Modelling Human Locomotion to Inform Exercise Prescription for Osteoporosis.

PURPOSE OF REVIEW: We review the literature on hip fracture mechanics and models of hip strain during exercise to postulate the exercise regimen for best promoting hip strength. RECENT FINDINGS: The superior neck is a common location for hip fracture and a relevant exercise target for osteoporosis. Current modelling studies showed that fast walking and stair ambulation, but not necessarily running, optimally load the femoral neck and therefore theoretically would mitigate the natural age-related bone decline, being easily integrated into routine daily activity. High intensity jumps and hopping have been shown to promote anabolic response by inducing high strain in the superior anterior neck. Multidirectional exercises may cause beneficial non-habitual strain patterns across the entire femoral neck. Resistance knee flexion and hip extension exercises can induce high strain in the superior neck when performed using maximal resistance loadings in the average population. Exercise can stimulate an anabolic response of the femoral neck either by causing higher than normal bone strain over the entire hip region or by causing bending of the neck and localized strain in the superior cortex. Digital technologies have enabled studying interdependences between anatomy, bone distribution, exercise, strain and metabolism and may soon enable personalized prescription of exercise for optimal hip strength.

Biomechanical Robustness of a Contemporary Cementless Stem to Surgical Variation in Stem Size and Position.

Successful designs of total hip replacement (THR) need to be robust to surgical variation in sizing and positioning of the femoral stem. This study presents an automated method for comprehensive evaluation of the potential impact of surgical variability in sizing and positioning on the primary stability of a contemporary cementless femoral stem (Corail®, DePuy Synthes). A patient-specific finite element (FE) model of a femur was generated from computed tomography (CT) images from a female donor. An automated algorithm was developed to span the plausible surgical envelope of implant positions constrained by the inner cortical boundary. The analysis was performed on four stem sizes: oversized, ideal (nominal) sized, and undersized by up to two stem sizes. For each size, Latin hypercube sampling was used to generate models for 100 unique alignment scenarios. For each scenario, peak hip contact and muscle forces published for stair climbing were scaled to the donor's body weight and applied to the model. The risk of implant loosening was assessed by comparing the bone-implant micromotion/strains to thresholds (150 µm and 7000 µÎµ) above which fibrous tissue is expected to prevail and the periprosthetic bone to yield, respectively. The risk of long-term loosening due to adverse bone resorption was assessed using bone adaptation theory. The range of implant positions generated effectively spanned the available intracortical space. The Corail stem was found stable and robust to changes in size and position, with the majority of the bone-implant interface undergoing micromotion and interfacial strains that are well below 150 µm and 7000 µÎµ, respectively. Nevertheless, the range of implant positions generated caused an increase of up to 50% in peak micromotion and up to 25% in interfacial strains, particularly for retroverted stems placed in a medial position.

A Computational Efficient Method to Assess the Sensitivity of Finite-Element Models: An Illustration With the Hemipelvis.

Assessing the sensitivity of a finite-element (FE) model to uncertainties in geometric parameters and material properties is a fundamental step in understanding the reliability of model predictions. However, the computational cost of individual simulations and the large number of required models limits comprehensive quantification of model sensitivity. To quickly assess the sensitivity of an FE model, we built linear and Kriging surrogate models of an FE model of the intact hemipelvis. The percentage of the total sum of squares (%TSS) was used to determine the most influential input parameters and their possible interactions on the median, 95th percentile and maximum equivalent strains. We assessed the surrogate models by comparing their predictions to those of a full factorial design of FE simulations. The Kriging surrogate model accurately predicted all output metrics based on a training set of 30 analyses (R2 = 0.99). There was good agreement between the Kriging surrogate model and the full factorial design in determining the most influential input parameters and interactions. For the median, 95th percentile and maximum equivalent strain, the bone geometry (60%, 52%, and 76%, respectively) was the most influential input parameter. The interactions between bone geometry and cancellous bone modulus (13%) and bone geometry and cortical bone thickness (7%) were also influential terms on the output metrics. This study demonstrates a method with a low time and computational cost to quantify the sensitivity of an FE model. It can be applied to FE models in computational orthopaedic biomechanics in order to understand the reliability of predictions.

