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Sadhna Verma, MD, FSAR

Sadhna Verma, MD, FSAR

Professor of Radiology at the University of Cincinnati College of Medicine

Cincinnati, Ohio

Sadhna Verma, MD, FSAR, is a Professor of Radiology, Radiation Oncology and Urology at University of Cincinnati Medical Center. She is also the Director of Prostate Imaging Program, Associate Chair of Quality and Performance Improvement at the Prostate Cancer Midwest Center of Excellence, as well as the Director Prostate Cancer Imaging Program at the U.S. Department of Veterans Affairs.

Dr. Verma completed a diagnostic radiology residency at the University of Cincinnati and a fellowship in Abdominal Imaging from the Johns Hopkins Medical Center. Dr. Verma’s clinical expertise and current clinical research interests are in genitourinary MR imaging. She has published extensively and delivered numerous invited lectures on the topic of prostate MRI and MR-Guided Interventional Procedures.

Disclosures:

Talks by Sadhna Verma, MD, FSAR

Prostate MRI for Dummies

Sadhna Verma, MD, FSAR, presents an overview of the use of multiparametric MRI in evaluating the prostate. Dr. Verma begins by reviewing the three elements of a multiparametric MRI in prostate cancer treatment: T2 Weighted Imaging (T2W), Diffusion Weighted Imaging (DWI), and Dynamic Contrast Enhanced (DCE) Imaging.

Dr. Verma presents examples of T1 and T2 Weighted (T2W) MRI images, which are used to illustrate the zonal anatomy of the prostate. She notes that T1 and T2 MRI is weak when it comes to identifying problems in the transition zone.

Dr. Verma then moves to Diffusion Weighted Imaging (DWI) to measure cell diffusion as a means of locating tumors. However, she notes that DWI is not very accurate for recently-biopsied patients.

Dr. Verma concludes by briefly touching on Dynamic Contrast Enhanced (DCE) Imaging to measure tumor vascularity, and how DCE combines with T2W and DWI to give each identified lesion a PI-RADS (Prostate Imaging Reporting and Data System) score. She emphasizes that a PI-RADS score should only be used in detection of clinically significant prostate cancer, and presents examples of how prostate cancer can be identified in peripheral zones, transition zones, and extra-prostatic locations through the use of multiparametric MRI.

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