Simulation of peri-implant bone healing due to immediate loading in dental implant treatments

Titanium nanotopography enhances mechano-response of osteocyte three-dimensional network toward osteoblast activation

The bone turnover capability influences the acquisition and maintenance of osseointegration. The architectures of osteocyte three-dimensional (3D) networks determine the direction and activity of bone turnover through osteocyte intercellular crosstalk, which exchanges prostaglandins through gap junctions in response to mechanical loading. Titanium nanosurfaces with anisotropically patterned dense nanospikes promote the development of osteocyte lacunar-canalicular networks. We investigated the effects of titanium nanosurfaces on intercellular network development and regulatory capabilities of bone turnover in osteocytes under cyclic compressive loading. MLO-Y4 mouse osteocyte-like cell lines embedded in type I collagen 3D gels on titanium nanosurfaces promoted the formation of intercellular networks and gap junctions even under static culture conditions, in contrast to the poor intercellular connectivity in machined titanium surfaces. The osteocyte 3D network on the titanium nanosurfaces further enhanced gap junction formation after additional culturing under cyclic compressive loading simulating masticatory loading, beyond the degree observed on machined titanium surfaces. A prostaglandin synthesis inhibitor cancelled the dual effects of titanium nanosurfaces and cyclic compressive loading on the upregulation of gap junction-related genes in the osteocyte 3D culture. Supernatants from osteocyte monolayer culture on titanium nanosurfaces promoted osteocyte maturation and intercellular connections with gap junctions. With cyclic loading, titanium nanosurfaces induced expression of the regulatory factors of bone turnover in osteocyte 3D cultures, toward higher osteoblast activation than that observed on machined surfaces. Titanium nanosurfaces with anisotropically patterned dense nanospikes promoted intercellular 3D network development and regulatory function toward osteoblast activation in osteocytes activated by cyclic compressive loading, through intercellular crosstalk by prostaglandin.

Comparative analysis of mechanical conditions in bone union following first metatarsophalangeal joint arthrodesis with varied locking plate positions: A finite element analysis

BACKGROUND

First metatarsophalangeal joint arthrodesis is a typical medical treatment performed in cases of arthritis or joint deformity. The gold standard for this procedure is arthrodesis stabilisation with the dorsally positioned plate. However, according to the authors' previous studies, medially positioned plate provides greater bending stiffness. It is worth to compare the mechanical conditions for bone formation in the fracture callus for both placements of the locking plate.

METHODS

Two finite element models of the first metatarsophalangeal joint with the dorsally and medially positioned plate were defined in the Abaqus software to simulate differentiation of the fracture callus. A simplified load application, i.e. one single step per each day and the diffusion of the mesenchymal stem cells into the fracture region were assumed in an iterative hardening process. The changes of the mesenchymal stem cells into different phenotypes during the callus stiffening were governed by the octahedral shear strain and interstitial fluid velocity according to Prendergast mechanoregulation theory. Basing on the obtained results the progress of the cartilage and bone tissues formation and their distribution within the callus were compared between two models.

FINDINGS

The obtained results suggest that after 6 weeks of simulation the healing progress is in general comparable for both plates. However, earlier closing of external callus was observed for the medially positioned plate which had greater vertical bending stiffness. This process enables faster internal callus hardening and promotes symmetrical bridging.

Peri-implant cell differentiation in delayed and immediately-loaded dental implant: A mechanobiological simulation

OBJECTIVE

This study aimed to investigate the effect of immediate versus delayed dental implant placement strategies on cell differentiation in a dental callus.

DESIGN

The implant was placed in the mandible with two nearby teeth using an idealized two-dimensional finite element model. Eight weeks after surgery, the mechanobiological modeling of healing was used to estimate cell differentiation. It was assumed that the callus was initially filled by mesenchymal cells. The model then transformed mechanical stimuli received by the callus from loadings in terms of distortional and dilatational strains into predictions of the cellular phenotypes, including fibroblasts, chondrocytes, and osteoblasts, or whether they would remain unchanged or die.

RESULTS

The results demonstrated that delayed loading led to greater bone formation than immediate loading. Osteoblast colonies were observed in the base of threads in the immediately-loaded implant, whereas the delayed loading caused distant bone formation from the surrounding bone side towards the implant. The osteoblasts were differentiated from both intramembranous and endochondral mechanisms of ossification. After eight weeks, approximately 61 % of the callus was ossified in the delayed placement model compared to 35 % in the immediate placement model, resulting in a greater amount of fibrocartilaginous tissue on the bone side of the callus.

