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Bone & Joint Open
Vol. 4, Issue 8 | Pages 573 - 579
8 Aug 2023
Beresford-Cleary NJA Silman A Thakar C Gardner A Harding I Cooper C Cook J Rothenfluh DA

Aims. Symptomatic spinal stenosis is a very common problem, and decompression surgery has been shown to be superior to nonoperative treatment in selected patient groups. However, performing an instrumented fusion in addition to decompression may avoid revision and improve outcomes. The aim of the SpInOuT feasibility study was to establish whether a definitive randomized controlled trial (RCT) that accounted for the spectrum of pathology contributing to spinal stenosis, including pelvic incidence-lumbar lordosis (PI-LL) mismatch and mobile spondylolisthesis, could be conducted. Methods. As part of the SpInOuT-F study, a pilot randomized trial was carried out across five NHS hospitals. Patients were randomized to either spinal decompression alone or spinal decompression plus instrumented fusion. Patient-reported outcome measures were collected at baseline and three months. The intended sample size was 60 patients. Results. Of the 90 patients screened, 77 passed the initial screening criteria. A total of 27 patients had a PI-LL mismatch and 23 had a dynamic spondylolisthesis. Following secondary inclusion and exclusion criteria, 31 patients were eligible for the study. Six patients were randomized and one underwent surgery during the study period. Given the low number of patients recruited and randomized, it was not possible to assess completion rates, quality of life, imaging, or health economic outcomes as intended. Conclusion. This study provides a unique insight into the prevalence of dynamic spondylolisthesis and PI-LL mismatch in patients with symptomatic spinal stenosis, and demonstrates that there is a need for a definitive RCT which stratifies for these groups in order to inform surgical decision-making. Nonetheless a definitive study would need further refinement in design and implementation in order to be feasible. Cite this article: Bone Jt Open 2023;4(8):573–579


Bone & Joint Open
Vol. 5, Issue 9 | Pages 809 - 817
27 Sep 2024
Altorfer FCS Kelly MJ Avrumova F Burkhard MD Sneag DB Chazen JL Tan ET Lebl DR

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