Specialty hernia centers produce better outcomes for complex cases, but there is no reliable way to predetermine which patients need specialty care. As a result, many hernia patients suffer postsurgical complications that might have been prevented, like wound infections, pulmonary failure or a recurrent hernia.
This is the first predictive tool to rely exclusively on objective data. Research behind the tool has won awards from the Americas Hernia Society and the American College of Surgeons.
“This tool could potentially help patients and surgeons make clear, educated decisions concerning if and where to have surgery and to what extent preoperative preparation is needed to prevent patients from needing additional hernia surgery or follow-up treatment,” says B. Todd Heniford, MD, chief of the Division of Gastro-intestinal and Minimally Invasive Surgery at Atrium Health Carolinas Medical Center’s Department of Surgery. “It also helps prove the value of advanced analytics in preoperative planning.”
Predicting surgical complexity
To make this tool, Dr. Heniford and a comprehensive team built a neural network – the layers of algorithmic calculation that form the AI’s “brain.” Then they trained the AI by feeding it CT scans from hundreds of past patients.
“Basically, the computer taught itself what to look for in a scan in order to tell whether someone can expect a complex surgery or complication,” Dr. Heniford says.
The program reviewed each image more than 12,000 times, recording features that correspond with the need for component separation, the development of wound infection after surgery and the development of postsurgic
Finally, they tested the AI by feeding it another batch of images from past patients and asking it to identify which ones developed the 3 outcomes. The AI was 89% accurate at predicting infection, and its success in predicting pulmonary failure was 54.5%.
A panel of international hernia experts reviewed the same scans and made predictions about the need for component separation. The AI was 75% accurate at
predicting surgical complexity, almost 15 points better than the experts.
“The computer beat us handily,” says Dr. Heniford.
Altogether, Dr. Heniford says these predictions not only identify who needs specialty care but can also help patients decide whether to pursue surgery.
“If I tell you there’s a 54% chance you’ll develop pulmonary failure as a result of this operation, you may decide against it,” adds Dr. Heniford.
Building a brighter surgical future
The team will soon share the model with other institutions, to test it using images of another 100 patients. Subsequently, Dr. Heniford plans to turn it into another app.
“Imagine,” he says, “dragging an image into this program and getting 3 clear answers: Yes, this patient needs component separation; yes, they’ll have an infection; no, they won’t have a lung problem. That
is game-changing clarity.”
The team hopes their work leads to similar models and apps in other areas with complex operations, such as liver and lung tumors.
“If we can do this for hernias, there’s no reason you can’t bring this kind of clarity to
other surgeries as well,” Dr. Heniford says.
- To learn more about this unique tool, email Dr. Todd Heniford at:
Todd.Heniford@AtriumHealth.org - Atrium Health Carolinas Medical Centre
https://atriumhealth.org/locations/detail/carolinas-medical-center
