Nicolas Rousseau
email: nrousseau@selenium-medical.com.

Inès Msolli

Patrick Chabrand

Arnaud Destainville

Olivier Richart

Jean-Louis Milan

Local tissue effects and peri-implant bone healing induced by implant surface treatment: an in vivo study in the sheep

Keywords: osseointegration, dental implants, surface treatment, sheep model

Objective:

The aim of this study was to assess, through biological analysis, the local effects and osseointegration of dental implants incorporating surface micro/nanofeatures compared to implants of identical design without surface treatment. Background: Known to impact bone cell behavior, surface chemical and topography modifications target improved osseointegration and long-term success of dental implants. Very few studies assess the performance of implants presenting both micro-and nanofeatures in vivo on the animal models used in preclinical studies for medical device certification. Methods: Implant surfaces were characterized in terms of topography and surface chemical composition. After 4 weeks and 13 weeks of implantation in sheep femoral condyles, forty implants were evaluated through micro-computed tomography, histopathologic, and histomorphometric analyses. Results: No local adverse effects were observed around implants. Histomorphometric analyses showed significantly higher bone-to-implant contact in the coronal region of the surface treated implant at week 4 and week 13, respectively 79.3±11.2% and 86.4±6.7%, compared to the untreated implant's 68.3±8.8% and 74.8±13%. Micro-computed tomography analyses revealed that healing patterns differed between coronal and apical regions, with higher coronal boneto-implant contact at week 13. Histopathologic results showed, at week 13, bone healing around the surface treated implant with undistinguishable defect margins while the untreated implant still presented bone condensation and traces of the initial drill defect. Conclusion: Our results suggest that the surface treated implant not only shows no deleterious effects on local tissues but also promotes faster bone healing around the implant. (word count: 241)

Introduction

Dental implants are commonly used for the oral rehabilitation of partially or fully edentulous patients. To improve osseointegration and ensure that implants remain well-integrated in bone long-term, researchers and manufacturers continue to develop new implant designs, altering their macrogeometry and modifying their surface at lower scales. Among the many surface modifications applied to improve initial and long-term osseointegration, the sandblasted acid-etched (SLA) surface treatment has been for several decades one of the most popular surface treatment on the market. This surface treatment provides dental implants with a microrough texture that improves bone apposition and biomechanical anchorage [START_REF] Buser | Influence of Surface Characteristcs on Bone Integration of Titanium Implants[END_REF]. Plasma spraying has also been used to obtain microrough titanium surfaces [START_REF] Vercaigne | The effect of titanium plasma-sprayed implants on trabecular bone healing in the goat[END_REF] or to generate a hydroxyapatite coating on the implant surface (3). However, clinical concerns were raised about reported hydroxyapatite coating resorption (4) and the long-term efficiency of plasma spraying was questioned [START_REF] Hahn | Long-term efficacy of Hydroxyapatite-coated cylindrical implants[END_REF]. Current research focuses particularly on the combination of micro-and nanofeatures obtained, for instance, by acid-etching followed by oxidation in flowing synthetic air [START_REF] Biggs | Interactions with nanoscale topography: Adhesion quantification and signal transduction in cells of osteogenic and multipotent lineage[END_REF], or by anodization yielding titanium nanotubes at the implant surface [START_REF] Gittens | The effects of combined micron-/submicron-scale surface roughness and nanoscale features on cell proliferation and differentiation[END_REF].

Generally speaking, it is accepted by the scientific literature that modifying the surface of implants in terms of chemical composition and topology affects their rate of osseointegration. In vivo studies demonstrated that micrometric-scale features introduced on titanium surfaces enhance bone-to-implant contact (BIC) 8 weeks following implantation, compared to smoother surfaces [START_REF] Buser | Enhanced bone apposition to a chemically modified SLA titanium surface[END_REF][START_REF] Schwartz | Effect of micrometer-scale roughness of the surface of Ti6Al4V pedicle screws in vitro and in vivo[END_REF].

In vitro studies confirmed such observations, reporting lower numbers of osteoblasts at the interface between bone and rough surfaces, along with increased differentiation markers such as alkaline phosphatase and osteocalcin [START_REF] Olivares-Navarrete | Integrin alpha2beta1 plays a critical role in osteoblast response to micron-scale surface structure and surface energy of titanium substrates[END_REF][START_REF] Andrukhov | Proliferation, behavior, and differentiation of osteoblasts on surfaces of different microroughness[END_REF]. The authors of these studies suggested that osteoblasts are sensitive to moderate micro-roughness, moving earlier from their proliferation phase to their differentiation phase, maturing faster, and rapidly starting to secrete extracellular matrix (ECM). On the other hand, surfaces presenting nanofeatures showed improved BIC and higher implant removal torque in vivo two weeks after implantation [START_REF] Jimbo | Genetic responses to nanostructured calcium-phosphate-coated implants[END_REF], as well as better adhesion of osteoblasts in vitro [START_REF] Webster | Specific proteins mediate enhanced osteoblast adhesion on nanophase ceramics[END_REF]. It should be noted that combining microfeatures and nanofeatures generates additive effects at both topographic levels, in addition to a drastic increase in surface hydrophilicity [START_REF] Gittens | The Roles of Titanium Surface Micro/Nanotopography and Wettability on the Differential Response of Human Osteoblast Lineage Cells[END_REF][START_REF] Zhao | The influence of hierarchical hybrid micro/nanotextured titanium surface with titania nanotubes on osteoblast functions[END_REF]. To our knowledge, very few in vivo studies assessed the combined influence of micro and nanofeatures on dental implant osseointegration, and these were only conducted either on small animals [START_REF] Li | Effects of hydrofluoric acid and anodised micro and micro/nano surface implants on early osseointegration in rats[END_REF][START_REF] Hoornaert | Biocompatibility and osseointegration of nanostructured titanium dental implants in minipigs[END_REF] or for very short periods [START_REF] Li | Formation and in vitro/in vivo performance of "cortex-like" micro/nano-structured TiO2 coatings on titanium by micro-arc oxidation[END_REF]. Recently, [START_REF] Liu | Effects of micro/nano strontium-loaded surface implants on osseointegration in ovariectomized sheep[END_REF] studied screw-shaped cylinders implanted for three months in osteoporotic sheep mandibulars and found higher biomechanical parameter values for surfaces presenting micro/nanofeatures [START_REF] Liu | Effects of micro/nano strontium-loaded surface implants on osseointegration in ovariectomized sheep[END_REF]. However, no assessment of the neo-bone formation, of fibrosis, nor of the bone texture was conducted in this study. Furthermore, none of these studies made a distinction between the coronal area and the apical area of the implant, and thus no difference in osseointegration could be observed. Distinguishing between the two areas would have enabled the local influence of implant design features to be assessed.

The purpose of this paper is twofold: (1) to assess the performance (osseointegration and osteogenesis) of a dental titanium implant presenting micro/nanofeatures; (2) to provide a comprehensive biological analysis of the local tissue effects of such an implant. Sheep were implanted with dental implants of a unique design, both untreated and treated with Starsurf® (Selenium Medical, La Rochelle, France), a chemical surface treatment that provides micro/nanofeatures. A total of eight sheep were bilaterally implanted in the medial femoral condyle and sacrificed four weeks and thirteen weeks after implantation. In addition to surface topography characterization and chemical composition assessment, Bone-to-Implant Contact (BIC) was evaluated through histomorphometric analysis to address the primary study objective both in the coronal and the apical regions. Local tissue effects of the endosseous implants were evaluated qualitatively and semi-quantitatively through histopathologic analysis. Finally, micro-computed tomography analyses were conducted to provide supporting data for both types of analysis.

Materials and method

Ethical Statement

The implantation protocol was approved by the Namsa Ethical Committee (Chasse-sur-Rhône, France) as part of a project authorization reviewed every five years by the French Ministry of Education, Higher Education and Research. The different surgical procedures and biological analyses were conducted by the Medical Research Organization Namsa (Chasse-sur-Rhône, France), in compliance with the OECD series on Good Laboratory Practice and compliance monitoring and FDA 21 CFR 58 on Good Laboratory Practice (GLP) for non-clinical studies. The study design was also based on the guidance provided in ISO 10993-6, Biological Evaluation of Medical Devices Part 6 (2016): Tests for Local Effects after implantation. The animal study was conducted in accordance with the ARRIVE guidelines [START_REF] Kilkenny | Improving bioscience research reporting: The arrive guidelines for reporting animal research[END_REF]. The relevance and use of animal selection were carefully established and considered.

Sample size calculation

The sample size calculation for this study was based on a power analysis [START_REF] Bhalerao | Sample size calculation[END_REF], considering a level of significance at 5% (P=0.05), a study power of 80% and assuming two-tailed hypothesis tests. Based on scientific literature (1), an effect size of at least 23% with a maximal standard deviation of 14% were expected for the BIC in this study. According to the calculation, a sample size of at least six implants per group is required. To obtain a finer statistical analysis and to avoid any adverse effect and unexpected event, ten implants were allocated per group as well as two reserve implants per group. Therefore, to study two types of implants at two time periods, forty-eight implants were necessary. With up to three screw-type implants per leg, eight sheep were required for the study. Such calculation was concomitant with qualitative and semi-quantitative evaluation of local tissue effect, as any level of difference was of interest in the absence of similar data in the literature.

