Biomechanical determinants of the stability of dental implants: influence of the bone-implant interface properties.

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Review

Biomechanical determinants of the stability of dental implants: Influence of the bone–implant interface properties Vincent Mathieu a, Romain Vayron a, Gilles Richard b, Grégory Lambert b, Salah Naili a, Jean-Paul Meningaud c, Guillaume Haiat d,n a

Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, UMR CNRS 8208, 61 avenue du Général de Gaulle, 94010 Créteil cedex, France Septodont, 58 Rue Pont de Créteil, 94100 Saint-Maur-des-Fossés, France c Service de Chirurgie Plastique, Reconstructrice et Esthétique, CHU H. Mondor, 94017 Créteil cedex, France d CNRS, Laboratoire Modélisation et Simulation Multi Echelle, UMR CNRS 8208, 61 avenue du Général de Gaulle, 94010 Créteil cedex, France b

art ic l e i nf o

a b s t r a c t

Article history: Accepted 24 September 2013

Dental implants are now widely used for the replacement of missing teeth in fully or partially edentulous patients and for cranial reconstructions. However, risks of failure, which may have dramatic consequences, are still experienced and remain difficult to anticipate. The stability of biomaterials inserted in bone tissue depends on multiscale phenomena of biomechanical (bone–implant interlocking) and of biological (mechanotransduction) natures. The objective of this review is to provide an overview of the biomechanical behavior of the bone– dental implant interface as a function of its environment by considering in silico, ex vivo and in vivo studies including animal models as well as clinical studies. The biomechanical determinants of osseointegration phenomena are related to bone remodeling in the vicinity of the implants (adaptation of the bone structure to accommodate the presence of a biomaterial). Aspects related to the description of the interface and to its spacetime multiscale nature will first be reviewed. Then, the various approaches used in the literature to measure implant stability and the bone–implant interface properties in vitro and in vivo will be described. Quantitative ultrasound methods are promising because they are cheap, non invasive and because of their lower spatial resolution around the implant compared to other biomechanical approaches. & 2013 Elsevier Ltd. All rights reserved.

Keywords: Bone Implant Osseointegration Biomechanical properties Stability

Contents 1. 2.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Description of the bone–implant interface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Geometrical description: bone–implant distance and micromotions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Mechanical description: stresses at the interface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Dynamic description: bone remodeling and osseointegration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Implant stability: a space-time multiscale issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Measurement of the multiscale bone properties around the interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Homogenization approaches of bone tissue around the interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Multiscale biomechanical modeling of the bone–implant interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Implant stability assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. X-ray and MRI based techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Invasive biomechanical methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Non invasive biomechanical methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict of interest statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Corresponding author. Tel.: þ 33 1 45 17 14 41; fax: þ33 1 45 17 14 33. E-mail address: [email protected] (G. Haiat).

0021-9290/$ - see front matter & 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jbiomech.2013.09.021

Please cite this article as: Mathieu, V., et al., Biomechanical determinants of the stability of dental implants: Influence of the bone– implant interface properties. Journal of Biomechanics (2013), http://dx.doi.org/10.1016/j.jbiomech.2013.09.021i

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V. Mathieu et al. / Journal of Biomechanics ∎ (∎∎∎∎) ∎∎∎–∎∎∎

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1. Introduction Dental implants (see Fig. 1) have been used clinically for more than thirty years (Albrektsson et al., 2008) and have allowed considerable progress in dental, oral and maxillofacial surgery, to restore one or more missing teeth caused by old age or accidents as well as for esthetic purposes in fully and partially edentulous patients. Dental implants are also used to support craniofacial reconstructions and for orthodontic appliances. Despite their routine clinical use, failures of implant integration still occur and remain difficult to anticipate. It is difficult to obtain an accurate estimation of dental implant success ratios due to the strong and aggressive competition among implant manufacturers as well as among dental surgeons. Another reason for the difficulty to assess the implant success ratio lies in its dependence on the time after surgery considered. A reasonable estimation of dental implant therapy success ratios is of the order of 75–95% at 10 years (Karoussis et al., 2004). Predicting dental implant biomechanical stability is important since implant failures necessitate additional hazardous painful and expensive surgical interventions. Despite the aforementioned difficulties, the implants industrial design has often been driven by an aggressive “copycat” marketing approach rather than by scientific advances (Brunski, 1999). Some companies have sometimes copied or made incremental changes to the sizes, shapes, material and surface properties of other companies' implants that were deemed to have “worked”. Clinicians have often used implants in new applications before research was carried out from a basic science viewpoint. Empirical approaches may have some advantages but remain limited when it comes to understand the interaction of the various mechanisms playing a role in bone healing around an implant. Two kinds of implant stability should be distinguished. The primary stability occurs at the moment of implant surgery. It is a phenomenon of biomechanical nature related to bone quality at the implant site, which is a necessary condition to obtain the implant osseointegration. Secondary stability is obtained after a given healing period and corresponds to the initial stability reinforced by newly formed bone production and maturation at

