1,461 research outputs found
Rapid three-dimensional multiparametric MRI with quantitative transient-state imaging
Novel methods for quantitative, transient-state multiparametric imaging are
increasingly being demonstrated for assessment of disease and treatment
efficacy. Here, we build on these by assessing the most common Non-Cartesian
readout trajectories (2D/3D radials and spirals), demonstrating efficient
anti-aliasing with a k-space view-sharing technique, and proposing novel
methods for parameter inference with neural networks that incorporate the
estimation of proton density. Our results show good agreement with gold
standard and phantom references for all readout trajectories at 1.5T and 3T.
Parameters inferred with the neural network were within 6.58% difference from
the parameters inferred with a high-resolution dictionary. Concordance
correlation coefficients were above 0.92 and the normalized root mean squared
error ranged between 4.2% - 12.7% with respect to gold-standard phantom
references for T1 and T2. In vivo acquisitions demonstrate sub-millimetric
isotropic resolution in under five minutes with reconstruction and inference
times < 7 minutes. Our 3D quantitative transient-state imaging approach could
enable high-resolution multiparametric tissue quantification within clinically
acceptable acquisition and reconstruction times.Comment: 43 pages, 12 Figures, 5 Table
Zero-DeepSub: Zero-Shot Deep Subspace Reconstruction for Rapid Multiparametric Quantitative MRI Using 3D-QALAS
Purpose: To develop and evaluate methods for 1) reconstructing
3D-quantification using an interleaved Look-Locker acquisition sequence with T2
preparation pulse (3D-QALAS) time-series images using a low-rank subspace
method, which enables accurate and rapid T1 and T2 mapping, and 2) improving
the fidelity of subspace QALAS by combining scan-specific deep-learning-based
reconstruction and subspace modeling. Methods: A low-rank subspace method for
3D-QALAS (i.e., subspace QALAS) and zero-shot deep-learning subspace method
(i.e., Zero-DeepSub) were proposed for rapid and high fidelity T1 and T2
mapping and time-resolved imaging using 3D-QALAS. Using an ISMRM/NIST system
phantom, the accuracy of the T1 and T2 maps estimated using the proposed
methods was evaluated by comparing them with reference techniques. The
reconstruction performance of the proposed subspace QALAS using Zero-DeepSub
was evaluated in vivo and compared with conventional QALAS at high reduction
factors of up to 9-fold. Results: Phantom experiments showed that subspace
QALAS had good linearity with respect to the reference methods while reducing
biases compared to conventional QALAS, especially for T2 maps. Moreover, in
vivo results demonstrated that subspace QALAS had better g-factor maps and
could reduce voxel blurring, noise, and artifacts compared to conventional
QALAS and showed robust performance at up to 9-fold acceleration with
Zero-DeepSub, which enabled whole-brain T1, T2, and PD mapping at 1 mm
isotropic resolution within 2 min of scan time. Conclusion: The proposed
subspace QALAS along with Zero-DeepSub enabled high fidelity and rapid
whole-brain multiparametric quantification and time-resolved imaging.Comment: 17 figures, 3 table
Current Applications and Future Development of Magnetic Resonance Fingerprinting in Diagnosis, Characterization, and Response Monitoring in Cancer
Magnetic resonance imaging (MRI) has enabled non-invasive cancer diagnosis, monitoring, and management in common clinical settings. However, inadequate quantitative analyses in MRI continue to limit its full potential and these often have an impact on clinicians' judgments. Magnetic resonance fingerprinting (MRF) has recently been introduced to acquire multiple quantitative parameters simultaneously in a reasonable timeframe. Initial retrospective studies have demonstrated the feasibility of using MRF for various cancer characterizations. Further trials with larger cohorts are still needed to explore the repeatability and reproducibility of the data acquired by MRF. At the moment, technical difficulties such as undesirable processing time or lack of motion robustness are limiting further implementations of MRF in clinical oncology. This review summarises the latest findings and technology developments for the use of MRF in cancer management and suggests possible future implications of MRF in characterizing tumour heterogeneity and response assessment
Highly efficient MRI through multi-shot echo planar imaging
Multi-shot echo planar imaging (msEPI) is a promising approach to achieve
high in-plane resolution with high sampling efficiency and low T2* blurring.
However, due to the geometric distortion, shot-to-shot phase variations and
potential subject motion, msEPI continues to be a challenge in MRI. In this
work, we introduce acquisition and reconstruction strategies for robust,
high-quality msEPI without phase navigators. We propose Blip Up-Down
Acquisition (BUDA) using interleaved blip-up and -down phase encoding, and
incorporate B0 forward-modeling into Hankel structured low-rank model to enable
distortion- and navigator-free msEPI. We improve the acquisition efficiency and
reconstruction quality by incorporating simultaneous multi-slice acquisition
and virtual-coil reconstruction into the BUDA technique. We further combine
BUDA with the novel RF-encoded gSlider acquisition, dubbed BUDA-gSlider, to
achieve rapid high isotropic-resolution MRI. Deploying BUDA-gSlider with
model-based reconstruction allows for distortion-free whole-brain 1mm isotropic
T2 mapping in about 1 minute. It also provides whole-brain 1mm isotropic
diffusion imaging with high geometric fidelity and SNR efficiency. We finally
incorporate sinusoidal wave gradients during the EPI readout to better use coil
sensitivity encoding with controlled aliasing.Comment: 13 pages, 10 figure
Time-efficient, High Resolution 3T Whole Brain Quantitative Relaxometry using 3D-QALAS with Wave-CAIPI Readouts
Purpose: Volumetric, high resolution, quantitative mapping of brain tissues
relaxation properties is hindered by long acquisition times and SNR challenges.
This study, for the first time, combines the time efficient wave-CAIPI readouts
into the 3D-QALAS acquisition scheme, enabling full brain quantitative T1, T2
and PD maps at 1.15 isotropic voxels in only 3 minutes. Methods: Wave-CAIPI
readouts were embedded in the standard 3d-QALAS encoding scheme, enabling full
brain quantitative parameter maps (T1, T2 and PD) at acceleration factors of
R=3x2 with minimum SNR loss due to g-factor penalties. The quantitative maps
using the accelerated protocol were quantitatively compared against those
obtained from conventional 3D-QALAS sequence using GRAPPA acceleration of R=2
in the ISMRM NIST phantom, and ten healthy volunteers. To show the feasibility
of the proposed methods in clinical settings, the accelerated wave-CAIPI
3D-QALAS sequence was also employed in pediatric patients undergoing clinical
MRI examinations. Results: When tested in both the ISMRM/NIST phantom and 7
healthy volunteers, the quantitative maps using the accelerated protocol showed
excellent agreement against those obtained from conventional 3D-QALAS at R=2.
Conclusion: 3D-QALAS enhanced with wave-CAIPI readouts enables time-efficient,
full brain quantitative T1, T2 and PD mapping at 1.15 in 3 minutes at R=3x2
acceleration. When tested on the NIST phantom and 7 healthy volunteers, the
quantitative maps obtained from the accelerated wave-CAIPI 3D-QALAS protocol
showed very similar values to those obtained from the standard 3D-QALAS (R=2)
protocol, alluding to the robustness and reliability of the proposed methods.
This study also shows that the accelerated protocol can be effectively employed
in pediatric patient populations, making high-quality high-resolution full
brain quantitative imaging feasible in clinical settings
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