Shawyon Chase Rohani1,2, Cara Morin1, Xiaodong Zhong3, Stephan Kannengiesser4, Joseph Holtrop1, Ayaz Khan1, Ralf Loeffler1,5, Claudia Hillenbrand1,5, Jane Hankins6, and Aaryani Tipirneni Sajja1,2
1Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, United States, 2Department of Biomedical Engineering, The University of Memphis, Memphis, TN, United States, 3Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States, 4MR Application Development, Siemens Healthcare, Erlangen, Germany, 5University of New South Wales, Sydney, Australia, 6Department of Hematology, St. Jude Children's Research Hospital, Memphis, TN, United States
1Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, United States, 2Department of Biomedical Engineering, The University of Memphis, Memphis, TN, United States, 3Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States, 4MR Application Development, Siemens Healthcare, Erlangen, Germany, 5University of New South Wales, Sydney, Australia, 6Department of Hematology, St. Jude Children's Research Hospital, Memphis, TN, United States
The free-breathing 3D Radial Dixon technique produced
sharper images with less motion artifacts and the R2* values showed an
excellent agreement with 3D Cartesian Dixon and biopsy-calibrated 2D GRE
acquisition.
Fig. 1 - Magnitude images of a 25 year old sedated patient obtained with a) 2D GRE, b) 3D Cartesian Dixon, and c) Free-breathing 3D Radial Dixon acquisitions. The 2D GRE and 3D Dixon Cartesian-based techniques exhibited motion artifacts (white arrows) whereas free-breathing 3D Radial Dixon showed noticeably less motion artifacts.
Fig. 2 - Linear regression analysis of
the HIC values obtained using (a) 3D Cartesian Dixon vs 3D Radial Dixon (b), 3D
Cartesian Dixon vs 2D GRE method, and (c) 3D Radial Dixon vs 2D GRE methods.