the bone–implant interface (Abrahamsson et al., 2004; Berglundh et al., 2007). This article reviews various types of works including fundamental, animal and clinical studies focusing on the biomechanics of the bone–dental implant interface but findings obtained in orthopedic surgery will also be considered since they carry useful information. The bone–implant interface (which is determinant for the clinical outcome of the implant (Franchi et al., 2007)) will first be described in terms of geometrical, mechanical and dynamical properties. Second, the space-time multiscale nature of the bone–implant interface will be considered, by reviewing the various experimental modalities used in vitro as well as the computational approaches which have been used to retrieve information on the interface. Eventually, the various methods used to assess the implant stability will be described. Note that purely biochemical or biological factors (Kerner et al., 2009; Michiardi et al., 2010) are out of scope of this review, focusing on biomechanical aspects which are still poorly understood. Although the importance of the mechanical strength (quasi-static situation) and of the stiffness degradation and endurance limit (which is assessed by fatigue tests) of the implant materials has been evidenced (Lee et al., 2009), the present paper is dedicated to bone biomechanics rather than to the implant material itself. The effects of implant surface (Taborelli et al., 1997), of surface functionalization (Junker et al., 2009), of implant geometry (Quaresma et al., 2008) and of biocompatibility as well as factors related to the patients are not considered in this study.

2. Description of the bone–implant interface The biomechanical properties of the bone–implant interface are the key determinants for the implant stability as well as for the evolution of the implant status. The bone–implant interface properties are determined by the quantity of the implant surface in intimate contact with mineralized bone tissue as well as by the mechanical quality of bone tissue around the interface. From the biomechanical point of view, the difficulty comes from the fact

10 mm

Fig. 1. Images of three examples of dental implants and their associated abutments: healing abutment for Nobel Biocare© (Kloten, Switzerland) (a), healing and closing abutments for Implant Diffusion International© (Montreuil, France) (b) and Tekka© (Brignais, France) (c).



2.2. Mechanical description: stresses at the interface When functional loading exerted via the implant exceeds “a certain stress s0”, the implant is regarded as being “overloaded”, leading to possible complications such as peri-implant bone resorption. However, stresses below s0 are beneficial for the implant outcome and stimulate bone remodeling phenomena. The determination of the value of s0 remains unclear (Zhang et al., 2012b) because (i) it is difficult to obtain a controlled stress field in vivo, (ii) the value of s0 depends on various factors such as bone remodeling properties, healing time (s0 is expected to increase as a function of healing time) or osseointegration and (iii) the value of s0 depends on the nature of the stress considered (shear or compression) as well as of the direction (bone being an anisotropic medium at all scales). Optimal loading conditions history strongly depends on the patient and on the ability of bone tissue to adapt its structure to its environment through remodeling phenomena (Albrektsson et al., 1981). An appropriate balance between reasonable initial stresses and a good primary stability is the key determinant for the long term success of the implant stability (Lioubavina-Hack et al., 2006). Note that the cortical bone–implant interface is the most important region regarding the implant success due to highest bone stresses occurring in cortical bone around the implant neck (Sutpideler et al., 2004).

Secondary stability

When an intimate surgical fit between bone and the implant surface occurs after surgery, the interfacial bone undergoes remodeling and is gradually substituted with mature lamellar bone. However, when a healing chamber forms in regions where bone and implants are not in intimate contact, rapid woven bone filling occurs and long term implant stability is ensured by bone modeling and remodeling processes. When primary stability is not sufficient, micro-movements may appear preventing good healing conditions and leading to the formation of fibrous tissue and to surgical failure (Heller and Heller, 1996; Rangert et al., 1997). Animal studies conducted in orthopedic surgery have suggested that relative micromotion between the implant and bone tissue should not exceed about 150 mm, above which fibrous tissue rather than bone ingrowth dominates (Pilliar et al., 1986; Søballe et al., 1992). Dental implant studies have shown that during bone healing, micromotions at a relatively low level may be responsible for biomechanical stimulation of bone remodeling. However, fibrous tissue may develop instead of an osseointegrated interface when there is excessive interfacial micromotion early after surgery (Duyck et al., 2006; Orlik et al., 2003). The critical parameter is not the absence of loading, but the absence of excessive micromotion at the bone–implant interface (Szmukler-Moncler et al., 2000). However, the precise determination of the evolution of the micromotion threshold (above which fibrous tissues develop) as a function of healing time remains to be investigated.