The implants

Forty-eight implants commercially available and made of commercially pure titanium (cpTi, grade IV) were used (Fig. 1), including eight reserves similarly treated and only intended for replacement in case of an adverse event. The intra-osseous part of the implant has a diameter of 3.5 mm and a length of 10 mm, one part being cylindrical (coronal area) and the other conical (apical area). The main thread is composed of a double fillet with a pitch of 2 mm. The conical part of the implant has a thread depth that increases from approximately 0.15 mm in the coronal area to 0.7 mm in the apical one. In the coronal area, the main thread is subdivided into two "micro" fillets of identical pitch. Such implant geometry is common and representative of implants currently on the market [START_REF] Guillaume | Dental implants : a review[END_REF]. Two configurations were tested in this study: a standard topography (REF, n=10 + 2 reserves at both 4 weeks and 13 weeks) and a Starsurf ® one (TEST, n=10 + 2 at both 4 weeks and 13 weeks) combining micro/nanofeatures. The standard topography is obtained through corundum grit-blasting, while the Starsurf ® topography results from a succession of mechanical and chemical treatments. First, implants are sandblasted using a mixture of hydroxyapatite (HA) and βtricalcium phosphate (β-TCP), a biocompatible material and a bone mineral constituent. In addition to the surface roughness and particular topography this grit-blasting process provides [START_REF] Citeau | In vitro biological effects of titanium rough surface obtained by calcium phosphate grid blasting[END_REF][START_REF] Park | Effect of implant surface microtopography by hydroxyapatite grit-blasting on adhesion, proliferation, and differentiation of osteoblast-like cell line, MG-63[END_REF], hydroxyapatite is fully soluble in acid solutions. Therefore, subsequent acid attack by hydrochloric and sulfuric acid dissolves HA particles along with surface etching [START_REF] Pearce | On the Dissolution of Hydroxyapatite in Acid Solutions[END_REF]. Finally, a basic attack is conducted using potassium hydroxide. Both series of implants were cleaned in clean rooms, and sterile packaging and final gamma irradiation were applied prior to implantation. Following implantation, the threads were engaged in the host bone cylindrical wall obtained after drilling, providing primary mechanical stability.

Implant surface characterization

Under a Captair Flow 468 ISO5 laminar flow hood (AirLab), the overall topography of REF and TEST implants was qualitatively examined using a Phenom ProX Scanning Electron Microscope (ThermoFisher scientific). Micrographs at different magnifications were observed to assess the topographies at different scales. Then, surface chemical composition was assessed by Energy Dispersive X-Ray Spectrometry (EDX). Next, roughness measurements were conducted on an Altisurf 3D profilometer (Altimet). Areas of 200×750µm for the interspaces of threads were evaluated in both coronal and apical areas. The arithmetic mean deviation (Sa), root-mean-square deviation (Sq), maximum peak-to-valley height (Sz) and developed interfacial area ratio (Sdr) of the surface were extracted, constituting the main roughness parameters. Three REF and TEST implants were examined and measurements were performed in triplicate. Finally, REF and TEST surfaces were reproduced on cpTi discs to assess implant surface energy. Wettability was tested through contact angle measurements on a DSA25 tensiometer (Krüss). Surface free energy was assessed using the Owens-Rankine formulation, with three liquids, droplets of 2µl, and ten contact angle measurements per liquid.

Study design and experimental animals

Animal model and management

Eight (n= 4 per time period) female Blanche du Massif Central sheep (Bergerie de la Combe aux Loups, France) were involved in the study. Sheep were aged from 2 to 4 years (mean=2.7 years), skeletally mature, and weighed from 57 to 68 kg at implantation (mean=61.25 kg). The sheep is an animal model identified as suitable for evaluating materials and is suggested in the ISO 10993 standard -part 6 (2016) for intraosseous implantations. Sheep were bilaterally implanted in the medial femoral condyle. Sheep femurs can be implanted with up to three screw-type implants per leg, increasing the number of sites per implant group without increasing the number of animals. Sheep were randomly attributed to the two periods of implantation studied and the number of sites per implant group was chosen in accordance with the guidance provided in ISO 10993 standard -part6. One group per condyle was implanted to allow suitable evaluation of the local tissue effects and performance and to avoid mixed tissue response between implant groups. Husbandry, housing, and environment conditions were in conformity with European Directive 2010/63/EU regarding the protection of animals used for scientific purposes. Animals were housed at Namsa, an AAALAC international accredited facility registered with the French Department of Agriculture for animal housing, care, and investigations. They were grouped in cages identified by a card indicating the study number, number of animals, sex, dates of beginning and end of experimental in-life phase. The animal housing room temperature and relative humidity were recorded daily. The recommended temperature range for the room was 10 -24 • C and the light cycle was controlled using an automatic timer (12 hours of light, 12 hours of dark). After the post-operative period, the sheep from the 13-week group were jointly housed in a farm setting (Bergerie de la Combe aux Loups, France), where environmental conditions were not controlled. Standard hay was provided ad libitum and supplemented with a commercially available pelleted sheep feed (Special Diet Services, France). Minerals were provided ad libitum (Sodimouton, Salins Agriculture). Drinking water was delivered ad libitum through species-appropriate containers or delivered through an automatic watering system.

Animal selection and randomization

Only healthy and previously unused animals were selected for this study. Each animal was randomly assigned to one of the two time periods. Three implants of the same configuration were installed per femoral condyle and each animal was implanted with both implant configurations. The implantation site of each implant was randomly allocated. The randomization was carried out electronically by an independent author involved neither in the animal selection nor in the surgical procedures.

Pre-operative procedure

On the day of surgery, pre-medication was performed by intravenous injection of a mixture of diazepam (Diazepam ® , TVM) and butorphanol (Torphasol ® , Axience). Anesthesia was induced by intravenous injection of propofol (Propovet ® , Zoetis). Each sheep was intubated, mechanically ventilated, and placed on isoflurane inhalant anesthetic (IsoFlo ® , Zoetis) for continued general anesthesia. A suitable electrolyte solution (Ringer lactate, Baxter) was administered via intravenous infusion during surgery. An anti-inflammatory drug (carprofen, Rimadyl ® , Zoetis, subcutaneous) and a prophylactic antibiotic treatment (amoxicillin, Duphamox LA ® , Zoetis, intramuscular) were administered via pre-operative injection. The surgical areas were clipped free of wool, scrubbed with povidone iodine (Vetedine savon ® , Vetoquinol), wiped with 70% isopropyl alcohol (Savetis), painted with povidone iodine solution (Vetedine solution ® , Vetoquinol), and draped. The sheep were placed in the supine position on a warmed pad. A rectal temperature probe and a rumen tube were inserted during surgery. Electrocardiogram (ECG), peripheral non-invasive arterial blood pressure, and oxygen saturation were monitored.

Surgical procedure

The surgery was performed in a dedicated operating theatre by a veterinary surgical specialist from Namsa, using standard aseptic techniques (Fig. 2). A cutaneous incision was made on the medial side of each femoral condyle. The muscles were separated using blunt dissection to access the femur, and the periosteum was carefully removed from the femoral epiphysis to expose the implant sites. For each site, four-step drilling sequences were conducted perpendicular to the bone surface to obtain a final hole of 3.5 mm diameter with an approximate depth of 10 mm. Each drilling step was performed at a maximum drilling speed of 1 200 rpm and followed by extensive rinsing with saline to control temperature increase at the implantation site and to remove bone debris. Following drilling, the implant was inserted with a maximum torque of 45 N.cm. The incision was closed by separately suturing the capsule, muscles, and the subcutaneous layer with absorbable thread (Ethicon ® PDS TM II 1 and Ethicon ® Coated VicrylTM 2-0). The skin layer was closed with surgical staples (ApposeTM ULC Auto SutureTM, CovidienTM). The wounds were disinfected using an iodine solution. The legs were not restrained in any manner post-surgery.

Post-operative and terminal procedures

The animals were observed daily for general health and to detect mortality and morbidity. The implantation sites were examined daily for adverse reactions until removal of sutures. When any animal exhibited adverse clinical signs, it was examined and treated as needed. An intramuscular injection of buprenorphine (Buprecare ® , Axience) was administered at the end of the surgery day, then daily for two days post-surgery. An anti-inflammatory drug (carprofen, Rimadyl ® , Zoetis) was subcutaneously injected daily for five days post-surgery and a n antibiotic (amoxicillin, Duphamox LA ® , Zoetis) was intramuscularly injected every two days for eight days post-surgery. The wounds were disinfected with iodine solution (Vetedine solution ® , Vetoquinol) daily until two days after removal of surgical staples. The surgical staples were removed after complete healing (2 weeks following surgery). On week 4 and week 13, the designated animals were weighed and euthanized by intravenous injection of a lethal solution (Doléthal ® , Vetoquinol). These intervals were chosen to evaluate local tissue effects and bone-healing performance after both a short and a midterm implantation, as suggested in ISO 10993 standard -part 6, for non-degradable materials. The distal femur was harvested and explants were fixed in 10% Neutral Buffered Formalin (NBF) for histopathologic analysis. If not used for replacement, reserve implant sites were harvested in the same way, fixed, dehydrated, embedded, and stored for potential use in subsequent analyses. The newly formed calcified mineralization fronts were marked by fluorescence via prior subcutaneous injections in the neck and the back of three fluorochromes: xylenol orange (XO), calcein green (CG), oxytetracyclin (OTC). These fluorochromes bind to calcium at sites of bone mineralization and, if injected at specific times, enable mineralization front demarcations to be distinguished. For the 4-week group, the three fluorochromes were respectively injected on day 5, day 15, and day 25. Injections for the 13-week group were performed in respectively week 4, week 8, and week 12.

