Abstract #0568
Rapid Free-Breathing Dynamic Contrast-Enhanced MRI Using Motion-Resolved Compressed Sensing
Li Feng 1 , Hersh Chandarana 1 , Davide Piccini 2,3 , Justin Ream 1 , Daniel K Sodickson 1 , and Ricardo Otazo 1
1
Center for Advanced Imaging Innovation and
Research (CAI2R), Department of Radiology, New York
University School of Medicine, New York, NY, United
States,
2
Advanced
Clinical Imaging Technology, Siemens Healthcare IM BM
PI, Lausanne, Switzerland,
3
Department
of Radiology, University Hospital (CHUV) and University
of Lausanne (UNIL) / Center for Biomedical Imaging (CIBM),
Lausanne, Switzerland
This work proposes a novel framework for free-breathing
3D golden-angle radial dynamic contrast-enhanced MRI
that employs respiratory motion sorting instead of
explicit motion correction. The continuously acquired
k-space data are sorted into different
contrast-enhancement phases at multiple respiratory
states using the self-navigation properties of radial
imaging. The undersampled five-dimensional dataset
(x-y-z-contrast-respiration) is reconstructed using a
multidimensional compressed sensing approach that
exploits sparsity along both contrast-enhancement and
respiratory motion dimensions. The performance of the
proposed approach is demonstrated for abdominal imaging
using two types of 3D golden-angle radial sampling
schemes that are based on stack-of-stars and spiral
phyllotaxis patterns.
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