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. Haldar^1,3

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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here