Abstract #0823
Quantification of Chemical-shift Apparent Diffusion Coefficients (ADC) of Fat and Water Signals Using Interleaved EPI based IDEAL Method and Multiplexed Parallel Image Reconstruction: Application to studies of parotid glands
Hing-Chiu Chang 1 , Chun-Jung Juan 2 , Hsiao-Wen Chung 3 , Shayan Guhaniyogi 1 , and Nan-Kuei Chen 1
1
Brain Imaging and Analysis Center, Duke
University Medical Center, Durham, North Carolina,
United States,
2
Department
of Radiology, Tri-Service General Hospital, Taipei,
Taiwan,
3
Graduate
Institute of Biomedical Electronics and Bioinformatics,
National Taiwan University, Taipei, Taiwan
The IDEAL based fat-water separation has not yet been
applied to chemical-shift ADC mapping, because of
several major technical challenges. Such as original
IDEAL framework may be not compatible with EPI data in
presence of significant pixel displacement due to
chemical-shift effect. To address these technical
challenges to enable chemical-shift ADC mapping, we
first evaluate the IDEAL framework in the presence of
large chemical-shift effect using both original and our
modified frameworks. Second, we integrated 1)
interleaved EPI sequence and 2) multiplexed sensitivity
encoding (MUSE) to reliably enable quantification of
chemical-shifting ADC mapping in parotid glands.
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