Debonding of coin-shaped osseointegrated implants: Coupling of experimental and numerical approaches.

While cementless implants are now widely used clinically, implant debonding still occur and is difficult to anticipate. Assessing the biomechanical strength of the bone-implant interface can help improving the understanding of osseointegration phenomena and thus preventing surgical failures. A dedicated and standardized implant model was considered. The samples were tested using a mode III cleavage device to assess the mechanical strength of the bone-implant interface by combining experimental and numerical approaches. Four rough (Sa = 24.5 µm) osseointegrated coin-shaped implants were left in sheep cortical bone during 15 weeks of healing time. Each sample was experimentally rotated at 0.03°/sec until complete rupture of the interface. The maximum values of the torque were comprised between 0.48 and 0.72 N m, while a significant increase of the normal force from 7-12 N to 31-43 N was observed during the bone-implant interface debonding, suggesting the generation of bone debris at the bone-implant interface. The experimental results were compared to an isogeometric finite element model describing the adhesion and debonding phenomena through a modified Coulomb's law, based on a varying friction coefficient to represent the transition from an unbroken to a broken bone-implant interface. A good agreement was found between numerical and experimental torques, with numerical friction coefficients decreasing from 8.93 to 1.23 during the bone-implant interface rupture, which constitutes a validation of this model to simulate the debonding of an osseointegrated bone-implant interface subjected to torsion.

Using an Instrumented Hammer to Predict the Rupture of Bone Samples Subject to an Osteotomy.

Osteotomies are common procedures in maxillofacial and orthopedic surgery. The surgeons still rely on their proprioception to control the progression of the osteotome. Our group has developed an instrumented hammer that was shown to provide information on the biomechanical properties of the tissue located around the osteotome tip. The objective of this study is to determine if this approach may be used to predict the rupture of a bone sample thanks to an instrumented hammer equipped with a force sensor. For each impact, an indicator τ is extracted from the signal corresponding to the variation of the force as a function of time. A linear by part regression analysis is applied to the curve corresponding to the variation of τ as a function of the distance d between the tip of the osteotome and the end of the sample. The experiments were conducted with plywood and bovine trabecular bone samples. The results show that τ starts increasing when the value of d is lower than 2.6 mm on average, which therefore corresponds to a typical threshold detection distance between the osteotome tip and the sample end. These findings open new paths for the development of this instrumented surgical hammer.

Mechanical micromodeling of stress-shielding at the bone-implant interphase under shear loading.

Inserting a titanium implant in the bone tissue may modify its physiological loading and therefore cause bone resorption, via a phenomenon called stress-shielding. The local stress field around the bone-implant interphase (BII) created under shear loading may be influenced by different parameters such as the bone-implant contact (BIC) ratio, the bone Young's modulus, the implant roughness and the implant material. A 2-D finite element model was developed to model the BII and evaluate the impact of the aforementioned parameters. The implant roughness was described by a sinusoidal function (height 2Δ, wavelength λ), and different values of the BIC ratio were simulated. A heterogeneous distribution of the maximum shear stress was evidenced in the periprosthetic bone tissue, with high interfacial stress for low BIC ratios and low implant roughness and underloaded regions near the roughness valleys. Both phenomena may lead to stress-shielding-related effects, which were concentrated within a distance lower than 0.8λ from the implant surface. Choosing an implant material with mechanical properties matching those of bone tissue leads to a homogenized shear stress field and could help to prevent stress-shielding effects. Finally, the equivalent shear modulus of the BII was derived to replace its complex behavior with a simpler analytical model in future studies. Schematic illustrations of the 2-D finite element model used in the present study and spatial variation of the maximal shear stress in the periprosthetic bone tissue for different implant roughness and bone-implant contact ratios.

Ultrasonic Evaluation of the Bone-Implant Interface.

While implant surgical interventions are now routinely performed, failures still occur and may have dramatic consequences. The clinical outcome depends on the evolution of the biomechanical properties of the bone-implant interface (BII). This chapter reviews studies investigating the use of quantitative ultrasound (QUS) techniques for the characterization of the BII.First, studies on controlled configurations evidenced the influence of healing processes and of the loading conditions on the ultrasonic response of the BII. The gap of acoustical properties at the BII increases (i) during healing and (ii) when stress at the BII increases, therefore inducing a decrease of the reflection coefficient at the BII.Second, an acoustical model of the BII is proposed to better understand the parameters influencing the interaction between ultrasound and the BII. The reflection coefficient is shown to decrease when (i) the BII is better osseointegrated, (ii) the implant roughness decreases, (iii) the frequency of QUS decreases and (iv) the bone mass density increases.Finally, a 10 MHz device aiming at assessing dental implant stability was validated in vitro, in silico and in vivo. A comparison between QUS and resonance frequency analysis (RFA) techniques showed a better sensitivity of QUS to changes of the parameters related to the implant stability.

