Journal of Craniovertebral Junction and Spine (Jan 2020)

Augmented reality and artificial intelligence-assisted surgical navigation: Technique and cadaveric feasibility study

  • Kris B Siemionow,
  • Karina M Katchko,
  • Paul Lewicki,
  • Cristian J Luciano

DOI
https://doi.org/10.4103/jcvjs.JCVJS_48_20
Journal volume & issue
Vol. 11, no. 2
pp. 81 – 85

Abstract

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Purpose: Augmented reality-based image overlay of virtual bony spine anatomy can be projected onto real spinal anatomy using computer tomography-generated DICOM images acquired intraoperatively. The aim of the study was to develop a technique and assess the accuracy and feasibility of lumbar vertebrae pedicle instrumentation using augmented reality-assisted surgical navigation. Subjects and Methods: An augmented reality and artificial intelligence (ARAI)-assisted surgical navigation system was developed. The system consists of a display system which hovers over the surgical field and projects three-dimensional (3D) medical images corresponding with the patient's anatomy. The system was registered to the cadaveric spine using an optical tracker and arrays with reflective markers. The virtual image overlay from the ARAI system was compared to 3D generated images from intraoperative scans and used to percutaneously navigate a probe to the cortex at the corresponding pedicle starting point. Intraoperative scan was used to confirm the probe position. Virtual probe placement was compared to the actual probe position in the bone to determine the accuracy of the navigation system. Results: Four cadaveric thoracolumbar spines were used. The navigated probes were correctly placed in all attempted levels (n = 24 levels), defined as Zdichavsky type 1a, Ravi type I, and Gertzbein type 0. The virtual overlay image corresponded to the 3D generated image in all the tested levels. Conclusions: The ARAI surgical navigation system correctly and accurately identified the starting points at all the attempted levels. The virtual anatomy image overlay precisely corresponded to the actual anatomy in all the tested scenarios. This technology may lead more uniform outcomes between surgeons and decrease minimally invasive spine surgery learning curves.

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