Researchers at the Center for Computational Imaging and Personalized Diagnostics (CCIPD) at Case Western Reserve University have preliminarily validated an artificial intelligence (AI) tool to predict how likely the disease is to recur following surgical treatment for prostate cancer.
The tool, called RadClip, uses AI algorithms to examine a variety of data, from MRI scans to molecular information. The research team included Cleveland Clinic, University Hospitals and the Louis Stokes Cleveland Veterans Administration Medical Center.
“This tool can help urologists, oncologists and surgeons create better treatment plans so that their patients can have the most precise treatment,” said Lin Li, a doctoral student in Case Western Reserve’s Biomedical Engineering Department and a member of the CCIPD team that developed the tool. “RadClip allows physicians to evaluate the aggressiveness of the cancer and the response to treatment so they don’t overtreat or undertreat the patient.”
Li is first author on a study used to validate the tool, which appeared this month in The Lancet‘s EBioMedicine journal. While other studies on prostate cancer have examined data from single sites, the CCIPD study included MRI scans from Cleveland Clinic, The Mount Sinai Hospital, University Hospitals and the Hospital of the University of Pennsylvania.
The multi-institutional study applied RadClip AI tool to pre-operative scans from nearly 200 patients whose surgeons removed their prostate gland because of cancer, then compared its results of other predictive approaches—as well as the patients’ outcomes in succeeding years.
One of the critical questions in managing prostate cancer in men undergoing surgery is identifying which are at highest risk of recurrence and prostate cancer-specific mortality so they can be identified early for additional therapy.
While RadClip has been shown to be able to predict the risk of disease recurrence, clinical trials will be needed