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Background: Corrective shoe insoles are prescribed for a range of foot deformities and are typically designed based on a subjective assessment limiting personalization and potentially leading to sub optimal treatment outcomes. The incorporation of in silico techniques in the design and customization of insoles may improve personalized correction and hence insole efficiency.Methods: We developed an in silico workflow for insole design and customization using a combination of measured motion capture, inverse musculoskeletal modelling as well as forward simulation approaches to predict the kinematic response to specific insole designs. The developed workflow was tested on twenty-seven participants containing a combination of healthy participants (7) and patients with flatfoot deformity (20).Results: Average error between measured and simulated kinematics were 4.7 ± 3.1, 4.5 ± 3.1, 2.3 ± 2.3, and 2.3 ± 2.7° for the chopart obliquity, chopart anterior-posterior axis, tarsometatarsal first ray, and tarsometatarsal fifth ray joints respectively.Discussion: The developed workflow offers distinct advantages to previous modeling workflows such as speed of use, use of more accessible data, use of only open-source software, and is highly automated. It provides a solid basis for future work on improving predictive accuracy by adapting the currently implemented insole model and incorporating additional data such as plantar pressure.

ABSTRACT: Segmental defects affecting the continuity of the mandible have a profound impact on a patient's quality of life. Adequate reconstruction of such continuity defects is essential to restore aesthetics and function. While reconstruction using an autologous bone transplant supported by a stock reconstruction plate is the gold standard treatment, it has various drawbacks that can be attested to the plates’ off-the-shelf nature.To mitigate these drawbacks, this study develops a patient-specific implant for the reconstruction of Brown class II defects with a high ramal osteotomy. The implant is intended to be additively manufactured in Ti6Al4V grade 23 ELI and features porous scaffold zones at the symphyseal and condylar sides which can induce bone ingrowth.Finite element (FE) analyses were used to assess the implants’ performance in terms of failure, stability and stress shielding by simulating four clenching tasks. In addition, the implant was topologically optimized and re-evaluated.The results showed that the implant experienced stress below its yield strength and fatigue limit. Relative micromotions between the implant and the bone indicated adequate stability to allow bone ingrowth to occur. Strains in the bone indicated limited stress shielding should occur between screw connections and around the osteotomy planes.Finally, topological optimization reduced implant volume by 49% compared to the initial design, while FE analyses showed similar performance to the original design. The resulting implant is a promising first prototype that is numerically evaluated and can be optimized further in terms of fixation, surgical approach and dental restoration by in situ testing.

Traumatic Brain Injury (TBI) in the elderly population leads to more severe consequences than in young patients. However, the impact that TBI has on elderly patients’ Quality of Life (QoL) has not been thoroughly investigated and is still unclear. Therefore, the main objective of this study is to qualitatively investigate changes in QoL after mild TBI in elderly patients.A focus group interview was conducted with 6 mild TBI patients, with a median age of 74 years old, admitted to the University Hospitals Leuven (UZ Leuven) between 2016 and 2022. The data analysis was performed following the guide provided by Dierckx de Casterlé et al. in 2012, using Nvivo software.Three themes emerged from the analysis: functional disturbances and symptoms, daily life after TBI, and life quality, feelings and satisfaction. The most reported factors that deteriorated QoL 1–5 years post-TBI in our cohort were the lack of support from partners and families, changes in self-perception and social life, tiredness, balance disturbances, headache, cognitive deterioration, changes in physical health, senses’ disturbances, changes in sexual life, sleep problems, speech disturbances and dependence for daily life activities. No symptoms of depression or feelings of shame were reported. The acceptance of the situation and hope for improvement were shown to be the most important coping mechanisms for these patients.In conclusion, mild TBI in elderly patients frequently leads to changes in self-perception, daily life activities and social life 1–5 years after the injury, which could contribute to a loss of independence and QoL deterioration. The acceptance of the situation and a good support network seem to be protective factors for these patients’ well-being after TBI.

