Abstract

Biplane video X-ray (BVX) – with models segmented from magnetic resonance imaging (MRI) – is used to directly track bones during dynamic activities. Investigating tibiofemoral kinematics helps to understand effects of disease, injury, and possible interventions.

Develop a protocol and compare in-vivo kinematics during loaded dynamic activities using BVX and MRI.

BVX (60 FPS) was captured whilst three healthy volunteers performed three repeats of lunge, stair ascent and gait. MRI scans were performed (Magnetom 3T Prisma, Siemens). 3D bone models of the tibia and femur were segmented (Simpleware Scan IP, Synopsis). Bone poses were obtained by manually matching bone models to X-rays (DSX Suite, C-Motion Inc.). Mean range of motion (ROM) of the contact points on the medial and lateral tibial plateau were calculated using custom MATLAB code (MathWorks). Results were filtered using an adaptive low pass Butterworth filter (Frequency range: 5-29Hz).

Gait and Stair ascent activities from one participant's data showed increased ROM for medial-lateral (ML) translation in the medial compartment but decreased ROM in anterior-posterior (AP) translation when comparing against the same translations on the lateral compartment of the tibial plateau. Lunge activity showed increased ROM for both ML and AP translation in the medial compartment when compared with the lateral compartment.

These results highlight the variability in condylar translations between different activities. Understanding healthy in-vivo kinematics across different activities allows the determination of suitable activities to best investigate the kinematic changes due to disease or injury and assess the efficacy of different interventions.

Acknowledgements: This research was supported by the Engineering and Physical Sciences Research Council (EPSRC) doctoral training grant (EP/T517951/1).

Regulation of articular cartilage homeostasis is a complex process in which biologic and mechanical factors are involved. Hyperactivation of Wnt signaling, associated with osteoarthritis (OA), could jeopardize the protective anabolic effect of physiological loading. Here, we investigated the role of excessive Wnt signalling in cartilage molecular responses to loading.

Human cartilage explants were harvested from hips of donors without OA. The Wnt agonist CHIR99021 was used to activate Wnt signalling 24 hours before cartilage explants were subjected to a loading protocol consisting of 2 cycles of 1 hour of 10% compression at 1 Hz, followed by 1-hour free swelling. Mechano-responsiveness was evaluated using the expression of type II collagen, aggrecan and MMP-13. Expression of known target genes TCF-1 and c-JUN was evaluated as positive control for Wnt and mechanical stimulation, respectively.

In the absence of loading, CHIR99021 decreased the expression of the cartilage anabolic genes type II collagen and aggrecan, and increased the levels of MMP-13, corroborating that Wnt hyperactivation disrupts cartilage homeostasis. In the absence of Wnt hyperactivation, the applied loading protocol, representative for a physiologic stimulation by mechanical loading, led to an increase in type II collagen and aggrecan levels. However, when cartilage explants were subjected to mechanical stimulation in the presence of CHIR99021, the expression of cartilage anabolic genes was decreased, indicating changes to the cells’ mechano-responsiveness. Interestingly, mechanical stimulation was able to reduce the expression levels of MMP-13 compared to the condition of CHIR stimulation without loading.

Hyperactivation of Wnt signaling switches the anabolic effect of physiologic compressive loading towards a potential catabolic effect and could contribute to the development and progression of OA.

Altered mechanical loading is a widely suggested, but poorly understood potential cause of cartilage degeneration in osteoarthritis. In rodents, osteoarthritis is induced following destabilization of the medial meniscus (DMM). This study estimates knee kinematics and contact forces in rats with DMM to gain better insight into the specific mechanisms underlying disease development in this widely-used model.

Unilateral knee surgery was performed in adult male Sprague-Dawley rats (n=5 with DMM, n=5 with sham surgery). Radio-opaque beads were implanted on their femur and tibia. 8 weeks following knee surgery, rat gait was recorded using the 3D²YMOX setup (Sanctorum et al. 2019, simultaneous acquisition of biplanar XRay videos and ground reaction forces).