Micro-Computed Tomography (Micro-CT)

Micro-CT preparation

After fixation in 10% NBF (VWR), a total of forty implanted sites, one non-implanted REF article and one non-implanted TEST article were scanned by cone beam micro-computed tomography (µCT 40, SCANCO, Switzerland). The specimens were placed in cylindrical holders to obtain transverse tomograms of the implanted article at peak kilovoltage of 70 kVp, an intensity of 114 µA, a resolution of 15 µm and an integration time of 900 ms. The implant and bone were separated from the background through segmentation performed in conjunction with a Gaussian bandpass filter, respectively applying lower and upper density thresholds of 330 mg/cm 3 and 2275 mg/cm 3 for bone and titanium.

Micro-CT evaluation

Two Volumes Of Interest (VOI) were defined (Fig. 3a). Each VOI consisted in a conical tube with the inner edge along the core of the article (excluding the core but including the threads) and the outer edge placed at a fixed distance of 1 mm from the inner edge. The upper VOI (VOI C) was placed in the coronal area of the article. The lower VOI (VOI A) was placed along the apical and conical remaining area of the article. For each VOI, Bone Volume (BV), Bone Volume/Total Volume of the VOI (BV/TV), Bone-to-Implant Contact (BIC), trabecular thickness (Tb.Th) and trabecular spacing (Tb.Sp) were computed. For each femoral condyle, Tb.Th and Tb.Sp were also computed for a volume of 4x4x4 mm 3 of trabecular healthy bone, as a reference. The non-implanted scanned implants served as a baseline to help distinguish the article from the bone.

Histopathology

Histologic preparation

After fixation in 10% NBF (VWR), a total of forty implanted sites, one non-implanted REF article and one non-implanted TEST article were dehydrated in alcohol solutions of increasing concentration, cleared in xylene and embedded in polymethylmetacrylate (PMMA). For each explant and non-implanted article, one central longitudinal section was obtained using a microcutting and grinding technique (Exakt TM , approximately 40 µm thick), for a total of ten sections per group. The sections were left unstained for epifluorescence analysis and then stained with modified Paragon for qualitative and semi-quantitative histopathologic analyses as well as quantitative histomorphometric analysis.

Histopathologic evaluation

Prior to section staining, an epifluorescence analysis was conducted. Bone mineralization rate was assessed by evaluating the progression of the mineralization front at the time of the corresponding fluorochrome injection. Qualitative and semi-quantitative histopathologic evaluations of the local tissue effects at the implantation sites were conducted by an independent senior histopathologist from Namsa using a microscope (Nikon Eclipse E600, Nikon, France) coupled with a digital camera (DN 100, Nikon, France) at magnifications of x2, x4, x10, x20 and x40. Tissue damage, cellular inflammatory response, repair phase of inflammation, fatty infiltrate, and other parameters such as hemorrhage, cell degeneration, bone ingrowth, encapsulation, and bone healing were evaluated semi-quantitatively and graded using a scoring method suggested in the standard ISO 10993 -part Scoring is described in Table 1.

Histomorphometric evaluation

As with histopathologic evaluation, histomorphometric analysis was conducted by an independent senior histopathologist Namsa, on forty modified Paragon sections. Sections were scanned (Zeiss AXIOSCAN Z1) and analyzed at a magnification of x20, with a color image analyzing system (Tribvn, France, CALOPIX 3.2.0) to perform a semi-automatic analysis. Four standardized Regions Of Interest (ROI C1, C2, A1, A2) were defined for each longitudinal section (Fig. 3b). Each ROI consisted of a rectangle with the inner edge along the core of the article (excluding the core but including the threads) and the outer edge placed at a fixed distance of 1 mm from the inner edge. The upper ROI (ROI C) was placed in the coronal area of the article. The lower ROI (ROI A) was placed along the apical and remaining conical area of the implant. Each zonal ROI (sum of ROI C1 and C2 and sum of ROI A1 and A2) of the TEST was compared to each corresponding ROI of the REF.

Statistical analyses

Minitab 19 was used to conduct statistical analyses. Student's t-tests were used for comparisons of the two implants, considering a P-value below 0.05 (α = 0.05) as statistically significant.

Results

Implant surface characterization

Scanning electron microscopy SEM micrographs of the implant's surface revealed significant differences between the samples' topographies. While the REF surface only shows a heterogeneous microtopography (Fig. 4a and4b), the TEST surface topography is entirely replaced by a homogeneous nodule-like microstructure (Fig. 4c). Furthermore, the nanotopography is visible as a spike-like structure (Fig. 4d).

Energy-dispersive X-Ray spectrometry

The EDX spectra revealed that both REF and TEST surfaces are mostly composed of oxygen, titanium and carbon (Table 2). A low concentration of aluminum was measured on the REF surface but none was detected on the TEST surface.

Roughness measurements

Roughness measurements revealed few differences between REF and TEST surfaces (Table 2). While Sa and Sq parameter values were similar from one surface to another, significant differences were observed for the Sz and Sdr parameters.

Wettability

Wettability measurements on the TEST surface showed significantly lower contact angles for every liquid compared to the REF surface (Table 2). Therefore, the TEST surface is more hydrophilic than the REF one, showing a contact angle with water of 8.76±3.20° while 46.51±4.44° for the REF surface. While surface free energy results tend to corroborate this behavior, statistical significance was not reached (P=0.097).

Micro-CT analysis

When REF and TEST implants were compared by Micro-CT analysis, no statistical difference was found in BIC and BV/TV (Table 3). At 4 weeks after implantation, BIC reached 65.1±10.9% for the REF implant in the coronal region, against 61.8±10.8% for the TEST one. At 13 weeks, BIC increased to 74.4±10.6% for the REF implant and significantly increased to 80.6±7.4% for the TEST one. There was no evidence of variation in BV/TV ratio over time. Bone response in the apical region followed a significantly different pattern from that of the coronal region for the same period. However, neither of these parameters' values in the apical region differed significantly between implants and between time periods. While no significant differences in Tb.Th were found between the REF and TEST implants at 4 weeks, both in the coronal and in the apical regions, at 13 weeks after implantation there were significant differences between the implants in the apical region, reaching respectively 0.26±0.03 mm and 0.32±0.07 mm. A similar trend was observed in the coronal region, with respective values of 0.32±0.03 mm and 0.37±0.06 mm, although without statistical significance (P = 0.075). In contrast, no differences in Tb.Sp were observed between regions or time periods.

Histopathologic analysis

Owing to an off-axis section, one REF implant was replaced by a reserve implant for histology. At 4 weeks (Fig. 5), qualitative analyses of explants did not reveal significant differences in impact on local tissue between the REF and the TEST implants. The defect generated through drilling during the surgical procedure was still visible for both implants, allowing distinction between host bone and healing chamber, particularly in the apical region of the implant. No marked inflammation was observed by the histopathologist, with only a small number of macrophages and osteoclasts admixed with a few lymphocytes and polymorphonuclear cells. Bone marrow formation was observed in 4 out of 10 sites for the REF implant against 7 out of 10 sites for the TEST one. Combined with qualitative observations, these results indicate for both implants a marked woven bone neoformation, without tangible evidence of bone remodeling. Bone condensation was visible around the implants, especially in the coronal region. Signs of bone apposition and moderate to marked osteoconduction were observed, along with the marked presence of osteoblasts. In particular, TEST implants quickly formed a thin and continuous film of bony tissue at their surface (Fig. 5e), as highlighted by epifluorescent analysis (Fig. 5f). Furthermore, the latter analysis showed that for both implants, bone mineralization activity had already started at day 5, reaching a peak at day 15 mostly through bone deposition, then slightly decreased at day 25 (Table 1). At 13 weeks (Fig. 6), while no significant differences were noted in the semi-quantitative bone healing parameters between the REF implant and the TEST one, differences were observed in bone response in terms of architecture. Both implants showed fewer osteoblasts than the 4W group, as well as marked signs of bone neoformation, osseointegration, and osteoconduction. Consistent bone marrow formation was found and epifluorescent analysis (Fig. 6c,f) revealed continuing strong bone mineralization activity, mostly through bone thickening and surface apposition, at week 4 and week 8, which then slowed to a more moderate level at week 12 (Table 1). Nevertheless, the TEST implant showed no more bone condensation and with thick bone trabeculae (Fig. 6e,f). The defect margins were undistinguishable between host bone and neoformed bone. For the REF implant, the defect margins remained somewhat visible and discrete bone condensation could still be observed (Fig. 6b), despite similar bone remodeling rate compared to the TEST implant (Table 1; Fig. 6c). Semi-quantitative histopathologic results at week 4 and week 13 are compiled in Table 1.

