Finite element analysis of dental implants with validation: to what extent can we expect the model to predict biological phenomena? A literature review and proposal for classification of a validation process

Abstract

A literature review of finite element analysis (FEA) studies of dental implants with their model validation process was performed to establish the criteria for evaluating validation methods with respect to their similarity to biological behavior. An electronic literature search of PubMed was conducted up to January 2017 using the Medical Subject Headings “dental implants” and “finite element analysis.” After accessing the full texts, the context of each article was searched using the words “valid” and “validation” and articles in which these words appeared were read to determine whether they met the inclusion criteria for the review. Of 601 articles published from 1997 to 2016, 48 that met the eligibility criteria were selected. The articles were categorized according to their validation method as follows: in vivo experiments in humans (n = 1) and other animals (n = 3), model experiments (n = 32), others’ clinical data and past literature (n = 9), and other software (n = 2). Validation techniques with a high level of sufficiency and efficiency are still rare in FEA studies of dental implants. High-level validation, especially using in vivo experiments tied to an accurate finite element method, needs to become an established part of FEA studies. The recognition of a validation process should be considered when judging the practicality of an FEA study.

Finite Element Analysis of a New Dental Implant Design Optimized for the Desirable Stress Distribution in the Surrounding Bone Region

“…However, when multiple design changes are made, the results derived by previous research cannot be used. To quickly analyze and predict the differences resulting from design changes in dental implant systems, the FEA is a mathematical model analysis that has been widely used in implant dentistry [12]. Therefore, this study was carried out using FEA to compare the mechanical behavior relative to design changes, including changes to implant body shape, implant collar shape, thread design and pitch, of a new dental implant design with a standard implant design with the same diameter and length.…”

“…However, there is a lack of data about the implant macro-design (body and neck) and threads design that can optimize the maintenance of peri-implant bone. In order to predict stress and strain within structures in a real situation, which cannot be solved by a traditional linear static model, nonlinear finite element analysis (FEA) is a mathematical model analysis that allows for evaluating, in a qualitatively detailed way, the mechanical behavior of dental implants, especially the stress distribution generated at the implant/bone interface [12]. In this study, a new type of dental implant, designed with the intention of creating stress initially at cancellous bone and to reduce the stress peaks in the surrounding upper cortical bone, was evaluated by FEA.…”

Influence of thickness and incisal extension of indirect veneers on the biomechanical behavior of maxillary canine teeth

“…A literature review performed by Chang et al . [ 30 ] in 2018 found that among 450 publications over the last 10 years about dental implants using FEA, only 47 articles used some kind of validation (clinical or laboratory experiments, findings in the literature, or another kind of validation), and the strain gauge method of laboratory testing was used in 15 of those 47 articles. That review recognized that simplifying the biomechanical behavior of tissues and ignoring the characteristics of each individual for computer analysis may neglect some aspects, resulting in inaccuracies in the predicted behavior of structures in the studied circumstances.…”

Optimized Planning and Evaluation of Dental Implant Fatigue Testing: A Specific Software Application

“…Numerical simulation analysis by finite elements and its validation through extensometry, photoelasticity, photogrammetry, fractal analysis and, most recently, DIC (digital image correlation) [6][7][8][9][10] are some of the most commonly used in vitro methods to evaluate results according to the load conditions and other characteristics of a given experiment. Anyway, since the simulation demands experimental verification to determine the long-term resistance of the components under real loads, it is of vital importance to conduct fatigue tests under the most realistic loads and effective chewing conditions possible.…”