Time-elapsed microstructural imaging of failure of the reverse shoulder implant.

BACKGROUND: Reverse Shoulder Arthroplasties (RSA) have become a primary choice for improving shoulder function and pain. However, the biomechanical failure mechanism of the humeral component is still unclear. The present study reports a novel protocol for microstructural imaging of the entire humerus implant under load before and after fracture. METHODS: A humerus specimen was obtained from a 75-year-old male donor. An expert surgeon implanted the specimen with a commonly used RSA implant (Aequalis reversed II, Stryker Orthopaedics, USA) and surgical procedure. The physiological glenohumeral contact force that maximized the distal implant migration was selected from a public repository ( orthoload.com ). Imaging and concomitant mechanical testing were performed using a large-volume micro-CT scanner (Nikon XT H 225 ST) and a custom-made compressive stage. Both when intact and once implanted, the specimen was tested under a pre-load and by imposing a constant deformation causing a physiological reaction load (650 N, 10 degrees adducted). The deformation of the implanted specimen was then increased up to fracture, which was identified by a sudden drop of the reaction force, and the specimen was then re-scanned. RESULTS: The specimen's stiffness decreased from 874 N/mm to 464 N/mm after implantation, producing movements of the bone-implant interface consistent with the implant's long-term stability reported in the literature. The micro-CT images displayed fracture of the tuberosity, caused by a combined compression and circumferential tension, induced by the distal migration of the implant. CONCLUSION: The developed protocol offers detailed information on implant mechanics under load relative to intact conditions and fracture, providing insights into the failure mechanics of RSA implants. This protocol can be used to inform future implant design and surgical technique improvements.

Cortical bone adaptation response is region specific, but not peak load dependent: insights from µ CT image analysis and mechanostat simulations of the mouse tibia loading model.

The two major aims of the present study were: (i) quantify localised cortical bone adaptation at the surface level using contralateral endpoint imaging data and image analysis techniques, and (ii) investigate whether cortical bone adaptation responses are universal or region specific and dependent on the respective peak load. For this purpose, we re-analyse previously published µ CT data of the mouse tibia loading model that investigated bone adaptation in response to sciatic neurectomy and various peak load magnitudes (F = 0, 2, 4, 6, 8, 10, 12 N). A beam theory-based approach was developed to simulate cortical bone adaptation in different sections of the tibia, using longitudinal strains as the adaptive stimuli. We developed four mechanostat models: universal, surface-based, strain directional-based, and combined surface and strain direction-based. Rates of bone adaptation in these mechanostat models were computed using an optimisation procedure (131,606 total simulations), performed on a single load case (F = 10 N). Subsequently, the models were validated against the remaining six peak loads. Our findings indicate that local bone adaptation responses are quasi-linear and bone region specific. The mechanostat model which accounted for differences in endosteal and periosteal regions and strain directions (i.e. tensile versus compressive) produced the lowest root mean squared error between simulated and experimental data for all loads, with a combined prediction accuracy of 76.6, 55.0 and 80.7% for periosteal, endosteal, and cortical thickness measurements (in the midshaft of the tibia). The largest root mean squared errors were observed in the transitional loads, i.e. F = 2 to 6 N, where inter-animal variability was highest. Finally, while endpoint imaging studies provide great insights into organ level bone adaptation responses, the between animal and loaded versus control limb variability make simulations of local surface-based adaptation responses challenging.

Cortical thickness adaptation to combined mechanical loading and parathyroid hormone treatments is site specific and synergistic in the mouse tibia model.