Implant osseointegration, a phenomenon discovered by Brånemark, consists in the time evolution of bone structure to obtain a direct, structural and functional connection between living bone and the loaded implant surface (Sykaras et al., 2000; Wenz et al., 2008). An implant is osseointegrated when newly formed bone tissue is in intimate contact with the implant surface so that at the microscopic level, no interposition of fibrous tissue occurs. Assessing the efficiency of osseointegration phenomena is a difficult problem because it requires the local (around the interface) measurement of the biomechanical properties of bone tissue, which has a complex nature with viscoelastic, anisotropic and heterogeneous properties. Moreover, bone tissue adapts its structure to mechanical stresses through remodeling phenomena (Wolff, 1892). Bone regeneration under implants lasts several months during which the temporal evolution and spatial distribution of the bone properties are strongly heterogeneous. Osteoblast cells rule the main steps of bone regeneration (Goto et al., 2004): (i) deposition of extracellular matrix (ECM), an unmineralized collagen-rich tissue, (ii) production of the hormones responsible for the mineralization of the ECM with calcium and phosphates ions to form woven bone and (iii) remodeling of woven bone to mature bone. The process of bone formation is affected by local features (fluid and chemical pathways and stress state) (Swan et al., 2003). It is generally assumed that osteoclastic activity undermines primary stability before new bone formation prevents implant micromotion. Note that bone remodeling related issues constitute a highly active field of research which is not detailed in the present paper. The effect of mechanical loading on bone adaptation primarily applies to tissue located around the implant (Duyck et al., 2007; Duyck et al., 2006; Isidor, 2006). Force or displacement controlled mechanical loading at low-frequency ( o10 Hz) improves bone formation around the implant. High-frequency whole body loading ( 410 Hz) can also lead to increased bone formation in the peri-implant surroundings and to an improved osseointegration (Akca et al., 2007; Ogawa et al., 2011a; Ogawa et al., 2011b). The optimal loading parameters have been determined (Zhang et al., 2012a; Zhang et al., 2012b) in terms of frequency and amplitude to enhance osseointegration. At much higher frequency, Low Intensity Pulsed UltraSound (LIPUS), which has widely been used to enhance bone fracture healing in the context of orthopedic surgery (Harle et al., 2001; Heybeli et al., 2002; Tsai et al., 1992; Wang

Time

2.1. Geometrical description: bone–implant distance and micromotions

2.3. Dynamic description: bone remodeling and osseointegration

Primary stability

the interface has a complex nature due to (i) its roughness, (ii) the fact that bone is in partial contact with the implant, (iii) adhesion phenomena between bone and the implant and (iv) the timeevolving nature of the interface properties. The problem considered can therefore be treated from various complementary points of view: by considering the interface geometry (bone–implant distance), the static mechanical phenomena (stresses at the interface) or from a dynamic (time evolving) point of view, thus considering remodeling phenomena of bone tissue around the interface.

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Hydroxyapatite

Collagen fibers

Trabeculae, osteons

Loading procedure

Implant Material

Surface treatment, roughness

Asepsis

50 nm

Micro motions, stresses

Temperature increase during drilling

5 µm

Anatomy

Surgical protocole

500 µm

Implant design

5 mm

Space Fig. 2. Diagram representing the multi-scale and multi-time natures of the different phenomena occurring during osseointegration of a dental implant. Three groups of factors are considered: the factors relative to implants properties (dashed line), to the surgeon (dotted line) and the ones related to bone properties (solid lines).



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et al., 1994; Yang et al., 1996), has also been employed recently to stimulate dental implant osseointegration (Hsu et al., 2011; Liu et al., 2012; Ustun et al., 2008). The various points of view considered in this section highlight the complex nature of the bone–implant interface. Another difficulty lies in its multiscale nature illustrated in Fig. 2 which shows a space-time diagram representing the various biomechanical factors influencing implant stability. Three groups of factors are considered: the factors relative to implants properties (dashed line), to the surgeon intervention (dotted line) and the ones related to bone properties (solid lines).

