Computer Methods in Biomechanics and Biomedical Engineering, 2015 Vol. 18, No. 12, 1349–1357, http://dx.doi.org/10.1080/10255842.2014.903931
Influence of ingrowth regions on bone remodelling around a cementless hip resurfacing femoral implant Ifaz T. Haidera1, Andrew D. Speirsa2, Paul E. Beaule´b3 and Hanspeter Freia* a
Department of Mechanical and Aerospace Engineering, Carleton University, 3135 Mackenzie Bldg, 1125 Colonel By Dr, Ottawa, ON, Canada K1S 5B6; bDivision of Orthopaedic Surgery, University of Ottawa, The Ottawa Hospital, 501 Smyth Road, CCW 1646, Ottawa, ON, Canada K1H 8L6 (Received 20 August 2012; accepted 10 March 2014) Hip resurfacing arthroplasty is an alternative to traditional hip replacement that can conserve proximal bone stock and has gained popularity but bone resorption may limit implant survival and remains a clinical concern. The goal of this study was to analyze bone remodelling patterns around an uncemented resurfacing implant and the influence of ingrowth regions on resorption. A computed tomography-derived finite element model of a proximal femur with a virtually implanted resurfacing component was simulated under peak walking loads. Bone ingrowth was simulated by six interface conditions: fully bonded; fully friction; bonded cap with friction stem; a small bonded region at the stem-cup intersection with the remaining surface friction; fully frictional, except for a bonded band along the distal end of the cap and superior half of the cap bonded with the rest frictional. Interface condition had a large influence on remodelling patterns. Bone resorption was minimized when no ingrowth occurred at the bone-implant interface. Bonding only the superior half of the cap increased bone resorption slightly but allowed for a large ingrowth region to improve secondary stability. Keywords: hip resurfacing arthroplasty; bone remodelling; finite element analysis; interface conditions
Introduction Hip resurfacing arthroplasty (HRA) is a conservative alternative to conventional total hip replacement (THR). This procedure involves removal of the diseased layer of cartilage and minimal bone tissue on both the femoral head and the acetabulum and replacing these surfaces with a ball-and-socket implant (Amstutz and Le Duff 2008; Heisel et al. 2009). The conservation of bone stock with HRA has led some surgeons to prefer HRA as an alternative to THR, especially in younger, more active patients (Buergi and Walter 2007; Spencer 2011). The indications for HRA have been refined and usually include osteoarthritis but exclude patients with nonosteoarthritic hip degeneration such as dysplasia (Dorey et al. 2004; Spencer 2011). In addition, head size is a strong predictor of implant survival, with every 1-mm increase in size associated with a 5 –8% reduction in risk of revision, suggesting that smaller patients and especially women are not good candidates for HRA (Smith et al. 2012). Clinical results show good short- to medium-term follow-up (Buergi and Walter 2007; Amstutz and Le Duff 2008; Quesada et al. 2008; Smolders et al. 2010; Baker et al. 2011). Advantages of HRA include an increase in range of motion, lower dislocation rates, increased levels of patient activity, more normal gait patterns, and ease of revision (Quesada et al. 2008; Baker et al. 2011; Spencer 2011). However, there are still clinical concerns associated
*Corresponding author. Email: [email protected]
q 2014 Taylor & Francis
with HRA implants, and short-term femoral neck fracture is a common mode of failure (Amstutz et al. 2004; Matharu et al. 2013). Early simulation studies have shown that HRA implants can cause stress shielding (Huiskes et al. 1985), which may trigger bone remodelling. This is supported by bone mineral density studies which have noted continuing changes at nine years post-operatively (Baker et al. 2011) and clinical and computer simulation studies which have shown bone loss associated with stress shielding (Gupta et al. 2006; Dabirrahmani et al. 2010; Dickinson, Taylor, and Browne 2010). Furthermore, computer simulation studies have noted severe bone loss in the region enclosed by the femoral component (Dickinson, Taylor, Jeffers, et al. 2010) which may predispose to implant loosening. In addition, femoral neck narrowing, which is poorly understood, remains a concern for the long-term performance of HRA and may lead to neck fracture (McMinn et al. 1996; Beaule´ et al. 2004; Hing et al. 2007; Spencer et al. 2008; Steffen et al. 2008). Traditionally, the femoral component in HRA is implanted using bone cement, which helps load transfer between implant and bone. However, the thickness of the cement layer varies considerably between different femoral resurfacing components as well as cementing techniques making it difficult to reproduce (Beaule´ et al. 2009). In addition, excessive cement penetration can result