10 trials (1 per rat) were calibrated and processed in XMALab (Knörlein et al. 2016). Hindlimb bony landmarks were labeled on the XRay videos using transfer learning (Deeplabcut, Mathis et al. 2019; Laurence-Chasen et al. 2020).

A generic OpenSim musculoskeletal model of the rat hindlimb (Johnson et al. 2008) was adapted to include a 3-degree-of-freedom knee. Inverse kinematics, inverse dynamics, static optimization of muscle forces, and joint reaction analysis were performed.

In rats with DMM, knee adduction was lower compared to sham surgery. Ground reaction forces were less variable with DMM, resulting in less variability in joint external moments. The mediolateral ground reaction force was lower, resulting in lower hip adduction moment, thus less force was produced by the rectus femoris. Rats with DMM tended to break rather than propel, resulting in lower hip flexion moment, thus less force was produced by the semimembranosus. These results are consistent with lower knee contact forces in the anteroposterior and axial directions.

These preliminary data indicate no overloading of the knee joint in rats with DMM, compared with sham surgery. We are currently expanding our workflow to finite element analysis, to examine mechanical cues in the cartilage of these rats (Fig1G).

In a clinical setting, there is a need for simple gait kinematic measurements to facilitate objective unobtrusive patient monitoring. The objective of this study is to determine if a learned classification model's output can be used to monitor a person's recovery status post-TKA.

The gait kinematics of 20 asymptomatic and 17 people with TKA were measured using a full-body Xsens model¹. The experimental group was measured at 6 weeks, 3, 6, and 12 months post-surgery. Joint angles of the ankle, knee, hip, and spine per stride (10 strides) were extracted from the Xsens software (MVN Awinda studio 4.4)¹.

Statistical features for each subject at each evaluation moment were derived from the kinematic time-series data. We normalised the features using standard scaling². We trained a logistic regression (LR) model using L1-regularisation on the 6 weeks post-surgery data2–4.

After training, we applied the trained LR- model to the normalised features computed for the subsequent timepoints. The model returns a score between 0 (100% confident the person is an asymptomatic control) and 1 (100% confident this person is a patient). The decision boundary is set at 0.5.

The classification accuracy of our LR-model was 94.58%. Our population's probability of belonging to the patient class decreases over time. At 12 months post-TKA, 38% of our patients were classified as asymptomatic.

The aim of this research was to determine biomechanical markers which differentiate medial knee osteoarthritis (OA) patients who do and do not show structural progression over a 2-year period.

A cohort of 36 subjects was selected from a longitudinal study (Meireles et al 2017) using Kellgren-Lawrence (KL) scores at baseline and 2-year follow-up. The cohort consisted of 10 healthy controls (HC) (KL=0 at both time points), 15 medial knee OA non-progressors (NPKOA) (KL≥1 at baseline and no change over 2 years), and 11 medial knee OA progressors (PKOA) (KL≥1 at baseline and increase of ≥1 over 2 years). 3D integrated motion capture data from three walking trials were processed through a musculoskeletal modelling framework (Smith et al 2016) to estimate knee joint loading parameters (i.e., magnitude of mean contact pressure, and centre of pressure (COP)). Parameters at first and second peak were extracted and compared between groups using Kruskal-Wallis and Mann-Whitney tests.

Higher magnitudes were observed in PKOA vs NPKOA, and PKOA vs HC groups at both time points. Additionally, a posterior (1st and 2nd peak), and lateral (2nd peak) shift in medial compartment COP was shown between PKOA and NPKOA, and PKOA and HC subjects. Interestingly, in the studied parameters, no differences were observed between NPKOA and HC groups.