In this study, we aimed to quantify the localised effects of mechanical loading (ML), low (20 µg/kg/day), moderate (40 µg/kg/day) or high (80 µg/kg/day) dosages of parathyroid hormone (PTH), and combined (PTHML) treatments on cortical bone adaptation in healthy 19-week old female C57BL/6 mice. To this end, we utilise a previously reported image analysis algorithm on µCT data of the mouse tibia published by Sugiyama et al. (2008) to measure changes in cortical area, marrow cavity area and local cortical thickness measures (ΔCt.Ar, ΔMa.Ar, ΔCt.Th respectively), evaluated at two cross-sections within the mouse tibia (proximal-middle (37 %) and middle (50 %)), and are compared to a superposed summation (P + M) of individual treatments to determine the effectiveness of combining treatments in vivo. ΔCt.Ar analysis revealed a non-linear, synergistic interactions between PTH and ML in the 37 % cross-section that saturates at higher PTH dosages, whereas the 50 % cross-section experiences an approximately linear, additive adaptation response. This coincided with an increase in ΔMa.Ar (indicating resorption of the endosteal surface), which was only counteracted by combined high dose PTH with ML in the middle cross-section. Regional analysis of ΔCt.Th changes reveal localised cortical thinning in response to low dose PTH treatment in the posteromedial region of the middle cross-section, signifying that PTH does not provide a homogeneous adaptation response around the cortical perimeter. We observe a synergistic response in the proximal-middle cross-section, with regions of compressive strain experiencing the greatest adaptation response to PTHML treatments, (peak ΔCt.Th of 189.32, 213.78 and 239.30 µm for low, moderate and high PTHML groups respectively). In contrast, PTHML treatments in the middle cross-section show a similar response to the superposed P + M group, with the exception of the combined high dose PTHML treatment which shows a synergistic interaction. These analyses suggest that, in mice, adding mechanical loading to PTH treatments leads to region specific bone responses; synergism of PTHML is only achieved in some regions experiencing high loading, while other regions respond additively to this combined treatment.

Imaging of the Microstructural Failure Mechanism in the Human Hip.

Imaging the bone microstructure under progressively increasing loads allows for observing the microstructural failure behavior of bone. Here, we describe a protocol for obtaining a sequence of three-dimensional microstructural images of the entire proximal femur under progressively increasing deformation, causing clinically relevant fractures of the femoral neck. The protocol is demonstrated using four femora from female donors aged 66-80 years at the lower end of bone mineral density in the population (T-score range = -2.09 to -4.75). A radio-transparent compressive stage was designed for loading the specimens replicating a one-leg stance, while recording the applied load during micro-computed tomography (micro-CT) imaging. The field of view was 146 mm wide and 132 mm high, and the isotropic pixel size was 0.03 mm. The force increment was based on finite-element predictions of the fracture load. The compressive stage was used to apply the displacement to the specimen and enact the prescribed force increments. Sub-capital fractures due to opening and shear of the femoral neck occurred after four to five load increments. The micro-CT images and the reaction force measurements were processed to study the bone strain and energy absorption capacity. Instability of the cortex appeared at the early loading steps. The subchondral bone in the femoral head displayed large deformations reaching 16% before fracture, and a progressive increase in the support capacity up to fracture. The deformation energy linearly increased with the displacement up to fracture, while the stiffness decreased to near-zero values immediately before fracture. Three-fourths of the fracture energy was taken by the specimen during the final 25% force increment. In conclusion, the protocol developed revealed a remarkable energy absorption capacity, or damage tolerance, and a synergic interaction between the cortical and trabecular bone at an advanced donor age.

Geometry and bone mineral density determinants of femoral neck strength changes following exercise.

Physical exercise induces spatially heterogeneous adaptation in bone. However, it remains unclear where the changes in BMD and geometry have the greatest impact on femoral neck strength. The aim of this study was to determine the principal BMD-and-geometry changes induced by exercise that have the greatest effect on femoral neck strength. Pre- and post-exercise 3D-DXA images of the proximal femur were collected of male participants from the LIFTMOR-M exercise intervention trial. Meshes with element-by-element correspondence were generated by morphing a template mesh to each bone to calculate changes in BMD and geometry. Finite element (FE) models predicted femoral neck strength changes under single-leg stance and sideways fall load. Partial least squares regression (PLSR) models were developed with BMD-only, geometry-only, and BMD-and-geometry changes to determine the principal modes that explained the greatest variation in neck strength changes. The PLSR models explained over 90% of the strength variation with 3 PLS components using BMD-only (R2 > 0.92, RMSE < 0.06 N) and 8 PLS components with geometry-only (R2 > 0.93, RMSE < 0.06 N). Changes in the superior neck and distal cortex were most important during single-leg stance while the superior neck, medial head, and lateral trochanter were most important during a sideways fall. Local changes in femoral neck and head geometry could differentiate the exercise groups from the control group. Exercise interventions may target BMD changes in the superior neck, inferior neck, and greater trochanter for improved femoral neck strength in single-leg stance and sideways fall.

