Abstract

Restoring lumbar lordosis is one of the main goals in lumbar spinal fusion surgery. The Mazor X-AlignTM software allows for the prediction of postoperative segmental lumbar lordosis based on preoperative imaging. There is limited data on the accuracy of this preoperative prediction, especially in patients undergoing short segment lumbar fusion. The objective of our study was to determine the accuracy of predicted postoperative segmental lumbar lordosis using the Mazor X-AlignTM software in patients requiring short segmental fusion.Retrospective analysis of adult patients undergoing pedicle screw spinal instrumentation of not more than four levels using the Mazor XTM Robot (Medtronic Inc., Minneapolis, MN, USA) between July 2017 to June 2020. The robotic guidance software, Mazor X-AlignTM (Medtronic Inc., Minneapolis, MN, USA) was used to calculate the predicted segmental lumbar lordosis based on preoperative CT-imaging and the plan was executed under intraoperative robotic guidance. Predicted segmental lumbar lordosis was compared to achieved segmental lumbar lordosis on 1-month postoperative x-rays using the Cobb angle methodology.A total of 15 patients (46.6% female) with a mean age of 61.5±10.9 years were included. All patients underwent posterior lumbo-sacral spinal fusion with the Mazor XTM robotic system with 11 patients (73.3%) undergoing anterior column reconstruction prior to posterior fixation. Instrumentation was performed across a mean of 2.6 levels per case. Preoperative, the mean segmental lumbar lordosis was 30.2±13.6 degrees. The mean planned segmental lumbar lordosis was 35.5±17.0 degrees while the mean achieved segmental lumbar lordosis was 35.8±16.7 degrees. There was no significant mean difference between the planned and achieved segmental lumbar lordosis (P=0.334).The Mazor XTM intraoperative robotic planning and guidance is accurate in predicting postoperative segmental lumbar lordosis after short segmental fusion. Our findings may assure surgical decision making and planning.

View details for DOI 10.23736/S0390-5616.23.06142-8

View details for PubMedID 37997323