Researching the “educated guess”

Top-scoring project to explore artificial intelligence in surgical decision-making
January 20th, 2022

Dr. Andrew Read-Fuller

Oral and maxillofacial surgery faculty member Dr. Andrew Read-Fuller is leading a study to investigate the potential of predictive analytics in improving treatment of a common type of fracture.

He and his research team garnered the Oral and Maxillofacial Surgery Foundation’s 2021 Stephen B. Milam Award and a $75,000 grant as the highest-scoring Research Support Grant project evaluated by the foundation’s research committee.

“What I’m studying is orbital floor fractures; when somebody breaks the bone underneath their eyes,” says Read-Fuller, clinical assistant professor and director of OMS residency training at Texas A&M College of Dentistry. “It’s one of the most common fractures we treat as part of our practice.

“One of the problems is that orbital fractures are very different from any other fracture you might get.”

While other types of broken bones usually require some procedure or surgery to fix, Read-Fuller says, orbital fractures involve numerous factors that determine whether or not surgery is necessary. These include the size and specific location of the fracture, symptoms the patient is facing, even the patient’s demographic information. While some cases obviously do or don’t require surgery, this current study addresses the middle ground for treatment decisions, he explains. “In the long term, we’re trying to create a tool that will help surgeons make that educated guess.”

“We’re working with some researchers whose area of expertise is artificial intelligence and machine learning,” Read-Fuller says. “This machine learning program they developed can analyze a lot of CT scans, a lot of patient data, and pick out the commonalities. All of these things are put together and, ultimately in the long term, we’re hoping to develop this into a type of computer program that can help the surgeon analyze the data.”

The first phase of research will probably last about two years, he says, beginning with gathering the data for analysis. Seeing how far the research team can go with this machine-learning tool will take several years more. Read-Fuller is hopeful the OMS Foundation grant will be augmented by additional funding from various sources.

“As a doctor you want to give the best advice you can to your patients,” he says. “There’s clearly been this need, at least in my own personal practice, to come up with something that would help with this.”

The project’s other primary investigators include University of Texas Southwestern Medical Center faculty members Drs. Ganesh Sankaranarayanan and Babak Namazi and College of Dentistry faculty members Dr. Matthew J. Kesterke, Dr. Madhu Nair and Dr. Likith Reddy.

— Caleb Vierkant