Journal of Craniovertebral Junction and Spine

ORIGINAL ARTICLE
Year
: 2021  |  Volume : 12  |  Issue : 3  |  Page : 223--227

Autonomous lumbar spine pedicle screw planning using machine learning: A validation study


Kris B Siemionow1, Craig W Forsthoefel2, Michael P Foy2, Dominik Gawel1, Christian J Luciano1 
1 Department of Research, Holo Surgical Inc, Chicago, IL, USA
2 Department of Orthopaedics, University of Illinois, Chicago, IL, USA

Correspondence Address:
Michael P Foy
E-270 MSS MC 844, 835 S. Wolcott Avenue, Chicago, IL
USA

Introduction: Several techniques for pedicle screw placement have been described including freehand techniques, fluoroscopy assisted, computed tomography (CT) guidance, and robotics. Image-guided surgery offers the potential to combine the benefits of CT guidance without the added radiation. This study investigated the ability of a neural network to place lumbar pedicle screws with the correct length, diameter, and angulation autonomously within radiographs without the need for human involvement. Materials and Methods: The neural network was trained using a machine learning process. The method combines the previously reported autonomous spine segmentation solution with a landmark localization solution. The pedicle screw placement was evaluated using the Zdichavsky, Ravi, and Gertzbein grading systems. Results: In total, the program placed 208 pedicle screws between the L1 and S1 spinal levels. Of the 208 placed pedicle screws, 208 (100%) had a Zdichavsky Score 1A, 206 (99.0%) of all screws were Ravi Grade 1, and Gertzbein Grade A indicating no breech. The final two screws (1.0%) had a Ravi score of 2 (<2 mm breech) and a Gertzbein grade of B (<2 mm breech). Conclusion: The results of this experiment can be combined with an image-guided platform to provide an efficient and highly effective method of placing pedicle screws during spinal stabilization surgery.


How to cite this article:
Siemionow KB, Forsthoefel CW, Foy MP, Gawel D, Luciano CJ. Autonomous lumbar spine pedicle screw planning using machine learning: A validation study.J Craniovert Jun Spine 2021;12:223-227


How to cite this URL:
Siemionow KB, Forsthoefel CW, Foy MP, Gawel D, Luciano CJ. Autonomous lumbar spine pedicle screw planning using machine learning: A validation study. J Craniovert Jun Spine [serial online] 2021 [cited 2021 Dec 8 ];12:223-227
Available from: https://www.jcvjs.com/article.asp?issn=0974-8237;year=2021;volume=12;issue=3;spage=223;epage=227;aulast=Siemionow;type=0