Histomorphometric analysis

Contrary to the Micro-CT evaluation, significant differences were pointed out by histomorphometric analyses. Only slight variations in BIC in the apical region were visible, increasing from 63.5±9.9% to 66.2±14.7% for the REF implant and decreasing from 69.2±10.3% to 64.2±14.6% for the TEST implant between week 4 and week 13 (Fig. 7). In the coronal region, the BIC of the REF implant increased from 68.3±8.8% to 74.8±13% between week 4 and week 13. BIC values for the TEST implant were significantly higher than for the REF one at both week 4 and week 13, respectively 79.3±11.2% and 86.4±6.7%. No implant impact on local tissue densities was observed. A significant decrease in fibrous tissue density was observed between week 4 and week 13 for both implants, and in both their coronal and apical regions. In particular, in the apical region this decrease led to significantly higher fibrous tissue density for the TEST implant at week 13.

Discussion

This study provides evidence that implant surface modifications have a significant impact on bone response in the coronal region. Several previous studies demonstrated that surface chemical composition modification may alter peri-implant bone response [START_REF] Vasak | Early bone apposition to hydrophilic and hydrophobic titanium implant surfaces: A histologic and histomorphometric study in minipigs[END_REF]. In the present study, both implant surfaces, composed of titanium, seem to have adsorbed hydrocarbons from the exposure to ambient environment, explaining the presence of carbon. Moreover, traces of aluminum contamination, supposedly due to the corundum grit-blasting, were detected on the REF surface. Such pollutants may alter the nature of bone response at the peri-implant interface. Moreover, our roughness measurements point to the influence of surface processing on implant topology. Indeed, the combination of grit-blasting and dual chemical etching resulted in a significantly lower peakto-valley height and developed surface interfacial area ratio, although the arithmetic mean deviation and root-mean-square deviation of the surface remained unaffected. It is assumed that while grit-blasting is responsible for topology modifications at the micrometric scale, chemical attacks act at lower scales, resulting in less marked differences in micro-roughness parameters. This is in fact corroborated by our wettability results. Depending on both the topography and chemical composition of the surface, the TEST contact angles for every liquid tested were significantly lower, therefore showing a more hydrophilic surface. Overall, these results, together with the histomorphometric BIC analysis, confirm previous conclusions in the scientific literature [START_REF] Gittens | The effects of combined micron-/submicron-scale surface roughness and nanoscale features on cell proliferation and differentiation[END_REF][START_REF] Gittens | The Roles of Titanium Surface Micro/Nanotopography and Wettability on the Differential Response of Human Osteoblast Lineage Cells[END_REF]: surfaces incorporating features at both microscopic and nanoscopic scales generate an additive effect on the adhesion, proliferation, and differentiation of osteogenic cell lines, leading to increased de novo bone formation in vivo. While the exact mechanisms of overall bone response enhancement remain unclear, studies suggest that the higher surface energy resulting from incorporation of nanofeatures positively affects the adsorption and conformation of vitronectin and fibronectin, proteins responsible for osteoblast adhesion, onto the implant surface. Such adhesion appears to regulate the subsequent proliferation and differentiation of mesenchymal stem cells [START_REF] García | Modulation of Cell Proliferation and Differentiation through Substrate-dependent Changes in Fibronectin Conformation[END_REF][START_REF] Park | TiO2 nanotube surfaces: 15 nm -an optimal length scale of surface topography for cell adhesion and differentiation[END_REF].

The absence of tissue deleterious response for both REF and TEST implants indicates that the implants' biocompatibility was preserved despite the topography and chemical modifications in this study. Furthermore, mineralization activity was not affected by the TEST surface treatment. In a study conducted in dog jaws, [START_REF] Abrahamsson | Early bone formation adjacent to rough and turned endosseous implant surfaces. An experimental study in the dog[END_REF] suggested that there was an increase in lamellar bone formation around dental implants between 2 weeks and 4 weeks after implantation [START_REF] Abrahamsson | Early bone formation adjacent to rough and turned endosseous implant surfaces. An experimental study in the dog[END_REF], which is similar to the peaks observed here for the REF and TEST implants 15 days after implantation. This same study also emphasized the presence of a front of bone deposition onto the implant surface. The semi-quantitative histopathologic evaluation used here suggests that the TEST surface treatment was not deleterious to bone mineralization activity and moreover promoted osteoconduction. Micro-CT evaluation demonstrated no significant difference between the REF and TEST implants regarding BIC and BV/TV parameters, in both coronal and apical regions. This lack of difference compared to the findings from histomorphometric analyses could be explained by the high interferences generated by titanium implants [START_REF] Liu | Limitations of Using Micro Computed Tomography to Predict Bone-Implant Contact and Mechanical Fixation[END_REF]. These artifacts hinder measurements close to the surface of implants, thus decreasing the accuracy of such evaluation. [START_REF] Schwartz | Effect of micrometer-scale roughness of the surface of Ti6Al4V pedicle screws in vitro and in vivo[END_REF] precluded assessment by Micro-CT of bone healing at the interface due to these artifacts, as well as to poor acquisition resolution [START_REF] Schwartz | Effect of micrometer-scale roughness of the surface of Ti6Al4V pedicle screws in vitro and in vivo[END_REF]. However, our analysis highlighted different implant osseointegration behaviors. First, while Tb.Th in the apical region did not significantly differ according to implant at 4 weeks, it was significantly higher for the TEST implant at 13 weeks. A similar trend, although without statistical significance, was observed in the coronal region, which gives additional weight to this observation. It should be noted that major differences in bone healing were observed within a given group of implants between the coronal and the apical regions. This could be explained by a different implant thread design in the apical region, altering local stress distribution at the interface with bone [START_REF] Abuhussein | The effect of thread pattern upon implant osseointegration: Review[END_REF][START_REF] Steigenga | Effects of Implant Thread Geometry on Percentage of Osseointegration and Resistance to Reverse Torque in the Tibia of Rabbits[END_REF] and increasing wound chamber dimensions [START_REF] Marin | Histomorphologic and histomorphometric evaluation of various endosseous implant healing chamber configurations at early implantation times: A study in dogs[END_REF], thereby modifying the osteogenic response to the implant [START_REF] Davies | Understanding peri-implant endosseous healing[END_REF].

These observations need to be viewed in conjunction with the histopathologic findings. Indeed, while at 4 weeks REF and TEST implants induced similar bone architecture, with bone condensation and presence of the initial defect margins, at 13 weeks the TEST implant induced bone healing, with trabeculae recovering their connectivity and no detectable trace of the drilling for implant insertion. In addition, trabeculae appeared to be oriented towards the thread tips of the implant, where interfacial mechanical stress is significant. This is in accordance with Wolff's law of bone remodeling [START_REF] Wolff | Das gesetz der transformation der knochen[END_REF], which led to the concept of "bone functional adaptation" [START_REF] Lanyon | Mechanically adaptive bone remodelling[END_REF], explaining the process of long-term osseointegration. According to this concept, mechanical load applied to living bone influences the structure of bone tissue over time. Increased local strain results in greater deposition of bone tissue while decreased strain leads to resorption of bone tissue until the original bone strain levels, also termed "optimum customary strain level", are restored Interestingly, similar patterns were observed in other in vivo studies. [START_REF] Perrin | Bone response to alteration of surface topography and surface composition of sandblasted and acid etched (SLA) implants[END_REF] inserted titanium dental implants of various topographies into Land Race pig mandibles, observing a preferential orientation and distribution of bone trabeculae after 10 weeks. These trabeculae were oriented perpendicular to the implant surface and located at the thread level of the implant [START_REF] Perrin | Bone response to alteration of surface topography and surface composition of sandblasted and acid etched (SLA) implants[END_REF]. The authors explained this behavior with reference to [START_REF] Gross | Implant surface roughness and mode of load transmission influence peri implant bone structure[END_REF], who inserted titanium cylinders of differing surface roughness into the distal epiphysis of rabbit femurs and noted the formation of a cortical shell around implants with smooth surfaces, opposed to oriented trabeculae with increased surface roughness [START_REF] Gross | Implant surface roughness and mode of load transmission influence peri implant bone structure[END_REF]. It was suggested that surface roughness promotes bone trabecularization around the implant, leading to better immobilization. In an animal experiment employing porous coated and proximally partially porous coated femoral canine implants, [START_REF] Bobyn | The effect of proximally and fully porouscoated canine hip stem design on bone modeling[END_REF] noted a similar shell around the smooth surface, interposed with a space filled with fibrous tissue [START_REF] Bobyn | The effect of proximally and fully porouscoated canine hip stem design on bone modeling[END_REF]. Based on these observations, Luo et al. (1999) used computational methods to indicate that such a shell should resorb over time, leading to trabecularization of the bone-implant interface [START_REF] Luo | The effect of surface roughness on the stress adaptation of trabecular architecture around a cylindrical implant[END_REF].

Clinically, in vivo investigations report successful osseointegration of dental implants for BIC between 50% and 80% [START_REF] Lian | Effect of bone to implant contact percentage on bone remodelling surrounding a dental implant[END_REF]. Considering the current experimental conditions and results, it is therefore assumed that both REF and TEST implants would achieve long-term stability. However, by positively affecting coronal BIC results both at 4 weeks and 13 weeks compared to the REF implant, it is supposed by the authors that the surface treatment applied to the TEST implant may be of interest for improving osseointegration of implants in bone of poor quality such as osteoporotic bone [START_REF] Liu | Effects of micro/nano strontium-loaded surface implants on osseointegration in ovariectomized sheep[END_REF].

