Fed Ghali, MD, and John Onofrey, PhD, lead the other team awarded in this year’s competition. They are set on answering the question asked by a subset of bladder cancer patients having surgery after chemo: "If there was no cancer in the bladder, why did I need to have this big surgery?”
“It turns out at least part of the answer is that we do not have a reliable way to identify chemo-responders that have been made cancer-free until their bladder is already removed and assessed by a pathologist,” says Ghali.
Through their research, titled "Integrating machine learning and radiomics for automated assessment of pathologic response following neoadjuvant chemotherapy in muscle-invasive bladder cancer,” Drs. Ghali and Onofrey are eager to see where it will lead patient care.
They have already begun to gather data and organize the next steps of their study, with a particular focus on technology.
“Dr. Onofrey and his associates specialize in machine learning and artificial intelligence for evaluating imaging studies. For instance, he and his lab use CT scans to glean all kinds of information that humans can’t extract by standard methods of interpretation,” says Ghali. “It’s possible this technology could help us identify those super-responders to chemotherapy and perhaps avoid radical surgery in up to 40% of patients.”