Hassan Haji-Valizadeh1, Jeremy D. Collins 2, Daniel C. Lee2,3, James C. Carr2, and Daniel Kim2
1Biomedical Engineering, Northwestern University, Chicago, IL, United States, 2Radiology, Northwestern university, Chicago, IL, United States, 3Division of Cardiology, Internal Medicine, Northwestern University, Chicago, IL, United States
Synopsis
We
sought to develop a high resolution single-shot LGE pulse
sequence using Radial Compressed Sensing. We then evaluated in patients the performance of our acquisition scheme with respect to segmented clinical LGE.
Introduction
Late gadolinium enhanced (LGE)1-3 is
considered the gold standard test for assessment of myocardial viability. LGE
MRI is typically administered in two different ways: (i) segmented, breath-held
(BH) acquisition with gradient echo readout and (ii) single-shot,
free-breathing acquisition with balanced steady-state free precession (b-SSFP)
readout. While a breath-hold LGE acquisition provides higher spatial resolution
than a single-shot LGE acquisition, it requires longer scan time and is
sensitive to arrhythmia and breathing motion. While a single-shot LGE acquisition
can be conducted during free-breathing and is insensitive to arrhythmia, it
provides lower spatial resolution than a segmented, breath-hold LGE acquisition.
Compressed sensing (CS)4 is revolutionizing
cardiovascular MRI with unprecedented imaging speed. A previous study using 3D
LGE with CS5
showed that high spatial resolution improves scar quantification and
identification of grey zones. We sought to develop and evaluate a single-shot
LGE pulse sequence with spatial high resolution using CS and radial k-space
sampling.Method
(Patient) We enrolled 14 patients (mean age = 57.14 ± 15.7 years; 5
males; 9 females) who were scheduled to undergo clinical cardiovascular MRI,
which included clinical BH LGE as reference. (Image Acquisition) Single-shot LGE pulse sequence with CS and
radial k-space sampling was implemented on 1.5T (Avanto, Aera, Siemens) and 3T
(Skyra, Siemens) scanners. Relevant image parameters are summarized in Table 1.
Note that radial scans acquired 42 radial rays with the 5th Golden angle sequence6. To suppress streak artifacts arising from k-space
undersampling, particularly in outer volume regions, we used a wideband inversion
pulse7. Single-shot LGE with CS was conducted
immediately after clinical LGE to sample a stack of short-axis planes. (Image reconstruction) We used the k-space
weighted image contrast (KWIC) filter8, 9 to choose
a unique inversion time (TI) for LGE reconstruction. As shown in Fig. 1, this
scheme enabled us to identify an optimal TI retrospectively and eliminate a need
to perform PSIR reconstruction10. After identifying an optimal TI, we removed
aliasing artifact using CS with spatial total variation (TV)4 with 100 iterations and
normalized regularization weight of 0.000025. (Data Analysis) With clinical segmented, BH LGE as reference, we
compared the image quality of single-shot LGE with CS (spatial TV and TGV). 26 short-axis
stacks (12 clinical LGE, 14 CS LGE) were randomized and evaluated by 2 readers
in a blinded, independent fashion for the following three categories using a 5-point
Likert scale: image quality, artifact level, and noise level. Note that an
entire short-axis stack received one score. An average score of ≥ 3.0 was
considered to be diagnostically acceptable. Qualitative scores were compared
using Wilcoxon signed rank test.Results
Figure 2 shows representative quality produced by
clinical segmented, breath-hold LGE and single-shot LGE with CS scans at 1.5T
and 3T. Table 2 summarizes the image quality scores. Averaging the results over
14 patients, the readers’ scores were not significantly different for all
categories.
Discussion
This
study demonstrates that a combination of CS and radial k-space sampling
produces single-shot LGE images with high spatial resolution and image quality.
A future study is warranted to rigorously evaluate the diagnostic performance of
single-shot LGE with CS in patients with myocardial scars. Acknowledgements
This work was supported by NIH Grant 1R01HL116895-01A1.
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