CONCLUSIONS

Immediate and delayed loading models generated different results. In the delayed strategy, bone cells were supplied appropriately during the first few weeks following surgery, whereas the immediate loading caused fibrocartilaginous tissue differentiation. In the form of distant osseointegration, the secondary stability of the dental implant was higher and faster due to the delayed placement.

On computational predictions of fluid flow and its effects on bone healing in dental implant treatments: an investigation of spatiotemporal fluid flow in cyclic loading

Fluid flow in (porous) bone plays an important role in its maintenance, adaptation, and healing after an injury. Experimental and computational studies apply mechanical loading on bone to predict fluid flow development and/or to find its material properties. In most cases, mechanical loading is applied as a linear function in time. Multiple loading functions-with identical peak load and loading frequency-were used to investigate load-induced fluid flow and predict bone healing surrounding a dental implant. Implementing an instantaneous healing stimulus led to major differences in healing predictions for slightly different loading functions. Load-induced fluid flow was found to be displacement-rate dependent with complex spatial-temporal variations and not necessarily symmetrical during loading and unloading phases. Haversine loading resulted in more numerical stability compared to ramped/triangular loading, providing the opportunity for further investigation of the effects of various physiological masticatory loadings. It was concluded that using the average healing stimulus during cyclic loading gives the most robust bone healing predictions.

Prediction of Bone Healing around Dental Implants in Various Boundary Conditions by Deep Learning Network

Tissue differentiation varies based on patients' conditions, such as occlusal force and bone properties. Thus, the design of the implants needs to take these conditions into account to improve osseointegration. However, the efficiency of the design procedure is typically not satisfactory and needs to be significantly improved. Thus, a deep learning network (DLN) is proposed in this study. A data-driven DLN consisting of U-net, ANN, and random forest models was implemented. It serves as a surrogate for finite element analysis and the mechano-regulation algorithm. The datasets include the history of tissue differentiation throughout 35 days with various levels of occlusal force and bone properties. The accuracy of day-by-day tissue differentiation prediction in the testing dataset was 82%, and the AUC value of the five tissue phenotypes (fibrous tissue, cartilage, immature bone, mature bone, and resorption) was above 0.86, showing a high prediction accuracy. The proposed DLN model showed the robustness for surrogating the complex, time-dependent calculations. The results can serve as a design guideline for dental implants.

Understanding the thrust force evolution and primary stability for dental implantation – An in-vitro experimental investigation

The dental implant is challenging due to the unstable quality of the surrounding bone. This study aimed to explore the feasibility of using thrust force characteristics to identify different bone types and the influencing mechanisms of spindle speed and feed rate on primary stability of dental implants through in-vitro experiments. 13 groups of osteotomy experiments were performed on mandibles and maxillae of pigs with different bone types (I, II, and III) under different spindle speeds (600 and 800 rpm) and feed rates (20 and 60 mm/min). The thrust force evolution under different conditions was extracted and analysed to elaborate the distribution and thickness of the cortical and trabecular bone layers on different bone types. Dental implant placements were performed, and corresponding primary stabilities were obtained. Furthermore, histologic observation was conducted to reveal the bone/implant contact morphology. From the results, the amplitude and trend of thrust force show a regular variation during drilling different bone types. The highly dynamic information of thrust force can be analysed to characterise the distribution and thickness of the cortical and trabecular bone layers, hence effectively detecting different bone types. Since a lower feed rate and resulting bone temperature elevation lead to more thermal damages, primary stability decreases with the decrease of feed rate. Spindle speed has no significant effect. This study establishes a more in-depth understanding into the thrust force evolution and also provide a clinical option for reducing the complexity of bone type and drilling parameters determination in osteotomy.