3. Implant stability: a space-time multiscale issue As shown in the previous section and in Fig. 2, the phenomena occurring at the bone–implant interface and involving load transfers between bone and the implant are of space-time multiscale nature. Note that as illustrated in Fig. 2, implant design at the scale of the millimeter (self tapping or not (Markovic et al., 2013), implant length (Hong et al., 2012), implant shape (Wu et al., 2012), abutment (Balik et al., 2012), thread pitch (Orsini et al., 2012)) plays an important role in implant stability (particularly for primary stability) and in stress distribution at the implant interface. At the scale of the implant (several millimeters), load is transferred via macroscopic stress distribution. At the scale of around 50 mm, the roughness plays a role in stimulating the growth of newly formed bone tissue (Shalabi et al., 2007). At the scale of around 100 nm, biochemical factors become important through adhesion phenomena between bone and implant surfaces. Moreover, the temporal multiscale nature of the problem comes from the fact that the time constant of the implant mechanical solicitation (typically around the second) is several orders of magnitude lower than the time constant of bone structure modifications (around several weeks). To understand this space-time multiscale issue, various complementary approaches need to be carried out. Bone tissue biomechanical properties have been measured around the implant but purely experimental approaches remain limited when it comes to understand the interaction between the different spatial and temporal constants. Therefore, homogenization techniques have been developed to climb the hierarchy of scales in newly formed bone tissue, from the nanoscale up to the macroscopic level (Sansalone et al., 2010). Computational approaches are necessary to assess the bone mechanical behavior on the basis of its internal structure and are complementary with experimental measurements since they use the experimental results as input data in the models.

100 µm

7 weeks

3.1. Measurement of the multiscale bone properties around the interface The biomechanical properties of bone tissue at a distance lower than around 100–200 mm from the implant surface are the critical parameters determining implant stability (Huja et al., 1999; Luo et al., 1999). Various experimental approaches may be used to retrieve complementary information on newly formed bone properties at the scale of around several micrometers. Such information may then be used as input data in the modeling of the mechanical behavior of bone tissue in the vicinity of the implant (see Section 3.2) and then at the scale of the implant. (i) Histology The gold standard for the assessment of the implant osseointegration is given by histological measurements, which are realized by embedding the samples in Methacrylate-based resin, cutting them in 100 mm thick slices (Bernhardt et al., 2012; Nkenke et al., 2003; Singhrao et al., 2012), and staining them (Artzi et al., 2003a, 2003b; Mathieu et al., 2011a). The visualization of the slides allows measuring the bone implant contact fraction (BIC). Coloring agents enable to obtain a qualitative estimation of the degree of mineralization of bone tissue around the implant (dark colors corresponding to more mineralized regions). Histological analysis enables (i) to distinguish mature pre-existing from newly-formed bone tissue (white dashed lines in Fig. 3), (ii) to measure a significant increase of BIC as a function of healing time and (iii) to obtain a qualitative estimation of the increase of mineralization of newly formed bone tissue. The key feature of quantitative bone– implant histology is the undecalcified embedding of the sample blocks without removing the implant. This was a breakthrough in the 1990's in comparison with conventional microtomy based histology, where implants had to be removed and bone samples to be decalcified, causing loss of interface information. However, histology does not provide quantitative information on the biomechanical properties of newly bone tissue. (ii) Small angle X-ray scattering (SAXS) SAXS is used to assess the thickness, orientation and shape/ arrangement of the mineral crystals in bone tissue. SAXS measurements have been carried out near the implant surface (Bunger et al., 2006) and showed that (i) the mineral crystals tended to be aligned with the surface of the implants and (ii) the mineral crystal thickness increased linearly with distance from the implant. However, SAXS does not allow to retrieve directly any mechanical properties. (iii) Nanoindentation Nanoindentation is a technique widely used to investigate the biomechanical properties of different materials at the

13 weeks

Fig. 3. Histological images of two fragments of bone–implant interfaces for 7 weeks (a) and 13 weeks (b) healing time. The limit between pre existing mature bone tissue and newly formed bone tissue is represented with white dotted lines.



microscopic scale (Zysset et al., 1999) yielding information on the apparent Young's modulus and on the hardness. Nanoindentation has been used to show that Young's modulus and hardness values are lower in the vicinity of the implant than in mature bone (Chang et al., 2003; Seong et al., 2009). (iv) Scanning Acoustic Microscopy (SAM) SAM (Meunier et al., 1988) is another technique allowing the measurement of an image of the acoustic impedance (given by the product of tissue mass density and ultrasonic velocity) at the scale of several micrometers. SAM was used for the qualitative assessment of the biomechanical microstructural properties of the bone–implant interface with a resolution of a few micrometers (Nomura et al., 2006). (v) Micro Brillouin scattering Micro Brillouin scattering technique uses the photo acoustic interaction between a laser beam and a sample to measure bone speed of sound with a resolution of a few micrometers. Using an animal model derived and adapted from (Rønold and Ellingsen, 2002b; Rønold et al., 2003a; Rønold et al., 2003b, 2003c), a “bone chamber” exclusively containing newly formed bone tissue (see Fig. 4) was used to measure the biomechanical properties of newly formed bone tissue with a multimodal experimental approach coupling nanoindentation (Vayron et al., 2011; Vayron et al., 2012), micro Brillouin scattering (Mathieu et al., 2011a) and histology. Histological analysis was carried out after different healing times (see Fig. 3). As shown in Table 1, lower ultrasonic velocity, Young's modulus and hardness values were obtained in newly formed bone tissue compared to mature bone, which might be explained by the lower mineral content. The coupling of nanoindentation with micro Brillouin analysis is a powerful approach because measurements are realized at the same scale (a few micrometers), allowing to retrieve the relative variation of mass density between newly formed and mature

Fig. 4. Schematic representation of the coin-shaped implant model.