Significantly higher magnitude, and a more posterior and lateral COP was observed between PKOA and NPKOA patients. These differences, combined with an absence of difference between NPKOA and HC suggest structural OA progression is driven by a combination of altered loading magnitude and location. These results may serve as guidelines for targeted gait retraining rehabilitation to slow or stop knee OA progression whereby shifting COP anterior and medial and reducing magnitude by ~22% may shift patients from a PKOA to a NPKOA trajectory.

Introduction and Objective

Low back pain (LBP) is a major cause of long-term disability in adults worldwide and it is frequently attributed to intervertebral disc (IVD) degeneration. So far, no consensus has been reached regarding appropriate treatment and LBP management outcomes remain disappointing. Spine unloading or traction protocols are common non-surgical approaches to treat LBP. These treatments are widely used and result in pain relief, decreased disability or reduced need for surgery. However, the underlying mechanisms -namely, the IVD unloading mechanobiology- have not yet been studied. The aim of this first study was to assess the feasibility of IVD unloading in a large animal organ culture set-up and evaluate its impact on mechanobiology.

In a healthy joint, mechanical loading increases matrix synthesis and maintains cell phenotype, while reducing catabolic activities. It activates several pathways, most of them yet largely unknown, with integrins, TGF-β, canonical (Erk 1/2) and stress-activated (JNK) MAPK playing a key role. Degenerative joint diseases are characterized by Wnt upregulation and by the presence of proteolytic fibronectin fragments (FB-fs). Despite they are known to impair some of the aforementioned pathways, little is known on their modulatory effect on cartilage mechanoresponsiveness. This study aims at investigating the effect of mechanical loading in healthy and in vitro diseased cartilage models using pro-hypertrophic Wnt agonist CHIR99021 and the pro-catabolic FB-fs 30 kDa.

Human primary chondrocytes from OA patients have been grown in alginate hydrogels for one week, prior to be incubated for 4 days with 3μM CHIR99021 or 1 μM FB-fs. Human cartilage explants isolated from OA patients have incubated 4 days with 3 μM CHIR99021 or 1 μM FB-fs. Both groups have then been mechanically stimulated (unconfined compression, 10% displacement, 1.5 hours, 1 Hz), using a BioDynamic bioreactor 5270 from TA Instruments. Expression of collagen type I, II and X, aggrecan, ALK-1, ALK-5, αV, α5 and β1 integrins, TGF-β1 have been assessed by Real Time-PCR and normalized with the expression of S29. Percentage of phosphorylated Smad2, Smad1 and JNK were determined through western blot. TGF-β1 content was quantified by sandwich ELISA; MMP-13 and GAG by western blot and DMMB assay, respectively. At least three biological replicates were used. ANOVA test was used for parametric analysis; Kruskal-Wallis and Mann-Whitney post hoc test for non-parametric.

Preliminary data show that compression increased collagen II expression in control, but not in CHIR99021 and FB-fs pre-treated group (Fig. 1A-B). This was associated with downregulation of β1-integrin expression, which is the main collagen receptor and further regulates collagen II expression, suggesting inhibition of Erk1/2 pathway. A trend of increase expression of collagen type X after mechanical loading was observed in CHIR and FB-fs group. ALK-1 and ALK-5 showed a trend toward stronger upregulation in CHIR99021 group after compression, suggesting the activation of both Smad1/5/8 and Smad 2/3 pathways. To further investigate pathways leading to these different mechano-responses, the phosphorylation levels of Smad1 and Smad2, Erk1/2 and JNK proteins are currently being studied. Preliminary results show that Smad2, Smad1 and JNK protein levels increased in all groups after mechanical loading, independently of an increase in TGF-β1 expression or content. Compression further increased phosphorylation of Smad2, but not of Smad1, in all groups.

To unravel the relation between mechanical loading and biological response, cell-seeded hydrogel constructs can be used in bioreactors under multi-axial loading conditions that combines compressive with torsional loading. Typically, considerable biological variation is observed. This study explores the potential confounding role of mechanical factors in multi-directional loading experiments. Indeed, depending on the material properties of the constructs and characteristics of the mechanical loading, the mechanical environment within the constructs may vary. Consequently, the local biological response may vary from chondrogenesis in some parts to proteoglycan loss in others.