Application of finite element analysis to tissue differentiation and bone remodelling approaches and their use in design optimization of orthopaedic implants: A review

Post-operative bone growth and long-term bone adaptation around the orthopaedic implants are simulated using the mechanoregulation based tissue-differentiation and adaptive bone remodelling algorithms, respectively. The primary objective of these algorithms was to assess biomechanical feasibility and reliability of orthopaedic implants. This article aims to offer a comprehensive review of the developments in mathematical models of tissue-differentiation and bone adaptation and their applications in studies involving design optimization of orthopaedic implants over three decades. Despite the different mechanoregulatory models developed, existing literature confirm that none of the models can be highly regarded or completely disregarded over each other. Not much development in mathematical formulations has been observed from the current state of knowledge due to the lack of in vivo studies involving clinically relevant animal models, which further retarded the development of such models to use in translational research at a fast pace. Future investigations involving artificial intelligence (AI), soft-computing techniques and combined tissue-differentiation and bone-adaptation studies involving animal subjects for model verification are needed to formulate more sophisticated mathematical models to enhance the accuracy of pre-clinical testing of orthopaedic implants.

Engineer design process assisted by explainable deep learning network

Engineering simulation accelerates the development of reliable and repeatable design processes in various domains. However, the computing resource consumption is dramatically raised in the whole development processes. Making the most of these simulation data becomes more and more important in modern industrial product design. In the present study, we proposed a workflow comprised of a series of machine learning algorithms (mainly deep neuron networks) to be an alternative to the numerical simulation. We have applied the workflow to the field of dental implant design process. The process is based on a complex, time-dependent, multi-physical biomechanical theory, known as mechano-regulatory method. It has been used to evaluate the performance of dental implants and to assess the tissue recovery after the oral surgery procedures. We provided a deep learning network (DLN) with calibrated simulation data that came from different simulation conditions with experimental verification. The DLN achieves nearly exact result of simulated bone healing history around implants. The correlation of the predicted essential physical properties of surrounding bones (e.g. strain and fluid velocity) and performance indexes of implants (e.g. bone area and bone-implant contact) were greater than 0.980 and 0.947, respectively. The testing AUC values for the classification of each tissue phenotype were ranging from 0.90 to 0.99. The DLN reduced hours of simulation time to seconds. Moreover, our DLN is explainable via Deep Taylor decomposition, suggesting that the transverse fluid velocity, upper and lower parts of dental implants are the keys that influence bone healing and the distribution of tissue phenotypes the most. Many examples of commercial dental implants with designs which follow these design strategies can be found. This work demonstrates that DLN with proper network design is capable to replace complex, time-dependent, multi-physical models/theories, as well as to reveal the underlying features without prior professional knowledge.

Novel Design and Finite Element Analysis of Diamond-like Porous Implants with Low Stiffness

The purpose of this study was to design porous implants with low stiffness and evaluate their biomechanical behavior. Thus, two types of porous implants were designed (Type I: a combined structure of diamond-like porous scaffold and traditional tapered thread. Type II: a cylindrical porous scaffold filled by arrayed basic diamond-like pore units). Three implant-supported prosthesis models were constructed from Type I, Type II and commercial implants (control group) and were evaluated by finite element analysis (FEA). The stress distribution pattern of the porous implants were assessed and compared with the control group. In addition, the stiffness of the cylindrical specimens simplified from three types of implants was calculated. The Type I implant exhibited better stress distribution than the Type II implant. The maximum stress between the cortical bone–Type I implant interface was 12.9 and 19.0% lower than the other two groups. The peak stress at the cancellous bone–Type I implant interface was also reduced by 16.8 and 38.7%. Compared with the solid cylinder, the stiffness of diamond-like pore cylinders simplified from the two porous implants geometry was reduced by 61.5 to 76.1%. This construction method of porous implant can effectively lower its stiffness and optimize the stress distribution at the implant–bone interface.

The role of cortical zone level and prosthetic platform angle in dental implant mechanical response: A 3D finite element analysis

OBJECTIVE

The aim of this study was to evaluate the influence of three different dental implant neck geometries, under a combined compressive/shear load using finite element analysis (FEA). The implant neck was positioned in D2 quality bone at the crestal level or 2 mm below.