Total knee arthroplasty (TKA) failures are often attributed to unbalanced knee ligament loading. The current study aims to develop a probabilistic planning process to optimize implant component positioning that achieves a ligament-balanced TKA. This planning process accounts for both subject-specific uncertainty, in terms of ligament material properties and attachment sites, and surgical precision related to the TKA process typically used in clinical practice. The consequent uncertainty in the implant position parameters is quantified by means of a surrogate model in combination with a Monte Carlo simulation. The samples for the Monte Carlo simulation are generated through Bayesian parameter estimation on the native knee model in such a way that each sample is physiologically relevant. In this way, a subject-specific uncertainty is accounted for. A sensitivity analysis, using the delta-moment-independent sensitivity measure, is performed to identify the most critical ligament parameters. The designed process is capable of estimating the precision with which the targeted ligament-balanced TKA can be realized and converting this into a success probability. This study shows that without additional subject-specific information (e.g., knee kinematic measurements), a global success probability of only 12% is estimated. Furthermore, accurate measurement of reference strains and attachment sites critically improves the success probability of the pre-operative planning process. To allow more precise planning, more accurate identification of these ligament properties is required. This study underlines the relevance of investigating in vivo or intraoperative measurement techniques to minimize uncertainty in ligament-balanced pre-operative planning results, particularly prioritizing the measurement of ligament reference strains and attachment sites.

Transcatheter mitral valve replacement (TMVR) has emerged as a minimally invasive alternative for treating patients suffering from mitral valve disease. The number of TMVR procedures is expected to rise as devices currently in clinical trials obtain approval for commercialization. Automating the planning of such interventions becomes, therefore, more relevant in an attempt to decrease inter-subject discrepancies and time spent in patient assessment. This study evaluates the performance of an automated method for detection of anatomical landmarks and generation of relevant measurements for device selection and positioning. Cardiac CT scans of 70 patients were collected retrospectively. Fifty scans were used to generate a statistical shape model (SSM) of the left heart chambers at ten different timepoints, whereas the remaining 20 scans were used for validation of the automated method. The clinical measurements resulting from the anatomical landmarks generated automatically were compared against the measurements obtained through the manual indication of the corresponding landmarks by three observers, during systole and diastole. The automatically generated measurements were in close agreement with the user-driven analysis, with intraclass correlation coefficients (ICC) consistently lower for the saddle-shaped (ICCArea = 0.90, ICCPerimeter 2D = 0.95, ICCPerimeter 3D = 0.93, ICCAP-Diameter = 0.71, ICCML-Diameter = 0.90) compared to the D-shaped annulus (ICCArea = 0.94, ICCPerimeter 2D = 0.96, ICCPerimeter 3D = 0.96, ICCAP-Diameter = 0.95, ICCML-Diameter = 0.92). The larger differences observed for the saddle shape suggest that the main discrepancies occur in the aorto-mitral curtain. This is supported by the fact that statistically significant differences are observed between the two annulus configurations for area (p < 0.001), 3D perimeter (p = 0.009) and AP diameter (p < 0.001), whereas errors for 2D perimeter and ML diameter remained almost constant. The mitral valve center deviated in average 2.5 mm from the user-driven position, a value comparable to the inter-observer variability. The present study suggests that accurate mitral valve assessment can be achieved with a fully automated method, what could result in more consistent and shorter pre-interventional planning of TMVR procedures.

Objective: The level of primary implant fixation in cementless total hip arthroplasty is a key factor for the longevity of the implant. Vibration-based methods show promise for providing quantitative information to help surgeons monitor implant fixation intraoperatively. A thorough understanding of what is driving these changes in vibrational behavior is important for further development and improvement of these methods. Additionally, an instrument must be designed to enable surgeons to leverage these methods. This study addresses both of these issues. Method: An augmented system approach was used to develop an instrument that improves the sensitivity of the vibrational method and enables the implementation of the necessary excitation and measurement equipment. The augmented system approach took into account the dynamics of the existing bone-implant system and its interaction with the added instrument. Results: Two instrument designs are proposed, accompanied by a convergence-based method to determine the insertion endpoint. The modal strain energy density distribution was shown to affect the vibrational sensitivity to contact changes in certain areas. Conclusion: The augmented system approach led to an instrument design that improved the sensitivity to changes in the proximal region of the combined bone-implant-instrument system. This fact was confirmed both in silico and in vitro. Clinical Impact: The presented method and instruments address practical intraoperative challenges and provide perspective to objectively support the surgeon’s decision-making process, which will ensure optimal patient treatment.

