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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