REMODELING OF FEMORAL STEM(2).docx

7/30/2019 REMODELING OF FEMORAL STEM(2).docx

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REMODELING OF FEMORAL STEM


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BACKGROUND

FEMUR

The femur is the longest and strongest bone in the skeleton, is almost perfectly cylindrical in the greater

part of its extent. In the erect posture it is not vertical, being separated above from its fellow by aconsiderable interval, which corresponds to the breadth of the pelvis, but inclining gradually downward

and medialward, so as to approach its fellow toward its lower part, for the purpose of bringing the knee-

joint near the line of gravity of the body. The degree of this inclination varies in different persons, and is

greater in the female than in the male, on account of the greater breadth of the pelvis.

Fractures

A femoral fracture that involves the femoral head, femoral neckor the shaft of the femur immediately

below the lesser trochanter may be classified as a hip fracture, especially when associated with

osteoporosis.

FEMORAL STEM

The femoral stem component replaces a large portion of bone in the femur, and this is therefore the load-

bearing part of the implant. To bear this load, it must have a Youngs Modulus comparable to that of

cortical bone. If the implant is not as stiff as bone, then the remaining bone surrounding the implant will

be put under increased stress. If it is stiffer than bone, then a phenomenon known as stress shielding will

occur.

DESIGN OF FEMORAL STEM

Design of the femoral stem is an important issue in the field of total hip arthroplasty, but designis just one component in the success or failure of the operation. Other components are surgical

technique, cement technique or press-fit technique, bone quality, as well as patient related

factors.

The quality of design may not also be matched with quality of manufacturing and machining of

the stem. The ultimate outcome of the arthroplasty obviously depends also on a matchingacetabular component.

Currently the femoral stem revision rate at 10-15 years is reported to be between 0% and 4.8%

and does not correlate well with the radiographic stem loosening.

Femoral stem design options are related to whether the stem is curved or straight, the presence orabsence of collar support on the calcar, the stem cross section, the stem offset, the surface finish,

as well as the value of stem modularity and some metallurgical issues.

Stem Offset?
http://en.wikipedia.org/wiki/Femoral_fracturehttp://en.wikipedia.org/wiki/Femoral_headhttp://en.wikipedia.org/wiki/Femoral_neckhttp://en.wikipedia.org/wiki/Shaft_of_the_femurhttp://en.wikipedia.org/wiki/Hip_fracturehttp://en.wikipedia.org/wiki/Osteoporosishttp://en.wikipedia.org/wiki/Osteoporosishttp://en.wikipedia.org/wiki/Hip_fracturehttp://en.wikipedia.org/wiki/Shaft_of_the_femurhttp://en.wikipedia.org/wiki/Femoral_neckhttp://en.wikipedia.org/wiki/Femoral_headhttp://en.wikipedia.org/wiki/Femoral_fracture


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The offset is the transverse distance between the centre of the head and the vertical linerepresenting mid-stem or mid-femur (fig.9). Variability of offset helps to replicate the anatomy

by insuring proper soft tissue tension (fig.10) which balances the hip bearings. Although a high

offset stem relatively increases its bending moment (fig.11), various reports show that a highoffset does not increase cement strain on medial cement mantle.

(fig.9)

Stem offset is the distance between the head centre and vertical linerepresenting the mid-stem.


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(fig.10)

The offset of the stem helps to replicate normal soft tissue tension.

(fig.11)

High offset stem resulted in lateralising the femur by 4.69 mm, 8 years follow

up x-ray.

A preoperative plan using a template (fig.12) of different offset stems help the surgeon to see

which offset is likely to replicate the soft tissue anatomy.


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(fig.12)X-ray template help in measuring the right offset for each patient.

Surface Finish?

How smooth should be the surface of the stem! Is a feature of great variation as it comes in five

different ranges? Any surface will show peaks and valleys when examined by scanning electron

microscopy (fig.13), the average between Peak and Valley is known as the Roughness Average(Ra); according to Ra the surface finish (fig.14) of femoral stems may be classified as:

1. Highly polished2. Satin3. Matt

4. Rough5. Textured


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(fig.13)

Metal surface, as seen by SEM, showing peaks and valleys.

(fig.14)

Different stem finishing levels, polished (a), satin (b), Matt (c), rough (d), and

textured (e) and (f).

