Aims. To report the development of the technique for minimally invasive lumbar decompression using robotic-assisted navigation. Methods. Robotic planning software was used to map out bone removal for a laminar decompression after registration of CT scan images of one cadaveric specimen. A specialized acorn-shaped bone removal robotic drill was used to complete a robotic lumbar laminectomy. Post-procedure advanced imaging was obtained to compare actual bony decompression to the surgical plan. After confirming accuracy of the technique, a minimally invasive robotic-assisted laminectomy was performed on one 72-year-old female patient with lumbar spinal stenosis. Postoperative advanced imaging was obtained to confirm the decompression. Results. A workflow for robotic-assisted lumbar laminectomy was successfully developed in a human cadaveric specimen, as excellent decompression was confirmed by postoperative CT imaging. Subsequently, the workflow was applied clinically in a patient with severe spinal stenosis. Excellent decompression was achieved intraoperatively and preservation of the dorsal midline structures was confirmed on postoperative MRI. The patient experienced improvement in symptoms postoperatively and was discharged within 24 hours. Conclusion. Minimally invasive robotic-assisted lumbar decompression utilizing a specialized robotic bone removal instrument was shown to be accurate and effective both in vitro and in vivo. The robotic bone removal technique has the potential for less invasive removal of laminar bone for spinal decompression, all the while preserving the spinous process and the posterior ligamentous complex. Spinal robotic surgery has previously been limited to the insertion of screws and, more recently, cages; however, recent innovations have expanded robotic capabilities to decompression of neurological structures. Cite this article: Bone Jt Open 2024;5(9):809–817

Aims

This systematic review aims to identify 3D predictors derived from biplanar reconstruction, and to describe current methods for improving curve prediction in patients with mild adolescent idiopathic scoliosis.