Secondary mitral regurgitation occurs when a left ventricular problem causes leaking of the mitral valve. The altered left ventricular geometry changes the orientation of the subvalvular apparatus, thereby affecting the mechanical stress on the mitral valve. This in turn leads to active remodeling of the mitral valve, in order to compensate for the ventricular remodeling. In this study, a biomechanical analysis was performed on eight human mitral valves with secondary mitral regurgitation and ten healthy human mitral valves to better understand this pathophysiology and its effect on the mechanical properties of these tissues. Samples were obtained from the anterior and posterior leaflet and used for planar biaxial mechanical experiments. Uniaxial experiments were performed on four groups of mitral valve chords: anterior basal, anterior marginal, posterior basal and posterior marginal chords. The mechanical response of the mitral valve leaflets was fitted to the May-Newman and Yin constitutive model, whereas the material parameters of the third order Ogden model were determined for the chord samples. Next, stiffnesses calculated at low and high stress levels were statistically analyzed. Leaflet samples with secondary mitral regurgitation showed a small thickness increase and a change in anisotropy index compared to healthy control valves. Diseased leaflets were more compliant circumferentially and stiffer radially, resulting in anisotropic samples with the radial direction being stiffest. In addition, chord samples were slightly thicker and less stiff at high stress in secondary mitral regurgitation, when grouped per leaflet type and insertion region. These results confirm mechanical alterations due to the pathophysiological valvular changes caused by left ventricular remodeling. It is important that these changes in mechanical behavior are incorporated into computational models of the mitral valve.

This study aims to evaluate the mechanical performance of a unique, state-of-the-art, patient-specific alloplastic total replacement system for the temporomandibular joint that allows for enthesis reconstruction developed by CADskills BV (Ghent, Belgium), and its influence on the remaining adjacent healthy tissue, by looking into the magnitude and location of the stresses and micromotions. Because the reattachment of the lateral pterygoid muscle is unique, having never before been used in temporomandibular joint prostheses, the loading patterns and performance may be completely different from existing devices and their analyses. Therefore, multiple finite element models were created to compare existing devices, prosthetic models of the CADskills device, and healthy situations. These were used to investigate the influence of such patient-specific prostheses through the evaluation of micromotion, loading on the opposite joint, strain on the healthy bone and condyle, and stress shielding.The results showed that the temporomandibular joint prostheses were subject to stress considerably below their yield strength, except for the polyethylene of the fossa component, which might undergo abrasion under extreme muscular loads (larger than loads occurring during the activities of daily living). Additionally, the implant was shown to have little influence on stresses in the bone compared to a healthy model. Furthermore, the dynamic model shows how the load upon and stresses in the healthy joint increase when maximum muscle activation takes place with the mouth open.

Preoperative determination of implant size for total knee arthroplasty surgery has numerous clinical and logistical benefits. Currently, surgeons use X-ray-based templating to estimate implant size, but this method has low accuracy. Our study aims to improve accuracy by developing a machine learning approach that predicts the required implant size based on a 3D femoral bone mesh, the key factor in determining the correct implant size. A linear regression framework imposing group sparsity on the 3D bone mesh vertex coordinates was proposed based on a dataset of 446 MRI scans. The group sparse regression method was further regularized based on the connectivity of the bone mesh to enforce neighbouring vertices to have similar importance to the model. Our hypergraph regularized group lasso had an accuracy of 70.1% in predicting femoral implant size while the initial implant size prediction provided by the instrumentation manufacturer to the surgeon has an accuracy of 23.1%. Furthermore, our method was capable of predicting the implant size up to one size smaller or larger with an accuracy of 99.1%, thereby surpassing other state-of-the-art methods. The hypergraph regularized group lasso was able to obtain a significantly higher accuracy compared to the implant size prediction provided by the instrumentation manufacturer.