Ultrasonic assessment of osseointegration phenomena at the bone-implant interface using convolutional neural network.

Although endosseous implants are widely used in the clinic, failures still occur and their clinical performance depends on the quality of osseointegration phenomena at the bone-implant interface (BII), which are given by bone ingrowth around the BII. The difficulties in ensuring clinical reliability come from the complex nature of this interphase related to the implant surface roughness and the presence of a soft tissue layer (non-mineralized bone tissue) at the BII. The aim of the present study is to develop a method to assess the soft tissue thickness at the BII based on the analysis of its ultrasonic response using a simulation based-convolution neural network (CNN). A large-annotated dataset was constructed using a two-dimensional finite element model in the frequency domain considering a sinusoidal description of the BII. The proposed network was trained by the synthesized ultrasound responses and was validated by a separate dataset from the training process. The linear correlation between actual and estimated soft tissue thickness shows excellent R2 values equal to 99.52% and 99.65% and a narrow limit of agreement corresponding to [ -2.56, 4.32 µm] and [ -15.75, 30.35 µm] of microscopic and macroscopic roughness, respectively, supporting the reliability of the proposed assessment of osseointegration phenomena.

Assessment of dental implant stability using resonance frequency analysis and quantitative ultrasound methods.

Purpose Quantitative ultrasound (QUS) and resonance frequency analyses (RFA) are promising methods to assess the stability of dental implants. The aim of this in vivo preclinical study is to compare the results obtained with these two techniques with the bone-implant contact (BIC) ratio, which is the gold standard to assess dental implant stability.Methods Twenty-two identical dental implants were inserted in the tibia and femur of 12 rabbits, which were sacrificed after different healing durations (0, 4, 8 and 13 weeks). For each implant, the ultrasonic indicator (UI) and the implant stability quotient (ISQ) were retrieved just before the animal sacrifice using the QUS and RFA techniques, respectively. Histomorphometric analyses were carried out to estimate the bone-implant contact ratio.Results UI values were found to be better correlated to BIC values (R²=0.47) compared to ISQ values (R²=0.39 for measurements in one direction and R²=0.18 for the other direction), which were shown to be dependent on the direction of measurements. Errors realized on the UI were around 3.3 times lower to the ones realized on the ISQ.Conclusions QUS provide a better estimation of dental implant stability compared to RFA. This study paves the way for the future clinical development of a medical device aiming at assessing dental implant stability in a patient-specific manner. Clinical studies should confirm these results in the future.

Analytical modeling of the interaction of an ultrasonic wave with a rough bone-implant interface.

Quantitative ultrasound can be used to characterize the evolution of the bone-implant interface (BII), which is a complex system due to the implant surface roughness and to partial contact between bone and the implant. The determination of the constitutive law of the BII would be of interest in the context of implant acoustical modeling in order to take into account the imperfect characteristics of the BII. The aim of the present study is to propose an analytical effective model describing the interaction between an ultrasonic wave and a rough BII. To do so, a spring model was considered to determine the equivalent stiffness K of the BII. The stiffness contributions related (i) to the partial contact between the bone and the implant and (ii) to the presence of soft tissues at the BII during the process of osseointegration were assessed independently. K was found to be comprised between 1013 and 1017 N/m3 depending on the roughness and osseointegration of the BII. Analytical values of the reflection and transmission coefficients at the BII were derived from values of K. A good agreement with numerical results obtained through finite element simulation was obtained. This model may be used for future finite element bone-implant models to replace the BII conditions.

Ultrasonic Propagation in a Dental Implant.