Bone healing and remodeling mechanisms are complex, and this study faced difficult choices. On the choice of animal model, canine and porcine models are known to provide bone healing and remodeling rates closer to humans than the sheep model. However, the sheep was shown to be a relevant model in many intraosseous implantation studies published in scientific peer-reviewed journals and is recognized by International Regulatory Organisms [START_REF] Nuss | An animal model in sheep for biocompatibility testing of biomaterials in cancellous bones[END_REF][START_REF] Sartoretto | Sheep as an experimental model for biomaterial implant evaluation[END_REF]. Compared to small animal models, the sheep model offers the advantage of a body weight, as well as bone healing and remodeling patterns, more similar to the human [START_REF] Pearce | Animal models for implant biomaterial research in bone: A review[END_REF]. Furthermore, this model currently raises fewer ethical issues than models such as the dog, and is easier to handle, more amenable to intervention, than the porcine model [START_REF] Pearce | Animal models for implant biomaterial research in bone: A review[END_REF]. On the choice of implantation site, it is universally recognized that the intended anatomical location of dental implants, alveolar bone from the jaw, is not equivalent to femoral bone in its origin, method of ossification, microstructure or rate of turnover. In addition, obtaining data related to dental implant evaluation, such as buccal and lingual bone crest levels, appears impractical from the femur, which partially limits the range of analyses specifically related to dental implants. Nonetheless, the sheep femoral implantation model is highly standardized and associated with low rates of complication. The osseointegration properties of dental implants can be assessed with minimal variability, enabling finer comparisons of surface treatment influence than with jawbone implantation [START_REF] Siddiqi | One-piece zirconia ceramic versus titanium implants in the jaw and femur of a sheep model: A pilot study[END_REF]. Histopathological analyses were performed by only one senior histopathologist who provided only one value per parameter and per sample. Therefore, unfortunately, the reproducibility of results for the same sample at different times cannot be clearly supported by any reliability data. Furthermore, implant dimensions constrained the sampling to only one longitudinal section per explant. However, the authors are confident that the preparation of ten slices per group, along with the assessment of the overall peri-implant bone architecture through micro-CT analyses, reduced any potential bias generated by the study design.

Conclusion

The present pre-clinical study evaluated the biocompatibility and osseointegration of dental implants with different surface characteristics in sheep femoral condyles. The REF implant surface was obtained by grit-blasting while the TEST implant surface resulted from a succession of gritblasting, acid-etching, and basic-etching, the two latter inducing nanofeatures at its surface. After 4 and 13 weeks of implantation, both implants showed good biocompatibility within their environment, without any deleterious local effect on the surrounding tissue. Bone apposition was significantly higher at both 4 and 13 weeks for the TEST implant, with thicker bone trabeculae in the apical region of the implant. This suggests that the presence of nanofeatures at the surface of TEST dental implants promoted faster bone healing. Finally, the distinction between the coronal and apical regions of the implant demonstrates that bone behavior differed along the implant, possibly due to differing implant thread geometry and the greater local stresses generated at the apex.

Figure legends

Figure 1 :

 1 Figure 1: (a) Full-Size High-Resolution SEM image of REF and TEST implant used for the study; (b) General implant dimensions.

Figure 2 :

 2 Figure 2: Surgery procedure for implantation. (a) Drilling at 1 200 rpm; (b) dental implant insertion at 45 N.cm; (c,d) implant positions on femoral condyle after completed surgery. Three sites per condyle are allocated for implants.

Figure 3 :

 3 Figure 3: (a) Tomogram obtained by Micro-CT tomography, presenting the different Volumes Of Interest (VOI A and C); (b) Representative photomicrograph used for histopathologic analysis, introducing four Regions Of Interest (ROI A1, A2, C1 and C2).

Figure 4 :

 4 Figure 4: SEM of implant surface (a,b) REF surface ; (c,d) TEST surface. The REF surface shows a heterogeneous microtopography while the TEST surface has a homogeneous nodule-like microstructure and a spike-like nanotopography.

Figure 5 :

 5 Figure 5: Photomicrograph of a (a,b,c) REF implant and (d,e,f) TEST implant, 4 weeks after implantation. Bone condensation is visible all around the implant, depicting the initial defect margins created through the surgical drilling. Signs of osseointegration are visible through woven bone neoformation at the surface of both REF and TEST implants. Under epifluorescence microscopy (c,f), calcein green (15 days) revealed bone mineralization at the surface of the TEST implant, where a continuous thin film of bony tissue is formed, while discrete and discontinuous on the REF implant (white lines). OB: old bone; OI: osseointegration; BM: bone marrow; NFB: Newly formed bone.

Figure 6 :

 6 Figure 6: Photomicrograph of (a,b,c) REF implant and (d,e,f) TEST implant, 13 weeks after implantation. While defect margins are still visible (black arrows) along with discrete bone condensation around the REF implant, the TEST implant showed almost invisible bone condensation and defect margins. Under epifluorescence microscopy (c,f), bone thickening and surface apposition are still observable for both implants, in xylenol orange (4 weeks) and calcein green (8 weeks). Oxytetracyclin (13 weeks) revealed slowing bone mineralization. OB: old bone; OI: osseointegration; BM: bone marrow; NFB: Newly formed bone; DM: drill margins.

Figure 7 :

 7 Figure 7: Histomorphometric analysis of BIC (%) in the coronal and apical portions of REF and TEST implants. * P<0.05 compared to REF group at the same time period.

Acknowledgements

The authors would like to thank Namsa (Chasse-sur-Rhône, France) for providing the animal model, housing and husbandry and performing the different surgical procedures, histopathologic and histomorphometric analyses. The authors also acknowledge Generic Implants (Saint-Genis-Laval, France) for supplying the implants used for the study and Selenium Medical (La Rochelle, France) for the surface treatment and packaging applied to these implants.

Conflict of Interest Statement

The study was financially supported by the company Selenium Medical. Some authors are employees of Selenium Medical and took part in the study design, implants physicochemical characterization and the writing of this article. However, the authors certify that they were not involved in surgical procedures nor in the micro-computed tomography, histopathologic and histomorphometric analyses, which were conducted by an external expertise.


Barthélémy Faudot
email: barthelemy.faudot@univ-amu.fr

Jean-Louis Milan

Benjamin Goislard De Monsabert

Thomas Le Corroller

Laurent Vigouroux

Estimation of joint contact pressure in the index finger using a hybrid finite element musculoskeletal approach

Keywords: Hand biomechanics, joint contact pressure, pinch grip task, finite element analysis, musculoskeletal model

Introduction

The human hand is a sophisticated biological tool involved in numerous everyday activities [START_REF] Bardo | The impact of hand proportions on tool grip abilities in humans, great apes and fossil hominins: A biomechanical analysis using musculoskeletal simulation[END_REF]. The gripping tasks performed by the hand are essential for most movements in daily and working life. One of the commonest of the various techniques (e.g.: cylindrical, key pinch, hook grip) [START_REF] Napier | THE PREHENSILE MOVEMENTS OF THE HUMAN HAND[END_REF]) used to manipulate objects is the pinch grip, which consists in holding an object between the thumb and the index fingertips [START_REF] Vergara | An introductory study of common grasps used by adults during performance of activities of daily living[END_REF]. Because of its specific biomechanical configuration, this grip technique can lead to high joint loadings that expose the fingers to injuries such as rheumatoid arthritis and osteoarthritis (OA) [START_REF] Jensen | Occupational use of precision grip and forceful gripping, and arthrosis of finger joints: a literature review[END_REF][START_REF] Mcquillan | Weaker Functional Pinch Strength Is Associated With Early Thumb Carpometacarpal Osteoarthritis[END_REF]. Cumulative excessive stress acting on normal joints has in fact been identified as one of the main risk factors for the development of OA [START_REF] Guilak | Biomechanical factors in osteoarthritis[END_REF][START_REF] Buckwalter | The Roles of Mechanical Stresses in the Pathogenesis of Osteoarthritis: Implications for Treatment of Joint Injuries[END_REF]. Hence, quantifying the biomechanical stress distribution on the finger's musculoskeletal system, especially joint contact pressure, could provide a better understanding of joint disease (Goislard de [START_REF] De Monsabert | Quantification of finger joint loadings using musculoskeletal modelling clarifies mechanical risk factors of hand osteoarthritis[END_REF]) and improve rehabilitation [START_REF] Fowler | Interphalangeal joint and tendon forces: normal model and biomechanical consequences of surgical reconstruction[END_REF][START_REF] Completo | Biomechanical evaluation of pyrocarbon proximal interphalangeal joint arthroplasty: An in-vitro analysis[END_REF].

Direct measurements of joint pressures have been estimated in-vivo using pressure sensors [START_REF] Rikli | Intra-articular pressure measurement in the radioulnocarpal joint using a novel sensor: in vitro and in vivo results[END_REF]) and instrumented prostheses for large joints (D' Lima et al. 2006). However, the highly invasive nature of such techniques makes them ethically questionable and a technical challenge, especially when applied to the small finger joints. Only a few in vitro experimental data for the hand are available, due to the joint size and to the surrounding tissues that complicate the insertion of such sensors. Therefore, computational modelling, being noninvasive, appears to be the most suitable method of estimating joint mechanics.

