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Abstract #3836

Development of Quantitative Multi-Parametric MRI Models for Prostate Cancer Assessment using Registered Correlative Pathology

Gregory J. Metzger 1 , Chaitanya Kalavagunta 1 , Stephen C Schmechel 2 , Patrick J. Bolan 1 , Badrinath Konety 3 , Benjamin Spilseth 4 , Christopher A. Warlick 3 , and Joseph S. Koopmeiners 5

1 Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, 2 Department of Pathology, University of Washington, Washington, United States, 3 Department of Urologic Surgery, University of Minnesota, Minneapolis, MN, United States, 4 Department of Radiology, University of Minnesota, Minneapolis, MN, United States, 5 Division of Biostatistics, University of Minnesota, Minneapolis, MN, United States

A process is presented for generating critical correlative pathology for developing predictive models from voxel-wise mpMRI data based on mapping regions of disease from assembles pathology to in vivo MRI. The models generated from this novel data show improved performance over single quantitative MRI parameters for detection. The generation of composite biomarker maps has the potential to improve the use of mpMRI in the management of prostate cancer by providing a quantitative means to assess and monitor disease.

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