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bone tissues, which is of the order of 13.5% (Vayron et al., 2012). The main challenge when employing experimental measurements to assess newly formed bone properties around the implant lies in the decrease of the resolution. Scale reduction is a critical point in order to be able to use accurate input data in the multiscale model of bone mechanical properties described below. 3.2. Homogenization approaches of bone tissue around the interface Recent studies pursued the idea to climb the hierarchy of scales, from the nanoscale up to the macroscopic level. A key point lies in the identification of building blocks at the microscopic- and nanoscopic-level which could explain bone elasticity at the macroscopic scale. At the organ level, models are often continuum based (Ilic et al., 2010) and describe the variation of bone apparent density as a function of the biological and mechanical stimuli. At the tissue level, models account for the bone microarchitecture and remodeling properties. At the cellular level, cellular interactions are analyzed in the temporal domain and molecular dynamics approaches are employed to obtain the elastic properties (Izaguirre et al., 2004; Vesentini et al., 2005). In addition to modulating cell adaptation, mechanochemical signals also influence proliferation, migration and differentiation (Knothe Tate, 2011; Knothe Tate et al., 2008). Although informative, most models are usually developed independently of each other and their interpretation is therefore limited. Continuum micromechanic approaches allow the modeling of bone anisotropic elastic behavior (Hellmich et al., 2008). Models should also account for the flow channels (Sansalone et al., 2012) which provide conduits for fluid flow, enhancing molecular and cellular transport and inducing shear stresses via fluid drag at the cell surfaces. Micromechanical models have considered microstructural features, such as osteonal fibers embedded in a matrix of interstitial bone (Dong and Guo, 2006). Coupling 3-D high-resolution reconstructions with numerical simulation tools (Haiat et al., 2009) has become a common approach to retrieve the bone mechanical properties because of the difficulty of achieving reliable estimations of stress and strain fields in vivo. However, a critical issue consists in the anisotropy and heterogeneity of bone tissue. When heterogeneity is accounted for, empirical regression analyses between tissue mineral density and Young's modulus have often been employed (Keyak and Falkinstein, 2003; Yosibash et al., 2007). An homogenization model was developed to infer the nanoscale up to the organ scale using data obtained from synchrotron radiation micro computed tomography (mCT) (Sansalone et al., 2012; Sansalone et al., 2010). However, the existing multiscale models (for instance accounting for the effect of angiogenesis (Checa and Prendergast, 2009), fluid flow (Geris et al., 2004) and blood clotting (Vanegas-Acosta et al., 2011)) do not account for the

Table 1 Mean values and standard deviation of the indentation modulus and hardness measured by nanoindentation and of the ultrasound velocity measured with micro Brillouin scattering in newly formed (7 weeks) and mature bone tissue of New Zealand White Rabbits. Data taken from (Vayron et al., 2011; Vayron et al., 2012; Mathieu et al., 2011a). The relatively low standard deviation may be explained by (i) the low number of measurements (only one implant was considered) and (ii) the combined use of histology and of the dedicated animal model, which allows to distinguish newly formed bone and mature bone tissue and to realize the measurements in each medium independently. Quantity (averaged values)

Newly formed bone tissue

Mature bone tissue

Young's modulus (GPa)

15.85 ( 71.55)

20.66 ( 72.75)

0.66 ( 70.1)

0.696 ( 70.15)

4970 ( 7140)

5310 ( 740)

Hardness (GPa) Ultrasound velocity (m/s)

Number of measurements New bone: 106 Mature bone: 132 New bone: 106 Mature bone: 132 New bone: 6 Mature bone: 6



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temporal bone evolution as well as for the full interaction between the nanoscale and the organ scale, which prevents one from understanding aspects related to bone regulation and regeneration. Many challenges have to be faced including the need for a model providing a reliable movie of the system evolution.