METHODS

One dental implant (4.2 × 9 mm) was digitized by reverse engineering techniques using micro CT and imported into Computer Aided Design (CAD) software. Non-uniform rational B-spline surfaces were reconstructed, generating a 3D volumetric model similar to the digitized implant. Three different models were generated with different implant neck configurations, namely 0°, 10° and 20°. D2 quality bone, composed of cortical and trabecular structure, was modeled using data from CT scans. The implants were included in the bone model using a Boolean operation. Two different fixture insertion depths were simulated for each implant: 2 mm below the crestal bone and exactly at the level of the crestal bone. The obtained models were imported to FEA software in STEP format. Von Mises equivalent strains were analyzed for the peri-implant D2 bone type, considering the magnitude and volume of the affected surrounding cortical and trabecular bone. The highest strain values in both cortical and trabecular tissue at the peri-implant bone interface were extracted and compared.

RESULTS

All implant models were able to distribute the load at the bone-implant contact (BIC) with a similar strain pattern between the models. At the cervical region, however, differences were observed: the models with 10° and 20° implant neck configurations (Model B and C), showed a lower strain magnitude when compared to the straight neck (Model A). These values were significantly lower when the implants were situated at crestal bone levels. In the apical area, no differences in strain values were observed.

SIGNIFICANCE

The implant neck configuration influenced the strain distribution and magnitude in the cortical bone and cancellous bone tissues. To reduce the strain values and improve the load dissipation in the bone tissue, implants with 10° and 20 neck configuration should be preferred instead of straight implant platforms.

Qualitative predictions of bone growth over optimally designed macro-textured implant surfaces obtained using NN-GA based machine learning framework

The surface features on implant surface can improve biologic fixation of the implant with the host bone leading to improved secondary (biological) implant stability. Application of finite element (FE) based mechanoregulatory schemes to estimate the amount of bone growth for a wide range of implant surface features is either manually intensive or computationally expensive. This study adopts an integrated approach combining FE, back-propagation neural network (BPNN) and genetic algorithm (GA) based search to evaluate optimum surface macro-textures from three representative implant models so as to enhance bone growth. Initial surface textures chosen for the implant models were based on an earlier investigation. Based on FE predicted dataset, a BPNN was formulated for faster prediction of bone growth. Using the BPNN predicted output, a GA-based search was carried out to maximize bone growth subject to clinically admissible micromotion at the bone-implant interface. The results from FE analysis and bone growth predictions from the BPNN were found to have strong correlation. The optimal osseointegration-maximized-textures (OMTs) obtained were found to offer enhanced biological fixation, as compared to that offered by the textures in the initial models. Results from the present study reveal that certain reduction in the dimension of ribs/grooves promotes bone growth. However, periodic patterns of ribs with higher and lower rib dimensions provide uniform stress environment at the interface thus promoting osseointegration.

Numerical simulations on periprosthetic bone remodeling: a systematic review

BACKGROUND AND OBJECTIVE

The aim of the present study was to review the literature concerning the analysis of periprosthetic bone remodeling through finite element (FE) simulation.

METHODS

A systematic review was conducted on 9 databases, taking into account a ten-year time period (from 2009 until 2020). The inclusion criteria were: articles published in English, publication date after 2009, full text articles, articles containing the keywords both in the abstract and in the title. The articles were classified through the following parameters: dimensionality of the simulation, modelling of the bone-prosthesis interface, output parameters, type of simulated prosthesis, bone remodeling algorithm.

RESULTS

Sixty-seven articles were included in the study. Femur and tooth were the most evaluated bone segment (respectively 41.8% and 29.9%). The 55.2% of the evaluated articles used a bonded bone-prosthesis interface, 73% used 3D simulations, 67.2% of the articles (45 articles) evaluate the bone remodeling by the bone density variation. At last, 59.7% of the articles employed algorithms based on a specific remodeling function.

CONCLUSIONS

Increasing interest in the bone remodeling FE analysis in different bone segments emerged from the review, and heterogeneous solutions were adopted. An optimal balance between computational cost and accuracy is needed to accurately simulate the bone remodeling phenomenon in the post-operative period.