Controlled cortical impact (CCI) on porcine brain is often utilized to investigate the pathophysiology and functional outcome of focal traumatic brain injury (TBI), such as cerebral contusion (CC). Using a finite element (FE) model of the porcine brain, the localized brain strain and strain rate resulting from CCI can be computed and compared to the experimentally assessed cortical lesion. This way, tissue-level injury metrics and corresponding thresholds specific for CC can be established. However, the variability and uncertainty associated with the CCI experimental parameters contribute to the uncertainty of the provoked cortical lesion and, in turn, of the predicted injury metrics. Uncertainty quantification via probabilistic methods (Monte Carlo simulation, MCS) requires a large number of FE simulations, which results in a time-consuming process. Following the recent success of machine learning (ML) in TBI biomechanical modeling, we developed an artificial neural network as surrogate of the FE porcine brain model to predict the brain strain and the strain rate in a computationally efficient way. We assessed the effect of several experimental and modeling parameters on four FE-derived CC injury metrics (maximum principal strain, maximum principal strain rate, product of maximum principal strain and strain rate, and maximum shear strain). Next, we compared the in silico brain mechanical response with cortical damage data from in vivo CCI experiments on pig brains to evaluate the predictive performance of the CC injury metrics. Our ML surrogate was capable of rapidly predicting the outcome of the FE porcine brain undergoing CCI. The now computationally efficient MCS showed that depth and velocity of indentation were the most influential parameters for the strain and the strain rate-based injury metrics, respectively. The sensitivity analysis and comparison with the cortical damage experimental data indicate a better performance of maximum principal strain and maximum shear strain as tissue-level injury metrics for CC. These results provide guidelines to optimize the design of CCI tests and bring new insights to the understanding of the mechanical response of brain tissue to focal traumatic brain injury. Our findings also highlight the potential of using ML for computationally efficient TBI biomechanics investigations.

Introduction: Traumatic brain injury (TBI) rates in the elderly are increasing worldwide, mainly due to fall accidents. However, TBI's impact on elderly patients' lives has not been thoroughly investigated. Research question: This systematic review and meta-analysis aims at describing post-TBI incidence of functional decline, dependency, nursing home admission, reduced quality of life and depression in the elderly. Materials and methods: A systematic literature search was performed in PubMed, EMBASE, Web Of Science, BIOSIS, Current Contents Connect, Data Citation Index, MEDLINE, SciELO, Cochrane library and CINAHL. Study selection was conducted by two independent reviewers. Meta-analysis was performed using a random-effects model. Results: Twenty-seven studies were included in the qualitative synthesis and twenty-five in a random-effects meta-analysis. The prevalence of unfavorable functional outcomes after TBI was 65.2% (95% CI: 51.1–78.0). Admission to a nursing home had a pooled prevalence of 28.5% (95% CI: 17.1–41.6) and dependency rates ranged between 16.9% and 74.0%. A reduced quality of life was documented throughout follow-up with SF12/36 scores between 35.3 and 52.3/100.2.6–4.8% of the patients with mild TBI reported depressive symptoms. A large heterogeneity was found among studies for functional outcomes and discharge destination. Discussion and conclusion: In conclusion, elderly patients have a significant risk for functional decline, dependency, nursing home admission and low quality of life following TBI. Moreover, more severe injuries lead to worse outcomes. These findings are important to provide accurate patient and family counseling, set realistic treatment targets and aim at relevant outcome variables in prognostic models for TBI in elderly patients.

The regional dynamic mechanical properties of mouse, rat, pig, and human brain tissue were compared directly in this first-of-its-kind study. Our results suggest the use of pig or mouse brain tissue as suitable surrogates to characterise human brain tissue. The importance of this work is highlighted by the extensive use of constitutive data from animal brain tissue in traumatic brain injury research in the absence of human brain tissue data without any direct evidence supporting their use. Indentation force-relaxation experiments were performed on mouse, rat, pig, and human brains at 10/s strain rate up to 35% strain to determine the dynamic mechanical properties of brain tissue. Finite element models have become useful tools to investigate the biomechanics of traumatic brain injury - a global leading cause of death and disability and a risk factor for developing neurodegenerative diseases. However, these models require accurate constitutive data for brain tissue to produce reliable results. The results presented here provide validation for the use of pig and mouse brain tissue data in such models. Statement of Significance: The significance of this work is underscored by the extensive use of animal brain tissue as a surrogate for human brain tissue without any direct evidence supporting the validity of their use. For the first time ever, we demonstrate that porcine and murine brain tissue can be used as surrogates for human brain tissue under dynamic loading conditions. These findings will allow researchers to select appropriate animal surrogates for human brain tissue under dynamic loading conditions. Furthermore, our findings support the use of animal surrogate data to improve the fidelity of computational models of the human brain, and provide experimental data to develop constitutive models of brain tissue.

