48 research outputs found
Radial cardiac T2 mapping with alternating T2 preparation intrinsically introduces motion correction
A robust broadband fat suppressing phaser T2 preparation module for cardiac magnetic resonance imaging at 3T
Purpose: Designing a new T2 preparation (T2-Prep) module in order to
simultaneously provide robust fat suppression and efficient T2 preparation
without requiring an additional fat suppression module for T2-weighted imaging
at 3T. Methods: The tip-down RF pulse of an adiabatic T2 preparation (T2-Prep)
module was replaced by a custom-designed RF excitation pulse that induces a
phase difference between water and fat, resulting in a simultaneous T2
preparation of water signals and the suppression of fat signals at the end of
the module (now called a phaser adiabatic T2-Prep). Using numerical
simulations, in vitro and in vivo ECG-triggered navigator gated acquisitions of
the human heart, the blood, myocardium and fat signal-to-noise ratio and right
coronary artery (RCA) vessel sharpness using this approach were compared
against previously published conventional adiabatic T2-Prep approaches Results:
Numerical simulations predicted an increased fat suppression bandwidth and
decreased sensitivity against transmit magnetic field inhomogeneities using the
proposed approach, while preserving the water T2 preparation capabilities. This
was confirmed by the tissue signals acquired on the phantom and the in vivo
MRA, which show similar blood and myocardium SNR and CNR and significantly
reduced fat SNR compared to the other methods tested. As a result, the RCA
conspicuity was significantly increased and the motion artifacts were visually
decreased. Conclusion: A novel fat-suppressing T2-preparation method was
developed and implemented that demonstrated robust fat suppression and
increased vessel sharpness compared with conventional techniques, while
preserving its T2 preparation capabilities.Comment: 23 pages, 5 figures, submitted to Magnetic Resonance in Medicin
Self-navigation with compressed sensing for 2D translational motion correction in free-breathing coronary MRI:a feasibility study
PURPOSE: Respiratory motion correction remains a challenge in coronary magnetic resonance imaging (MRI) and current techniques, such as navigator gating, suffer from sub-optimal scan efficiency and ease-of-use. To overcome these limitations, an image-based self-navigation technique is proposed that uses "sub-images" and compressed sensing (CS) to obtain translational motion correction in 2D. The method was preliminarily implemented as a 2D technique and tested for feasibility for targeted coronary imaging.
METHODS: During a 2D segmented radial k-space data acquisition, heavily undersampled sub-images were reconstructed from the readouts collected during each cardiac cycle. These sub-images may then be used for respiratory self-navigation. Alternatively, a CS reconstruction may be used to create these sub-images, so as to partially compensate for the heavy undersampling. Both approaches were quantitatively assessed using simulations and in vivo studies, and the resulting self-navigation strategies were then compared to conventional navigator gating.
RESULTS: Sub-images reconstructed using CS showed a lower artifact level than sub-images reconstructed without CS. As a result, the final image quality was significantly better when using CS-assisted self-navigation as opposed to the non-CS approach. Moreover, while both self-navigation techniques led to a 69% scan time reduction (as compared to navigator gating), there was no significant difference in image quality between the CS-assisted self-navigation technique and conventional navigator gating, despite the significant decrease in scan time.
CONCLUSIONS: CS-assisted self-navigation using 2D translational motion correction demonstrated feasibility of producing coronary MRA data with image quality comparable to that obtained with conventional navigator gating, and does so without the use of additional acquisitions or motion modeling, while still allowing for 100% scan efficiency and an improved ease-of-use. In conclusion, compressed sensing may become a critical adjunct for 2D translational motion correction in free-breathing cardiac imaging with high spatial resolution. An expansion to modern 3D approaches is now warranted
Compressed Sensing with Signal Averaging for Improved Sensitivity and Motion Artifact Reduction in Fluorine-19 MRI
Fluorine-19 (19F) MRI of injected perfluorocarbon emulsions (PFCs) allows for
the non-invasive quantification of inflammation and cell tracking, but suffers
from a low signal-to-noise ratio and extended scan time. To address this
limitation, we tested the hypothesis that a 19F MRI pulse sequence that
combines a specific undersampling regime with signal averaging has increased
sensitivity and robustness against motion artifacts compared to a non-averaged
fully-sampled dataset, when both are reconstructed with compressed sensing. To
this end, numerical simulations and phantom experiments were performed to
characterize the point spread function (PSF) of undersampling patterns and the
vulnerability to noise of acquisition-reconstruction strategies with paired
numbers of x signal averages and acceleration factor x (NAx-AFx). At all
investigated noise levels, the DSC of the acquisition-reconstruction strategies
strongly depended on the regularization parameters and acceleration factor. In
phantoms, motion robustness of an NA8-AF8 undersampling pattern versus NA1-AF1
was evaluated with simulated and real motions. Differences were assessed with
Dice similarity coefficients (DSC), and were consistently higher for NA8-AF8
compared to NA1-AF1 strategy, for both simulated and real cyclic motions
(P<0.001). Both acquisition-reconstruction strategies were validated in vivo in
mice (n=2) injected with perfluoropolyether. These images displayed a sharper
delineation of the liver with the NA8-AF8 strategy than with the NA1-AF1
strategy. In conclusion, we validated the hypothesis that in 19F MRI, the
combination of undersampling and averaging improves both the sensitivity and
the robustness against motion artifacts compared to a non-averaged
fully-sampled dataset, when both are reconstructed with compressed sensing
Fast high-resolution metabolite mapping in the rat brain using 1H-FID-MRSI at 14.1T
Magnetic resonance spectroscopic imaging (MRSI) enables the simultaneous
non-invasive acquisition of MR spectra from multiple spatial locations inside
the brain. While 1H-MRSI is increasingly used in the human brain, it is not yet
widely applied in the preclinical settings, mostly because of difficulties
specifically related to very small nominal voxel size in the rodent brain and
low concentration of brain metabolites, resulting in low signal-to-noise ratio
SNR.
In this context, we implemented a free induction decay 1H-MRSI sequence
(1H-FID-MRSI) in the rat brain at 14.1T. We combined the advantages of
1H-FID-MRSI with the ultra-high magnetic field to achieve higher SNR, coverage
and spatial resolution in the rodent brain, and developed a custom dedicated
processing pipeline with a graphical user interface: MRS4Brain toolbox.
LCModel fit, using the simulated metabolite basis-set and in-vivo measured
MM, provided reliable fits for the data at acquisition delays of 1.3 and 0.94
ms. The resulting Cram\'er-Rao lower bounds were sufficiently low (<40%) for
eight metabolites of interest, leading to highly reproducible metabolic maps.
Similar spectral quality and metabolic maps were obtained between 1 and 2
averages, with slightly better contrast and brain coverage due to increased SNR
in the latter case. Furthermore, the obtained metabolic maps were accurate
enough to confirm the previously known brain regional distribution of some
metabolites. The acquisitions proved high repeatability over time.
We demonstrated that the increased SNR and spectral resolution at 14.1T can
be translated into high spatial resolution in 1H-FID-MRSI of the rat brain in
13 minutes, using the sequence and processing pipeline described herein.
High-resolution 1H-FID-MRSI at 14.1T provided reproducible and high-quality
metabolic mapping of brain metabolites with significantly reduced technical
limitations.Comment: Dunja Simicic and Brayan Alves are joint first author