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 Cao^4,5, Andrey Fedorov⁶, Laura Bell⁷, C. Chad Quarles⁷, Melissa Prah², Kathleen Schmainda², Stefanie Hectors⁸, Bachir Taouli⁸, Eve LoCastro⁹, Yousef Mazaheri^9,10, Amita Shukla-Dave^9,10, 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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