Replicate bones are widely used as an alternative for cadaveric bones for in vitro testing. These composite bone models are more easily available and show low inter-specimen variability compared to cadaveric bone models. The combination of in vitro testing with in silico models can provide further insights in the evaluation of the mechanical behavior of orthopedic implants. An accurate numerical representation of the experimental model is important to draw meaningful conclusions from the numerical predictions. This study aims to determine the elastic material constants of a commonly used composite clavicle model by combining acoustic experimental and numerical modal analysis. The difference between the experimental and finite element (FE) predicted natural frequencies was minimized by updating the elastic material constants of the transversely isotropic cortical bone analogue that are provided by the manufacturer. The longitudinal Young’s modulus was reduced from 16.00 GPa to 12.88 GPa and the shear modulus was increased from 3.30 GPa to 4.53 GPa. These updated material properties resulted in an average natural frequency difference of 0.49% and a maximum difference of 1.73% between the FE predictions and the experimental results. The presented updated model aims to improve future research that focuses on mechanical simulations with clavicle composite bone models.

The total number of total hip arthroplasties is increasing every year, and approximately 10% of these surgeries are revisions. New implant design and surgical techniques are evolving quickly and demand accurate preclinical evaluation. The initial stability of cementless implants is one of the main concerns of these preclinical evaluations. A broad range of initial stability test methods is currently used, which can be categorized into two main groups: Load-to-failure tests and relative micromotion measurements. Measuring relative micromotion between implant and bone is recognized as the golden standard for implant stability testing as this micromotion is directly linked to the long-term fixation of cementless implants. However, specific custom-made set-ups are required to measure this micromotion, with the result that numerous studies opt to perform more straightforward load-to-failure tests. A custom-made micromotion test set-up for artificial acetabular bone models was developed and used to compare load-to-failure (implant push-out test) with micromotion and to assess the influence of bone material properties and press-fit on the implant stability. The results showed a high degree of correlation between micromotion and load-to-failure stability metrics, which indicates that load-to-failure stability tests can be an appropriate estimator of the primary stability of acetabular implants. Nevertheless, micromotions still apply as the golden standard and are preferred when high accuracy is necessary. Higher bone density resulted in an increase in implant stability. An increase of press-fit from 0.7 mm to 1.2 mm did not significantly increase implant stability.

OBJECTIVES:The current study quantified the influence of cartilage defect location on the tibiofemoral load distribution during gait. Furthermore, changes in local mechanical stiffness representative for matrix damage or bone ingrowth were investigated. This may provide insights in the mechanical factors contributing to cartilage degeneration in the presence of an articular cartilage defect. METHODS:The load distribution following cartilage defects was calculated using a musculoskeletal model that included tibiofemoral and patellofemoral joints with 6 degrees-of-freedom. Circular cartilage defects of 100 mm2 were created at different locations in the tibiofemoral contact geometry. By assigning different mechanical properties to these defect locations, softening and hardening of the tissue were evaluated. RESULTS:Results indicate that cartilage defects located at the load-bearing area only affect the load distribution of the involved compartment. Cartilage defects in the central part of the tibia plateau and anterior-central part of the medial femoral condyle present the largest influence on load distribution. Softening at the defect location results in overloading, i.e., increased contact pressure and compressive strains, of the surrounding tissue. In contrast, inside the defect, the contact pressure decreases and the compressive strain increases. Hardening at the defect location presents the opposite results in load distribution compared to softening. Sensitivity analysis reveals that the surrounding contact pressure, contact force and compressive strain alter significantly when the elastic modulus is below 7 MPa or above 18 MPa. CONCLUSION:Alterations in local mechanical behavior within the high load bearing area resulted in aberrant loading conditions, thereby potentially affecting the homeostatic balance not only at the defect but also at the tissue surrounding and opposing the defect. Especially, cartilage softening predisposes the tissue to loads that may contribute to accelerated risk of cartilage degeneration and the initiation or progression towards osteoarthritis of the whole compartment.