3.3. Multiscale biomechanical modeling of the bone–implant interface Various approaches have been developed to model the mechanical behavior of the bone–implant interface. The biological threshold for micro-movements being in the range 100–200 mm, the difficulty lies in that the accuracy must be lower than 10–20 mm or better. Finite element methods (FEM) have been widely employed to simulate the mechanical behavior of an implant at the organ scale using large sliding contact elements in the case of primary stability (Bernakiewicz and Viceconti, 2002; Lin et al., 2006; Viceconti et al., 2000). Frictional Coulomb law has been employed (Andreaus and Colloca, 2009), some methods using empirical remodeling laws (Folgado et al., 2009; Perez et al., 2008; Rungsiyakull et al., 2010), non linear anisotropic FEM (Simon et al., 2003) or coupling of FEM with statistical techniques (Laz et al., 2006; Viceconti et al., 2006; Younesi et al., 2010) to account for the uncertainty related to the in vivo situation. However, the existing approaches to model bone– implant interfaces do not account for the multiscale and evolving nature of bone tissue. The biomechanical modeling of the bone– implant interface often remains simplistic, due to a lack of experimental data at the scale of 1–100 mm and the main challenge consists in accounting for the heterogeneity of bone biomechanical properties around the implant at the micrometer scale (described in Sections 3.1 and 3.2) on the implant mechanical behavior.

4. Implant stability assessment Basic scientists as well as clinical investigators have attempted to decrease treatment time frames by reducing the healing period. To do so, assessing the implant stability is of critical importance to adapt surgical strategies to the various factors affecting implant stability (see Fig. 2).

4.2. Invasive biomechanical methods Numerous animal studies have focused on the mechanical stability of implants but these studies often remain of limited interest to understand the basic phenomena responsible for implant stability because they use real implants with complex geometrical configurations, which does not allow (i) to carry out biomechanical testing under controlled conditions and (ii) to retrieve quantitative information on the adhesion of the bone– implant interface. For these reasons, specific implant models with a planar bone– implant interface have been conceived to minimize the effects of friction and of mechanical forces introduced by surface roughness and to work under standardized conditions (Skripitz and Aspenberg, 1998). Rønold et al. (Rønold and Ellingsen, 2002a) have carried out nice systematic studies aiming at establishing a model for testing functional attachment of implants in situ. Their pull-out model makes it possible to study the relation between kinematics and strength of bone bonding with negligible influence of shear forces or mechanical interlocking. The systematic approach of Rønold et al. is promising but remains in some regards limited when it comes to the analysis of the phenomena involved in the rupture between bone and the implant. From an adhesive contact mechanics point of view, the tensile test performed corresponds to a flat-punch configuration (see Fig. 5a), which is a mechanically unstable situation (Maugis, 2000). Therefore, the measured pullout force strongly depends on initial and boundary conditions and cannot be used to retrieve the adhesion energy, which is the only physically meaningful parameter. For these reasons, an experimental approach based on a mode III cleavage mechanical device aiming at understanding the behavior of a planar bone–implant interface submitted to torsional loading was developed (see Fig. 5b) (Mathieu et al., 2012b). Coin-shaped titanium implants (see Fig. 4) were inserted on the tibiae of a New Zealand White rabbit for seven weeks. After sacrifice, mode III cleavage experiments were performed on bone samples. An analytical model allowed to assess the values of different parameters related to bone tissue at the vicinity of the implant. The approach allows to estimate different physical quantities related to the bone–implant interface such as: torsional stiffness (around 20.5 N m rad 1), bone shear modulus (around 240 MPa), maximal torsional loading (around 0.056 N m), mode III fracture energy (around 77.5 N m 1) and the associated stress intensity factor (0.27 MPa m1/2). 4.3. Non invasive biomechanical methods

4.1. X-ray and MRI based techniques The resolution of clinical X-ray based techniques (such as radiography or mCT) around the implant interface is limited due to X-ray metal artifacts related to the presence of metallic components in the constitution of the large majority of dental implants (Shalabi et al., 2007). Similarly, the use of magnetic resonance imaging (MRI) (Potter et al., 2004) has been proposed but remains of limited interest due to magnetic fields disturbance (Gill and Shellock, 2012; Hecht et al., 2011; Knothe Tate et al., 2008). X-ray or MRI based techniques can give access to information on bone microstructure and tissue mineral density which have a strong influence on the mechanical properties of bone tissue (Hsu et al., 2013a). However, the estimation of bone microstructure and tissue mineral density is not sufficient for the direct characterization of bone mechanical properties since material properties at the microscale are also important. As a consequence, X-ray or MRI based techniques are not commonly used in order to assess the biomechanical properties of the bone– implant interface. For these reasons, biomechanical methods have been developed.

