# Planning the Surgical Correction of Spinal Deformities: Toward the Identification of the Biomechanical Principles by Means of Numerical Simulation

## TL;DR

This paper introduces a software tool that uses 3D imaging and simulations to plan spinal surgery and predict stresses on implants and tissues.

## Contribution

A novel software approach for simulating spinal deformity correction and identifying biomechanical principles using patient-specific data.

## Key findings

- A user-friendly interface allows planning of deformity correction and simulation of pedicle screw implantation.
- Finite element simulations predict loads and stresses in instrumentation and biological tissues.
- A test case on spondylolisthesis showed plausible results, indicating the method's potential.

## Abstract

In decades of technical developments after the first surgical corrections of spinal deformities, the set of devices, techniques, and tools available to the surgeons has widened dramatically. Nevertheless, the rate of complications due to mechanical failure of the fixation or the instrumentation remains rather high. Indeed, basic and clinical research about the principles of deformity correction and the optimal surgical strategies (i.e., the choice of the fusion length, the most appropriate instrumentation, and the degree of tolerable correction) did not progress as much as the implantable devices and the surgical techniques. In this work, a software approach for the biomechanical simulation of the correction of patient-specific spinal deformities aimed to the identification of its biomechanical principles is presented. The method is based on three-dimensional reconstructions of the spinal anatomy obtained from biplanar radiographic images. A user-friendly graphical user interface allows for the planning of the desired deformity correction and to simulate the implantation of pedicle screws. Robust meshing of the instrumented spine is provided by using consolidated computational geometry and meshing libraries. Based on a finite element simulation, the program is able to predict the loads and stresses acting in the instrumentation as well as those in the biological tissues. A simple test case (reduction of a low-grade spondylolisthesis at L3–L4) was simulated as a proof of concept, and showed plausible results. Despite the numerous limitations of this approach which will be addressed in future implementations, the preliminary outcome is promising and encourages a wide effort toward its refinement.