The current study aimed to assess the potential of different exercises triggering an osteogenic response at the femoral neck in a group of postmenopausal women. The osteogenic potential was determined by ranking the peak hip contact forces (HCFs) and consequent peak tensile and compressive strains at the superior and inferior part of the femoral neck during activities such as (fast) walking, running and resistance training exercises. Results indicate that fast walking (5-6 km/h) running and hopping induced significantly higher strains at the femoral neck than walking at 4 km/h which is considered a baseline exercise for bone preservation. Exercises with a high fracture risk such as hopping, need to be considered carefully especially in a frail elderly population and may therefore not be suitable as a training exercise. Since superior femoral neck frailness is related to elevated hip fracture risk, exercises such as fast walking (above 5 km/h) and running can be highly recommended to stimulate this particular area. Our results suggest that a training program including fast walking (above 5 km/h) and running exercises may increase or preserve the bone mineral density (BMD) at the femoral neck.

BACKGROUND:Lack of intra-operative haptic information during robotic surgery increases the risk for unintended tissue overload and damage. Knowledge about the acute and chronic fundamental relationship between force load and induced damage in healthy and diseased arteries is crucial to enable intra-operative haptic feedback or shared autonomy and improve patient safety. METHODS:Arteries of wildtype and atherosclerotic mice were clamped in vivo for 2 minutes (0.0N, 0.6N or 1.27N). Histological analysis (Verhoeff's-Van Gieson, Osteopontin, CD45, CD105) was performed immediately, or after 6 hours, 2 weeks or 1 month. Endothelium-dependent and-independent vasodilatation was assessed immediately or 1 month after clamping. RESULTS:Endothelium dependent vasodilatation is worse after clamping of wildtype arteries, but is restored after one month. Clamping also results in flattening of the innermost elastic membrane of both genotypes, which is reversed over time for wildtype arteries but not for vessels from atherosclerotic mice. Higher osteopontin content in wildtype and LDLR-/- mice after 2 weeks suggests a phenotypic switch of the medial smooth muscle cells (SMCs), an effect that is reversed after 1 month. While inflammation in the intima diminishes, medial CD45 content rises through time in both genotypes. CD105 staining shows that even manipulation without clamping results in endothelial cell loss in both LDLR+/+ and LDLR-/- mice. CONCLUSIONS:Arterial clamping induces different acute and long-term injury to the vessel wall of atherosclerotic and healthy arteries.

Tactile feedback is a major missing feature in minimally invasive procedures; it is an essential means of diagnosis and orientation during surgical procedures. Previous works have presented a remote palpation feedback system based on the coupling between a pressure sensor and a general haptic interface. Here a new approach is presented based on the direct estimation of the tissue mechanical properties and finally their presentation to the operator by means of a haptic interface. The approach presents different technical difficulties and some solutions are proposed: the implementation of a fast Young’s modulus estimation algorithm, the implementation of a real time finite element model, and finally the implementation of a stiffness estimation approach in order to guarantee the system’s stability. The work is concluded with an experimental evaluation of the whole system.

Abstract Background Understanding the development of ankle osteoarthritis (OA) is of high importance and interest; however its causality is poorly understood and several links to joint loading conditions have been made. One way of quantifying joint loading conditions is by measuring the intra‐articular pressure distribution during gait simulations performed by in‐vitro experimental set‐ups. However the effect of inserting a pressure sensing array in the ankle joint could potentially disturb the proper kinematics and therefore the loading conditions. Methods In this study, we performed in‐vitro gait simulations in 7 cadaveric feet, before and after inserting a pressure sensing array and quantified the effect on the joints range of motion (ROM). The gait was simulated with a stance phase duration of one second using a custom build cadaveric gait simulator (CGS). Results The results show a limited effect in the ROM for all the joints of the hind foot, not exceeding the variability observed in specimens without a sensor. However, no consistent direction (increase/decrease) can be observed. Conclusion The results suggest that even though the effect of inserting a pressure sensing array is minimal, it needs to be evaluated against the demands/requirements of the application.

