The algorithm leverages 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.
This new update also includes enhancements to the pediatric and adult deformity algorithms predicting compensatory changes to the spine. Medtronic is the first and only company to have FDA cleared predictive models for spine surgery.
The 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,” says Dan Wolf, vice president and general manager, intelligent Data Solutions within the Cranial & Spinal Technology business, which is part of the Neuroscience Portfolio at Medtronic. “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.”
Degenerative spine disease is a common health condition and significant cause of disability for many patients worldwide1. The UNiD ASI Degen Algorithm helps surgeons achieve spinal alignment by more accurately planning procedures and predicting spinal alignment after six months.
Surgical planning, using the UNiD Spine Analyzer, is especially important for degenerative spine procedures, as studies suggest nearly a third of these degenerative patients have a hidden deformity2. A study suggests that when sagittal alignment is not achieved during these procedures, patients are at 10 times greater risk of experiencing degeneration of discs above or below the level where the operation was performed3 Moreover a study shows that 62% of patients remained sagittally malaligned after their procedure,4 which may lead to revision surgery3,5.
“Alignment matters for all spinal surgery – both short construct degen and long construct deformity cases,” says 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.”
This new technology also demonstrates Medtronic’s commitment to offering solutions for all spinal pathologies, including deformity and degenerative conditions. Over time, UNiD ASI technology will continue to evolve as more case data is added and predictive algorithms are further refined to help make spine surgery more predictable for surgeons and patients alike.
- Ravindra, Vijay M, et al. Degenerative Lumbar Spine Disease: Estimating Global Incidence and Worldwide Volume. Global Spine. 2018
- Leveque, Jean-Christophe A., et al. “A multicenter radiographic evaluation of the rates of preoperative and postoperative malalignment in degenerative spinal fusions.” Spine 43.13 (2018): E782-E789.
- Rothenfluh DA, Mueller DA, et al. Pelvic incidence lumbar lordosis mismatch predisposes to adjacent segment disease after lumbar spinal fusion. Eur Spine J (2015) 24:1251-1258.
- Moal B, Schwab F, Ames CP, et al. Radiographic Outcomes of Adult Spinal Deformity Correction: A Critical Analysis of Variability and Failures Across Deformity Patterns. Spine Deform. 2014.
- Jang J-S, Lee S-H, Min J-H, Kim SK, Han K-M, Maen DH. Surgical treatment of failed back surgery syndrome due to sagittal imbalance. Spine (Phila. Pa. 1976). 2007.