A polished surface will show less fixation strength to cement, to the contrary of rougher surfaces

which show greater fixation strength to cement.

Debonding is the loss of fixation between metal and cement. When debonding happens roughsurfaces behave badly, as it will abrade the adjacent cement and will cause microfractures in

cement mantle, ultimately leading to loss of fixation. This may lead also to the release into the

effective joint space of abrasive wear debris from cement and metal, which when ground insidethe bearings will act by 3

rdbody wear mechanism to release submicron poly wear particles

initiating the process of osteolysis.


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Surface Features?

These are any irregularities present on the stem surface apart from its finish discussed above, like

flanges, serrations, centralizers, pre-coated beads and knobsetc..

The only surface features that may be beneficial are flanges and centralizers.

Flanges are a part of the stem popularized in later Charnley design stems (fig.15) to help

pressurize the cement as the proximal stem part is pushed into the femur.

(fig.15)

The flanged design followed the roundback design in the Charnley stem series.

The stem centralizer (fig.16) is also beneficial as it prevents the stem from deviating in the canal,

insuring even cement mantle and perhaps preventing an unwanted varus position of the stem.

Non end-bearing centralizers may prevent cement fracture below the stem when subsidenceoccurs.


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(fig.16)

Stem centraliser insures a regular cement mantle and a centrally located stem.

Pre-coating with PMMA was a good idea assuming better cement bonding to the PMMA pre-

coat as compared to metal. This did not seem to work, as there were reports by Mohler, 1995 of

early femoral loosening in 2-10 years, other reported 15% stem failure rate over 6 years due topoor cement mantle and centralization.

Modularity?

Modularity helps intra-operative adjustment of components, most designs allow neck length

(fig.17) and head size modularity, and a select few allow modularity in anteversion and CCD

angle.


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(fig.17)

Modular neck length, the short, standard and long heads can vary the necklength, allowing adjustments during surgery.

The questions of increased wear and corrosion due to micromotion between the different piecesof the modular stem remain to be proven to assume a clinical disadvantage to these designs,

however; the clinical problems of impingement / dislocation (e.g. by using a skirted extra-long

head, or a very short head on a broad conical neck, fig.18) and of undue lengthening (fig.19) fall

under the technical control of the surgeon, who must be aware of design and limitations of thestem he is implanting.


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(fig.18)

Using a short head, with a combination of conical neck and an antiluxation

acetabular rim resulted in impingement during external rotation with slightabduction.

(fig.19)

Leg lengthening due to the use of extra-long head

The modular stem costs more than the monoblock sibling, and adds to the logistics of the

hospital creating more stock control overload on the administrator.

CHECK FROM DESIGN CRETERIA

Metallurgical Issues

The current concept in hip arthroplasty prefers Cobalt-Chrome or Stainless steel for thecemented stems and Titanium for the cementless. Other ideas are also available; but the majority

of surgeons world wide support this current concept.

The Scope of Stem Design


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This presentation stressed mainly on the standard cemented stem, but the scope of stem design is

much larger, the cementelss stem may share many of the above points of discussion apart from

those related to cement mantle and bonding. The surface of the cementless stem and its coatingmay warrant a separate article.

The recent evolution of special stems used in femoral reconstruction and revisions is also notcovered in this article, the author believe that these are better understood when discussed among

topics related to complex femoral reconstruction and revision arthroplasty

PURPOSE OF FEMORAL STEM REMODELING

A hip replacement with a femoral stem produces an effect on the bone called adaptive remodeling,

attributable to mechanical and biological factors. All of the prostheses designs try to achieve an optimal

load transfer in order to avoid stress-shielding, which produces an osteopenia.

INTRODUCTION

The implantation of a cemented or cementless femoral stem implies an important change in thephysiological load distribution. The bone reacts to the new situation, in accordance with Wolff 's law,

undergoing a process of adaptive remodelling [1], related to both mechanical and biological factors, being

the most important the initial bone mass [2].

