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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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