Finite element (FE) and musculoskeletal (MSK) are the main modelling approaches currently used to study joint loadings [START_REF] Henak | Subject-specific analysis of joint contact mechanics: application to the study of osteoarthritis and surgical planning[END_REF]. They have been widely applied to the lower limb during isometric tasks [START_REF] Cheung | Three-dimensional finite element analysis of the foot during standing--a material sensitivity study[END_REF]) and gait locomotion [START_REF] Andriacchi | Gait mechanics influence healthy cartilage morphology and osteoarthritis of the knee[END_REF] to estimate either joint kinematics, reaction forces or joint cartilage stress. Due to the number of anatomical components involved and the complexity of soft-tissue interaction, multi- [START_REF] Fowler | Interphalangeal joint and tendon forces: normal model and biomechanical consequences of surgical reconstruction[END_REF][START_REF] Synek | The effect of the extensor mechanism on maximum isometric fingertip forces: A numerical study on the index finger[END_REF], the thumb-index pinch complex [START_REF] Barry | Development of a dynamic index finger and thumb model to study impairment[END_REF] or the entire hand (Goislard de [START_REF] De Monsabert | Quantification of finger joint loadings using musculoskeletal modelling clarifies mechanical risk factors of hand osteoarthritis[END_REF]. Although such models provide estimations of tendon forces and resultant joint contact forces, they neglect the non-linear deformation of soft tissues and the local stress distribution. Conversely, FE hand models provide estimations of local contact mechanics but focus on a single joint [START_REF] Hashizume | Stress Analysis of PIP Joints using the Three-Dimensional Finite Element Method[END_REF], model joints in 2D (Butz et al. 2012a), neglect muscle actions and tendon paths (Butz et al. 2012b) and apply nonphysiological boundary conditions [START_REF] Harih | Development of a Tendon Driven Finger Joint Model Using Finite Element Method[END_REF]. To take advantage of both approaches, hybrid MSK-FE models have been developed to investigate different musculoskeletal structures, such as the wrist [START_REF] Gíslason | Finite element model creation and stability considerations of complex biological articulation: The human wrist joint[END_REF], the ankle [START_REF] Wang | Computational Models of the Foot and Ankle for Pathomechanics and Clinical Applications: A Review[END_REF] or the knee [START_REF] Besier | A modeling framework to estimate patellofemoral joint cartilage stress in vivo[END_REF][START_REF] Halonen | Workflow assessing the effect of gait alterations on stresses in the medial tibial cartilage -combined musculoskeletal modelling and finite element analysis[END_REF]. However, the implementation of this hybrid approach remains challenging when modelling the hand, whose multi-joint configuration makes it particularly difficult to validate the numerical procedure.

A hybrid MSK-FE model representing bones, cartilage, tendons, annular pulleys and ligaments while considering the multi-joint actions of tendons would help to improve the understanding of musculoskeletal diseases. To the best of our knowledge, no studies have so far applied this hybrid approach to the hand joints. Thus, the purpose of this paper was to provide a validated hybrid biomechanical model of the index finger that estimates in-vivo joint contact pressure by applying realistic muscle actions during a static maximal strength pinch grip task.

Methods

The workflow of the study is presented in forces from kinematic and force data through an inverse dynamic approach. Tendon forces were then inputted into the FE model and joint contact pressures were computed.

[Figure 1 about here]

Experimental kinematic and force data

The experimental setup and protocol already reported (Goislard de Monsabert et al. 2014) are briefly described here. Ten healthy right-handed males free of upper extremity disorders were recruited (age: 25.5±3.2 years; height: 178.6±6.1 cm; weight: 71.2±7.2 kg; hand length: 19.0±0.8 cm). Kinematic and force data (Fig. 2) were simultaneously recorded. A six-axial force sensor (Nano-25; ATI Industrial Automation, USA) 5.5 cm long was used to record the force applied by the thumb and index fingertips. The 3D position of hand segments was tracked using spherical reflecting markers and a six-camera optoelectronic system (MX T40; Vicon, UK). Joint angles and the three grip force components were then inputted into the MSK model.

[Figure 2 about here]

Tendon force estimation using a musculoskeletal model

A full description of the MSK model is provided in a previous study [START_REF] De Monsabert | Quantification of hand and forearm muscle forces during a maximal power grip task[END_REF]. The model estimated 42 tendon forces to balance 23 degrees of freedom (DoF) representing the five fingers and the wrist. The segments were modelled as rigid bodies articulated by sixteen frictionless joints. In the first step, the 42 tendon forces required to balance external forces were estimated using a static optimisation to solve the muscular redundancy problem. In the second step, joint reaction forces were derived from tendon and external fingertip forces using the force equilibrium equation.

Finite element model

Model geometry

A healthy male subject free of upper extremity disorders was recruited to acquire computed tomography (CT) images of the right hand (age: 37 years; height: 185 cm; weight: 74 kg; hand 6 length: 19.7 cm). The participant signed an informed consent form and the protocol was approved by the local ethics committee. The CT system was a LightSpeed VCT (GE Medical Systems, USA) (150 mA x 120 kV; slice thickness 625 μm; pixel size 325 μm). The subject placed his hand in a semi-rigid cast that constrained him in a pinch grip posture. The cast was made prior to the acquisition to avoid any effect of fatigue. Polyurethane resin tapes (Soft Cast, 3M, USA) were positioned while the subject was holding a 5.5 cm-long tube, i.e. the same length as the force sensor.

Segmentation of bones was performed from the CT-scan acquisition using the 3D image reconstruction software Mimics (Research 20.0; Materialise, Belgium). Index phalanges and truncated metacarpal bone were meshed using quadratic tetrahedral elements (C3D10) with a maximum element edge length of 1.5 mm. Solid geometries were imported into Abaqus (2018; Simulia, USA). The cartilage was manually created by identifying joint surfaces on bones and then extruding surface elements to form two-layer wedge elements (C3D6), each of whose widths equalled half the minimum distance between bones [START_REF] Anderson | Effects of idealized joint geometry on finite element predictions of cartilage contact stresses in the hip[END_REF]. Cartilage distribution and thickness (from 0.4 to 0.8 mm) were compared against literature values [START_REF] Robson | A combined analysis and magnetic resonance imaging technique for computerised automatic measurement of cartilage thickness in the distal interphalangeal joint[END_REF]. The FE model's total number of elements was roughly 200 000.

Modelling tissue properties

Finger bones were modelled as a linear elastic isotropic material, distinguishing between cortical (E=18 GPa, ν=0.2) and cancellous bone (E=300 MPa, ν=0.25) [START_REF] Rho | Elastic properties of human cortical and trabecular lamellar bone measured by nanoindentation[END_REF]), see Fig. 3(B). Cartilage was modelled using a 3 rd order Ogden hyper-elastic material as detailed in Table 1. Supplementary analysis was performed to investigate the effect of bone material properties on the model results. dimensions [START_REF] An | Normative model of human hand for biomechanical analysis[END_REF]. Each tendon was modelled using straight beams (B31) to connect the points given by the anatomical dataset, i.e. two points at each joint. Tendons were held tight to the bone by annular pulleys modelled with shell elements (S4) for both flexor and extensor tendons (see Fig. 3).

Collateral ligaments and volar plates were modelled as the main stabilisers of the index finger joints [START_REF] Minami | Ligament stability of the metacarpophalangeal joint: a biomechanical study[END_REF]. The same attachment points as those used for the MSK model were estimated from an anatomical study [START_REF] An | Normative model of human hand for biomechanical analysis[END_REF]. Distributed insertions were simulated by applying ligaments in parallel at adjacent node points on the bone surface. Ligaments were modelled as non-linear spring elements (CONN3D2) with tension-only behaviour and prestrain at initial length [START_REF] Rhee | A biomechanical study of the collateral ligaments of the proximal interphalangeal joint[END_REF]. Model values are summarised in Table 1.

[Table 1 about here] [Figure 3 about here]

Loads and boundary conditions

Loadings on the hybrid model were driven through the estimation of tendon forces provided by the MSK analysis previously described. Four of the ten subjects were excluded from the analysis due to the large difference between their joint angles and those of the scanned subject.

For the six remaining subjects, tendon forces were applied to the end of each tendon in the direction of the last beam segment (Fig. 3) and the six datasets were analysed. An extra simulation was performed using the average value of tendon forces. Supplementary analysis was also conducted to investigate the effect of tendon forces on the model results. Bone and cartilage were fixed together so as to allow no relative motion between them. A friction coefficient of 0.02 [START_REF] Wright | Lubrication and cartilage[END_REF]) was applied to each cartilage joint surface.

The proximal end of the truncated metacarpal bone was fully constrained and index fingertip nodes were restricted to one DoF to model the contact with the force sensor (see Fig. 3).

The Abaqus explicit solver was used for the analysis, this algorithm making the contact model robust.

Verification and validation of the hybrid model

To validate the hybrid approach, several analyses were performed to assess the quality of the hybrid model. First, the FE environment was evaluated through an assessment of the mesh quality and the convergence criterion. Resultant fingertip forces estimated in the hybrid model at the fixed fingertip nodes were compared to the experimental forces measured by the force sensor. The ratio of inputted tendon forces to estimated fingertip forces provided by the hybrid model for both FDP and FDS was compared to literature values. Lastly, the sum of reaction forces for all nodes of each joint in the hybrid model was compared to the joint reaction forces of the MSK model. These comparisons were performed using the average value of tendon forces of the six subjects inputted into the hybrid model.