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in a high interface temperature (Saha and Pal 1984) which may cause thermal necrosis in the bone tissue (Jones and Hungerford 1987; Beaule´ et al. 2007). This has been associated with early failures of the femoral component of HRA through loosening or femoral neck fracture (McMinn et al. 1996; Beaule´ et al. 2004; Campbell et al. 2006; Hing et al. 2007; Spencer et al. 2008; Steffen et al. 2008). Furthermore, the cement layer prevents bone ingrowth on the implant surface, preventing long term integration with the host bone. Use of a cementless femoral component has been proposed recently as an alternative and have shown good short-term results (Ho et al. 2010; Gross and Liu 2011), and although clinical experience with conventional THR has shown that uncemented femoral stem designs provide better long term results than their cemented counterparts (Berend et al. 2006; Martı´nez de Arago´n and Keisu 2007), long-term results with cementless femoral components with HRA are still lacking. One of the major concerns with hip resurfacing is femoral neck narrowing which may be reduced when a cementless femoral component is used (Ho et al. 2010). In vivo studies of HRA in canines have shown that the bone remodelling process can be strongly influenced by the geometry of the implant –bone interface (Hedly et al. 1982), a fact supported by FE simulations by Rothstock et al. (2011). Previous FE studies have also shown that the remodelling process can also be influenced by contact conditions at this interface. Implant models that prohibit bone ingrowth (frictional contact) are predicted to cause less bone resorption than those that allow ingrowth (fixed contact) (Ong et al. 2006; Gupta et al. 2010). While a fully frictional interface is sufficient for primary stability (Pal and Gupta 2011), it is not well understood whether the implant would be able to maintain secondary stability once bone resorption begins to take place. Thus, the goal of this investigation was to use an adaptive finite element model to identify a contact interface scheme that reduced bone resorption, while still allowing osteointegration.
Methods A three-dimensional finite element model of a proximal human femur was generated from quantitative computed tomography (CT) scans of a fresh frozen cadaveric specimen. The specimen was obtained from the University of Ottawa’s division of clinical and functional anatomy, after approval from their research ethics board. Inclusion of a CT calibration phantom (Mindways Software, Austin, TX, USA) with the specimen allowed estimation of bone density from the image intensity values. Scans were performed with a 0.5-mm slice thickness and 0.49 mm (0.49 mm in-plane resolution. The femur was segmented from the CT scan (OsiriX Imaging Software, osirixviewer.com) and converted to a parametric solid model
(Pro/ENGINEER v5.0, Parametric Technology Corporation, Needham, MA, USA). A solid model of a 50-mm diameter femoral resurfacing implant (ReCap, Biomet, Inc., Warsaw, IN, USA) was virtually implanted according to the surgical guidelines into the intact femur with an idealized congruent interface surface between the implant and the bone (Biomet Orthopedics Inc. 2010). Both the intact and resurfaced femoral models were meshed in PATRAN (v2008r2, MSC Software, Newport Beach, CA, USA) using 220,000 and 190,000 quadratic tetrahedral elements (2.5 mm mean element length), respectively. To limit partial volume effects, the mesh was finest at the surface, with an average element length of 1.5 mm. The mesh for the bone region of the intact and resurfaced models was identical except for the region removed to accommodate the resurfacing implant, which was modelled using 39,407 quadratic tetrahedral elements. Convergence was assessed by refining the mesh; increasing the number of elements by a factor of 8 resulted in a very small (, 8%) change in peak strain energy density. Thus, the mesh was considered sufficient. All finite element analyses were performed in Abaqus (v6.8-2, Dassault Syste`mes, Paris, France), with geometric nonlinearity enabled and using C3D10M elements which have a modified formulation to improve contact stresses. These robust elements perform well for models with and without contact and are recommended by the ABAQUS user manual for most stress/strain problems with a tetrahedral mesh. Because they have an accurate contact formulation, no special elements were required at the bone –implant interface. Bone was modelled as an isotropic, linearly elastic material. Properties were assigned element-by-element by sampling the CT intensity of each element volume using Amira (v5.2, Visage Imaging, Richmond, Australia). CT intensity was related to apparent density by developing a linear regression equation using measured CT intensities in the phantom compared to known density values provided by the manufacturer’s certificate. The elastic modulus, E, of each element was then calculated from the density value as E ¼ 7281r 1.52 (Gupta et al. 2006) and assigned to the element at the start of the analysis, resulting in a maximum element elastic modulus of 13.3 GPa, before remodelling. Poisson’s ratio was 0.3 (Gupta et al. 2004; Sharma et al. 2009). The Co –Cr implant was assigned a uniform elastic modulus of 220 GPa (Ethier and Simmons 2007) and Poisson’s ratio of 0.31. The intact femur model, with element-specific elastic modulus, was validated in simple static compression against the actual cadaveric femoral specimen used to generate the model. The intact femur was loaded quasistatically with 2000 N on a servo-hydraulic load frame (858 Mini Bionix II, MTS Systems Corp. Eden Prairie, MN, USA). Surface strains were measured using rosette strain gauges (Tokyo Sokki Kenkyujo Co., Ltd., BC,