Healing Pattern Analysis for Dental Implants Using the Mechano-Regulatory Tissue Differentiation Model

(1) Background: Our aim is to reveal the influence of the geometry designs on biophysical stimuli and healing patterns. The design guidelines for dental implants can then be provided. (2) Methods: A two-dimensional axisymmetric finite element model was developed based on mechano-regulatory algorithm. The history of tissue differentiation around eight selected implants can be predicted. The performance of the implants was evaluated by bone area (BA), bone-implant contact (BIC); (3) Results: The predicted healing patterns have very good agreement with the experimental observation. Many features observed in literature, such as soft tissues covering on the bone-implant interface; crestal bone loss; the location of bone resorption bumps, were reproduced by the model and explained by analyzing the solid and fluid biophysical stimuli and (4) Conclusions: The results suggested the suitable depth, the steeper slope of the upper flanks, and flat roots of healing chambers can improve the bone ingrowth and osseointegration. The mechanism related to solid and fluid biophysical stimuli were revealed. In addition, the model developed here is efficient, accurate and ready to extend to any geometry of dental implants. It has potential to be used as a clinical application for instant prediction/evaluation of the performance of dental implants.

The effect of diameter, length and elastic modulus of a dental implant on stress and strain levels in peri-implant bone: A 3D finite element analysis

This study investigated the effect of three different parameters of a dental implant on stress and strain values in the peri-implant bone by finite element analysis. In this work, the effect of diameter, length and elastic modulus on the biomechanical behavior of a new dental implant was simulated using the finite element method. A three-dimensional model of a mandible segment corresponding to the premolar region and twelve dental implant models were obtained. Loads in three directions were distributed on the surface of the coronal area of the dental implants. The dental implant models were obtained in the FreeCAD 0.16 software and the simulations were made using the Abaqus/CAE software. In all cases, higher stress concentrations were obtained in the peri-implant cortical bone between 40.6 and 62.8 MPa, while the highest levels of strain were observed in the peri-implant trabecular bone between 0.002544 and 0.003873. In general, the highest von Mises equivalent stress values were observed in the peri-implant cortical bone. However, in this bone, both the maximum von Mises equivalent stress values and the von Mises strain are similar or inferior to those reported in different studies by finite element for other models of dental implants under immediate loading. Maximum von Mises strain values were observed in peri-implant trabecular bone. However, in this bone strains levels were obtained that maintain bone density or increase it. The effect of the three simulated variables (implant diameter, length, and elastic modulus) have a statistically significant influence on the von Mises equivalent stress and in von Mises strain values.

Novel design of additive manufactured hollow porous implants

OBJECTIVE

Our aim is to examine the mechanical properties of two types of additive manufactured hollow porous dental implants and 6 and 12-week bone ingrowth after insertion in animals. A 3D numerical model is also developed to show detailed tissue differentiation and to provide design guidelines for implants.

METHODS

The two porous and a commercial dental implant were studied by series of in vitro mechanical tests (three-point bending, torsional, screwing torque, and sawbone pull-out tests). They also evaluated by in vivo animal tests (micro-CT analysis) and ex vivo pull-out tests. Moreover, the mechano-regulation algorithm was implemented by the 3D finite element model to predict the history of tissue differentiation around the implants.

RESULTS

The results showed that the two porous implants can significantly improve osseointegration after 12-week bone healing. This resulted in good fixation and stability of implants, giving very high maximum pull-out strength 413.1 N and 493.2 N, compared to 245.7 N for the commercial implant. Also, several features were accurately predicted by the mechano-regulation model, such as transversely connected bone formation, and bone resorption occurred in the middle of implants.

SIGNIFICANCE

Systematic studies on dental implants with multiple approaches, including new design, mechanical tests, animal tests, and numerical modeling, were performed. Two hollow porous implants significantly improved bone ingrowth compared with commercial implants, while maintaining mechanical strength. Also, the numerical model was verified by animal tests. It improved the efficiency of design and reduce the demand for animal sacrifice.

The influence of macro-textural designs over implant surface on bone on-growth: A computational mechanobiology based study

The longerterm secondary stability of an uncemented implant depends primarily on the quality and extent of bone in-growth or on-growth at the bone-implant interface. Investigations are warranted to predict the influences of implant macro-textures on bone on-growth pattern. Mechanoregulatory tissue differentiation algorithms can predict such patterns effectively. There is, however, a dearth of volumetric in silico study to assess the influence of macro-textures on bone growth. The present study investigated the influence of macro-textural grooves/ribs on changes in tissue formation at the bone-implant interface by carrying out a 3D finite element (FE) analysis. Three distinct macro-textures, loosely based on commercially viable hip stem models, were comparatively assessed for varying levels of interfacial micromotion. The study predicted elevated fibrogenesis and chondrogenesis, followed by a suppressed osteogenesis for higher levels of micromotion (60 μm and 100 μm), resulting in weak bone-implant interface strength. However, small judicious modifications in implant surface texture may enhance bone growth to a considerable extent. The numerical scheme can further be used as a template for more rigorous parametric and multi-scale studies.