Results

Results of the MSK model

The MSK model results are summarised here, for a full description see (Goislard de Monsabert Subjects gripped the object using a variety of finger postures. DIP, PIP, and MCP flexion angles ranged from 8.9° to 28.8°, -1.0° to 21.3° and 46.5° to 64.4°, respectively. The scanned subject had flexion angles of 9.3°, 16.9°, and 47.6° for DIP, PIP and MCP joints, respectively.

Finite element environment quality indicators

Mesh quality was checked against the recommendations of a previously published article [START_REF] Burkhart | Finite element modeling mesh quality, energy balance and validation methods: a review with recommendations associated with the modeling of bone tissue[END_REF], detailed in Table 2, ensuring that elements with poor mesh metrics were located far from areas of interest. The model converged, at the end of the load step, with a mean kinetic energy of 3.4% of the total strain energy. Any dynamic behaviour was excluded according to the literature [START_REF] Choi | Comparison of Implicit and Explicit Finite-Element Methods for the Hydroforming Process of an Automobile Lower Arm[END_REF], leading to a quasi-static simulation.

[Table 2 about here]

Validation of the hybrid model

The hybrid model outputs agreed well with experimental and MSK model results. The fingertip reaction force estimated by the hybrid model using averaged tendon force was 54.8 N, lower than the experimental measurement by the force sensor, but remained within one standard deviation (66.2±13.3 N). The hybrid model estimated a tendon force to external fingertip force ratio of 1.85 and 2.67 for FDP and FDS, respectively, as shown in Table 3. The joint reaction forces estimated by the hybrid model were higher than those of the MSK model but remained within one standard deviation. The sum of DIP, PIP and MCP joint reaction forces was 758.2 N, 481.7 N and 248.7 N, respectively. The results are summarised in Table 4.

[Table 3 about here] [Table 4 about here]

Joint mechanical stresses estimated by the hybrid model

Joint contact pressure on cartilage surfaces and Von Mises stress distribution on bones of the index finger during a pinch grip task for one dataset of tendon forces are displayed in Fig. 4.

The highest stress was found on the surface of the metacarpal bone. High stress-intensity regions were visible at bone-pulley interface and at ligament insertions because of the node coupling points (Fig. 4). However, these stresses were highly localised and not representative of the real bone condition, being due to numerical artefacts. Finger joint contact areas were computed by summing all the facets bearing contact force and yielded 53.4±4.6 mm², 76.2±5.1 mm² and 94.8±2.1 mm² for DIP, PIP and MCP joints, respectively. Maximal contact pressure on cartilage was computed as well as mean contact pressure by averaging pressure values on the contact area at each joint (Fig. 4). For DIP, PIP, and MCP joints, maximal contact pressure was 30.3±8.2 MPa, 31.9±8.8 MPa, and 33.8±6.9 MPa and mean contact pressure was 7.2±2.6 MPa, 7.0±1.3 MPa, and 8.0±1.4 MPa, respectively, as shown in Table 5.

[Table 5 about here]

[Figure 4 about here]

Sensitivity analysis

The sensitivity analysis on material properties showed that considering bones as rigid or homogeneous elastic solid tended to increase joint contact pressure. On sensitivity to tendon force, the results showed that joint contact pressure and external fingertip force decreased linearly with tendon force intensity. Further details can be found in Supplementary Material B.

Discussion

We described here the development of a hybrid biomechanical model of the index finger to estimate joint contact pressure during a static maximal strength pinch grip task in an FE environment driven by tendon forces calculated by an MSK model. This method combines two different numerical hand models to estimate joint mechanical stresses, notably mean and maximal joint contact pressures. This highly innovative approach represents, to the best of our knowledge, the first attempt to apply and validate a multi-articular hybrid model to the hand joints. When evaluated through a combination of sensitivity analysis and comparison with experimental measurements, MSK results and literature data, the hybrid model was shown to provide realistic estimation of hand loadings. First, the estimated fingertip reaction force was in good agreement with the experimental grip force recorded using the force sensor, with only a 17% difference stable across subjects. The consistency of this gap suggests that its origin lies in the use of a single bone geometry in the hybrid model, whereas the experimental gripping task involved six subjects, each with a different bone geometry. There was good agreement in resultant joint reaction forces between the hybrid and the MSK models, both of which showed an increase from distal to proximal joints and a major difference at the DIP joint. The negligible differences between the hybrid and the MSK model may be explained by the use of different assumptions in the two numerical approaches, such as non-deformable bodies in the MSK model versus a more accurate representation of bone and cartilage in the hybrid model. Lastly, joint contact areas predicted in the hybrid model showed similar values to those of the MSK model and literature data [START_REF] Moran | Finger joint contact areas and pressures[END_REF].

The hybrid model proposes a new tendon force transmission based on a tendon-pulley system, where both flexor and extensor tendons slid in annular pulleys. This yielded estimations of the ratio of flexor tendon forces to fingertip force that were consistent with in-vivo measurements found in the literature [START_REF] Schuind | Flexor tendon forces: in vivo measurements[END_REF][START_REF] Dennerlein | Tensions of the flexor digitorum superficialis are higher than a current model predicts[END_REF][START_REF] Kursa | In vivo forces generated by finger flexor muscles do not depend on the rate of fingertip loading during an isometric task[END_REF]) and with MSK results, thus validating this approach (Table 3). In a previous study [START_REF] Harih | Development of a Tendon Driven Finger Joint Model Using Finite Element Method[END_REF]), the DIP joint was driven by a concentrated force at the end of a wire connector which modelled the distal part of the flexor tendon. The same approach has been used in some foot FE models [START_REF] Isvilanonda | Finite element analysis of the foot: model validation and comparison between two common treatments of the clawed hallux deformity[END_REF][START_REF] Morales-Orcajo | Influence of first proximal phalanx geometry on hallux valgus deformity: a finite element analysis[END_REF][START_REF] Wang | Computational Models of the Foot and Ankle for Pathomechanics and Clinical Applications: A Review[END_REF], with tendons crossing several joints and the tendon final insertion attached to the bone.

The choice of material properties in the hybrid model was based on several factors. Sensitivity analysis (see Supplementary Material B) showed that bone representation had an impact on 12 joint contact pressures. Distinguishing between cortical and cancellous bone ensured here that the structure was rigid enough for good transmission of stresses between cartilage layers and bones. This suggests that piecewise assigning of linear-elastic material properties to bones, by calculating the density of the CT-scan gray value of each element, better matches the real microarchitecture of the bone. Cartilage was represented here as a monophasic timeindependent hyperelastic material that could handle large deformations greater than 5%.

Although this did not account for either poroelastic behaviour or fluid matrix interactions such as osmotic swelling or mechanical exudation of interstitial fluid [START_REF] Halloran | Multiscale mechanics of articular cartilage: potentials and challenges of coupling musculoskeletal, joint, and microscale computational models[END_REF], hyperelastic models are deemed adequate to characterise the equilibrium response of cartilage [START_REF] Brown | Assessment of common hyperelastic constitutive equations for describing normal and osteoarthritic articular cartilage[END_REF].

The calculation of mean contact pressures for the maximal strength grip task performed by six subjects showed significant differences among them. For two subjects (4 and 9), mean contact pressures resulted in greater values for the DIP joint than for PIP and MCP joints. For the index finger, several studies have shown that OA is more frequent in the DIP joint than in the proximal joints [START_REF] Caspi | Clinical, radiologic, demographic, and occupational aspects of hand osteoarthritis in the elderly[END_REF][START_REF] Dahaghin | Prevalence and pattern of radiographic hand osteoarthritis and association with pain and disability (the Rotterdam study)[END_REF]. It can therefore be concluded that cumulative excessive stresses acting on joints should lead to the occurrence and development of OA, consistent with previous findings [START_REF] Guilak | Biomechanical factors in osteoarthritis[END_REF][START_REF] Buckwalter | The Roles of Mechanical Stresses in the Pathogenesis of Osteoarthritis: Implications for Treatment of Joint Injuries[END_REF]. In contrast, the remaining four subjects (1, 2, 3 and 7) showed higher mean contact pressures in the MCP joint than in the PIP and DIP joints. Studies have found that the MCP joint is the most subject to OA development during maximal strength tasks [START_REF] Jensen | Occupational use of precision grip and forceful gripping, and arthrosis of finger joints: a literature review[END_REF], while the DIP joint is the most sensitive under precision repetitive grip tasks [START_REF] Lehto | Roentgenological arthrosis of the hand in dentists with reference to manual function[END_REF]). Furthermore, to perform the maximal strength grip task, different neuromuscular strategies were employed by the subjects.

Since these strategies activated the muscles in varying ways, they resulted in varying joint contact pressures. In subjects 4 and 9, greater mean contact pressures at the distal joint were induced by higher FDP muscular activity resulting in higher FDP tendon force. In subject 7, greater mean contact pressures at proximal and metacarpophalangeal joints were due to higher FDS and RI muscular activities resulting in higher FDS and RI tendon forces.