(i) Empirical approaches Surgeons commonly use empirical tests to estimate the primary stability of dental implants. The most widely used approach consists in hitting the implant with a stick and listening to the noise produced by the system. Another approach consists in measuring the insertion torque during the surgical procedure. However, these methods remain highly empirical and do not allow assessing the biomechanical properties of the bone–implant interface. (ii) Impact based approaches The PerioTests device (Schulte et al., 1983) has been on the market since the 80's. Initially, it was dedicated to the evaluation of tooth mobility in the context of parodontopathies. Then, its use has been extended to assess dental implant stability. The device comprises a hand piece which is positioned perpendicularly to the implant axis. A metallic rod hits the implant and the contact duration is recorded, leading to a PerioTest value (PTVs). However, the criteria for evaluating natural tooth mobility are different from those used to assess implant mobility because the supporting mechanism of



Implant Bone tissue

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Implant Bone tissue

Fig. 5. Schematic representation of two configurations of mechanical loadings for the rupture of the bone–implant interface using coin shaped implants.

dental implant is different from that of a natural tooth. A correlation between PTV values and (i) implant mobility and (ii) the level of marginal bone (Chai et al., 1993; Haas et al., 1999; Nkenke et al., 2003) has been shown but PTV values depend on the anatomical location of the implant (Salonen et al., 1997; Tricio et al., 1995; Vansteenberghe et al., 1995). Numerous studies have shown that PTV values decrease as a function of healing time, when bone density increases around the implant. However, no correlation was found between PTV and the bone implant contact (BIC) using histomorphometric analyses (Caulier et al., 1997; Mericskestern et al., 1995; Nkenke et al., 2003), which indicates that the Periotest method is sensitive to variations of the surrounding bone properties but not to the bone–implant interface properties. PTV measurements are strongly influenced by the position of the impact location and by the angle of the device relatively to the implant axis (Derhami et al., 1995). Therefore, it remains difficult to use the Periotest for monitoring purposes due to reproducibility and precision error related issues. (iii) Resonance frequency analysis In the field of structural integrity monitoring, the analysis of the frequency response of mechanical structures to dynamic loads has been widely investigated for decades (Adams et al., 1978). The frequency response has been used as a diagnostic parameter in structural assessment procedures using vibration monitoring: natural frequencies are sensitive indicators of structural integrity and relationships between frequency changes and structural damage have been evidenced (Salawu, 1997). In the 90's, the technique of resonance frequency analysis (RFA) was transposed to the field of implant stability diagnosis (Meredith et al., 1996). It consists in the measurement of the first resonance frequency of the bone–implant system. A L-shaped transducer is screwed into the implant and is excited at various frequencies (from 5 to 15 kHz). The first resonance frequency is used as an indicator of the implant stability through an index called Implant Stability Quotient (ISQs). The system is commercialized under the name Osstell™ (Integration Diagnostics Ltd., Göteborgsvägen, Sweden). The latest version of the RFA device uses a “Smartpeg” (Herrero-Climent et al., 2012), which is a piece screwed into the implant abutment. The “Smartpeg” is excited mechanically in a non contact mode using a hand-held probe and allowing to increase measurement accuracy in a clinical context (Geckili et al., 2012; Hsu et al., 2013b; Oh and Kim, 2012). The main interest of the ISQ score in a clinical context is that it

allows quantification tool for clinicians (Park et al., 2012). The RFA technique is sensitive to the rigidity of the implant and of the surrounding bone. An increase of ISQ values has been evidenced as a function of healing time, which has been explained by bone formation around the implant. A correlation has been shown between the initial ISQ value and (i) the cutting torque (Friberg et al., 1999) and (ii) bone density measurements assessed empirically by the surgeon before implantation (Alsaadi et al., 2007). A correlation between cortical bone thickness and the ISQ value has also been established (Nkenke et al., 2003; Sennerby et al., 2005). A relationship between ISQ values and the anatomical region of implantation has been evidenced (Balleri et al., 2002; Barewal et al., 2003; Bischof et al., 2004; Ostman et al., 2006). However, various limitations have been mentioned in the literature. The “fundamental flaw” in the Osstell device is that it reduces the dynamic response of the bone–implant system to the first resonance frequency and tries to capture this in an ‘ISQ’ value, which is intuitively easy for the clinician but has only limited value from a structural mechanics point of view. ISQ may be seen as an “oversimplification” of the frequency response of the bone–implant system. The correlation between ISQ values and marginal bone level is only obtained during the first six months after surgery (Turkyilmaz, 2006). At early times after surgery, a decrease of stability may occur (Balshi et al., 2005; Coelho et al., 2010; Glauser et al., 2004; Huwiler et al., 2007; Raghavendra et al., 2005). However, it is not clear whether the decrease of ISQ values during the first several weeks is exclusively related to marginal bone loss since other reasons such as bone relaxation following the compression of bone tissue during the implant insertion may also play a role (Barewal et al., 2003; Glauser et al., 2003; Glauser et al., 2004; Huwiler et al., 2007). The sensitivity of the ISQ value to the implant stability depends on the implant type (Nedir et al., 2004a). The clear cut relationship between ISQ values and the percentage of bone in contact with the implant remains unclear (Scarano et al., 2006; Seong et al., 2009). The rigidity of the entire bone–implant system measured with the RFA device depends on the biomechanical properties of the implant, of the bone–implant interface and of the surrounding bone tissue. Therefore, the first resonance frequency is not only related to bone–implant interface properties but rather to the bone properties at the scale of the organ (Aparicio et al., 2006). Meanwhile, bone properties at the scale of around 50–200 mm are the critical properties determining the implant osseointegration (Winter et al., 2004). Moreover, the fixation and the orientation of the