Latarjet's muscular alterations increase glenohumeral joint stability: A theoretical study.

The surgical Latarjet procedure aims to stabilise the glenohumeral joint following anterior dislocations. Despite restoring joint stability, the procedure introduces alterations of muscle paths which likely modify the shoulder dynamics. Currently, these altered muscular functions and their implications are unclear. Hence, this work aims to predict changes in muscle lever arms, muscle and joint forces following a Latarjet procedure by using a computational approach. Planar shoulder movements of ten participants were experimentally assessed. A validated upper-limb musculoskeletal model was utilised in two configurations, i.e., a baseline model, simulating normal joint, and a Latarjet model simulating its related muscular alterations. Muscle lever arms and differences in muscle and joint forces between models were derived from the experimental marker data and static optimisation technique. Lever arms of most altered muscles, hence their role, were substantially changed after Latarjet. Altered muscle forces varied by up to 15% of the body weight. Total glenohumeral joint force increased by up to 14% of the body weight after Latarjet, mostly due to increase in compression force. Our simulation indicated that the Latarjet muscular alterations lead to changes in the muscular recruitment and contribute to the stability of the glenohumeral joint by increasing compression force during planar motions.

Determining the relationship between tibiofemoral geometry and passive motion with partial least squares regression.

Tibiofemoral geometry influences knee passive motion and understanding their relationship can provide insight into knee function and mechanisms of injury. However, the complexity of the geometric constraints has made characterizing the relationship challenging. The aim of this study was to determine the tibiofemoral bone geometries that explain the variation in passive motion using a partial least squares regression (PLSR) model. The PLSR model was developed for 29 healthy cadaver specimens (10 female, 19 male) with femur and tibia geometries retrieved from MRI images and six degree-of-freedom tibiofemoral kinematics determined during a flexion cycle with minimal medial pressure. The first 13 partial least squares (PLS) components explained 90% of the variation in the kinematics and accounted for 89% of the variation in geometry. The first three PLS components which shared geometric changes to particular surface congruencies of the tibial and femoral condyles explained the most amount of variation in the kinematics, primarily in anterior-posterior translation. Meanwhile, variations in femoral condyle width and the intercondylar space, tibia plateau size and conformity, and tibia eminences heights in PLS 2 and 4 explained the greatest amount of variation in internal-external rotation. PLS 4 exhibiting variation in overall size of the knee accounted for greatest amount of variation in geometry (50%) and had the greatest influence on the abduction-adduction motion and some on internal-external rotation but, overall, explained only a small proportion of the kinematics (10%). Elucidating the complex relationship between tibiofemoral bone geometry and passive kinematics may help personalize treatments for improved functional outcomes in patients.

Muscle discretization affects the loading transferred to bones in lower-limb musculoskeletal models.

Modelling the mechanical effect of muscles is important in several research and clinical contexts. However, few studies have investigated the effect of different muscle discretizations from a mechanical standpoint. The present study evaluated the errors of a reduced discretization of the lower-limb muscles in reproducing the muscle loading transferred to bones. Skeletal geometries and a muscle data collection were derived from clinical images and dissection studies of two cadaver specimens. The guidelines of a general method previously proposed for a different anatomical district were followed. The data collection was used to calculate the mechanical effect of muscles, i.e. the generalized force vectors, and the errors between a large and a reduced discretization, in a reference skeletal pose and in the extreme poses of the range of motion of joints. The results showed that the errors committed using a reduced representation of muscles could be significant and higher than those reported for a different anatomical region. In particular, the calculated errors were found to be dependent on the individual anatomy and on the skeletal pose. Since different biomechanical applications may require different discretization levels, care is suggested in identifying the number of muscle lines of action to be used in musculoskeletal models.

The effect of age and initial compression on the force relaxation response of the femur in elderly women.