Achieving good primary fixation is of crucial importance in cementless hip arthroplasty to ensure good

short-term and long-term results. Lack of primary stability leads to thigh pain and eventual loosening of

the prosthesis because of a continuous disruption of the bone formation process around the implant (Kim

et al., 2003; Knight et al., 1998;Mont and Hungerford, 1997; Petersilge et al., 1997). The stability, or the

lack of it, is commonly measured as the amount of relative motion at the interface between the bone and

the stem under physiological load. Large interfacial relative movements reduce the chance of

osseointegration, and cause the formation of a fibrous tissue layer at the boneimplant interface (Pilliar et

al.,1986), which may eventually lead to loosening and failure of the arthroplasty.

The threshold value of micromotion, above which a fibrous tissue layer forms, has been studied in both

animals and humans. In a review of dental implants in animals, a threshold micromotion value between

50 and 150 mm was found (Szmukler-Moncler et al., 1998). A similar range of values was reported for

orthopaedic implants in humans. In a retrieval study of cementless femoral components, Engh et al.

(1992) found indications that micromotions less than 40 mm had resulted in osseointegration while

micro-motions of 150 mm had caused the interposition of a fibrous tissue layer at the stembone

interface. It can be concluded from these reports that the value of micromotion, above which

osseointegration is disrupted, ranges from 50 to 150 mm, possibly skewed towards the lower end of this

range.

While many believe a sufficiently high interference fit is essential to achieve good primary stability, it is

also clear that introducing a interference fit has caused a clinically significant increase in intra-operative

femoral canal fractures (Cameron, 2004; Meek et al., 2004), an effect which has also been demonstrated

during in vitro testing (Jastiet al., 1993; Monti et al., 2001). The appropriate range of interference fit that

ensures primary stability without risking femoral fracture is not well understood.


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There are in principle two parts to this study. In order to get a rough idea of the interference fit introduced

using current surgical practise, in the first part of this study, finite element predictions were correlated

with in vitro micromotion measurements. The aim of this was to enable back calculation of the real

interference fit introduced by the surgeon during the in vitro experiment. In the second part

of the study, the effect of a range of interference fits on micromotion predictio ns was investigated using

finite element models of a more physiologically realistic loading scenario than was possible during thefirst part of the study.

METHODOLOGY

In the first part of the study, the finite element models were based on CT scans from the specific bones

used in the experiment. In the second part of the study, the CT scans from the visible human dataset were

used. Also in the first part of the study, the purpose was simply to compare finite element predictions and

experiments and to simplify the experiments, a simple load configuration was chosen. In the second part

of the study, physiological loads including muscle loads were used.

In vitro experimental set-up

The experiment was designed for direct comparison of micromotion values between experiment and FE

analyses. Four cadaver femurs and Alloclassic (Zimmer GmbH, Winterthur, Switzerland) hip stems were

used, and two points, one in the proximal part and another in the distal part of the stem (Fig. 1), were

chosen for micromotion measurement. In order to avoid damaging the stembone interface during drilling

action, the two points on the implant were drilled before implantation. A guide jig ensured that the bone,

subsequent to stem insertion, was drilled in the position matching these same two points on the stem.

Finally, steel pegs were glued into the holes in the stem and protruding through the bone (Fig. 1, right). A

linear variable differential transducer (LVDT Model DFg5, DC Miniature series, Solartron Metrology,

UK), was rigidly fixed to the outside of the femur (Fig. 1, right). The connecting rod of the LVDT core

rested on the free-end of the steel peg. When the implant was loaded, the implant and hence the pegmoved relative to the bone and the LVDT measured the axial movement of the peg relative to the

transducer, thus providing an estimate of the relative axial movement between bone and stem.

Implantation was carried out by an experienced orthopaedic surgeon (D.L.). The neck of the femur was

first resected, and the femur was then reamed with firm impaction using a series of reamers to open the

canal. A femoral stem was then implanted in the femur.


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Fig. 1. The jig used to position the holes in the bone and the pegs in the

implant, respectively (left). The implantbone specimen with LVDT

attached to the femur loaded in compression in the mechanical testing

machine (right).

The femur was sectioned 250mm distal to the lesser trochanter and its distal end fixed inside a cylindrical

metal container using polymethyl- methacrylate (PMMA). These were then placed onto the table bed of a

universal materials testing machine (Instron 5565, Instron Corp., Canton, MA). The specimen was

adjusted so that the long axis of the stem was coaxial to the direction of loading. A cyclical axialcompression load of 02 kN and triangular waveform was applied to the shoulder of the stem for 50

cycles at a rate of 1 kN/min using a 5 kN load cell. Micromotion readings via the LVDT were taken

manually at maximum load of 2 kN and when fully unloaded at each cycle.

