spatial resolution due to lower
signal to noise (SNR), although higher spatial resolution within clinically
feasible scan times is desired. 3D Cartesian turbo spin echo (TSE) has become a
promising acquisition method for ASL-MRI in both brain and kidneys.[1-3] 3D
Cartesian TSE with Variable Density (VD) sampling acquires the center of
k-space with increased number of averages and improves SNR and robustness
compared to single-average TSE acquisitions.[4][5] Furthermore, Cartesian TSE sampling
can be readily combined with novel accelerated imaging techniques such as Compressed
Sensing–Sensitivity Encoding (CS-SENSE).[6] The purpose of this study was to apply
CS-SENSE to 3D Cartesian TSE to achieve higher spatial resolution ASL-MRI
without prolonging the acquisition time. Methods
Pseudo-continuous
ASL (pCASL) with optimized background suppression (BGS) was used for both brain
and kidney perfusion imaging on a 3T Philips Ingenia scanner under IRB approval. For kidney imaging, an unbalanced pCASL labelling scheme with numerically
optimized gradients (Gmax= 3.5 mT/m, Gave = 0.5 mT/m) was
used to improve labelling robustness. 3D TSE Cartesian acquisition with Spiral
Profile Reordering and Variable Density Sampling (VD-CASPR) was used, which defines
3 regions in the ky-kz space with increasing distances from the center of the
k-space. Region 1 (R1) is an elliptical region in the center, surrounded by
annular regions 2 (R2) and 3 (R3), with profiles in regions 1, 2 and 3 acquired
using 3, 2 and 1 NSAs respectively. CS-SENSE, which randomly undersamples the
k-space, was applied to VD-CASPR acquisition (Figure 1). Proton-density weighted (M0) images was acquired
with partial k-space. [4][5]
Brain
Imaging: Four
healthy volunteers were scanned in an axial orientation for brain imaging. The
parameters were: TR/TE = 6000/14 ms, FOV = 220x220x110 mm3, matrix =
88x88 with 36 slices, acquired resolution = 2.5x2.5x6 mm3,
reconstructed resolution = 1.5x1.5x3 mm3, ETL = 80, echo spacing =
2.8 ms, label duration = 1.8 s, post-label delay = 1.8 s, and 4 BGS pulses. Two
CS-SENSE acquisitions with 2-fold-acceleration were performed with number of
profiles in R1 and R2 set to (i) 160 (2×ETL) in 3:24 min; and (ii) 240 (3×ETL)
profiles in 4:00 min. An additional acquisition using same parameters but without
acceleration and 160 (2×ETL) profiles in R1 and R2 was performed in 5:12 min.
M0 images were acquired with same parameters and a single-average CASPR using 1/3rd
of the k-space acquired in the center, in 20 s with 2-fold-accelerated CS-SENSE
and 40 s with no acceleration.
Kidney Imaging: Five healthy volunteers were scanned for kidney
imaging in an axial orientation. Parameters were: TR/TE = 6500/14 ms, FOV =
200x300x80 mm3, matrix = 80x121 with 26 slices, acquired resolution
= 2.5x2.5x6 mm3, reconstructed resolution = 1.7x1.7x3 mm3,
ETL = 120, echo spacing = 2.8 ms, 2-fold acceleration for CS-SENSE, with 360 (3×ETL)
profiles in R1 and R2, label duration = 1.5 s, post-label delay = 1.5 s, 4 BGS
pulses, and acquisition time = 4:46 min. For comparison, an additional sequence
with no acceleration was acquired at a reduced resolution of 3x3x6 mm3,
with 240 profiles (2×ETL) in R1 and R2, in 5:00 min. M0 images were acquired
using 1/3rd of central k-space in 28 s with CS-SENSE (resolution
2.5x2.5x6 mm3) and in 37 s (resolution 3x3x6 mm3) with no
acceleration.
In
2 brain volunteers, ROIs were drawn on different regions of gray matter on their
CBF maps. The agreement between the quantified mean CBF values in these ROIs
was compared using Bland-Altman analysis, between VD-CASPR with 2-fold-accelerated
CS-SENSE, and with no acceleration, both using M0 with 1/3rd
acquired k-space.Results
Brain
perfusion weighted images at a higher spatial resolution of 2.5x2.5x6 mm3
acquired with VD-CASPR and CS-SENSE showed good SNR (Figure 2a). The higher number of profiles in R1 and R2 (240
vs. 160) achieved enhanced SNR and reduced artifacts, albeit at slightly longer
scan time (Figure 2b). The image quality was comparable to images without
acceleration and slightly lower spatial resolution (Figure 2c). Higher spatial resolution (2.5x2.5x6 mm3)
kidney perfusion weighted images with CS-SENSE also showed good SNR and better
image sharpness compared to images acquired at lower resolution (3x3x6 mm3)
without acceleration (Figure 3). The CBF values measured in brain gray matter ROIs
showed good agreement, between VD-CASPR with 2-fold-accelerated CS-SENSE, and
with no acceleration (Figure 4).Discussion and Conclusion
We applied CS-SENSE to VD-CAPSR to achieve
higher spatial resolution ASL MRI without prolonging the scan time. Perfusion
images acquired with CS-SENSE showed good SNR and image quality in both brains
and kidneys, without introducing bias to perfusion quantification. The
combination of VD-CASPR and CS-SENSE may be particularly useful to measure perfusion
changes in small-sized lesions in both brains and kidneys, such as small renal
masses. Acknowledgements
NIH/NCI U01CA207091References
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