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Updated: Aug 26, 2025
Cone Beam Intraoperative Computed Tomography-based Image Guidance for Minimally Invasive Transforaminal Interbody Fusion
Published on: August 6, 2019
Augmented Reality to Improve Surgical Workflow in Minimally Invasive Transforaminal Lumbar Interbody Fusion - A
Fabian Sommer1, Ibrahim Hussain1, Sertac Kirnaz1
1Department of Neurological Surgery, Weill Cornell Medicine, New York Presbyterian Hospital/Och Spine, New York, NY, USA.
Objective:
Minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) is a highly reproducible procedure for the fusion of spinal segments. We recently introduced the concept of "total navigation" to improve workflow and eliminate fluoroscopy. Imageguided surgery incorporating augmented reality (AR) may further facilitate workflow. In this study, we developed and evaluated a protocol to integrate AR into the workflow of MISTLIF.
Methods:
A case series of 10 patients was the basis for the evaluation of a protocol to facilitate tubular MIS-TLIF by the application of AR. Surgical TLIF landmarks were marked on a preoperative computed tomography (CT)-scan using dedicated software. This marked CT scan was fused intraoperatively with the low-dose navigation CT scan using elastic image fusion, and the markers were transferred to the intraoperative scan. Our experience with this workflow and the surgical outcomes were collected.
Results:
Our AR protocol was safely implemented in all cases. The TLIF landmarks could be preoperatively planned and transferred to the intraoperative imaging. Of the 10 cases, 1 case had additionally a synovial cyst resection and in 2 cases an additional bony decompression was performed due to central stenosis. The average procedure time was 160.6 ± 31.9 minutes. The AR implementation added 1.72 ± 0.37 minutes to the overall procedure time. No complications occurred.
Conclusion:
Our findings support the idea that total navigation with AR may further facilitate the workflow, especially in cases with more complex anatomy and for teaching and training purposes. More work is needed to simplify the software and make AR integration more user-friendly.