Finite element methodology for correlation study

A 3D model of a hip stem (Alloclassic, Zimmer GmbH) was constructed from CAD files received from

the manufacturer (Fig. 2).


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Fig. 2. The hip stem used in the study indicating the FE mesh used (left)

and the implant inserted in the femur (right).

In the correlation part of the study, the finite element model needs to be as accurate a representation of theexperimental set-up as possible. Hence, the FE simulations of this part of the study were based on CT

scans of the specific bones used in the experiments. There were two sets of scans: one scan prior to

inserting the implant in the femur and a subsequent scan after implantation. The first set of scans was used

to derive bone geometry and material properties from the Houndsfield units of the scan, while the second

set of scans was used to ensure that the implant position and orientation in the FE model precisely

matched the implant position within the femur in the experiment. The reason for this two-step procedure

is that it would be inappropriate to use the CT datasets from the implanted femur for bone property

assignment due to artefacts in these datasets caused by the metal stem.

The construction of 3D models of the hip was done using AMIRA software (Mercury Computer Systems,

Inc., San Diego, CA). Segmentation was compiled automatically using the softwares marching cubes

algorithm which generates a 3D triangular surface mesh. The completed model was then converted to

solid linear tetrahedral elements using Marc.Mentat (MSC.Software, Santa Ana, CA) software. The mesh

was inspected to ensure it was reasonably shaped throughout. The Marc finite element software package

was used in this study.

Material properties for the bone were assigned based on the grey-scale value of the CT images on an

element-by-element basis. The grey-level of the CT images was related to the apparent density using a


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linear correlation (Cann and Genant, 1980; McBroom et al., 1985). This allowed for the transformation of

the spatial radiological description into the description of bone density. The modulus of elasticity of

individual elements was then calculated from the assigned apparent densities using the cubic relationship

proposed by Carter and Hayes (1977). The material properties were assumed to be linear elastic and

isotropic with Poissons ratio set to 0.35. The FE model was loaded at the centre of the shoulder of the

stem with 2 kN, the stem being coaxial to the direction of loading, hence, matching the loadingconfiguration in the experiment.

Mesh convergence is a standard issue in any finite element analysis and in a contact analysis, there are

many other numerical parameters that affect the predicted micromotions. The default contact strategy in

Marc is a direct constraint algorithm (MSC.Marc-Manual, 2004) which most importantly requires the

input of a contact zone size (CZS). Furthermore, Bernakiewicz and Viceconti (2002) described the

importance of the convergence tolerance (CTol) in non-linear analyses. They also suggested that the

appropriate parameter settings should be such that the resultant change in predicted micromotion between

models with different parameter settings should be small relative to 150 mm. A sequential sensitivity

analysis involving mesh density, CZS and CTol was carried out and a model with 12,078 nodes, CZS

0.025mm and CTol 1% was found to be sufficient for an accurate solution.

We also chose a Coulomb friction model which in Marc requires theinput of the friction coefficient (m) as

well as a parameter (SL). The Marc software has introduced the parameter SL, which describes a

smoothing of the step-function of the Coulomb model, only in order to deal with an otherwise

numerically difficult to handle discontinuity. However, not only does this parameter dramatically affect

the predicted micromotion (Fig. 3) it also has an important physical interpretation. Shirazi-Adl et al.

(1993) showed that the boneimplant interface friction curve is highly non-linear, exhibiting micromotion

on the order of 150 mm (that is in the order of the critical level for osseointegration) before the slip load

predicted by the Coulomb model is reached. The implication of Shirazi-Adl et al.s work is that adopting

the ideal Coulomb model is inadequate. However, the SL parameter can be interpreted and used to

represent this non-linear behaviour.


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Fig. 3. Contour plots of micromotion over the surface of the Alloclassic

stem under stairclimbing loads and for different values of the SL

parameter (SL describes the non-linear friction characteristics of the

interface).