The effect of force amount, age, body weight and bone mineral density (BMD) on the femur's force relaxation response was analysed for 12 donors (age: 56-91 years). BMD and fracture load, F L, were estimated from clinical CT images. The 30 min force relaxation was obtained using a constant compression generating an initial force F 0 between 7% and 78% of F L. The stretched decay function (F(t) = A × e (-t/τ)ß ) proposed earlier for bone tissue was fitted to the data and analysed using robust linear regression. The relaxation function fitted well to all the recordings (R 2 = 0.99). The relative initial force was bilinearly associated (R 2 = 0.83) to the shape factor, ß, and the characteristic time, τ, when F 0/F L was less than 0.4, although ß was no longer associated with F 0/F L by pooling all the data. The characteristic time τ increased with age (R 2 = 0.37, p = 0.03) explaining 35% of the variation of τ in the entire dataset. In conclusion, the relative initial force mostly determines the femur's force relaxation response, although the early relaxation response under subcritical loading is variable, possibly due to damage occurring at subcritical loading levels.

Statistical Quantification of the Effects of Marker Misplacement and Soft-Tissue Artifact on Shoulder Kinematics and Kinetics.

The assessment of shoulder kinematics and kinetics are commonly undertaken biomechanically and clinically by using rigid-body models and experimental skin-marker trajectories. However, the accuracy of these trajectories is plagued by inherent skin-based marker errors due to marker misplacements (offset) and soft-tissue artifacts (STA). This paper aimed to assess the individual contribution of each of these errors to kinematic and kinetic shoulder outcomes computed using a shoulder rigid-body model. Baseline experimental data of three shoulder planar motions in a young healthy adult were collected. The baseline marker trajectories were then perturbed by simulating typically observed population-based offset and/or STA using a probabilistic Monte-Carlo approach. The perturbed trajectories were then used together with a shoulder rigid-body model to compute shoulder angles and moments and study their accuracy and variability against baseline. Each type of error was studied individually, as well as in combination. On average, shoulder kinematics varied by 3%, 6% and 7% due to offset, STA or combined errors, respectively. Shoulder kinetics varied by 11%, 27% and 28% due to offset, STA or combined errors, respectively. In conclusion, to reduce shoulder kinematic and kinetic errors, one should prioritise reducing STA as they have the largest error contribution compared to marker misplacements.

The effects of anatomical errors on shoulder kinematics computed using multi-body models.

Joint motion calculated using multi-body models and inverse kinematics presents many advantages over direct marker-based calculations. However, the sensitivity of the computed kinematics is known to be partly caused by the model and could also be influenced by the participants' anthropometry and sex. This study aimed to compare kinematics computed from an anatomical shoulder model based on medical images against a scaled-generic model and quantify the effects of anatomical errors and participants' anthropometry on the calculated joint angles. Twelve participants have had planar shoulder movements experimentally captured in a motion lab, and their shoulder anatomy imaged using an MRI scanner. A shoulder multi-body dynamics model was developed for each participant, using both an image-based approach and a scaled-generic approach. Inverse kinematics have been performed using the two different modelling procedures and the three different experimental motions. Results have been compared using Bland-Altman analysis of agreement and further analysed using multi-linear regressions. Kinematics computed via an anatomical and a scaled-generic shoulder models differed in average from 3.2 to 5.4 degrees depending on the task. The MRI-based model presented smaller limits of agreement to direct kinematics than the scaled-generic model. Finally, the regression model predictors, including anatomical errors, sex, and BMI of the participant, explained from 41 to 80% of the kinematic variability between model types with respect to the task. This study highlighted the consequences of modelling precision, quantified the effects of anatomical errors on the shoulder kinematics, and showed that participants' anthropometry and sex could indirectly affect kinematic outcomes.

EMG-Informed Neuromusculoskeletal Models Accurately Predict Knee Loading Measured Using Instrumented Implants.