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transducer influence significantly the measured ISQ values, thus rendering its clinical use difficult (Pattijn et al., 2007). Diagnostic criteria for the failure of the implantation have not been established (Atsumi et al., 2007). Despite the aforementioned limitations, RFA is still being used in many clinical studies to quantify implant stability (Nedir et al., 2004b; Rabel et al., 2007; Turkyilmaz et al., 2007; Valderrama et al., 2007). (iv) Quantitative ultrasound methods Quantitative ultrasound (QUS) techniques are now routinely used clinically to assess bone fragility (Laugier and Haiat, 2011). In dentistry, QUS is mostly used to measure enamel thickness (Ghorayeb et al., 2008) and periodontal pocket depth (Lynch and Hinders, 2002; Palou et al., 1987). The main interest of QUS is that it is non invasive, it is relatively cheap and that it does not involve ionizing radiation. Moreover, ultrasound being mechanical waves, it is adapted to retrieve the biomechanical properties of living tissues. Storani et al. (Storani de Almeida et al., 2007) performed experiments with a screw inserted in an aluminum block and measured the variations of its ultrasonic response. This technique was adapted by investigating the potentiality of QUS to assess the amount of bone in contact with titanium prototype cylindrical implants. The 10 MHz ultrasonic response of the implant was processed to derive a quantitative indicator I, based on the temporal variation of the signal amplitude (Mathieu et al., 2011c). The results revealed a statistical distribution of I significantly correlated with the amount of bone in contact with the cylinders. Moreover, 2-D finite difference time domain simulations were performed (Mathieu et al., 2011b) to understand the propagation phenomena of ultrasonic waves in the prototype cylindrically shaped implants. The ultrasonic response is influenced by (i) the amount of bone in contact with the implant, (ii) cortical bone thickness, and (iii) surrounding bone material properties. The approach was applied to real dental implants used in the clinic which were embedded in a biomaterial used as bone substitute material and subject to fatigue loading (Vayron et al., 2013). The indicator I was shown to be sensitive to the fatigue time. Moreover, the same approach was carried out to show that the ultrasound response of an implant varies as a function of bone primary stability (Vayron et al., Haïat, submitted for publication). Recently, several studies have shown the potential of non linear ultrasound techniques to study the stability of dental implants (Riviere et al., 2010; Riviere et al., 2012a; Riviere et al., 2012b). All these studies show the potentiality of QUS methods to assess the quality of bone tissue in contact with the implants, opening new paths to (i) investigate the material properties around a dental implant and (ii) optimize the conception of bone substitute materials in the context of dental implant surgery. The coin-shaped implants described in (Section 3.1) were also used to investigate the effect of bone healing on the ultrasonic response of the bone–implant interface. The ultrasound response of the interface was measured in vitro at 15 MHz after seven and thirteen weeks of healing time (Mathieu et al., 2012a). The bone–implant contact was measured by histomorphometry and the degree of mineralization of bone was estimated qualitatively by histological staining. The significant decrease of the amplitude of the echo of the bone–implant interface as a function of healing time is explained by (i) the increase of the BIC (from 27% to 69%) and (ii) the increase of mineralization of newly formed bone tissue. All these studies show the potentiality of QUS techniques to investigate bone quality around the implant. However, further work is necessary in order to improve the reproducibility of the measurements and to consider real implants used in the clinics.

5. Conclusion Assessing primary and secondary dental implant stability is a complex problem due to the multiscale and time dependent nature of newly formed bone tissue around implants. While multiscale models have been developed to bridge the nanoscale up to the organ scale, the main difficulty now lies in introducing remodeling phenomena within these models in order to understand the evolution of dental implant stability. The evolution of newly formed bone properties around implants is the determinant factor in order to predict the clinical outcome of dental implants. Different invasive methods have been developed in the laboratory in order to measure in vitro newly formed bone tissue, but most of them remain difficult to be employed in vivo. X-ray or MRI based techniques are not adapted to an in vivo use due to resolution issues at the bone–implant interface. Therefore, various biomechanical methods have been developed in order to overcome this limitation but most of them are limited when it comes to analyze the biomechanical properties of newly formed bone tissue. Quantitative ultrasound methods are promising because they are cheap, non invasive and because of their higher spatial resolution around the implant compared to other biomechanical approaches.

Conflict of interest statement There is no conflict of interest of any kind.

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