To establish the appropriate setting of the SL parameter, we simulated Shirazi-Adl et al.s relatively

simple experiment consisting of a bone cube exposed to normal and tangential loads moving on a metal

plate. In Fig. 4 is shown Shirazi-Adls experimental curve of tangential load versus tangential

displacement. The tangential load that would initiate slip according to the Coulomb model is 30.6. The

finite element predicted curves for various settings of SL is also shown and a setting of SL 0.1 predicts

the experimental curve well. Hence, in the rest of this study, this setting was used.


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Fig. 4. Tangential load versus tangential displacement of bone cube

sliding on metal plate. The finite element predicted non-linear friction

behaviour for different levels of the parameter SL is shown as well as the

experimental curve reported by Shirazi-Adl et al. (1993). The critical value

at which sliding would initiate according to an ideal Coulomb friction

model is also indicated.

The effect of friction coefficient on micromotion is relatively minor for friction coefficients higher than

0.15 (Kuiper and Huiskes, 1996). Viceconti et al. (2000) found that a friction coefficient between 0.2 and

0.5 led to the best correlation with experiments. Rancourt et al. (1990) measured friction coefficients

experimentally and found a coefficient of0.4. Based on these previous studies, a friction coefficient of 0.4

was used in this study.

The objective of this study was to estimate the effective interference fit. Hence, we varied the interference

fit in the finite element models. The predictions were then compared to the experimentally measured

values to estimate which level of interference best matched the experiment.


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Finite element methodology for parametric study on the effect of interference fit

In this part of the study, geometry and material characterisation was based on the CT scans available from

the visible human project (VHP) dataset. The hip stem model was aligned inside the femur according to

the recommendations of the manufacturer (Alloclassic surgical technique, Zimmer Ltd., Warsaw, IN) and

an experienced surgeon (D.L.) inspected the resulting configurations and considered them appropriate.

The models were restrained distally and loaded with physiological stair-climbing loads including all

relevant muscle forces. Stair-climbing loads were applied as this loading scenario has been shown to be

more critical than other activities (Kassi et al., 2005). Similarly, Kassi et al. (2005) showed that it is

essential to include muscle loads although this issue has been debated (Cristofolini and Viceconti, 2006).

This load configuration was based on the extensive work by Bergmann (2001) and Heller et al. (2005) in

which load directions and muscle attachments are described. The magnitudes of the loads in percentage

body weight are shown in Table 1 and a body weight of 82 kg was used. All other aspects of the modelwere as described in Section 2.2.

RESULTS

In vitro micromotion measurements and correlation with model predictions

During the experiments, the stem initially subsided into the bone but after a sufficient number of cycles

the stem settled. Even in this relatively stable state, there continued to be low levels of reversible motion

at the stembone interface as a result of the continued loadunload cycle. It is high levels of this

continued disruption of the interface that is thought to prevent osteogenic cells from bonding to the

surface of the stem (Pilliar et al., 1986). Hence, in terms of evaluating the ingrowth potential of an

arthroplasty, it is the reversible micromotion rather than subsidence which is the relevant constituent of

the overall relative motion between bone and implant. The reversible micromotion during a load cycle

was estimated as the difference between the total micromotion measured at maximum load and the total

micromotion when the specimen was unloaded. For the remainder of this study, we will refer to this

quantity as reversible micromotion or just micromotion.


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In Fig. 5 is shown the experimentally determined reversible micromotion for each of the four specimens

plotted against load cycles for the distal and proximal parts, top and bottom, respectively. During the

initial cycles, this micromotion was high but then stabilised at a lower value. Relatively high levels of

micromotion during the first few times a patient exposes a joint to loading, are probably not critical. It is

the long term or stabilised value of reversible micromotion that will continue to disrupt the implantbone

interface and prevent osseointegration. Hence, it is the converged values of Fig. 5 which are relevant.Based on the data of Fig. 5, the converged average value in the distal and proximal regions were 1872 and

1975 mm, respectively.

Fig. 5. Distal micromotion (top) and proximal micromotion (bottom)

results from the experiment.


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The results of the FE analyses using different levels of interference fit and simulating the experiment are

shown in Fig. 6. The figure shows that with just 1 mm of interference, the level of micromotion is

predicted to be in the range of 2030 mm. With 2 mm of interference, this drops to 1020 mm.

Comparing this to the experimental values of 18 and 19 mm also shown in the figure, this implies that the

interference fit introduced by the surgeon is only 1 or 2 mm.

