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Abstract #3598

Multi-site concordance of diffusion weighted imaging derived metrics, a comparison of fitting algorithms for differentiating whole-mount, pathologically confirmed, prostate cancer of differing Gleason patterns

Peter S LaViolette1, Sean D McGarry2, John D Bukowy1, Allison K Lowman1, Anjishnu Banerjee3, Dariya Malyarenko4, Tom Chenevert4, Yue Cao4,5, Andrey Fedorov6, Laura Bell7, C. Chad Quarles7, Melissa Prah2, Kathleen Schmainda2, Stefanie Hectors8, Bachir Taouli8, Eve LoCastro9, Yousef Mazaheri9,10, Amita Shukla-Dave9,10, Thomas Yankeelov11, David A Hormuth II11, Ananth J Madhuranthakam12, Keith Hulsey12, Kurt Li13, Wei Huang13, Mark Muzi14, Kenneth Jacobsohn15, Mark Hohenwalter1, Petar Duvnjak1, Michael Griffin1, William See15, Marja Nevalainen16, and Kenneth A Iczkowski16

1Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, 2Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States, 3Biostatistics, Medical College of Wisconsin, Milwaukee, WI, United States, 4Radiology, University of Michigan, Ann Arbor, MI, United States, 5Radiation Oncology, University of Michigan, Ann Arbor, MI, United States, 6Radiology, Brigham and Women's Hospital, Boston, MA, United States, 7Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States, 8Radiology, Mount Sinai, New York, NY, United States, 9Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 10Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 11Institute for Computational Engineering and Sciences, University of Texas, Austin, TX, United States, 12Radiology, University of Texas Southwestern Medical Center, Dallas, TX, United States, 13Advanced Imaging Research Center, Oregon Health Sciences University, Portland, OR, United States, 14Department of Radiology, University of Washington, Seattle, WA, United States, 15Urological Surgery, Medical College of Wisconsin, Milwaukee, WI, United States, 16Pathology, Medical College of Wisconsin, Milwaukee, WI, United States

We present a multi-site study measuring the ability of various software platforms to fit diffusion weighted imaging (DWI) models for differentiating prostate cancer (PCA) of different Gleason patterns. A dataset of DWI collected from 33 PCA patients was distributed to ten collaborating groups who fit the multi-b DWI models with onsite software and submitted the derived parametric maps to a central analysis site. Each map was aligned to the T2-weighted image and compared to pathologist annotations of whole-mount prostate samples. A statistical analysis was performed for similarity of the quantitative values, and the ability of each metric to differentiate PCA.

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