Abstract Background When researchers describe data from their studies, there is no rule defining the best way to represent results. Therefore, collecting and explaining results from personal research or understanding data from publications is not always straightforward. These issues are even worse in fields such as biomedical engineering, where researchers from different backgrounds, usually engineers and surgeons, need to interact and exchange information. For these reasons, the purpose of this study is to introduce and illustrate an innovative method to represent, concisely and intuitively, biomechanical knee behavior, called KneePrints. Methods To test the KneePrints method, a huge amount of data from previously published sensitivity analyses were used and represented both with conventional techniques and with this new graphical method. Then, a survey has been distributed among different international specialists in the orthopedic field, such as surgeons and researchers. In the survey, interviewees were asked to select the favorite method that addressed to be the most effective to show the same results. Results Collecting the outcomes from the survey, the KneePrints method resulted to be more effective than standard graphs, such as tables and histograms. KneePrints method has been selected to be clearer in representing outputs and more immediate in results understanding independently from the occupation of the interviewees by the survey. The general preference for the KneePrints is 63 %, up to 74 % being surgeons’ choice. Conclusions The innovative KneePrints method has been endorsed to be effective in representing and making more understandable knee joint outputs. This method can be extended also to other topics.

Exposure to microgravity causes loss of lower body bone mass in some astronauts. Low-magnitude high-frequency loading can stimulate bone formation on earth. Here we hypothesized that low-magnitude high-frequency loading will also stimulate bone formation under microgravity conditions. Two groups of six bovine cancellous bone explants were cultured at microgravity on a Russian Foton-M3 spacecraft and were either loaded dynamically using a sinusoidal curve or experienced only a static load. Comparable reference groups were investigated at normal gravity. Bone structure was assessed by histology, and mechanical competence was quantified using μCT and FE modelling; bone remodelling was assessed by fluorescent labelling and secreted bone turnover markers. Statistical analyses on morphometric parameters and apparent stiffness did not reveal significant differences between the treatment groups. The release of bone formation marker from the groups cultured at normal gravity increased significantly from the first to the second week of the experiment by 90.4% and 82.5% in response to static and dynamic loading, respectively. Bone resorption markers decreased significantly for the groups cultured at microgravity by 7.5% and 8.0% in response to static and dynamic loading, respectively. We found low strain magnitudes to drive bone turnover when applied at high frequency, and this to be valid at normal as well as at microgravity. In conclusion, we found the effect of mechanical loading on trabecular bone to be regulated mainly by an increase of bone formation at normal gravity and by a decrease in bone resorption at microgravity. Additional studies with extended experimental time and increased samples number appear necessary for a further understanding of the anabolic potential of dynamic loading on bone quality and mechanical competence.

Recently developed atrophic non-union models are a good representation of the clinical situation in which many non-unions develop. Based on previous experimental studies with these atrophic non-union models, it was hypothesized that in order to obtain successful fracture healing, blood vessels, growth factors, and (proliferative) precursor cells all need to be present in the callus at the same time. This study uses a combined in vivo-in silico approach to investigate these different aspects (vasculature, growth factors, cell proliferation). The mathematical model, initially developed for the study of normal fracture healing, is able to capture essential aspects of the in vivo atrophic non-union model despite a number of deviations that are mainly due to simplifications in the in silico model. The mathematical model is subsequently used to test possible treatment strategies for atrophic non-unions (i.e. cell transplant at post-osteotomy, week 3). Preliminary in vivo experiments corroborate the numerical predictions. Finally, the mathematical model is applied to explain experimental observations and identify potentially crucial steps in the treatments and can thereby be used to optimize experimental and clinical studies in this area. This study demonstrates the potential of the combined in silico-in vivo approach and its clinical implications for the early treatment of patients with problematic fractures.