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Figure 1. Experimental setup for model verification. The distal end of the shaft was fixed and a load of 2 kN was applied to the head. Strain gauge 1 was located on the femoral neck, below the head, while strain gauges 2 and 3 were located along the femoral shaft. Please note that the right half of the image has been magnified in order to show the locations of the strain gauge.
Canada) at three locations, shown in Figure 1, and compared to the strains predicted by the finite element model under the same load and boundary conditions, i.e. fixed at the distal end and loaded over 11 nodes on the femoral head. The mechanical test was repeated twice and differences between experimental and finite element models were less than 300 microstrain (0.7 – 11%) for both tests, except in one location of high local bone density
where differences of 450 microstrain (17%) were measured, as shown in Figure 2. Bone remodelling was simulated using changes in strain energy density from a reference state (Weinans et al. 1993). For each element in the model, the remodelling signal, S, in the implanted model was compared with a reference signal Sref from the corresponding element of the intact model. A lazy zone, x, is defined about Sref, within which no remodelling occurs and bone density changes depend on the deviation of the remodelling signal from the lazy zone and a proportionality constant, C (Equation (1)). The value of C affects how quickly the simulation reaches steady state, i.e. bone remodelling ceases. However, it has little influence on the final density distributions (Gupta et al. 2010). For very large values of C, however, the prescribed density change Dr may oscillate between positive and negative values without reaching the lazy zone. The remodelling signal used in the current study was the ratio of strain energy density, U, to local bone density (S ¼ U/r). 8 C½S 2 ð1 þ xÞSref ; for S $ ð1 þ xÞref ; > > < Dr ¼ C ½S 2 ð1 2 xÞSref ; for S $ ð1 2 xÞref ; > > : 0; otherwise:
Equation (1) was implemented as a Fortran subroutine within ABAQUS. Values of C ¼ 50 £ 1026 and x ¼ 0.75 were assigned to all elements in the model; this provided a good compromise between solution convergence time and accuracy. In addition, upper and lower limits of 0.01 g/cc
Figure 2. Model validation. Minimum and maximum principal strains measured at three strain gauge locations, compared to those predicted by the finite element model.
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and 2.0 g/cc were placed on bone densities for calculating the elastic modulus. The lower limit was a practical requirement to prevent element collapse during the analysis. Bone density was allowed to change at each material point within the bone region at the end of each analysis step. Both the intact and resurfaced models were subjected to the same boundary conditions (Figure 3). The static hip contact force was applied to the femoral head, over 12 nodes corresponding to an area of approximately 130 mm2, with components of 225% body-weight (BW), 54% BW and 30% BW in the inferior, lateral and posterior directions, respectively, corresponding to the peak hip force during normal walking (Bergmann et al. 2001); a body weight of 80 kg was assumed. The simulations were relatively insensitive to contact area; doubling the area of the applied load resulted in less than 5% change in final bone density in the regions of interest (Figure 5). Muscle loads were neglected, as previous studies show that they have relatively small (, 1%) influence on strains in a proximal femur subject to walking loads (Speirs et al. 2007). The femur was rigidly constrained at the midshaft location (Figure 3) to place the constraints sufficiently away from regions of significant remodelling. Six separate analysis cases were examined using the resurfaced femur model, differing only in the contact properties and regions of contact between the implant and
Figure 3. Femur model loading and boundary conditions. The boundary conditions from the intact femur model (left) are transferred directly to the resurfaced model (right). The resurfaced model experiences the same load magnitude as the intact model. In both models, the load is shared evenly over 12 nodes and directed through the head-centre.
