BACKGROUND:A preoperative planning system facilitates improving surgical outcomes that depend on the experience of the surgeons, thanks to real-time interaction between the system and surgeons. It visualizes intermediate surgical planning results to help surgeons discuss the planning. The purpose of this study was to demonstrate the use of a newly-developed preoperative planning system for surgeons less experienced in pedicle-screw fixation in spinal surgery, especially on patients with anatomical variations.METHODS:The marching cubes algorithm, a typical surface extraction technique, was applied to computed tomography (CT) images of vertebrae to enable three-dimensional (3D) reconstruction of a spinal mesh. Real-time processing of such data is difficult, as the surface mesh extracted from high-resolution CT data is rough, and the size of the mesh is large. To mitigate these factors, Laplacian smoothing was applied, followed by application of a quadric error metric-based mesh simplification to reduce the mesh size for the level-of-detail (LOD) image. Taubin smoothing was applied to smooth out the rough surface. On a multiplanar reconstruction (MPR) cross-sectional image or a 3D model view, the insertion position and orientation of the pedicle screw were manipulated using a mouse. The results after insertion were then visualized in each image.RESULTS:The system was used for pre-planning pedicle-screw fixation in spinal surgery. Using any pointing device such as a mouse, surgeons can manipulate the position and angle of the screws. The pedicle screws were easy to manipulate intuitively on the MPR images, and the accuracy of screw fixation was confirmed on a trajectory view and 3D images. After surgery, CT scans were performed again, and the CT images were checked to ensure that the screws were inserted properly.CONCLUSION:The preoperative planning system allows surgeons and students who are not familiar with pedicle-screw fixation to safely undertake surgery following preoperative planning. It also provides opportunities for screw-fixation training and simulation.? 2020 The Korean Academy of Medical Sciences.
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