Fig. 6. Contour plots of micromotion over the surface of the stem under

an axial load of 2 kN, using interference fits of (from left to right) 0, 1, 2

and 5 mm, respectively. The experimentally determined proximal and distal

micromotion is also indicated.

This seems perhaps unrealistically low. Shultz et al. (2006) considered an interference fit of 100 mm to

cause bone interface damage and reported this level of interference as a threshold value. Therefore, we

included an interference fit of 100 mm in one of the finite element models and inspected the resulting

tensile hoop stresses (Fig. 7). This model was not exposed to any other loads. As can be seen from the

figure, interference induced hoop stresses are on the order of 50MPa on the surface of the bone (internally

the stresses are somewhat higher).Comparing this stress level with the transverse tensile strength of

cortical bone of approximately 50MPa (Reilly and Burstein, 1975), it would seem that 100 mm represents

the critical level of effective interference fit above which the femoral canal will fracture. The location ofhigh hoop stresses towards the distal end of the implant seen in Fig. 7 also matches the location of 77% of

intra-operative fractures (Meek et al., 2004).


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Fig. 7. Hoop stresses in femoral bone caused by an interference fit of

100 mm. No external loads are applied in this model.

Considering that femoral canal fractures are not infrequently occurring intra-operatively (Cameron, 2004;

Meek et al., 2004), it would seem that surgeons are introducing close to the critical level of interference fit

of 100 mm.

Assuming that surgeons are able to control the insertion process within a factor of 2, perhaps a realisticrange of interference fit can be argued to be in the range of 50100 mm. In summary, this first part of the

study indicates that the range of realistic interference fits may be within a range of very low levels (just a

few microns) and up to 100 mm.

The effect of interference fit on micromotion

Fig. 8 shows contour plots of predicted micromotion over the stem surface under stairclimbing loads and

for four different levels of interference fit. Fig. 9 shows the change in micromotion with levels of

interference fit for the two points labelled P (proximal) and D (distal) shown on the left model of Fig. 8.

Also in Fig. 9 is indicated, by the grey-coloured region, the threshold range of micromotion above which

soft tissue formation will be predicted and below which osseointegration would be expected. From thesetwo figures, it is clear that the interference fit had a very large effect on micromotion predictions. In the

case of no interference fit, the entire surface area of the implant was in or above the grey area indicating

that theprimary stability of the implant is at risk. In contrast, with 50 mm of interference, all but the mostproximal part of the implant was predicted to osseointegrate. Interestingly, increasing the level of

interference beyond 50 mm had negligible effect. Also, it is clear that the effect of the interference fit was

most dramatic at low levels of interference. Including just 5 mm of interference causes almost a 50%

reduction in micromotion and including more interference only has a relatively small effect.


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Fig. 8. Contour plots of micromotion over the surface of the stem under

stairclimbing loads and with interference fits of (from left to right) 0, 5, 25

and 50 mm, respectively.

Fig. 9. Micromotion at points P (proximal) and D (distal) as a function of

the level of interference fit. Locations of point P and D are shown in Fig. 8

(left). The grey area indicates the range of the critical micromotion

threshold. Above this level, fibrous tissue formation would be expected;

below, osseointegration is anticipated.


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CONCLUSION

This study has shown that modeling the interference fit characteristic of hip stems is crucial forquantitative predictions of micro-motion. Ignoring the interference fit will probably lead to an under

estimation of the stability of the stem. In contrast, ignoring the non-linear friction behavior reported byShirazi-Adl et al. (1993) and reproduced in Fig. 4, will probably to lead to too optimistic predictions ofstem stability. The magnitude of interference fit is fundamentally unknown and may be the reason mostprevious works have omitted this parameter from their finite element analyses. Indeed, during this study itbecame clear just how difficult it is to estimate this parameter. Nevertheless, this study demonstrates theimportance of the interference fit as including only a small level of interference changed the evaluation ofthe investigated stem from that of an unstable stem to that of a stable stem.