This study uses the finite element method to investigate the effects of material properties of cell-seeded constructs and multiaxial loading characteristics on local mechanical environment (stresses and strains) and relate these to chondrogenesis (based on maximum compressive principal strain (MCPS) - Zahedmanesh et al., 2014) and proteoglycan loss (based on fluid velocity (FV) - Orozco et al., 2018).

The construct was modelled as a homogenized poro-hyperelastic (using a Neohookean model and Darcys law) cylinder of 8mm diameter and equal height using Abaqus. The bottom surface was fully constrained and dynamic unconfined compression and torsion loading were applied to the top surface. Free fluid flow was allowed through the lateral surface. We studied the sensitivity of the maximum values of the target parameters at 9 key locations to the material parameters and loading characteristics. Six input parameters were varied in preselected ranges: elastic modulus (E=[20,80]kPa), Poissons ratio (nu=[0.1,0.4]), permeability (k=[1,4]e-12m4/Ns), compressive strain (Comp=[5,20]%), rotation (Rot=[5,20]°) and loading frequency (Freq=[1,4]Hz). A full-factorial design of experiment method was used and a first-order polynomial surface including the interactions fitted the responses.

MCPS varies between 7.34% and 33.52% and is independent of the material properties (E, nu and k) and Freq but has a high dependency on Comp and a limited dependency on Rot. The maximum value occurs centrally in the construct, except for high values of Rot and low Comp where it occurs at the edges. FV vary between 0.0013mm/sec and 0.1807mm/sec and dominantly depends on E, k and Comp, while its dependency on Rot and Freq is limited. The maximum value usually occurs at the edges, although at high Freq it may move towards the center of the superficial and deep zones. This study can be used as a guideline for the optimized selection of mechanical parameters of hydrogel for cell-seeded constructs and loading conditions in multi-axial bioreactor studies. In future work, we will study the effect in intact and injured cartilage explants.

Mechanical loading regulates the metabolism of chondrocytes in cartilage1. Nowadays, studies exploring the in vitro response of cartilage towards loading often rely on bioreactor experiments applying only compressive loading. This is likely not sufficiently representative for the complex multi-directional loading profile in vivo (i.e. where typical compressive and shear loading are both present). The impact of multi-axial loading is specifically relevant in the context of the onset of osteoarthritis (OA) due to joint destabilization. Here, alterations in the 3D loading profile, and in particular increased shear forces, are suggested to initiate catabolic molecular responses leading to cartilage degeneration3. However, in vitro/ex vivo data confirming this hypothesis are currently lacking. Therefore, we aim to investigate how increased shear loading affects the metabolism and ECM deposition of a healthy chondrogenic cell line and if this response is different in osteoarthritic primary chondrocytes.

A murine chondrogenic precursor cell line (ATDC5) and primary human osteoarthritic articular chondrocytes (hOACs) were encapsulated in 2.2% alginate disks and cultured in DMEM medium for three days. Hydrogels seeded with the different cell groups were loaded in the TA ElectroForce BioDynamic Bioreactor and subjected to following loading conditions: (a) 10% compression at 1Hz for 1h, (b) 10% compression and 10° shear loading at 1Hz for 1h. Unloaded constructs were used as control. After loading, hydrogel constructs were stabilized in culture medium for 2 hours, to facilitate adequate gene expression responses, before being dissolved and snap frozen. RNA was isolated and gene expression levels specific for anabolic pathways, characterized by extracellular matrix (ECM) genes (Col2a1, Aggrecan and Perlecan), catabolic processes (MMP-3 and MMP-13) and chondrogenic transcription factor (Sox9) were evaluated using RT-qPCR. The TA ElectroForce BioDynamic Bioreactor was successfully set-up to mimic cartilage loading.

