Based on their work in Capstone Design in Spring 2021, the idea is to quickly and accurately give surgeons data on how well they have corrected the curvature of the patient’s spine without traditional radiographic tools. Usually that information would come via X-ray or CT scan in the operating room, with doctors pausing the procedure to acquire key metrics, like the Cobb angle and plumb line.

“There's currently not a convenient way to measure, intraoperatively, the alignment of the spine during scoliosis surgery,” said Kelly Qiu, who graduated in 2021 and was a member of the team. “The current methods are radiographic; however, because they are radiographic, they take a long time to take an image of the spine during the surgery, and it also exposes the patient as well as the staff in the OR to a lot of radiation.”

The group is the third Capstone team in the Wallace H. Coulter Department of Biomedical Engineering to publish their work in a peer-reviewed journal in the last year, a first for the program. Along with Qiu, the team included Yoel Alperin, Parth Gami, and Sindhu Kannappan, who all finished their bachelor’s degrees in 2021.

The measurement device relies on custom 3D-printed markers placed at key locations on the spine during surgery. An off-the-shelf camera captures an image, and a custom deep learning algorithm spots the markers and makes quick calculations for surgeons. Deep learning builds layers of algorithms in networks modeled on the human brain.

The team validated the system using a cadaver with scoliosis and reported the automated approach produced data well within clinically accepted parameters. The study also noted the prototype device could cut time for intraoperative measurement from 15 minutes for a typical radiographic approach to roughly one minute. 

“We really took advantage of these brand new computational processing techniques. The fact that we're able to use a deep learning algorithm with image processing allows us to get rid of that need for massive radiographic instrumentation [in the operating room] like X-ray or CT machines,” Gami said, explaining that their relatively simple device is easy to operate and maneuver in the sterile operating room environment. 

All of that streamlining could reduce costs for patients along with reducing risks of infection and exposure to radiation, Alperin said.

“There are huge savings on the actual device itself, and on top of that, anytime that you bring another person into the operating room, that's additional cost to the patient,” he said. “You have to bring in that person to actually run the [imaging] arm. And then there’s additional costs from the extension of the length of surgery.”