Abstract #0671

Novel Informatics Modeling of Magnetic Resonance Imaging Metrics for Characterizing Prostate Lesions with Pathology Correlation.

Katarzyna J. Macura^1,2, Vishwa Parekh³, Seyed Saeid ⁴, and Michael A. Jacobs^1,2

¹The Russell H. Morgan Dept of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, ³Computer Science, The Johns Hopkins University, Baltimore, MD, United States, ⁴Dept of Radiology, University of Minnesota, Minneapolis, United States

Precision medicine is increasingly being used in radiological applications. Advanced machine learning coupled with informatics modeling of clinical and radiological variables can provide the foundation to relate to precision medicine in patients with prostate cancer. We test our modeling using multiparametric prostate MR imaging (mpMRI) and MR-guided prostate biopsy with magnetic resonance-transrectal ultrasound (MR-TRUS) fusion to correlate the imaging features with histopathological results.

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