A Hybrid Model for Predicting Bone Healing around Dental Implants

BACKGROUND

The effect of the short-term bone healing process is typically neglected in numerical models of bone remodeling for dental implants. In this study, a hybrid two-step algorithm was proposed to enable a more accurate prediction for the performance of dental implants.

METHODS

A mechano-regulation algorithm was firstly used to simulate the tissue differentiation around a dental implant during the short-term bone healing. Then, the result was used as the initial state of the bone remodeling model to simulate the long-term healing of the bones. The algorithm was implemented by a 3D finite element model.

RESULTS

The current hybrid model reproduced several features which were discovered in the experiments, such as stress shielding effect, high strength bone connective tissue bands, and marginal bone loss. A reasonable location of bone resorptions and the stability of the dental implant is predicted, compared with those predicted by the conventional bone remodeling model.

CONCLUSIONS

The hybrid model developed here predicted bone healing processes around dental implants more accurately. It can be used to study bone healing before implantation surgery and assist in the customization of dental implants.

The interplay between bone healing and remodeling around dental implants

Long-term bone healing/adaptation after a dental implant treatment starts with diffusion of mesenchymal stem cells to the wounded region and their subsequent differentiation. The healing phase is followed by the bone-remodeling phase. In this work, a mechano-regulatory cellular differentiation model was used to simulate tissue healing around an immediately loaded dental implant. All tissue types were modeled as poroelastic in the healing phase. Material properties of the healing region were updated after each loading cycle for 30 cycles (days). The tissue distribution in the healed state was then used as the initial condition for the remodeling phase during which regions healed into bone adapt their apparent density with respect to a homeostatic remodeling stimulus. The short- (bone healing) and long-term (bone remodeling) effects of initial implant micromotion during the healing phase were studied. Development of soft tissue was observed both in the coronal region due to high fluid velocity, and on the vertical sides of the healing-gap due to high shear stress. In cases with small implant micromotion, tissue between the implant threads differentiated into bone during the healing phase but resorbed during remodeling. In cases with large implant micromotion, higher percentage of the healing region differentiated into soft tissue resulting in smaller volume of bone tissue available for remodeling. However, the remaining bone region developed higher density bone tissue. It was concluded that an optimal range of initial implant micromotion could be designed for a specific patient in order to achieve the desired long-term functional properties.

Numerical Simulation of Mandible Bone Remodeling under Tooth Loading: A Parametric Study

Bone adapts to the change of mechanical stimulus by bone remodeling activities. A number of numerical algorithms have been developed to model the adaptive bone remodeling under mechanical loads for orthopedic and dental applications. This paper examines the effects of several model parameters on the computed apparent bone density in mandible under normal chewing and biting forces. The density change rate was based on the strain energy density per unit mass. The algorithms used in this study containing an equilibrium zone (lazy zone) and saturated values of density change rate provides certain stability to result in convergence without discontinuous checkerboard patterns. The parametric study shows that when different boundary conditions were applied, the bone density distributions at convergence were very different, except in the vicinity of the applied loads. Compared with the effects of boundary conditions, the models are less sensitive to the choice of initial density values. Several models starting from different initial density values resulted in similar but not exactly the same bone density distribution at convergence. The results also show that higher reference value of mechanical stimulus resulted in lower average bone density at convergence. Moreover, the width of equilibrium zone did not substantially affect the average density at convergence. However, with increasing width, the areas with the highest and the lowest bone density areas were all reduced. The limitations of the models and challenges for future work were discussed for the better agreement between the computed results and the in vivo data.

