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Abstract #1871

5D reconstruction exploiting spatial-motion-echo sparsity for accelerated free-breathing liver R2*/QSM

Mungsoo Kang1, Ricardo Otazo1,2, Gerald Behr2, and Youngwook Kee1
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 2Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States

Synopsis

Keywords: Image Reconstruction, Image Reconstruction, QSM

Motivation: Conventional compressed sensing-based 4D respiratory motion-resolved image reconstruction techniques are limited in their ability to utilize correlations between echoes for free-breathing 3D multi-echo liver MRI, which is inherently a 5D imaging problem.

Goal(s): Develop a 5D reconstruction algorithm to jointly exploit correlations between echoes and motion states.

Approach: 5D reconstruction with sparsity constraints along the motion and echo dimensions was developed to reconstruct retrospectively undersampled k-space data and compared with the 4D reconstruction on one volunteer and one patient.

Results: Compared to the 4D reconstruction, the proposed reconstruction showed comparable image quality to the reference (undersampling factor=1) and more reliable liver R2*/QSM values.

Impact: Using the proposed 5D image reconstruction, the scan time of free-breathing 3D multi-echo liver MRI for R2*/QSM can be reduced while preserving image quality and providing reliable R2*/QSM values.

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Keywords