The mean contact pressures obtained in the hybrid simulation reached 8.0±1.4 MPa at the MCP joint (Table 5), which could indicate tissue consolidation. Indeed, this value was in the range of those moderate normal loadings needed for cartilage development and renewal, and to maintain functional integrity [START_REF] Vanwanseele | Knee cartilage of spinal cord-injured patients displays progressive thinning in the absence of normal joint loading and movement[END_REF], thus keeping cartilage healthy [START_REF] Parkkinen | Local stimulation of proteoglycan synthesis in articular cartilage explants by dynamic compression in vitro[END_REF][START_REF] Clements | How severe must repetitive loading be to kill chondrocytes in articular cartilage?[END_REF]). However, peak contact pressures at DIP, PIP and MCP joints (higher than 15 MPa) corresponded to an excessive mechanical load which could therefore cause chondrocyte death and extracellular matrix damage [START_REF] Torzilli | Effect of impact load on articular cartilage: cell metabolism and viability, and matrix water content[END_REF], thus leading to OA initiation. It should be noted that this study examined an extreme force intensity of one of the most common techniques for manipulating objects, the pinch grip. While a pinch strength of 10 N will actually suffice for 90% of daily living activities [START_REF] Hunter | Rehabilitation of the hand[END_REF], the simulated pinch strength here was more than 5 times higher, with an experimental fingertip force of 66.2 ± 13.3 N. Thus, the task studied here could be considered as a worst-case for which the conditions of OA occurrence were assessed and evaluated.

The hybrid method presented in this article offers access to individual subjects' local stress distribution in index finger joints through a non-invasive evaluation. It can be applied and extended to the complete hand to simulate tasks such as the power grip and to potentially link the mechanical determinants and consequences of diseases such as OA. A deeper understanding of the biomechanics of the hand related to joint disease occurrence could provide the groundwork to improve surgical procedures, such as arthroplasty, through more effective numerical models.

  as the finger, wrist or ankle have received less attention. Most hand biomechanical models use an MSK representation for either the index finger

Fig. 1 .

 1 This hybrid approach combined an already published MSK model based on experimental data with a newly developed FE model of the index finger based on medical imaging and literature data. The MSK model estimated tendon

  All the tendons and muscles involved in index finger function were modelled: terminal extensor, flexor digitorum profundus (FDP) at distal interphalangeal (DIP) joint, extensor slip, radial band, ulnar band, flexor digitorum superficialis (FDS) at proximal interphalangeal (PIP) long extensor (considering both extensor digitorum communis (EDC) and extensor digitorum indicis (EDI)), radial interosseus (RI), ulnar interosseus (UI), lumbrical (LU) at metacarpophalangeal (MCP) joint. The paths of these tendons were determined by the same anatomical and geometrical data in the MSK model and scaled according to phalange

  et al. 2014). Tendon forces and averaged tendon force values for the six subjects are given in Supplementary Material A. For flexor tendons, resulting tensions were 158.0 ± 82.2 N and 109.8 ± 41.0 for the FDP and FDS tendons, respectively. For the extensor mechanism, resulting tensions were 5.1 ± 5.6 N, 181.2 ± 46.3 N, 0.0 ± 0.0 N, 85.6 ± 34.1 N, 110.0 ± 43.8 N for the LU, RI, UI, EDC and EDI tendons, respectively.

Figure 1 .

 1 Figure Captions

Figure 2 .

 2 Figure 2. Pulp pinch grip posture and experimental acquisition system. A motion capture system

Figure 3 .

 3 Figure 3. (A) Index finger finite element model of the hybrid approach including bones,

F

Figure 1 .Figure 2 .Figure 4 .

 124 Figure 1. Hybrid musculoskeletal-finite element model applied to the index finger for the estimation of joint contact pressure during a static maximal strength pinch grip task. The musculoskeletal model applied to six subjects estimated tendon and joint forces from motion capture and force data through an inverse dynamic approach. The finite element model based on medical imaging data and including all the major structures of the index finger was driven by tendon forces of the musculoskeletal model. This hybrid approach validated by comparison with experimental data and musculoskeletal results yielded mean and maximal contact pressures at the three index finger joints. 569x379mm (300 x 300 DPI)

Table 1 .

 1 Figure 4. Von Mises stress distribution of the index finger and contact pressure distribution at distal interphalangeal (DIP), proximal interphalangeal (PIP) and metacarpophalangeal (MCP) joints during a static maximal strength pinch grip task applying one dataset of tendon forces. Material properties and element types of the index finger hybrid finite element model

	o r
	P
	e e r
	R e v
	i e w
	O n
	l
	y

Table 2 .

 2 Mesh quality metrics of the hybrid finite element model

	Mesh quality metric	Assessment criteria	Accurate elements
	Jacobian elements	> 0.2	94%
	Aspect ratio	< 3	96%
	Max angles	< 120°99%

Table 3 .

 3 Comparison of ratios of tendon force to external fingertip force during pinch grip between MSK model, hybrid model and in-vivo measurements reported in the literature

		FDP	FDS
	MSK model	1.7	2.4
	Hybrid model	2.0	2.9
	Schuind et al.	7.9 ± 6.3	1.7 ± 1.5
	Denenrlein et al.	--	3.3 ± 1.4
	Kursa et al.	2.4 ± 0.7	1.5 ± 1.0

Table 4 .

 4 Force values obtained from musculoskeletal and hybrid models of the index finger.

	External fingertip force and joint reaction force in distal interphalangeal (DIP), proximal
	interphalangeal (PIP) and metacarpophalangeal (MCP) joints from the two models are
	compared.
		External fingertip	DIP joint reaction	PIP joint reaction	MCP joint
		force (N)	force (N)	force (N)	reaction force (N)
	MSK model	66.2 ± 13.3	125.5 ± 87.6	324.4 ± 144.4	609.6 ± 161.8
	Hybrid model	54.8	193.5	418.6	718.2

Table 5 .

 5 Cartilage contact pressures at distal interphalangeal (DIP), proximal interphalangeal (PIP) and metacarpophalangeal (MCP) joints estimated by the hybrid model for each of the six subjects and for the average. External fingertip force produced by the hybrid model.

						Subject number
				1	2	3	4		7	9	Average
	Cartilage contact	pressure (MPa)	DIP joint PIP joint MCP	𝜎 max = 19.8 𝜎 mean = 4.8 𝜎 max = 22.8 𝜎 mean = 5.9 𝜎 max = 28.9	𝜎 max = 26.7 𝜎 mean = 6.2 𝜎 max = 27.4 𝜎 mean = 6.6 𝜎 max = 29.1	𝜎 max = 26.8 𝜎 mean = 5.7 𝜎 max = 31.9 𝜎 mean = 7.2 𝜎 max = 35.9	𝜎 max = 31.7 𝜎 mean = 7.1 𝜎 max = 24.2 𝜎 mean = 5.8 𝜎 max = 26.1	𝜎 max = 32.2 𝜎 mean = 7.3 𝜎 max = 42.2 𝜎 mean = 9.2 𝜎 max = 44.3	𝜎 max = 44.3 𝜎 mean = 12.2 𝜎 max = 42.6 𝜎 mean = 7.5 𝜎 max = 38.4	𝜎 max = 33.0 𝜎 mean = 6.6 𝜎 max = 33.3 𝜎 mean = 7.8 𝜎 max = 40.4
			joint	𝜎 mean = 6.8	𝜎 mean = 7.1	𝜎 mean = 8.9	𝜎 mean = 6.6	𝜎 mean = 10.0	𝜎 mean = 8.6	𝜎 mean = 9.5
	External fingertip	F exp = 42.5	F exp = 62.4	F exp = 65.2	F exp = 53.5	F exp = 78.4	F exp = 64.7	F exp = 66.2
		force (N)	F 𝑠𝑖𝑚 = 36.6	F 𝑠𝑖𝑚 = 45.7	F 𝑠𝑖𝑚 = 48.3	F 𝑠𝑖𝑚 =	39.7	F 𝑠𝑖𝑚 = 59.6	F 𝑠𝑖𝑚 = 47.6	F 𝑠𝑖𝑚 = 54.8

Acknowledgment

The authors wish to thank André Jacques for his assistance with the numerical simulations.

Conflict of Interest Statement

Supplementary Material A. Tendon forces for the index finger derived from the musculoskeletal model for each of the ten subjects (in N). In bold, the six subjects involved in the analysis.

Supplementary Material B. Sensitivity analysis

A sensitivity analysis was performed to investigate the effect of bone material properties and tendon force on the model prediction results. The bone was modelled with three different types of material properties:

rigid behaviour;

a single Young's modulus value for all the bone averaged between cortical and cancellous elasticity values;

distinct cortical and cancellous bone regions (Fig. 3(B))

Tendon force analysis included six cases of tendon force: 100%, 90%, 80%, 70%, 60% and 50% from the baseline values in Supplementary Material A to simulate submaximal grip force levels.

Representing the bone with either rigid behaviour or a single Young's modulus value for all the bone averaged between cortical and cancellous elasticity values led respectively to 11% and 3% higher mean contact pressure at the PIP joint than when distinct cortical and cancellous bone regions were used. All three representations of materials yielded the same values for fingertip force estimation and joint forces. Reducing tendon forces resulted in decreased joint contact pressure, fingertip force, and joint forces. In particular, fingertip force decreased linearly with tendon force (linear correlation of 0.47, R²=0.99) from 54.8 N at maximal tendon force to 25.8 N at halved tendon force. Mean contact pressure also decreased linearly with tendon force (linear correlation of 0.59), from 9.5 MPa, 7.8 MPa, 6.6 MPa at maximal tendon force to 5.5 MPa, 4.9 MPa, 4.2 MPa at halved tendon force for MCP, PIP and DIP joint, respectively.