Chitosan nerve guidance channels with different geometries and their numerical analysis

Introduction: Peripheral nerve injuries are a major cause of permanent disabilities and have a negative impact on the quality of life of patients. The consequences of these injuries affect their daily living and work activities. Approximately 3% of trauma patients worldwide are affected by these injuries which are commonly attributed to direct mechanical trauma and to surgical resection. Although the knowledge about the pathophysiology of these injuries has been progressing, they still present as a challenge to surgeons. The most severe type of nerve injury is known as neurotmesis, which in the most extreme case results in a completely transected nerve. This originates a nerve gap, with total interruption of the structural integrity of the support structure of the nerve. There are different strategies that can be used to repair a peripheral nerve injury, being that both surgical and non-surgical approaches can be implemented. Whenever tensionless suture across the nerve gap is not possible, surgeons resort to the gold-standard technique which is the use of autologous nerve grafts (autografts). To overcome the disadvantages associated to this technique, nerve guidance channels (NGCs) made of biomaterials have been viewed as an alternative approach. One of the biomaterials that has been considered as a preferable candidate for peripheral nerve regeneration is chitosan. Methodology: In order to understand how these chitosan NGCs mechanically behave after being implanted at an injury site, discrete models of the NGCs containing a segment of a peripheral nerve were built using numerical methods to analyze them such as the finite element method (FEM) and the radial point interpolation method (RPIM). The discrete models had variable geometrical parameters: the length of the NGC and its wall thickness. The elastic constants considered were the Poisson’s coefficient and the Young’s modulus. Results and Discussion: Stress and displacement fields were obtained in order to comprehend the structural response of the NGCs when subjected to external forces. With the obtained results concerning stress and displacement distributions, it was possible to understand how the NGCs mechanically behave and which structural features are more indicated for their use. Conclusions: Although many advances have been made in the past decades, there is still the need to evolve and improve the different approaches to repair injuries in the peripheral nervous system. Numerical methods such as FEM and RPIM can numerically simulate the mechanical behavior of the chitosan NGCs and help to understand how they can be mechanically improved.