reamed femur regions. Tangential contact interactions were either fixed (displacement and rotation compatible) representing a region of bone ingrowth in which no relative motion between adjacent surfaces occurred or there was friction with a coefficient of 0.4 to simulate a fit with no bone ingrowth (Gebert et al. 2009). The six analysis cases are outlined in Figure 4. The first two cases represented simple scenarios where the implant is entirely fixed or entirely frictional contact. These cases represent a long-term stable implant, including ingrowth on the stem and the immediate post-operative situation, respectively. In the third case, the implant cap was fixed but the stem was modelled using friction contact; this case represents the ingrowth pattern that is expected to occur in vivo as current implant designs have a porous cup to allow for bone ingrowth with a smooth stem. The next three are all hypothetical cases designed to limit bone resorption. In the fourth, a small bonded region at the stem–cup intersection was fixed while the remainder of the cap was modelled with friction and the distal half of the stem was ignored. The fifth case had the distal rim of the cap fixed, with the rest of the interface modelled with friction. The sixth, and final, case fixed the superolateral half only, with the rest of the interface modelled with friction. For all cases, normal contact was modelled as ‘hard contact’, which minimizes surface penetration and does not allow for the transfer of tensile stresses. The analysis routine was run until no further remodelling occurred. The average density at the end of the remodelling simulation was calculated as the volume-averaged element density in zones within the femur (Figure 5). The zones are analogous to Gruen zones used in THR (Gruen et al. 1979), adapted to HRA (Ha¨kkinen et al. 2011), with the addition of zones enclosed by the implant cap as well as a zone distal to the stem. The average bone density in each region was compared across model cases to examine the influence of implant fixation on bone remodelling patterns.
Results Remodelling simulations showed differences in final bone density distributions depending on the interface conditions (Figures 6 and 7). All cases showed bone density increases in regions surrounding the distal half of the stem (zones 1– 6, and 9), and most cases showed significant decreases in bone density within the proximal femoral head (zone 8). The most severe bone loss was seen in the fully fixed case (I), which lost 40% bone density in the region under the proximal half of the cap (zone 8). For this contact case, small density increases (, 12%) were found in all regions surrounding the distal implant stem (zones 1– 6, and 9). Bone density also increased locally around the distal tip of the stem (Figure 6). This is indicative of stress shielding, which causes load from the femoral head to be transferred preferentially through the stiff implant. The best results
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Figure 4. Six implant interface cases. Case I involves fixing the entire inner surface of the femoral cap as well as the stem. Case II models all inner surfaces as friction interfaces. Case III is a hybrid model where the inner surface of the cap is tied, but the stem is modelled with friction. Cases IV– VI are all hypothetical, selectively fixed models. In case IV, the proximal half of the stem and inner section of the cap are fixed while the remainder of the cap surface is modelled with friction, and contact in the distal region of the stem is neglected. Case V has the distal rim of the cap fixed, with the remainder of the implant modelled with friction. Case VI fixed the superior half of the cap only, with the rest of the surfaces modelled with friction.
Zones used for analysis of bone density changes.
were seen in the fully frictional interface case (II), which showed bone density increases in all zones. However, some bone loss was still observed at the superior tip of the femoral head, where the stem of the implant meets the cap (Figure 6).
