Journal Article10.1016/j.mri.2024.03.023
Phase-sensitive deep reconstruction method for rapid multiparametric MR fingerprinting and quantitative susceptibility mapping in the brain.
Jessica A. Martinez,Victoria Yu,Kathryn R. Tringale,Ricardo Otazo,Ouri Cohen +4 more
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TL;DR: A novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) enables rapid multiparametric Magnetic Resonance Fingerprinting and quantitative susceptibility mapping in the brain, simultaneously quantifying T1, T2, B1+, phase, and QSM maps within 2 minutes and 1 second of acquisition and reconstruction time.
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Abstract: This study explores the potential of Magnetic Resonance Fingerprinting (MRF) with a novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) for simultaneous quantification of T1, T2, Proton Density, B1+, phase and quantitative susceptibility mapping (QSM). Data were acquired at 3 T in vitro and in vivo using an optimized EPI-based MRF sequence. Phantom experiments were conducted using a standardized phantom for T1 and T2 maps and a custom-made agar-based gadolinium phantom for B1 and QSM maps. In vivo experiments included five healthy volunteers and one patient diagnosed with brain metastasis. PSDRONE maps were compared to reference maps obtained through standard imaging sequences. Total scan time was 2 min for 32 slices and a resolution of [1 mm, 1 mm, 4.5 mm]. The reconstruction of T1, T2, Proton Density, B1+ and phase maps were reconstructed within 1 s. In the phantoms, PS-DRONE analysis presented accurate and strongly correlated T1 and T2 maps (r = 0.99) compared to the reference maps. B1 maps from PS-DRONE showed slightly higher values, though still correlated (r = 0.6) with the reference. QSM values showed a small bias but were strongly correlated (r = 0.99) with reference data. In the in vivo analysis, PS-DRONE-derived T1 and T2 values for gray and white matter matched reference values in healthy volunteers. PS-DRONE B1 and QSM maps showed strong correlations with reference values. The PS-DRONE network enables concurrent acquisition of T1, T2, PD, B1+, phase and QSM maps, within 2 min of acquisition time and 1 s of reconstruction time.
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Citations
<scp>Microstructure‐Informed Myelin Mapping</scp> (<scp>MIMM</scp>) from routine multi‐echo gradient echo data using multiscale physics modeling of iron and myelin effects and <scp>QSM</scp>
Mert Şişman,Thanh D. Nguyen,Alexandra Roberts,Dominick Romano,Alexey Dimov,İlhami Kovanlıkaya,Pascal Spincemaille,Yi Wang +7 more
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References
•Posted Content
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke,Sam Gross,Francisco Massa,Adam Lerer,James Bradbury,Gregory Chanan,Trevor Killeen,Zeming Lin,Natalia Gimelshein,Luca Antiga,Alban Desmaison,Andreas Kopf,Edward Z. Yang,Zachary DeVito,Martin Raison,Alykhan Tejani,Sasank Chilamkurthy,Benoit Steiner,Lu Fang,Junjie Bai,Soumith Chintala +20 more
TL;DR: PyTorch as discussed by the authors is a machine learning library that provides an imperative and Pythonic programming style that makes debugging easy and is consistent with other popular scientific computing libraries, while remaining efficient and supporting hardware accelerators such as GPUs.
25.9K
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TL;DR: An automated method for segmenting magnetic resonance head images into brain and non‐brain has been developed and described and examples of results and the results of extensive quantitative testing against “gold‐standard” hand segmentations, and two other popular automated methods.
11K
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TL;DR: An approach to data acquisition, post-processing and visualization that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue is introduced—which is termed ‘magnetic resonance fingerprinting’ (MRF).
Correction for geometric distortion in echo planar images from B0 field variations
Peter Jezzard,Robert S. Balaban +1 more
TL;DR: A method is described for the correction of geometric distortions occurring in echo planar images, caused in large part by static magnetic field inho‐mogeneities, leading to pixel shifts, particularly in the phase encode direction.
1.5K
Actual flip-angle imaging in the pulsed steady state: a method for rapid three-dimensional mapping of the transmitted radiofrequency field.
TL;DR: The AFI method overcomes the limitation of previous methods that required long relaxation delays between sequence repetitions and is useful for time‐efficient whole‐body B1 mapping and correction of T1 maps obtained using a variable FA technique in the presence of nonuniform RF excitation.
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