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Investigation of undersampling and reconstruction algorithm dependence on respiratory correlated 4D-MRI for online MR-guided radiation therapy. Phys Med Biol 2017 04 21;62(8):2910-2921



Pubmed ID




Scopus ID

2-s2.0-85016933762   37 Citations


The purpose of this work is to investigate the effects of undersampling and reconstruction algorithm on the total processing time and image quality of respiratory phase-resolved 4D MRI data. Specifically, the goal is to obtain quality 4D-MRI data with a combined acquisition and reconstruction time of five minutes or less, which we reasoned would be satisfactory for pre-treatment 4D-MRI in online MRI-gRT. A 3D stack-of-stars, self-navigated, 4D-MRI acquisition was used to scan three healthy volunteers at three image resolutions and two scan durations. The NUFFT, CG-SENSE, SPIRiT, and XD-GRASP reconstruction algorithms were used to reconstruct each dataset on a high performance reconstruction computer. The overall image quality, reconstruction time, artifact prevalence, and motion estimates were compared. The CG-SENSE and XD-GRASP reconstructions provided superior image quality over the other algorithms. The combination of a 3D SoS sequence and parallelized reconstruction algorithms using computing hardware more advanced than those typically seen on product MRI scanners, can result in acquisition and reconstruction of high quality respiratory correlated 4D-MRI images in less than five minutes.

Author List

Mickevicius NJ, Paulson ES


Nikolai J. Mickevicius PhD Assistant Professor in the Radiology department at Medical College of Wisconsin
Eric Paulson PhD Associate Professor in the Radiation Oncology department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Healthy Volunteers
Imaging, Three-Dimensional
Magnetic Resonance Imaging
Online Systems
Radiographic Image Interpretation, Computer-Assisted
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Image-Guided
Respiratory-Gated Imaging Techniques