Toward the Development of Virtual Surgical Tools to Aid Orthopaedic FE Analyses

Computational models of joint anatomy and function provide a means for biomechanists, physicians, and physical therapists to understand the effects of repetitive motion, acute injury, and degenerative diseases. Finite element models, for example, may be used to predict the outcome of a surgical intervention or to improve the design of prosthetic implants. Countless models have been developed over the years to address a myriad of orthopaedic procedures. Unfortunately, few studies have incorporated patient-specific models. Historically, baseline anatomic models have been used due to the demands associated with model development. Moreover, surgical simulations impose additional modeling challenges. Current meshing practices do not readily accommodate the inclusion of implants. Our goal is to develop a suite of tools (virtual instruments and guides) which enable surgical procedures to be readily simulated and to facilitate the development of all-hexahedral finite element mesh definitions

A survey on static and quasi-static finite element models of the human cervical spine

Finite element analyses are an important source of information on the biomechanical behaviour of the cervical spine; as well as an important tool in the design and evaluation of spinal instrumentation. This article presents a comprehensive survey of the finite element models of the cervical spine that have been used to study its pathological/nonpathological biomechanics under static/quasi-static loading conditions. Publications that met the inclusion criteria were analysed to extract parameters relative to model identification (e.g., spine segment, population, utility, limitations), model structure (e.g., loading/boundary conditions, anatomical structures, constitutive representation), simulation structure (e.g., software), verification (e.g., convergence) and validation (e.g., validated procedure/output, assumptions). Besides summarizing different modelling approaches with their associated parameters, this article outlines generalities and issues related to the obtainment of such models. The survey shows that authors often fail to report parameters that are critical for the reproducibility of results and that, even with fully reported parameters, these models are inherently difficult to replicate because they generally are patient-specific with their geometry based on data from in-house specimens/subjects. Overall, while the survey contributes to an understanding of the implications of following different modelling approaches and allows to take advantage of previously developed models, further research is required to improve the accuracy and utility of these models. © 2017, Springer-Verlag France SAS, part of Springer Nature