364 research outputs found
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
Development of whole-heart myocardial perfusion magnetic resonance imaging
Myocardial perfusion imaging is of huge importance for the detection of
coronary artery disease (CAD), one of the leading causes of morbidity
and mortality worldwide, as it can provide non-invasive detection at the
early stages of the disease. Magnetic resonance imaging (MRI) can assess
myocardial perfusion by capturing the rst-pass perfusion (FPP) of a
gadolinium-based contrast agent (GBCA), which is now a well-established
technique and compares well with other modalities. However, current MRI
methods are restricted by their limited coverage of the left ventricle. Interest
has therefore grown in 3D volumetric \whole-heart" FPP by MRI, although
many challenges currently limit this. For this thesis, myocardial perfusion
assessment in general, and 3D whole-heart FPP in particular, were reviewed
in depth, alongside MRI techniques important for achieving 3D FPP. From
this, a 3D `stack-of-stars' (SOS) FPP sequence was developed with the aim
of addressing some current limitations. These included the breath-hold
requirement during GBCA rst-pass, long 3D shot durations corrupted by
cardiac motion, and a propensity for artefacts in FPP. Parallel imaging and
compressed sensing were investigated for accelerating whole-heart FPP, with
modi cations presented to potentially improve robustness to free-breathing.
Novel sequences were developed that were capable of individually improving
some current sequence limits, including spatial resolution and signal-to-noise
ratio, although with some sacri ces. A nal 3D SOS FPP technique was
developed and tested at stress during free-breathing examinations of CAD
patients and healthy volunteers. This enabled the rst known detection of an
inducible perfusion defect with a free-breathing, compressed sensing, 3D FPP
sequence; however, further investigation into the diagnostic performance is
required. Simulations were performed to analyse potential artefacts in 3D
FPP, as well as to examine ways towards further optimisation of 3D SOS
FPP. The nal chapter discusses some limitations of the work and proposes
opportunities for further investigation.Open Acces
Non-Rigid Groupwise Registration for Motion Estimation and Compensation in Compressed Sensing Reconstruc- tion of Breath-Hold Cardiac Cine MRI
Purpose: Compressed sensing methods with motion estimation and compensation techniques
have been proposed for the reconstruction of accelerated dynamic MRI. However, artifacts that
naturally arise in compressed sensing reconstruction procedures hinder the estimation of motion
from reconstructed images, especially at high acceleration factors. This work introduces a robust
groupwise non-rigid motion estimation technique applied to the compressed sensing reconstruction
of dynamic cardiac cine MRI sequences.
Theory and Methods: A spatio-temporal regularized, groupwise, non-rigid registration method
based on a B-splines deformation model and a least squares metric is used to estimate and to
compensate the movement of the heart in breath-hold cine acquisitions and to obtain a quasi-static
sequence with highly sparse representation in temporally transformed domains.
Results: Short axis in vivo datasets are used for validation, both original multi-coil as well as
DICOM data. Fully sampled data were retrospectively undersampled with various acceleration
factors and reconstructions were compared with the two well-known methods k-t FOCUSS and
MASTeR. The proposed method achieves higher signal to error ratio and structure similarity index
for medium to high acceleration factors.
Conclusions: Reconstruction methods based on groupwise registration show higher quality recon-
structions for cardiac cine images than the pairwise counterparts tested
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