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Abstract #5640

Online Free-Breathing Liver Perfusion Imaging Using Parallel Computing and the Gadgetron Framework

Kun Yang1, Yong Chen2, Satyam Ghodasara3, Wei-Ching Lo1, Yun Jiang2, Nicole Seiberlich1, Katherine Wright2, and Vikas Gulani1,2

1Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 2Dept. of Radiology, University Hospitals of Cleveland, Cleveland, OH, United States, 3School of Medicine, Case Western Reserve University, Cleveland, OH, United States

Accelerated image acquisition, advanced reconstruction and registration methods, and perfusion modeling have recently enabled free-breathing and quantitative 4D DCE MRI in the liver. However, the reconstruction, registration and model fitting steps are performed offline as they are time consuming; each data set takes more than a day to analyze. This makes quantitative 3D liver perfusion unsuitable for clinical deployment. We propose using a GPU-based Gadgetron framework for parallelized and near-immediate provision of all data, including a Spiral GRAPPA reconstruction, non-rigid image registration, and pharmacokinetic modeling using a dictionary-based approach. This approach reduces the reconstruction time from hours to minutes.

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