Use of Digital Pathology and Artificial Intelligence for Prostate Cancer Risk Stratification in the Post-Surgical Setting
Principal Investigator
Name
Danielle Croucher
Degrees
M.Sc., Ph.D.
Institution
Artera Inc.
Position Title
Scientific Director
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCOI-1703
Initial CDAS Request Approval
Oct 11, 2024
Title
Use of Digital Pathology and Artificial Intelligence for Prostate Cancer Risk Stratification in the Post-Surgical Setting
Summary
Radical prostatectomy is one of the standard-of-care management treatments for men with localized prostate cancer. Although this approach improves overall survival and delays the development of metastatic disease compared with observation, a subset of patients will experience disease recurrence and require additional forms of adjuvant and/or salvage treatment including radiotherapy with or without hormone treatment. However, there are limited predictive tools to guide risk stratification and inform treatment decisions in these patients.
Artificial intelligence (AI)-based approaches have shown promise towards personalizing cancer decision making, including AI models developed using digital histopathology images of prostate cancer biopsies or radical prostatectomy specimens. In the proposed study, we will assess performance of an AI-based model developed using radical prostatectomy images and clinical variables to predict clinical outcomes such as disease recurrence and distant metastasis. Access to PLCO data will allow for validation of the model across a diverse patient cohort, ensuring robustness and generalizability. This project will advance AI-driven biomarkers for improved post-surgical decision-making.
Artificial intelligence (AI)-based approaches have shown promise towards personalizing cancer decision making, including AI models developed using digital histopathology images of prostate cancer biopsies or radical prostatectomy specimens. In the proposed study, we will assess performance of an AI-based model developed using radical prostatectomy images and clinical variables to predict clinical outcomes such as disease recurrence and distant metastasis. Access to PLCO data will allow for validation of the model across a diverse patient cohort, ensuring robustness and generalizability. This project will advance AI-driven biomarkers for improved post-surgical decision-making.
Aims
- Investigate the performance of validated prognostic and predictive AI algorithms for men undergoing prostatectomy
- Explore the prognostic performance of AI algorithms in clinically-relevant patient subpopulations
- Compare performance of AI algorithms to established clinical risk stratification tools
Collaborators
Meghan Tierney, Artera Inc.
Sanghita Nag, Artera Inc.
Trevor Royce, Artera Inc.