Toward virtual modeling and templating for enhanced spine surgery planning

Cristian A. Linte, Kurt E. Augustine, Jon J. Camp, Richard A. Robb, David R. Holmes

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Traditional 2D images provide limited use for accurate planning of spine interventions, due to their inability to display the complex 3D spine anatomy and close proximity of nerve bundles and vascular structures that must be avoided during the procedure. We have developed a platform for spine surgery planning that employs standard of care 3D pre-operative images and enables oblique reformatting and 3D rendering of individual or multiple vertebrae, interactive templating, and placement of virtual pedicle implants into the patient-specific CT data. Here we propose a combined surrogate metric—the Fastening Strength—to provide estimates of the optimal implant selection and trajectory based on implant dimension and bone mineral density of the displaced bone substrate. We conducted a retrospective clinical study based on pre-and post-operative data from four patients who underwent procedures involving pedicle screw implantation. We assessed the retrospective plans against the post-operative imaging data according to implant dimension, mean voxel intensity of implant trajectory, and Fastening Strength and showed consistency between the proposed plans and the post-operative procedure outcome. Our preliminary studies have demonstrated the feasibility of the platform in assisting the surgeon with the selection of appropriate size implant and trajectory that optimizes Fastening Strength, given the intrinsic vertebral geometry and bone mineral density. Herein we describe the platform infrastructure and capabilities, present preliminary studies conducted to assess impact on typical instrumentation procedures, and share our initial clinical experience in employing the proposed tool for the planning of several complicated spinal correction procedures for which the traditional planning approaches proved insufficient. Lastly, we also disseminate on several clinical cases and their post-operative assessment for which the proposed platform was employed by the surgical team.

Original languageEnglish (US)
Pages (from-to)441-467
Number of pages27
JournalLecture Notes in Computational Vision and Biomechanics
StatePublished - 2015

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Artificial Intelligence


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