Abstract #1148

Image-Space Self-Navigation for Respiratory Motion Compensation in 2D Axial Radial Free-Breathing MRE of the Liver

Timoteo I. Delgado^1,2, Sevgi Gokce Kafali^1,3, Shu-Fu Shih^1,3, Timothy R. Adamos⁴, Shahnaz Ghahremani¹, Kara L. Calkins⁵, Xiaodong Zhong⁶, Vibhas Deshpande⁷, Bradley D. Bolster Jr.⁸, and Holden H. Wu^1,2,3

¹Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States, ²Physics and Biology in Medicine, University of California Los Angeles, Los Angeles, CA, United States, ³Bioengineering, University of California Los Angeles, Los Angeles, CA, United States, ⁴Gastroenterology, University of California Los Angeles, Los Angeles, CA, United States, ⁵Pediatrics, University of California Los Angeles, Los Angeles, CA, United States, ⁶Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States, ⁷Siemens Medical Solutions USA, Inc., Austin, TX, United States, ⁸Siemens Medical Solutions USA, Inc., Salt Lake City, UT, United States

Synopsis

Keywords: Motion Correction, LiverPrevious work has proposed self-navigated golden-angle (GA) radial free-breathing (FB) MR elastography (MRE) of the liver. This work employed a standard DC-based motion compensation framework that proved suboptimal. Here we propose an image-space based motion-compensation framework for 2D free-breathing radial MRE. The proposed method is compared to the standard DC-based method by measuring the signal-to-noise (SNR) after self-navigated motion-compensation by each method (8 subjects). The median (interquartile range) SNR across subjects was 4.8 (3.6-5.7) and 6.8 (6.3-7.5) for the standard and proposed methods, respectively. Inclusion of image-space data may allow for more robust motion compensation for 2D radial axial acquisitions.

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