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Purpose: To demonstrate the feasibility of QSM and to show the potential of simultaneous , , and proton density (PD) mapping in the human brain at 7T based on phase-cycled balanced SSFP (bSSFP) MRI.
Methods: An algorithm was developed to estimate off-resonance frequency in multi-compartment scenarios by combining elliptic phase-cycled bSSFP signal fitting with dictionary matching. Phase-cycled bSSFP-based tissue phase and susceptibility maps were compared with multi-echo gradient-echo (MEGRE)-based maps in the brains of eight healthy subjects at 7T. Additionally, , , and PD maps were obtained from the same phase-cycled bSSFP data. To demonstrate the potential of matching scan time with MEGRE, bSSFP profiles were subsampled by 50% and resulting maps compared with the reference data.
Results: The tissue phase maps obtained from phase-cycled bSSFP data agreed well with the reference, with a mean absolute deviation of Hz in the entire brain of all subjects. The mean absolute deviation of tissue susceptibility was parts-per-billion (ppb). Susceptibility in the globus pallidus was overestimated by 67 ppb (p < 0.05), while no significant biases were observed in other regions: 3.2 ppb in putamen, 15.5 ppb in thalamus, and 11.9 ppb in caudate nucleus (all p > 0.05). Quantitative maps showed good contrast between different regions of the brain, aligning well with the literature. Profile subsampling did not significantly (p > 0.05) change the quantitative susceptibility maps.
Conclusion: The feasibility of phase-cycled bSSFP for QSM at 7T was demonstrated, with the added benefit of simultaneous , , and PD mapping, with a total scan time of ˜20 min.
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http://dx.doi.org/10.1002/mrm.30571 | DOI Listing |
Magn Reson Med
October 2025
Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Purpose: To demonstrate the feasibility of QSM and to show the potential of simultaneous , , and proton density (PD) mapping in the human brain at 7T based on phase-cycled balanced SSFP (bSSFP) MRI.
Methods: An algorithm was developed to estimate off-resonance frequency in multi-compartment scenarios by combining elliptic phase-cycled bSSFP signal fitting with dictionary matching. Phase-cycled bSSFP-based tissue phase and susceptibility maps were compared with multi-echo gradient-echo (MEGRE)-based maps in the brains of eight healthy subjects at 7T.
Sci Rep
February 2025
Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany.
To accelerate the clinical adoption of quantitative magnetic resonance imaging (qMRI), frameworks are needed that not only allow for rapid acquisition, but also flexibility, cost efficiency, and high accuracy in parameter mapping. In this study, feed-forward deep neural network (DNN)- and iterative fitting-based frameworks are compared for multi-parametric (MP) relaxometry based on phase-cycled balanced steady-state free precession (pc-bSSFP) imaging. The performance of supervised DNNs (SVNN), self-supervised physics-informed DNNs (PINN), and an iterative fitting framework termed motion-insensitive rapid configuration relaxometry (MIRACLE) was evaluated in silico and in vivo in brain tissue of healthy subjects, including Monte Carlo sampling to simulate noise.
View Article and Find Full Text PDFMagn Reson Med
April 2025
Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Purpose: To develop and validate a novel analytical approach simplifying , , proton density (PD), and off-resonance quantifications from phase-cycled balanced steady-state free precession (bSSFP) data. Additionally, to introduce a method to correct aliasing effects in undersampled bSSFP profiles.
Theory And Methods: Off-resonant-encoded analytical parameter quantification using complex linearized equations (ORACLE) provides analytical solutions for bSSFP profiles.
J Cardiovasc Magn Reson
December 2024
National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. Electronic address:
Background: Cardiac balanced steady state free precession (bSSFP) cine imaging suffers from banding and flow artifacts induced by off-resonance. The work aimed to develop a twofold phase cycling sequence with a neural network-based reconstruction (2P-SSFP+Network) for a joint suppression of banding and flow artifacts in cardiac cine imaging.
Methods: A dual-encoder neural network was trained on 1620 pairs of phase-cycled left ventricular (LV) cine images collected from 18 healthy subjects.
Phys Med Biol
June 2024
Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America.
The objective of this work is to: (1) demonstrate fluorine-19 (F) MRI on a 3T clinical system with a large field of view (FOV) multi-channel torso coil (2) demonstrate an example parameter selection optimization for aF agent to maximize the signal-to-noise ratio (SNR)-efficiency for spoiled gradient echo (SPGR), balanced steady-state free precession (bSSFP), and phase-cycled bSSFP (bSSFP-C), and (3) validate detection feasibility intissues.Measurements were conducted on a 3.0T Discovery MR750w MRI (GE Healthcare, USA) with an 8-channelH/F torso coil (MRI Tools, Germany).
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