Our predictions showed high levels of micro-motion distally and proximally while micro-motion at the stemmidsection was lower (Fig. 8, left). This is qualitatively consistent with the finite element predictions byKeaveny and Bartel (1993). Keaveny and Bartel did not include an interference fit and predicted very highabsolute values of micromotion (0550 mm). Keaveny and Bartel simulated a cylindrical stem which islikely to be less resistant to torsional loads and that may explain the higher levels ofmicromotion as compared to our results. Viceconti et al. (2000) did simulate a press-fit although it is notpossible to quantify this press-fit in a manner that allows a direct correlation with our results. Vicecontietal. predicted micromotions ranging from 17 to 49 mm across the surface of the implant which isreasonably consistent with our results simulating an interference fit of 25 mm (Fig. 8).

The results ofFig. 6 indicate that surgeons introduce very low interference fits, on the order of 12 mm.Apart from any aspects of the model that may cause inaccurate predictions, it is of course also possiblethat the experimental results are inaccurate. Notably, our experiment, like the vast majority of otherexperimental micromotion studies, does not measure the actual interface micromotion but insteadmeasures the motion between the LVDT fixation point on the bone and the point of the peg insertion onthe implant. The motion measured, therefore, includes other flexibilities such as bone deformation and willtend to overestimate micromotion (Bu hler et al., 1997). If these flexibilities are substantial compared tothe true interface micromotion, it would cause our methodology to predict very small levels of interferencewhich is of course what seems to be the case.

In connection with Fig. 7, we proposed that surgeons are in fact more likely to introduce interference fitsof 50100 mm. Shultz et al. (2006) predicted that with an interference fit of 100 mm, the hoop stresses inthe bone would visco-elastically relax by approximately 50%. In other words, if a surgeon introduces aninterference fit of 100 mm, this would relax and represent an effective interference of 50 mm. Shultzreported that interference fits lower than 100 mm would relax less than 50%. Therefore, even if a surgeononly achieves the lower range of the50100 mm interference, we have estimated, there should be at least25 mm of effective interference left after relaxation, well above the 12 mm estimated from theexperiment. We have no evidence to explain the small levels of interference fit predicted from theexperiments but we are inclined to believe that the experiment overestimated the micromotion, for thereasons noted above.

We have assumed a uniform interference fit over the entire surface of the implant. Accordingly, the press-

fit (pressure) varied considerably from the proximal cancellous femur to the cortical distal femur asmodelled through the variation in the local Youngs modulus of the bone adjacent to the implant. Thisvariation in press-fit between the proximal and distal region is undoubtedly qualitatively correct. However,our study was not set up to investigate variation in interference fit. This was not included due to thepractical difficulty in quantifying the variation and generalising such variation that is likely to vary betweenimplants. It is also probable, given the very small interferences calculated, that surgeons cannot createimplant cavities with uniform interference across the interface area, so that clinical cases would includevariations from the micromotions predicted. The effects of a more realistic scenario are not yet known.


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The results of this study support the suggestion made earlier ( Shirazi-Adl et al., 1994) that the cavity thatis created in the femur is larger than is indicated by the nominal interference of 0.30.5mm (Otani et al.,1995;Ramamurti et al., 1997); such a large interference would cause the femur to fracture, according toour results.

Perhaps the most important result of the study and the result with direct clinical relevance relates to Figs.7 and 9. Fig. 7 predicts that surgery is safe against femoral canal fracture at interference fits lower than100 mm. Fig. 9 predicts that the stem would osseointegrate at interference levels of 50 mm. Therefore,the recommendation is for the surgeon to err on the side of a low interference fit during surgery as only 50mm is enough to achieve stability and provides a safety factor of 2 against femoral canal fracture. Ifconsidering a stem likely to be successful as long as just the distal part of the stem (embedded in thestrong cortical bone) osseointegrates, Fig. 9 indicates that just 10 mm of interference fit is necessary forstability and provides a safety factor of 10 against femoral canal fracture.

Of course, our computational predictions should be further investigated before being applied in clinicalpractise. It is likely, that stems with different geometry or material will behave differently. The Alloclassicstem in this study, for example, has a rectangular cross-section, which might be advantageous inresisting torsional loading during the stairclimbing simulated. Nevertheless, the predictions clearly indicatea recommendation to modify surgical practise thereby reducing or even eliminating the 7% intra-operativefemoral canal fractures during primary hip surgery reported by Cameron, (2004) and the 650% fracture

rates reported by Meek et al. (2004) in connection with revision hip surgery.

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REMODELING OF FEMORAL STEM(2).docx