Combined Bone Ingrowth and Remodeling Around Uncemented Acetabular Component: A Multiscale Mechanobiology-Based Finite Element Analysis

Bone ingrowth and remodeling are two different evolutionary processes which might occur simultaneously. Both these processes are influenced by local mechanical stimulus. However, a combined study on bone ingrowth and remodeling has rarely been performed. This study is aimed at understanding the relationship between bone ingrowth and adaptation and their combined influence on fixation of the acetabular component. Based on three-dimensional (3D) macroscale finite element (FE) model of implanted pelvis and microscale FE model of implant–bone interface, a multiscale framework has been developed. The numerical prediction of peri-acetabular bone adaptation was based on a strain-energy density-based formulation. Bone ingrowth in the microscale models was simulated using the mechanoregulatory algorithm. An increase in bone strains near the acetabular rim was observed in the implanted pelvis model, whereas the central part of the acetabulum was observed to be stress shielded. Consequently, progressive bone apposition near the acetabular rim and resorption near the central region were observed. Bone remodeling caused a gradual increase in the implant–bone relative displacements. Evolutionary bone ingrowth was observed around the entire acetabular component. Poor bone ingrowth of 3–5% was predicted around the centro-inferio and inferio-posterio-superio-peripheral regions owing to higher implant–bone relative displacements, whereas the anterio-inferior and centro-superior regions exhibited improved bone ingrowth of 35–55% due to moderate implant–bone relative displacement. For an uncemented acetabular CoCrMo component, bone ingrowth had hardly any effect on bone remodeling; however, bone remodeling had considerable influence on bone ingrowth.

Influence of Implant Surface Texture Design on Peri-Acetabular Bone Ingrowth: A Mechanobiology Based Finite Element Analysis

The fixation of uncemented acetabular components largely depends on the amount of bone ingrowth, which is influenced by the design of the implant surface texture. The objective of this numerical study is to evaluate the effect of these implant texture design factors on bone ingrowth around an acetabular component. The novelty of this study lies in comparative finite element (FE) analysis of 3D microscale models of the implant-bone interface, considering patient-specific mechanical environment, host bone material property and implant-bone relative displacement, in combination with sequential mechanoregulatory algorithm and design of experiment (DOE) based statistical framework. Results indicated that the bone ingrowth process was inhibited due to an increase in interbead spacing from 200 μm to 600 μm and bead diameter from 1000 μm to 1500 μm and a reduction in bead height from 900 μm to 600 μm. Bead height, a main effect, was found to have a predominant influence on bone ingrowth. Among the interaction effects, the combination of bead height and bead diameter was found to have a pronounced influence on bone ingrowth process. A combination of low interbead spacing (P = 200 μm), low bead diameter (D = 1000 μm), and high bead height (H = 900 μm) facilitated peri-acetabular bone ingrowth and an increase in average Young's modulus of newly formed tissue layer. Hence, such a surface texture design seemed to provide improved fixation of the acetabular component.

Determination of spatially dependent diffusion parameters in bovine bone using Kalman filter

Although many studies have been made for homogenous constant diffusion, bone is an inhomogeneous material. It has been suggested that bone porosity decreases from the inner boundaries to the outer boundaries of the long bones. The diffusivity of substances in the bone matrix is believed to increase as the bone porosity increases. In this study, an experimental set up is used where bovine bone samples, saturated with potassium chloride (KCl), were put into distilled water and the conductivity of the water was followed. Chloride ions in the bone samples escaped out in the water through diffusion and the increase of the conductivity was measured. A one-dimensional, spatially dependent mathematical model describing the diffusion process is used. The diffusion parameters in the model are determined using a Kalman filter technique. The parameters for spatially dependent at endosteal and periosteal surfaces are found to be (12.8 ± 4.7) × 10(-11) and (5 ± 3.5) × 10(-11)m(2)/s respectively. The mathematical model function using the obtained diffusion parameters fits very well with the experimental data with mean square error varies from 0.06 × 10(-6) to 0.183 × 10(-6) (μS/m)(2).

Influence of a micro-thread at cervical position and a cylindrical intermediate zone on the mechanical behaviour of dental implants: A three-dimensional finite element analysis

The purpose of this work is to analyse the influence on the biomechanical behaviour of dental implants of a micro-thread at their cervical part as well as of a cylindrical geometry at an intermediate zone. Stresses and strains in the elements involved, that is, bone, implant, screw and abutment, have to be considered in detail. Three different three-dimensional finite element models are generated to analyse the behaviour of the various components under the so-called tightening and operating conditions. For the modelling, material specifications for the cancellous bone and cortical bone, on one hand, and titanium properties for the implant, screw and abutment, on the other, are implemented. The tightening condition was fixed according to the stresses in the screw. The operating conditions were simulated by applying a force of 150 N, taking into account ISO 14801:2007 standard. The maximum stress under tightening conditions occurs always in the screw, while under operating conditions it is produced at the screw or the abutment, although considerable stress values are also present in the implant. In all the models, the maximum stress at the junction between the implant and the bone occurs within the cortical bone. Implants provided with micro-thread at the cervical position are advantageous over homogeneously threaded implants since lower stresses in both the implant and the adjacent bone are produced. A cylindrical intermediate portion on the implant surface does not present special advantage over the implants with continuous external thread under tightening and operating conditions.

