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2024 AIRA Matrix – PCF Challenge Award

Quantitative MRI to Guide Targeted Radiotherapy for Aggressive, Pre-Metastatic Prostate Cancer

Principal Investigators: Tyler Seibert, MD, PhD (University of California, San Diego), Mirabela Rusu, PhD (Stanford University), Matthew Cooperberg, MD, MPH (University of California, San Francisco), Jeffry Simko, MD, PhD (University of California, San Francisco),

Co-Investigators: Ahmed Shabaik, MD (University of California, San Diego), Michael Hahn, MD, PhD (University of California, San Diego), Jingjing Zou, PhD (University of California, San Diego), Xenia Ray, PhD (University of California, San Diego), Anders Dale, PhD (University of California, San Diego), Christopher Kane, MD (University of California, San Diego), Aditya Bagrodia, MD (University of California, San Diego), Sean Woolen, MD (University of California, San Francisco), Geoffrey Sonn, MD (Stanford University), Uttara Joshi, MBBS (AIRA Matrix), Nitin Singhal, MS (AIRA Matrix), Robert Dess, MD (University of Michigan), Uulke A. van der Heide, PhD (Leiden University Medical Center)

Young Investigator: Sophia Kamran, MD (Harvard: Massachusetts General Hospital)

Description:

  • Aggressive, organ-confined, clinically significant prostate cancer has the potential to become metastatic but is still curable with prostatectomy or radiotherapy. 
  • A Phase III randomized controlled trial (FLAME) showed that focally increasing radiation dose to MRI-visible tumors significantly improved outcomes without additional toxicity.
  • Unfortunately, widespread adoption of this therapeutic advance has been slowed by a lack of expertise among radiation oncologists in accurately identifying and targeting cancer on prostate MRI. 
  • Dr. Tyler Seibert and team have developed an advanced MRI tool, Restriction Spectrum Imaging restriction score (RSIrs), which considerably improved radiation oncologists’ accuracy in this setting. Artificial intelligence (AI) based tools are also promising for automated detection of cancer. 
  • In this project, Dr. Seibert and team will define the accuracy of RSIrs as well as AI-based radiology algorithms to detect aggressive vs. non-aggressive prostate cancer on MRI, as compared with gold standard pathology methods.
  • Clinically significant prostate cancer that is invisible on MRI will be evaluated for distinct pathology and molecular imaging features.
  • Whether combining PSMA PET with RSIrs improved detection of high-grade prostate cancer will be tested.
  • If successful, this project will develop quantitative, reproducible tools to identify high-grade tumors that can be targeted with focally boosted radiation therapy, empower radiation oncologists to cure more patients with aggressive, pre-metastatic prostate cancer.

What this means to patients: Recent trials have found that outcomes in patients with clinically significant localized prostate cancer can be significantly improved by focally increasing radiation doses to tumors detectable on MRI. Dr. Seibert and team are developing novel molecular imaging and AI-based tools to improve the accuracy of detection of clinically significant prostate cancer on MRI, which will enable radiation oncologists to treat these lesions and increase their chances of curing more patients.