In most cases, modification of the ingrowth pattern did not yield significantly improved results, compared to the fully fixed case. Cases III– V all showed significant bone loss in the femoral head, though the magnitude of loss was somewhat attenuated compared to case I. Of the modified
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Figure 6. Final bone density distribution for each implant case relative to the normal density field in the intact model. Regions in black are an artifact of Abaqus’ extrapolation algorithm for displaying field variables in the output database. These regions have a density of 0.01 (min. allowable). No integration points can be assigned density values below 0.01. All density values are recorded in g/cc. Most cases showed significant bone loss in the proximal head region contained within the implant cap. Case II, where there is only frictional contact between implant and bone, was the only case which did not exhibit significant bone loss. Of the models that allowed bone ingrowth, resorption was lowest in case VI.
Figure 7. Bone density changes, relative to the intact femur, in all zones due to varying interface conditions. See Figure 3 and text for the definition of the zones.
ingrowth patterns investigated, the best results were seen in case VI, where the superolateral half of the implant was fixed and the rest was frictional. In this case, bone loss in region 8 was limited to 8%, and bone density increases (, 18%) were seen in all other zones.
Discussion This study has demonstrated bone remodelling patterns around the femoral component of a cementless HRA. Patterns of bone density changes depended on the region of implant fixation. Fixation over the entire contact
Computer Methods in Biomechanics and Biomedical Engineering interface resulted in extensive stress shielding and significant bone loss in the femoral head as load transfer bypassed these regions. In the friction-only case (II), representative of the primary stability phase, bone loss occurred only in the most proximal region of the head (Figure 6) but stress shielding was less extensive. However, this analysis case did not consider gradual bone ingrowth that would affect the interface. Preventing bone ingrowth on the stem (case III) did not prevent significant bone resorption within the head. There was also no benefit to limiting ingrowth to only the distal rim of the cap (case V) compared to allowing ingrowth throughout the entire cap (case III). In contrast, limiting ingrowth to the superolateral half of the cap (case VI) lowered bone resorption compared to all but the fully frictional case (II), while maintaining a large ingrowth region for secondary stability. This study is a simulation of a complex process that controls bone remodelling. Bone remodelling was predicted using strain energy density relative to an element-specific target value (Weinans et al. 1993). However, differing approaches are also suggested in the literature. For example, some remodelling algorithms use microdamage as a remodelling stimulus (Doblare´ and Garcı´a 2002; McNamara and Prendergast 2007). Also, the mechanostat theory (Frost 2003) suggests that remodelling is driven by a single target stimulus for the whole bone, rather than an element-specific one. As the underlying mechanisms for bone remodelling remain unknown, it is difficult to determine how to best predict bone remodelling. However, the remodelling algorithm used in this study was selected because it previously demonstrated clinically relevant changes around traditional femoral stem components (Kerner et al. 1999; Bitsakos et al. 2005). Use of a CT-derived model allowed accurate reproduction of the geometry and density distribution and showed good agreement with in vitro-measured strains of the same bone. It should be noted that the contact model was not validated experimentally due to difficulties in matching implant alignment of the model to that of an experiment. However, contact simulations were neithersensitive to further mesh refinement nor to the choice of contact algorithm (, 5% difference between models). The internal stress distribution should therefore be a good approximation of the in vivo situation for the load case considered, i.e. normal walking. Also, while this study was limited to this one load case, other load cases have been investigated in the literature (Pal and Gupta 2011). Another difficulty in predicting bone remodelling using FEM is that the magnitude of the remodelling threshold or ‘lazy zone’ is not well known. Previous studies have used values between 0.75 and 0.35 (Huiskes et al. 1992; Rothstock et al. 2011). While the size of the lazy zone has a large effect on the magnitude of bone resorption predicted, it has little influence on resorption
