Design of patient specific dental implant using FE analysis and computational intelligence techniques

Roy, Sandipan; Dey, Shobhana; Khutia, Niloy; Chowdhury, Amit Roy; Datta, Shubhabrata

doi:10.1016/j.asoc.2018.01.025

Cited by 71 publications

(43 citation statements)

References 22 publications

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“…Several studies showed that the bone quality is an effective parameter during implant design. 17,27 The bone quality considered for the present study is not based on any experimental mandible bone data, rather it is in line with the material property combination used by Wang et al where a variation in bone quality with ±50% in mechanical properties from that of the normal bone is considered. 28 The variations in Young’s modulus, Poisson’s ratio, and density were imposed within the limits of ±20% of that of the normal bone in this study (Table 2).…”

Section: Methodsmentioning

confidence: 90%

Design of dental implant using design of experiment and topology optimization: A finite element analysis study

Gupta

Iyer

Dommeti

et al. 2020

Proc Inst Mech Eng H

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Ever since the introduction of topology optimization into the industrial and manufacturing fields, it has been a top priority to maximize the performance of any system by optimizing its geometrical parameters to save material while keeping its functionality unaltered. The purpose of this study is to design a dental implant macro-geometry by removing expendable material using topology optimization and to evaluate its biomechanical function. Three-dimensional finite element models were created of an implant embedded in cortical and cancellous bone. Parameters like the length and diameter of the implant and the bone quality (±20% variation in Young’s modulus, Poisson’s ratio and density for both cortical and cancellous bone) were varied to evaluate their effect on the principal stresses induced on the peri-implant bone tissues and the micromotion of the implant at 150 N applied load. Design optimization is used to select one suitable implant for each material property combination with optimum parameters that experiences the least von Mises stress and axial deformation, out of twenty implants with different length and diameter for each material property combination. Topology optimization was then used on the selected implants to remove the redundant material. The biomechanical functions of the implants with optimized parameter and volume were then evaluated. The finite element analyses estimated that a reduction of 32% to 45% in the implant volume is possible with the implant still retaining all of its functionality.

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Section: Methodsmentioning

confidence: 90%

Design of dental implant using design of experiment and topology optimization: A finite element analysis study

Gupta

Iyer

Dommeti

et al. 2020

Proc Inst Mech Eng H

Self Cite

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“…Recently, several authors have investigated the osteointegration of dental implants using finite element analysis [4,7,12,18,19,29,33,37]. Mainly the relevance of osteointegration in the implant's longevity as well as in the mechanical stimulation of bone is studied [14,28,33].…”

Section: Introductionmentioning

confidence: 99%

“…Authors mainly considered a static scenario, i.e. an implant is inserted on the bone and loaded in different forms, or the bone tissue mechanical characteristics were tested, or different implant materials were tried, and the stress, strains or displacements were investigated [7,9,12,25,29,33,37,37].…”

Section: Introductionmentioning

confidence: 99%

“…Mainly the relevance of osteointegration in the implant's longevity as well as in the mechanical stimulation of bone is studied [14,28,33].Authors mainly considered a static scenario, i.e. an implant is inserted on the bone and loaded in different forms, or the bone tissue mechanical characteristics were tested, or different implant materials were tried, and the stress, strains or displacements were investigated [7,9,12,25,29,33,37,37].It has been widely observed the importance of implant's design on the osteointegration, implying that "one implant fits all" is not possible anymore [32,37]. So, more studies on the influence of different parameters involved in the mechanics of dental implant are needed, for example, considering implant material as metamaterials [2,6,15,16,26] Our study concentrates on the bone's natural remodelling process and the interaction with the implant in the case where a bone substitute material is used to improve fixation.…”

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confidence: 99%

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Finite memory model of bone healing in analysis of moving interface between mandible tissue and bone substitute material after tooth implant application

Hernandez-Rodriguez

Lekszycki

2021

Continuum Mech. Thermodyn.

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A previous bone remodelling model was presented elsewhere [30], and in the present paper, the same model was tested with new conditions; an interaction between bone tissue, bone substitute material and a dental implant was considered. The bone substitute material was assumed to be dead tissue, which does not synthesizes neither absorbs bone tissue, and it was considered, as well, resolvable. A moving border between the bone substitute material and the bone tissue was studied. The border moved as the newly synthesised bone tissue took over the bone substitute material. After the numerical calculations of time-steps, the whole bone substitute material was replaced by normal bone tissue and the implant was fixed in place only by bone tissue. Dynamical studies of the interaction of bone tissue and implant are used to improved implant design considering different factors, in this case, the presence of bone substitute material helping to fix the implant.

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“…It has proved to be capable to act effectively as objective functions for optimization using GA . ANN‐based surrogate model from FE analyses is used as objective functions for implant design by making se of GA to optimize shape and geometry of the implant to minimize postoperative micromotion, under simulated physiological loading conditions and for designing porous dental implant …”

Section: Introductionmentioning

confidence: 99%

Computational intelligence based design of implant for varying bone conditions

Chatterjee

Dey

Majumder

et al. 2019

Numer Methods Biomed Eng

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The objective is to make the strain deviation before and after implantation adjacent to the femoral implant as close as possible to zero. Genetic algorithm is applied for this optimization of strain deviation, measured in eight separate positions. The concept of composite desirability is introduced in such a way that if the microstrain deviation values for all eight cases are 0, then the composite desirability is 1. Artificial neural network (ANN) models are developed to capture the correlation of the microstrain in femur implants using the data generated through finite element simulation. Then, the ANN model is used as the surrogate model, which in combination with the desirability function serves as the objective function for optimization. The optimum achievable deviation was found to vary with the bone condition. The optimum implant geometry varied for different bone condition, and the findings act as guideline for designing patient-specific implant.

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Design of patient specific dental implant using FE analysis and computational intelligence techniques

Cited by 71 publications

References 22 publications

Design of dental implant using design of experiment and topology optimization: A finite element analysis study

Design of dental implant using design of experiment and topology optimization: A finite element analysis study

Finite memory model of bone healing in analysis of moving interface between mandible tissue and bone substitute material after tooth implant application

Computational intelligence based design of implant for varying bone conditions

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