Medtronic (NYSE:MDT) announced today that it received FDA 510(k) clearance for its UNiD spine analyzer v4.0 planning platform.
The UNiD spine analyzer v4.0 includes a new Degen algorithm for degenerative spine procedures, with the algorithm designed to leverage machine learning to help surgeons plan and personalize procedures for patients undergoing lower lumbar spine surgery and predicts spinal compensation mechanisms six months after the operation.
According to a news release, the new update includes enhancements to the pediatric and adult deformity algorithms predicting compensatory changes to the spine. The company said it is the first and only company with FDA-cleared predictive models for spine surgery.
Medtronic’s release comes with a new UNiD hub patient-centric platform that enables surgeons to track patients throughout the perioperative care pathway and assess surgical results through long-term radiographic and patient-reported outcomes data collection.
“Patient by patient, our UNiD lab engineers have learned from more than 10,000 spine surgery cases to deliver greater insights to surgeons that lead to better patient alignment,” Medtronic VP and GM of Intelligent Data Solutions within the Cranial & Spinal Technology business Dan Wolf said in the release. “It is truly exciting to share that we have expanded our UNiD ASI technology to include hardware and software solutions dedicated to helping spine surgeons treat degenerative spinal pathologies, where the majority of spine surgery is performed.”
Medtronic said its new technology demonstrates its commitment to offering solutions for all spinal pathologies, with the expectation that the UNiD technology will continue to evolve with more case data and more refined predictive algorithms.
“Alignment matters for all spinal surgery – both short construct degen and long construct deformity cases,” said Dr. Christopher Kleck, an orthopedic spine surgeon at the University of Colorado. “Planning all of these cases with my UNiD lab engineer ensures that my surgical plan is backed by artificial intelligence and clinically important predictive models to set my patients up for long-term success.”