Speaker: Neil M. Rofsky, MD, FACR
Title: Controversies and Opportunities in Prostate MRI
The Department of Medical Imaging is pleased to have Neil M. Rofsky, MD, FACR, presenting at our Grand Rounds on Wednesday, October 18th, at 12:00 pm in the College of Medicine, Room 3117.
Dr. Rofsky is Professor and Chair of UT Southwestern’s Department of Radiology and the Effie and Wofford Cain Distinguished Chair in Diagnostic Imaging. He also serves as Co-Director of Translational Research for the Advanced Imaging Research Center (AIRC), a collaboration of UT Southwestern and the University of Texas at Dallas.
A native of New York, Dr. Rofsky received his bachelor’s degree in biochemistry from the University of Maryland and his medical degree from New York Medical College. He then completed an internship in internal medicine at Middlesex University Hospita and a fellowship in nuclear medicine at the University of Utah Medical Center. His residency in radiology and fellowships in abdominal imaging and magnetic resonance imaging were completed at New York University Medical Center, where he was mentored by Morton Bosniak, MD, Alec J. Megibow, MD, MPH, FACR, and Jeffrey C. Weinreb, MD, FACR, FISMRM, FSCBT/MR.
Before joining the faculty of UT Southwestern, Dr. Rofsky served as Chief of MRI at Beth Israel Deaconess Medical Center, Boston, and as Professor of Radiology at Harvard Medical School.
Abstract: Prostate cancer is a common but heterogeneous disease, and most men with the disease will ultimately die of other causes. Multiparametric MR imaging (mpMRI) is the most accurate imaging technique for prostate cancer detection and staging, and contributes to an improved individualized risk assessment and management strategy. With mpMRI, the anatomic details from high-resolution T2-weighted images are supplemented by physiologic information from diffusion-weighted and dynamic contrast material–enhanced images for improved performance over any one of these techniques alone. By integrating mpMRI information into a variety of biopsy approaches, the yield of relevant cancer detection can be significantly improved.
College of Medicine, Room 3117