OBJECTIVE: Using a musculoskeletal modelling framework, we aimed to (1) estimate knee joint loading using static optimization (SO); (2) explore different calibration functions in electromyogram (EMG)-informed models used in estimating knee load; and (3) determine, when using an EMG-informed stochastic method, if the measured joint loadings are solutions to the muscle redundancy problem when investigating only the uncertainty in muscle forces. METHODS: Musculoskeletal models for three individuals with instrumented knee replacements were generated. Muscle forces were calculated using SO, EMG-informed, and EMG-informed stochastic methods. Measured knee joint loads from the prostheses were compared to the SO and EMG-informed solutions. Root mean square error (RMSE) in joint load estimation was calculated, and the muscle force ranges were compared. RESULTS: The RMSE ranged between 192-674 N, 152-487 N, and 7-108 N for the SO, the calibrated EMG-informed solution, and the best fit stochastic result, respectively. The stochastic method produced solution spaces encompassing the measured joint loading up to 98% of stance. CONCLUSION: Uncertainty in muscle forces can account for total knee loading and it is recommended that, where possible, EMG measurements should be included to estimate knee joint loading. SIGNIFICANCE: This work shows that the inclusion of EMG-informed modelling allows for better estimation of knee joint loading when compared to SO.

Ex vivo assessment of surgically repaired tibial plateau fracture displacement under axial load using large-volume micro-CT.

Postoperative weight bearing has the potential to generate fragmental motion of surgically repaired tibial plateau fractures (TPFs), which may contribute to loss of fracture reduction. The effect of loading on the internal distribution of fragmentary displacements is currently unknown. The aim of this study was to determine the internal displacements of surgically repaired split TPFs due to a three-bodyweight load, using large-volume micro-CT imaging and image correlation. Fractures were generated and surgically repaired for two cadaveric specimens. Load was applied to the specimens inside a large-volume micro-CT system and scanned at 0.046 mm isotropic voxel size. Pre- and post-loading images were paired, co-registered, and internal fragmentary displacements quantified. Internal fragmental displacements of the cadaveric bones were compared to in vivo displacements measured in the lateral split fragments of TPFs in a clinical cohort of patients who had similar surgical repair and were prescribed pain tolerated postoperative weight bearing. The split fragments of cadaveric specimens displaced, on average, less than 0.3 mm, consistent with in vivo measurements. Specimen one rotated around the mediolateral axis, while specimen two displaced consistently caudally. Specimen two also had varying displacements along the mediolateral axis where, at the fracture site, the fragment displaced caudally and laterally, while the most lateral edge of the tibial plateau displaced caudally and medially. The methods applied in this study can be used to measure internal fragmental motion within TPFs.

Real-time replication of three-dimensional and time-varying physiological loading cycles for bone and implant testing: A novel protocol demonstrated for the proximal human femur while walking.

In vitro real-time replication of three-dimensional, time-varying load profiles acting on human bones during physical activity can advance bone and implant testing protocols. This study aimed to develop a novel protocol for applying the three-dimensional, time-varying hip contact force while walking to a human femur specimen. The target force profile was obtained from the literature. A proximal femur from an elderly female donor was instrumented using ten rosette strain gages and tested using a custom-made hexapod robot. A load-control algorithm determined the robot position generating the target force at low frequency (0.0004 Hz). Five cycles of the robot position were played back at five intermediate frequencies up to real-time (0.04, 0.08, 0.16, 0.4, and 0.8 Hz). The hip reaction force, the length of the actuators (position), and cortical strains were compared. The error in the load-control force was 0.3 ± 4.2 N (mean ± SD). The last three force, position, and strain cycles varied by less than 1.1% for every frequency analyzed. Across frequencies, the force increased by 28% at 0.8 Hz as a logarithmic function of frequency (R2 = 0.98). The position and strain error linearly increased with frequency up to 0.4 Hz. The median position error and the interquartile range of the strain error reached 15% and 13% at 0.8 Hz. Changes of force and cortical strain at increasing frequencies were linearly related (R2 = 0.99). Therefore, the protocol developed can provide repeatable three-dimensional time-varying load profiles, although the comparison of the specimen deformation obtained across frequencies should be considered with care, particularly in the higher frequency range. This information supports the design of dynamic tests of bone and implants.

Body Anthropometry and Bone Strength Conjointly Determine the Risk of Hip Fracture in a Sideways Fall.

