Biomechanical analysis of the novel S-type dynamic cage by implementation of teaching learning based optimization algorithm - An experimental and finite element study.

Anterior Cervical Discectomy and Fusion (ACDF) is the most popular and effective procedure for patients with intervertebral disc degeneration, where the degenerated disc is replaced with an interbody implant (widely known as cage). The design of the cage plays a vital role since it has to provide stability for the anterior cervical column without any side-effects. We designed a novel S-type dynamic cage for C4-C5 level, using Polyetheretherketone (PEEK) material considering four different shapes namely: square, circle, rectangle and elliptical, for the central window to occupy bone graft. The major design constrain for a successful cage is minimized cage stress, in order to avoid subsidence. Finite Element (FE) analysis results revealed that the cage stress values obtained during the physiological motion varied depending upon the shape of the central window provided for bone graft. The objective of this study is to optimize the central window shape using the Teaching Learning Based Optimization (TLBO) algorithm. It was found that square and elliptical shape bone graft cavity resulted in better outcomes. Additional experimental study was also conducted with a six-axis spine simulator. Based on the optimization results, we manufactured two PEEK cage models with square and elliptical shaped central window using additive manufacturing. A prototype model of the C4-C5 level made of Polyvinylchloride (PVC) was used for experiment due to the existing constraints for using a cadaveric model. The experimental results were cross-verified using FE analysis. Thus, we would like to conclude that square and elliptical shape of the central window were the better design factor for our novel dynamic cage.