Meeting Banner
Abstract #0375

Noninvasive Prostate Cancer Grading Using Diffusion MR Structural Fingerprints

Zezhong Ye1, Qingsong Yang2, Joshua Lin1, Peng Sun1, Chunyu Song1, Ajit George1, Sam E. Gary3, Jeffrey D. Viox4, Ruimeng Yang5, Jie Zhan6, Joseph Ippolito1, Jianping Lu2, and Sheng-Kwei Song1

1Radiology, Washington University School of Medicine, Saint Louis, MO, United States, 2Radiology, Changhai Hospital, Shanghai, China, 3Medical Scientist Training Program, The University of Alabama at Birmingham, Birmingham, AL, United States, 4Medicine, University of Missouri – Kansas City, Kansas City, MO, United States, 5Radiology, Guangzhou First People's Hospital, Guangzhou, China, 6Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, China

Prostate cancer (PCa) is second most common cause of cancer death among American men. Curently clinicians rely on needle biopsies for PCa grading, although biopsy Gleason scores often differ from those of pathological analyses. We demonstrated modified-DBSI captured and quantified heterogeneous diffusion fingerprints reflecting prostatic histopathology, capable of noninvasively grading PCa with high accuracy. The diagnostic power of modified-DBSI could prevent low-grade cancer patients from undergoing unnecessary and costly invasive procedures, offering patients more reliable assessments on cancer progression during active surveillance, and helping patients and clinicians to determine the most appropriate treatment options.

This abstract and the presentation materials are available to members only; a login is required.

Join Here