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ADEPT: Accurate Diffusion Echo-Planar imaging with multi-contrast shoTs
被引:3
|作者:
Shafieizargar, Banafshe
[1
,2
]
Jeurissen, Ben
[1
,2
]
Poot, Dirk H. J.
[3
]
Klein, Stefan
[3
]
Van Audekerke, Johan
[2
,4
]
Verhoye, Marleen
[2
,4
]
den Dekker, Arnold J.
[1
,2
]
Sijbers, Jan
[1
,2
]
机构:
[1] Univ Antwerp, Dept Phys, Iimec Vis Lab, Univ Pl 1,DN 103, B-2610 Antwerp, Belgium
[2] Univ Antwerp, NEURO Res Ctr Excellence, Antwerp, Belgium
[3] Erasmus MC, Dept Radiol & Nucl Med, Biomed Imaging Grp Rotterdam, Rotterdam, Netherlands
[4] Univ Antwerp, Dept Biomed Sci, Bioimaging Lab, Antwerp, Belgium
基金:
欧盟地平线“2020”;
关键词:
diffusion MRI;
model-based reconstruction;
multi-shot EPI;
phase correction;
QMRI;
MODEL-BASED RECONSTRUCTION;
RICIAN DISTRIBUTION;
WEIGHTED-MRI;
RESOLUTION;
MOTION;
CONVERGENCE;
ARTIFACTS;
SENSE;
EPI;
D O I:
10.1002/mrm.29398
中图分类号:
R8 [特种医学];
R445 [影像诊断学];
学科分类号:
1002 ;
100207 ;
1009 ;
摘要:
Purpose To introduce a novel imaging and parameter estimation framework for accurate multi-shot diffusion MRI. Theory and Methods We propose a new framework called ADEPT (Accurate Diffusion Echo-Planar imaging with multi-contrast shoTs) that enables fast diffusion MRI by allowing diffusion contrast settings to change between shots in a multi-shot EPI acquisition (i.e., intra-scan modulation). The framework estimates diffusion parameter maps directly from the acquired intra-scan modulated k-space data, while simultaneously accounting for shot-to-shot phase inconsistencies. The performance of the estimation framework is evaluated using Monte Carlo simulation studies and in-vivo experiments and compared to that of reference methods that rely on parallel imaging for shot-to-shot phase correction. Results Simulation and real-data experiments show that ADEPT yields more accurate and more precise estimates of the diffusion metrics in multi-shot EPI data in comparison with the reference methods. Conclusion ADEPT allows fast multi-shot EPI diffusion MRI without significantly degrading the accuracy and precision of the estimated diffusion maps.
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页码:396 / 410
页数:15
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