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Abstract #3669

Spectrally-selective and Interleaved Water Imaging and Fat Imaging (siWIFI) for Model-free Fat Quantification

Soo Hyun Shin1, Qingbo Tang1,2, Michael Carl3, Christine B. Chung1,4, Graeme M. Bydder1, Eric Y. Chang1,4, Jiang Du1,4,5, and Yajun Ma1
1Department of Radiology, University of California, San Diego, La Jolla, CA, United States, 2Research Service, VA San Diego Healthcare System, La Jolla, CA, United States, 3GE HealthCare, San Diego, CA, United States, 4Radiology Service, VA San Diego Healthcare System, La Jolla, CA, United States, 5Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States

Synopsis

Keywords: Fat & Fat/Water Separation, Fat

Motivation: Reliable water-fat separation and quantification are of critical importance in the MRI assessment of diseases involving metabolic disruption and fat infiltration.

Goal(s): To develop a model-free approach for spectrally selective and interleaved water imaging and fat Imaging (siWIFI).

Approach: We designed a new sequence that selectively acquires water and fat signals in an interleaved fashion. This new sequence was tested on phantoms and healthy subjects.

Results: The measured fat fraction showed excellent correlation with fat concentrations of phantoms. Both phantom and healthy subject images were comparable to those from standard IDEAL scans.

Impact: Our new method, termed siWIFI, selectively images water and fat for water-fat quantification which does not require complicated post-processing. Combining with MT preparation shows the feasibility of simultaneous quantification of fat infiltration and fibrosis development.

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Keywords