Researchers funded by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) have developed a way to automatically label images of individual vertebrae during spine surgery, preventing mistakes and saving surgeons both time and stress in the operating room. New work recently published by the team demonstrates the accuracy, feasibility, and advantages of having the technology in the operating room.
To reduce both the chance of error and the burden on the surgeons, a team from Johns Hopkins University and Siemens Healthcare in Germany have developed an algorithm dubbed “LevelCheck” to help identify and label vertebrae in real-time during surgery.
“It’s more than just avoiding those one in 3,000 cases. It actually provides assurance to the surgeon, so it means they can be more confident. It just makes for a better procedure,” says Steven Krosnick, M.D., director of the NIBIB program in Image-Guided Interventions. It fits into the surgical workflow and doesn’t require much additional time during surgery, he says.
“When you look at a radiograph [such as an x-ray] of the spine, it is difficult to say with 100 percent certainty what you’re looking at. The potential for human error is one that an algorithm could help to avoid,” says Jeffrey Siewerdsen Ph.D., professor of biomedical engineering and computer science at Johns Hopkins University and senior author of the recent paper. “Surgeons spend a lot of time, energy, and stress to get it right, and we wanted to provide some decision support for that.”
In the new work, published in the Oct. 15, 2016, issue of the journal Spine, the researchers examined the usefulness of the LevelCheck algorithm by applying it to nearly 400 images previously taken from spinal surgery patients. Three spine surgeons evaluated both the algorithm’s accuracy and how useful they thought such a tool would be during surgery. LevelCheck labeled the vertebrae correctly in every case and the surgeons judged it to be helpful in 42 percent of the cases and to improve confidence in 31 percent. The algorithm was particularly advantageous when anatomical landmarks usually used to count spine segments, such as the sacrum or twelfth rib, were missing, obscured, or abnormal; when spine segments were not easily distinguishable; and when the image quality of the radiographs was poor. As for the additional time spent waiting for the labels to appear, the surgeons said they’d be willing to wait up to a minute for the extra assurance.
Even though surgeons are accurate the vast majority of the time, an independent check can still help, especially since it doesn’t require additional work. Siewerdsen compares LevelCheck to GPS in cars; you rely on it when you’re driving somewhere new, but you might also use it as a check or confirmation even when going places you’ve been before. “Most of the time it is just confirming something that you would have gotten right anyway,” he says. “But decision support can help you reach that decision a bit faster, with a bit more certainty. And every once in a while, it could even help prevent an error.”
The team has also designed a version that can be used when only preoperative MRIs, rather than CT scans, are available. Siewerdsen also sees potential for the technology to track and guide devices during surgery and to provide easier ways to collect quantitative data about surgeries.
The current work is retrospective—the researchers added the labels to images after surgery. Clinical trials that use the technology during operations are now underway. Still, Siewerdsen thinks LevelCheck could one day be commonplace in the operating room, installed into imaging systems so labels—and the precision and confidence they provide—are just a button push away.
The research was funded in part by NIBIB grant EB017226.
Utility of the LevelCheck Algorithm for Decision Support in Vertebral Localization. De Silva T, Lo SL, Aygun N, Aghion DM, Boah A, Petteys R, Uneri A, Ketcha MD, Yi T, Vogt S, Kleinszig G, Wei W, Weiten M, Ye X, Bydon A, Sciubba DM, Witham TF, Wolinsky JP, Siewerdsen JH. Spine (Phila Pa 1976). 2016 Oct 15.
—Teal Burrell, special to NIBIB