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Abstract #3454

Diffusion Tensor Imaging of the Brain on a Prototype 0.55T System using SNR-Enhancing Joint Reconstruction

Hao-Ting Kung1, Sophia X. Cui2, Jonas T. Kaplan3, Anand A. Joshi1, Richard M. Leahy1, Krishna S. Nayak1, Jay Acharya4, and Justin P. Haldar1,3
1Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, United States, 2Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States, 3Brain and Creativity Institute, University of Southern California, Los Angeles, CA, United States, 4Department of Clinical Radiology, University of Southern California, Los Angeles, CA, United States

Synopsis

There has been substantial recent interest in MRI systems with lower $$$B_0$$$ field strengths, which can improve the value and accessibility of MRI. This work investigates the performance of diffusion tensor imaging on a prototype whole-body 0.55T system equipped with high-performance shielded gradients. Although the images suffer from noise contamination when using conventional image reconstruction techniques, we demonstrate that the use of an SNR-enhancing joint reconstruction technique can substantially reduce noise concerns, enabling high quality diffusion tensor imaging results. In addition, compared to diffusion data acquired on a conventional 3T scanner, the 0.55T images demonstrate substantially reduced susceptibility-induced geometric distortions.

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Keywords