Matthew R. Orton1, James A. d'Arcy2, Keiko Miyazaki2, Nina Tunariu, 23, David J. Collins, 23, Martin O. Leach2
1CR-UK and EPSRC Cancer Imaging Centre , Institute of Cancer Research, Sutton, Surrey, United Kingdom; 2CR-UK and EPSRC Cancer Imaging Centre, Institute of Cancer Research, Sutton, Surrey, United Kingdom; 3Clinical MRI Unit, Royal Marsden Hospital, Sutton, Surrey, United Kingdom
First-pass curves from DSC-MRI data can be characterized by fitting them to a model, from which summary parameters can be derived in this case the procedure is effectively a de-noising operation. A less widely used application is to fit a model that includes specific parameters describing the tissue properties, in a similar manner to that routinely used with DCE-MRI data. Either way, the success of the technique depends on how well the model describes the data. We propose a novel model to describe DSC-MRI first-pass data, and demonstrate that it gives improved fits compared with two established models.
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