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Abstract #0667

Can Model Weighting Improve the Accuracy of DCE-MRI Parameter Estimation?

Xia Li 1 , Lori R. Arlinghaus 1 , Erin Rericha 1 , and Thomas Yankeelov 1

1 Vanderbilt University, Nashville, Tennessee, United States

Many pharmacokinetic models have been proposed for analyzing dynamic contrast enhanced MRI with different assumptions. It is difficult to select which model is most appropriate for a particular study. To address this limitation, we have taken an approach in which multiple models are weighted by a factor determined by how well they fit the data. We analyze each voxel in a DCE-MRI data set with an array of models and compute the Akaike Information Criteria for each fit. The AIC is then used to determine the statistically optimal model on a voxel-by-voxel basis.

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