Ultrasound techniques can be used to characterize and stimulate dental implant osseointegration. However, the interaction between an ultrasonic wave and the implant-bone interface (IBI) remains unclear. This study-combining experimental and numerical approaches-investigates the propagation of an ultrasonic wave in a dental implant by assessing the amplitude of the displacements along the implant axis. An ultrasonic transducer was excited in a transient regime at 10 MHz. Laser interferometric techniques were employed to measure the amplitude of the displacements, which varied 3.2-8.9 nm along the implant axis. The results demonstrated the propagation of a guided wave mode along the implant axis. The velocity of the first arriving signal was equal to 2110 m.s-1, with frequency components lower than 1 MHz, in agreement with numerical results. Investigating guided wave propagation in dental implants should contribute to improved methods for the characterization and stimulation of the IBI.

Reflection of an ultrasonic wave on the bone-implant interface: Comparison of two-dimensional and three-dimensional numerical models.

Quantitative ultrasound is used to characterize osseointegration at the bone-implant interface (BII). However, the interaction between an ultrasonic wave and the implant remains poorly understood. Hériveaux, Nguyen, and Haiat [(2018). J. Acoust. Soc. Am. 144, 488-499] recently employed a two-dimensional (2D) model of a rough BII to investigate the sensitivity of the ultrasonic response to osseointegration. The present letter aimed at assessing the validity of the 2D assumption. The values of the reflection coefficient of the BII obtained with two and three-dimensional models were found not to be significantly different for implant roughness lower than 20 µm. 2D modeling is sufficient to describe the interaction between ultrasound and the BII.

Elastography of the bone-implant interface.

The stress distribution around endosseous implants is an important determinant of the surgical success. However, no method developed so far to determine the implant stability is sensitive to the loading conditions of the bone-implant interface (BII). The objective of this study is to investigate whether a quantitative ultrasound (QUS) technique may be used to retrieve information on compressive stresses applied to the BII. An acousto-mechanical device was conceived to compress 18 trabecular bovine bone samples onto coin-shaped implants and to measure the ultrasonic response of the BII during compression. The biomechanical behavior of the trabecular bone samples was modeled as Neo-Hookean. The reflection coefficient of the BII was shown to decrease as a function of the stress during the elastic compression of the trabecular bone samples and during the collapse of the trabecular network, with an average slope of -4.82 GPa-1. The results may be explained by an increase of the bone-implant contact ratio and by changes of bone structure occurring during compression. The sensitivity of the QUS response of the BII to compressive stresses opens new paths in the elaboration of patient specific decision support systems allowing surgeons to assess implant stability that should be developed in the future.

Reflection of an ultrasonic wave on the bone-implant interface: Effect of the roughness parameters.

Quantitative ultrasound can be used to characterize the evolution of the bone-implant interface (BII), which is a complex system due to the implant surface roughness and to partial contact between bone and the implant. The aim of this study is to derive the main determinants of the ultrasonic response of the BII during osseointegration phenomena. The influence of (i) the surface roughness parameters and (ii) the thickness W of a soft tissue layer on the reflection coefficient r of the BII was investigated using a two-dimensional finite element model. When W increases from 0 to 150 µm, r increases from values in the range [0.45; 0.55] to values in the range [0.75; 0.88] according to the roughness parameters. An optimization method was developed to determine the sinusoidal roughness profile leading to the most similar ultrasonic response for all values of W compared to the original profile. The results show that the difference between the ultrasonic responses of the optimal sinusoidal profile and of the original profile was lower to typical experimental errors. This approach provides a better understanding of the ultrasonic response of the BII, which may be used in future numerical simulation realized at the scale of an implant.

Reflection of an ultrasonic wave on the bone-implant interface: A numerical study of the effect of the multiscale roughness.

Quantitative ultrasound is used to characterize and stimulate osseointegration processes at the bone-implant interface (BII). However, the interaction between an ultrasonic wave and the implant remains poorly understood. This study aims at investigating the sensitivity of the ultrasonic response to the microscopic and macroscopic properties of the BII and to osseointegration processes. The reflection coefficient R of the BII was modeled for different frequencies using a two-dimensional finite element model. The implant surface roughness was modeled by a sinusoidal function with varying amplitude h and spatial frequency L. A soft tissue layer of thickness W was considered between bone tissue and the implant in order to model non-mineralized fibrous tissue. For microscopic roughness, R is shown to increase from around 0.55 until 0.9 when kW increases from 0 to 1 and to be constant for kW > 1, where k is the wavenumber in the implant. These results allow us to show that R depends on the properties of bone tissue located at a distance comprised between 1 and 25 µm from the implant surface. For macroscopic roughness, R is highly dependent on h and this dependence may be explained by phase cancellation and multiple scattering effects for high roughness parameters.