We hypothesize that variations of body anthropometry, conjointly with the bone strength, determine the risk of hip fracture. To test the hypothesis, we compared, in a simulated sideways fall, the hip impact energy to the energy needed to fracture the femur. Ten femurs from elderly donors were tested using a novel drop-tower protocol for replicating the hip fracture dynamics during a fall on the side. The impact energy was varied for each femur according to the donor's body weight, height and soft-tissue thickness, by adjusting the drop height and mass. The fracture pattern, force, energy, strain in the superior femoral neck, bone morphology and microarchitecture were evaluated. Fracture patterns were consistent with clinically relevant hip fractures, and the superior neck strains and timings were comparable with the literature. The hip impact energy (11 - 95 J) and the fracture energy (11 - 39 J) ranges overlapped and showed comparable variance (CV = 69 and 61%, respectively). The aBMD-based definition of osteoporosis correctly classified 7 (70%) fracture/non-fracture cases. The incorrectly classified cases presented large impact energy variations, morphology variations and large subcortical voids as seen in microcomputed tomography. In conclusion, the risk of osteoporotic hip fracture in a sideways fall depends on both body anthropometry and bone strength.

Damage tolerance and toughness of elderly human femora.

Observations of elastic instability of trabecular bone cores supported the analysis of cortical thickness for predicting bone fragility of the hip in people over 60 years of age. Here, we falsified the hypothesis that elastic instability causes minimal energy fracture by analyzing, with a micrometric resolution, the deformation and fracture behavior of entire femora. Femur specimens were obtained from elderly women aged between 66 - 80 years. Microstructural images of the proximal femur were obtained under 3 - 5 progressively increased loading steps and after fracture. Bone displacements, strain, load bearing and energy absorption capacity were analyzed. Elastic instability of the cortex appeared at early loading stages in regions of peak compression. No elastic instability of trabecular bone was observed. The subchondral bone displayed local crushing in compression at early loading steps and progressed to 8 - 16% compression before fracture. The energy absorption capacity was proportional to the displacement. Stiffness decreased to near-zero values before fracture. Three-fourth of the fracture energy (10.2 - 20.2 J) was dissipated in the final 25% force increment. Fracture occurred in regions of peak tension and shear, adjacent to the location of peak compression, appearing immediately before fracture. Minimal permanent deformation was visible along the fracture surface. Elastic instability modulates the interaction between cortical and trabecular bone promoting an elastically stable fracture behavior of the femur organ, load bearing capacity, toughness, and damage tolerance. These findings will advance current methods for predicting hip fragility.

Cortical Thickness Adaptive Response to Mechanical Loading Depends on Periosteal Position and Varies Linearly With Loading Magnitude.

The aim of the current study was to quantify the local effect of mechanical loading on cortical bone formation response at the periosteal surface using previously obtained µCT data from a mouse tibia mechanical loading study. A novel image analysis algorithm was developed to quantify local cortical thickness changes (ΔCt.Th) along the periosteal surface due to different peak loads (0N ≤ F ≤ 12N) applied to right-neurectomised mature female C57BL/6 mice. Furthermore, beam analysis was performed to analyse the local strain distribution including regions of tensile, compressive, and low strain magnitudes. Student's paired t-test showed that ΔCt.Th in the proximal (25%), proximal/middle (37%), and middle (50%) cross-sections (along the z-axis of tibia) is strongly associated with the peak applied loads. These changes are significant in a majority of periosteal positions, in particular those experiencing high compressive or tensile strains. No association between F and ΔCt.Th was found in regions around the neutral axis. For the most distal cross-section (75%), the association of loading magnitude and ΔCt.Th was not as pronounced as the more proximal cross-sections. Also, bone formation responses along the periosteum did not occur in regions of highest compressive and tensile strains predicted by beam theory. This could be due to complex experimental loading conditions which were not explicitly accounted for in the mechanical analysis. Our results show that the bone formation response depends on the load magnitude and the periosteal position. Bone resorption due to the neurectomy of the loaded tibia occurs throughout the entire cross-sectional region for all investigated cortical sections 25, 37, 50, and 75%. For peak applied loads higher than 4 N, compressive and tensile regions show bone formation; however, regions around the neutral axis show constant resorption. The 50% cross-section showed the most regular ΔCt.Th response with increased loading when compared to 25 and 37% cross-sections. Relative thickness gains of approximately 70, 60, and 55% were observed for F = 12 N in the 25, 37, and 50% cross-sections. ΔCt.Th at selected points of the periosteum follow a linear response with increased peak load; no lazy zone was observed at these positions.