patterns (Huiskes et al. 1992). Therefore, conclusions regarding the relative effects of different contact conditions are valid, despite the uncertainty in this value. The bone remodelling process is driven by the deformation of implanted bone relative to its unimplanted state. Changes to the geometry of the implant interface may alter the deformation and thus the remodelling pattern. In particular, some implants make use of a chamfered bone – implant interface, as opposed to the spherical interface of the implant used in this study. Rothstock et al. (2011) found that there were differences between spherical verses conical interfaces for cemented implants, with a spherical interface resulting in higher final bone densities than a standard conical implant. However, the effect of implant shape for an uncemented implant, under different ingrowth patterns, requires further investigation. Other variables may also affect bone remodelling in patients. Bone geometry, initial density, implant position, activity level, diet and genetic factors may all influence the final bone remodelling pattern. In order to investigate the influence of varying contact conditions alone, we chose to hold all other model parameters constant. The most extensive remodelling occurred in the trabecular bone within the proximal head (zones 7 and 8). In all cases, the bone adjacent to the proximal end of the implant, where the stem meets the cap, was reduced to the minimum density value within the remodelling simulation. The resorption of bone in this region may be an unavoidable consequence of cementless resurfacing. The upper surface of the implant cap shields the bone tissue directly below regardless of interface condition (Dickinson, Taylor, Jeffers, et al. 2010; Pal et al. 2010). Tying the implant surface to the bone (cases I and III) resulted in extensive stress shielding of the trabecular bone in the femoral head. In contrast to the intact situation, load was transferred through the stiff implant to the femoral cortex via the distal implant rim resulting in bone resorption. When the interface surface interaction was changed to friction, resorption was less severe. Friction contact permitted small sliding displacements between the implant and the bone surface, thus allowing for some deformation of the bone material adjacent to the implant. This allowed the remodelling routine to return the model to a stimulus state similar to that of the intact femur. Because the tied cap interface in cases I and III caused complete resorption of bone in the proximal head to the minimum threshold, elements in this region could not return to the normal stimulus. The patterns of bone loss found in this study were similar to clinical results which measured bone density increased in the femoral neck (Smolders et al. 2010; Ha¨kkinen et al. 2011). Previous simulation studies of bone remodelling predict extensive bone loss within the femoral head (Dickinson, Taylor, Jeffers, et al. 2010; Gupta et al.
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2010; Pal and Gupta 2011; Rothstock et al. 2011), in agreement with our results. Also, contact cases I– III were previously investigated by Ong et al. (2006), who found that the remodelling stimulus predicts large bone loss in the femoral head for a fully fixed interface (case I), an intermediate degree of bone loss when the cap alone is fixed (case III) and the least bone loss when the contact surfaces are fully frictional. Unfortunately, the study did not simulate bone remodelling, making more quantitative comparisons difficult, but their results are consistent with this study. Also, a shorter stem (Dickinson, Taylor, Jeffers, et al. 2010) or no stem (Pal et al. 2010) was shown to reduce the stress shielding effect on bone remodelling, which agrees with the results of Case IV. Interestingly, most simulation studies predict extensive bone loss in the region enclosed by the implant which is obscured in radiographic studies and therefore cannot be analyzed in clinical follow-up. Bone density reductions of up to 80% have been reported in this region of cemented HRA (Gupta et al. 2006; Dickinson, Taylor, Jeffers, et al. 2010; Pal et al. 2010), compared to 40% in the most proximal zone in the current study if the implant was fully bonded. These results suggest that insidious bone resorption within the implant may lead to implant loosening and therefore limit the long term performance of HRA. This study did however find that such resorption could be reduced by preventing bone ingrowth in all regions of the implant, as per Case II. However, further investigation is required to determine whether this would result in an inadequate secondary stability leading to failure of the implant. Bone remodelling patterns around a cementless femoral resurfacing component depend on the extent of the ingrowth region. A fully frictional implant which prevents osteointegration (Case II) is predicted to minimize bone resorption, but it is not known whether such an implant would have sufficient secondary stability. Surface treatments of the implant could be designed to control where ingrowth occurs in order to minimize bone resorption while still allowing for bone ingrowth. HRA shows promise, and use of uncemented designs may limit complications associated with cement. While proximal bone resorption remains a concern, this study has shown that modification of the ingrowth pattern can result in a significant attenuation in bone loss, while also maintaining large regions for bone ingrowth (case VI). Further optimization of the ingrowth pattern may be possible and is a topic for future work.
Acknowledgements This study was partially funded by the Natural Sciences and Engineering Research Council of Canada [grant number 342890]. The authors thank T. Elgin for technical assistance in preparing the finite element models.
Conflict of interest statement: Paul E Beaule´ is a consultant with CORIN, MEDACTA, and Smith-Nephew. The other authors have no conflict of interest related to this study.
Notes 1. 2. 3.
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