elastography of the bone-implant interface

International audiencethe 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. Endosseous cementless titanium implants are now widely used in orthopedic, dental and maxillofacial surgeries 1,2. However, despite a routine clinical use, osseointegration failures still occur and may have dramatic consequences. The implant surgical success is directly determined by the evolution of the biomechanical properties of the bone-implant interface (BII) 3-5. During surgery, endosseous implants are inserted in a slightly undersized bone cavity formed by drilling or cutting, leading to a pre-stressed state of the bone-implant system referred to as primary implant stability. A compromise should be found between (i) insufficient primary stability leading to excessive interfacial micromotion following surgery 6-8 , which may imply implant migration 9 and failure and (ii) excessive stresses at the BII, which may lead to bone necrosis 10,11. During healing, osseointegration phenomena, corresponding to an apposition of bone tissue around the implant surface, are stimulated by "low level" stresses applied to the BII 12 , but excessive level of stresses may damage the consolidating BII and lead to implant failure. As a consequence, the stress distribution around the implant during and after surgery is an important determinant for the implant success 13 , but it remains difficult to be assessed experimentally. X-ray based techniques 14 and magnetic resonance imaging 15 cannot be used to assess the level of stress at the BII due to diffraction phenomena related to the presence of metal. Therefore, biomechanical methods are needed. An interesting approach to assess the level of stress at the BII consists in employing finite element analysis (FEA). For example, stress and strain fields have been predicted around the BII in the context of dental 16,17 and orthopedic implants applications 18. The results showed that stresses in the range of 0-10 MPa could be obtained at the BII, depending on the physiological boundary conditions. However, despite the progresses realized in computational analyses, it remains difficult to assess in a patient specific manner the loading conditions at the BII due to the complexity of the implant geometry and of the bone material properties. Different biomechanical techniques have been developed to assess implant stability. For example, percussion test methods based on the measurement of the contact duration between the implant and the impacting device have been developed in the context of dental 19 and orthopedic surgery 20,21. The most commonly used biome-chanical technique is the resonance frequency analysis (RFA) 22 , which consists in measuring the first bendin

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: Comparison of two-dimensional and three-dimensional numerical models

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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

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Ultrasonic propagation in a dental implant

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Measurement of the propagation of a guided wave in a dental implant

International audienceUltrasound techniques can be used to characterize and stimulate dental implant osseointegration. The acoustical energy transmitted to the bone-implant interface is an important parameter for both applications since it should be sufficiently low to avoid damaging the surrounding tissues, but sufficiently high for stimulation purposes to enhance bone growth. However, the interaction between an ultrasonic wave and a dental implant remains unclear. The objective of this study combining experimental, analytical and numerical approaches is to investigate 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 transient regime at 10MHz. Laser interferometric techniques were employed to measure the amplitude of the displacements, which varied between 5 to 12 nm according to the position. The results show the propagation of a guided wave mode along the implant axis with a first arriving signal velocity equal to 2110 m.s-1 and frequency components lower than 1 MHz, which was confirmed by the analytical and numerical results. This work paves the way to improve techniques for the characterization and stimulation of the bone-implant interface

Numerical simulation of stress-shielding at the bone-implant interface under shear loading

International audienceInserting a titanium implant in bone tissue may modify its physiological loading and therefore cause bone resorption, a phenomenon known as stress-shielding [1]. While monitoring and preventing stress-shielding is necessary to ensure the surgical success, it remains difficult to experimentally retrieve information on the properties of the interfacial tissues at the scale of 1-100 μm from the implant surface, where this phenomenon is localized. Numerical modelling represents a complementary tool to better understand phenomena related to the coupled bone-implant system due to the difficulty of measuring the stress distribution in vivo. The aim of this study is to investigate numerically the influence of various geometrical and material parameters on the local stress field around a bone-implant interface (BII) subject to shear loading

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

International audienceAlthough 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 to ensure 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 simulation based-convolution neural network (CNN). A large-annotated dataset was constructed using a 2-D 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 R 2 values equal to 99.52% and 99.65%, and narrow limit of agreement corresponded to [-2.56, 4.32 µm] and [-15.75, 30.35 µm] for the microscopic and macroscopic roughness respectively, supporting the reliability of the proposed assessment for the osseointegration phenomena