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

Development and validation of an algorithm to determine the minimal factors needed for non-invasive measurement of the in vivo primary stability of cementless hip implants

Aseptic loosening is a frequent cause for revision of endoprosthesis. X-ray examinations like Radio-Stereometry-Analysis (RSA) are among the most widely used in vivo methods for its detection. Nevertheless, this method is not used routinely because of bone marker and related radiation exposure. This work aims at creating a new in vivo concept to detect implant stability measuring micromotions without x-ray and to develop a corresponding algorithm. Based on the assumption of contactless measurement, the input parameters for the algorithm are the distances of each ultrasound sensor to the object (prosthesis and bone) and its position. First, the number of parameters necessary for a precise reconstruction and measurement of micromotions between objects had to be defined. Therefore, the algorithm has been tested with simulations of these parameters. Two experimental measurements, either using contact sensors or ultrasound, were used to prove the accuracy of the algorithm. Simulations indicate a high accuracy with three distances as initial parameters for each object. Contact measurements show precise representation of micromotion, and the contactless measurements show the possibility of detecting various materials with a high resolution. This work lays the foundations for non-invasive detection of micromotions between the implant-bone interface.

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.

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.

Quantitative ultrasound assessment of the influence of roughness and healing time on osseointegration phenomena

The evolution of bone tissue quantity and quality in contact with the surface of orthopedic and dental implants is a strong determinant of the surgical outcome but remains difficult to be assessed quantitatively. The aim of this study was to investigate the performance of a quantitative ultrasound (QUS) method to measure bone-implant interface (BII) properties. A dedicated animal model considering coin-shaped titanium implants with two levels of surface roughness (smooth, S_a = 0.49 µm and rough, S_a = 3.5 µm) allowed to work with a reproducible geometry and a planar interface. The implants were inserted in rabbit femurs and tibiae for 7 or 13 weeks. The ultrasonic response of the BII was measured ex vivo, leading to the determination of the 2-D spatial variations of bone in contact with the implant surface. Histological analysis was carried out to determine the bone-implant contact (BIC) ratio. The amplitude of the echo was significantly higher after 7 weeks of healing time compared to 13 weeks, for both smooth (p < 0.01) and rough (p < 0.05) implants. A negative correlation (R = − 0.63) was obtained between the ultrasonic response and the BIC. This QUS technique is more sensitive to changes of BII morphology compared to histological analyses.

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.