A rising number of hospitals and spine surgeons are implementing robotics and computer-navigated spine surgery, which aims to improve precision, accuracy and predictability.
Drawbacks of robotic surgery include additional operating room time and concerns related to the accurate implantation of pedicle screws. But Darren Lebl, MD, of New York City-based Hospital for Special Surgery believes the technology has reached a tipping point.
"I think they're good enough to greatly improve what we do in terms of minimally invasive surgery," Dr. Lebl said in a Sept. 2 news release. "In my own practice, I've seen the benefits for patients in terms of a shorter hospital stay, quicker mobility and decreased healing times."
In a study published in June in the Journal of Spine Surgery, Dr. Lebl and other spine surgeons from Hospital for Special Surgery attempted to determine the learning curve associated with implanting pedicle screws with robotic systems compared to conventional techniques.
Six study findings:
1. The study collected data from 65 adults who had robotic-navigated posterior spinal fusion by a single spine surgeon.
2. Of the 364 instrumented pedicles that were planned robotically, 311 (85.4 percent) were placed robotically; 17 screws (4.7 percent) converted to k-wire, a spine surgery stabilization system, 21 screws (5.8 percent) converted to freehand and 15 (4.1 percent) planned freehand.
3. In the 311 robotically-placed screws, 3D imaging showed 291 (93.5 percent) were rated as Gordon Research Seminar Grade A in the axial plane — fully contained within the pedicle — and 281 (90.4 percent) were GRS Grade A in the sagittal plane.
4. Two patients experienced six (1.9 percent) critical breaches from hypoplastic pedicles, and 3 (0.9 percent) unplanned lateral breaches were found in another patient.
5. One patient (0.3 percent) experienced skive because of morphology and spinal instability from isthmic spondylolisthesis.
6. For the first several cases, the learning curve showed improvement in screw times, according to the study. The authors said that understanding the learning curve and occasions where the robot may be suboptimal can help guide the surgeon as well as the increased refinement of robotic technologies.