Evaluation of bone remodeling around single dental implants of different lengths: a mechanobiological numerical simulation and validation using clinical data

Algorithmic models have been proposed to explain adaptive behavior of bone to loading; however, these models have not been applied to explain the biomechanics of short dental implants. Purpose of present study was to simulate bone remodeling around single implants of different lengths using mechanoregulatory tissue differentiation model derived from the Stanford theory, using finite elements analysis (FEA) and to validate the theoretical prediction with the clinical findings of crestal bone loss. Loading cycles were applied on 7-, 10-, or 13-mm-long dental implants to simulate daily mastication and bone remodeling was assessed by changes in the strain energy density of bone after a 3, 6, and 12 months of function. Moreover, clinical findings of marginal bone loss in 45 patients rehabilitated with same implant designs used in the simulation (n = 15) were computed to validate the theoretical results. FEA analysis showed that although the bone density values reduced over time in the cortical bone for all groups, bone remodeling was independent of implant length. Clinical data showed a similar pattern of bone resorption compared with the data generated from mathematical analyses, independent of implant length. The results of this study showed that the mechanoregulatory tissue model could be employed in monitoring the morphological changes in bone that is subjected to biomechanical loads. In addition, the implant length did not influence the bone remodeling around single dental implants during the first year of loading.

The influence of the connection, length and diameter of an implant on bone biomechanics

BACKGROUND

Regardless of the multiple options of connections, diameters and heights for dental implants, the clinician should know the biomechanical behavior of the bone to plan the treatment according to the biological and anatomical conditions of each patient, without risk to the long-term treatment success.

REVIEW

The following review attempts to summarize the relevant literature to establish guidelines for clinicians based on the scientific evidence regarding the influence by the implant's connection, diameter and length on the bone biomechanics.

CONCLUSIONS

The length, diameter and connection of each implant have a degree of influence in bone biomechanics. Despite the influence of different implant connections, diameters and lengths on peri-implant bone stress and strain, these characteristics should remain within the physiological limits to avoid a pathological overload, bone resorption and consequent risk to the long-term success of implant-prosthetic treatment.

Bone ingrowth around porous-coated acetabular implant: a three-dimensional finite element study using mechanoregulatory algorithm

Fixation of uncemented implant is influenced by peri-prosthetic bone ingrowth, which is dependent on the mechanical environment of the implant-bone structure. The objective of the study is to gain an insight into the tissue differentiation around an acetabular component. A mapping framework has been developed to simulate appropriate mechanical environment in the three-dimensional microscale model, implement the mechanoregulatory tissue differentiation algorithm and subsequently assess spatial distribution of bone ingrowth around an acetabular component, quantitatively. The FE model of implanted pelvis subjected to eight static load cases during a normal walking cycle was first solved. Thereafter, a mapping algorithm has been employed to include the variations in implant-bone relative displacement and host bone material properties from the macroscale FE model of implanted pelvis to the microscale FE model of the beaded implant-bone interface. The evolutionary tissue differentiation was observed in each of the 13 microscale models corresponding to 13 acetabular regions. The total implant-bone relative displacements, averaged over each region of the acetabulum, were found to vary between 10 and 60 μm. Both the linear elastic and biphasic poroelastic models predicted similar mechanoregulatory peri-prosthetic tissue differentiation. Considerable variations in bone ingrowth (13-88%), interdigitation depth (0.2-0.82 mm) and average tissue Young's modulus (970-3430 MPa) were predicted around the acetabular cup. A progressive increase in the average Young's modulus, interdigitation depth and decrease in average radial strains of newly formed tissue layer were also observed. This scheme can be extended to investigate tissue differentiation for different surface texture designs on the implants.