In ATDC5 cells, compression elicits an increase in all measured ECM genes (Col2a1, Aggrecan and Perlecan) compared to unloaded controls, suggesting an anabolic response. This upregulation is decreased when adding additional shear strain. In contrast to ATDC5 cells, the anabolic response of proteoglycans Aggrecan and Perlecan to compressive loading was lower in osteoarthritic chondrocytes, and Col2a1 expression appeared decreased. Adding shear strain reversed this effect on Col2a1 expression. Multi-directional loading increased transcription factor Sox9 expression compared to compression in both ATDC5 and OA chondrocytes. In OA chondrocytes, both loading regimens increased MMP-3 and MMP-13 expression. Shear loading reduces the anabolic effect of compressive loading in both cell types. OA cells presented more catabolic response to mechanical loading compared to precursors, given the increase in catabolic enzymes MMP-3 and MMP-13.

Abstract

Osteoarthritis is a multifactorial disease in which altered mechanical loading is one of the agreed contributing factors. Whereas in the past, altered mechanical loading was merely deferred from static, image-based evaluations of malalignment, the recent use of 3D motion capture allowed dynamic evaluation of joint loading in terms of dynamic alignment (e.g. varus trust) and even joint loading strategy (merely using proxy measures like knee adduction moment.) Combining these measurements with musculoskeletal models, the overall loading distribution in the joint due to muscle action underlying the patient's motion pattern can be quantified. Using this approach, our group showed the potential of this technique to differentiate between control subjects and subjects with early medial knee OA before the presence of radiographic evidence of structural joint degradation. Nevertheless, no changes in loading distribution could be detected in a cohort of subjects suffering of local cartilage defects in an otherwise healthy knee joint, indicating that patients did not present active unloading strategies despite the presence of clinical symptoms. Furthermore, subject-specific strategies aiming contributing to modified loading of the hip joint have been evaluated.

In knee osteoarthritis (OA) patients, a focal cartilage defect is commonly found, especially in the medial compartment. In addition, cartilage softening is often observed at the defect rim. Both factors may alter the loading distribution and thereby the contact pressures, previously related to cartilage degeneration. To determine contact pressure in-vivo during motion, computational modelling can be used. The aim of this study was to analyse knee cartilage pressures during walking in healthy and damaged cartilage using a multi-scale modelling approach. Using 3D motion capture and musculoskeletal models, multi-body simulations of the stance phase of gait calculated knee kinematics and muscle, ligament and contact forces. These were subsequently imposed to a finite element (FE) model including tibial and femoral bones and cartilage. FE analyses were performed using intact cartilage as well as including a medial tibial cartilage defect, with and without softening of the defect rim. Specifically during loading response, a medial cartilage defect reduced the contact surface (−28%) and thereby increased the contact pressure (+33%) compared to intact cartilage, particularly on the medial compartment (+75% in contact pressure). Including softening of the cartilage rim increased the contact area (+22%) and decreased contact pressures (−9%) compared to the defect. This indicates that a focal defect increases the cartilage loading. This is partially compensated by softening of the cartilage rim. Therefore, the role of focal defects in altered cartilage loading and consequent OA development always needs to be discussed acknowledging the cartilage status at the defect rim.

Last decade, a shift towards operative treatment of midshaft clavicle fractures has been observed [T. Huttunen et al., Injury, 2013]. Current fracture fixation plates are however suboptimal, leading to reoperation rates up to 53% [J. G. Wijdicks et al., Arch. Orthop. Trauma Surg, 2012]. Plate irritation, potentially caused by a bad geometric fit and plate prominence, has been found to be the most important factor for reoperation [B. D. Ashman et a.l, Injury, 2014]. Therefore, thin plate implants that do not interfere with muscle attachment sites (MAS) would be beneficial in reducing plate irritation. However, little is known about the clavicle MAS variation. The goal of this study was therefore to assess their variability by morphing the MAS to an average clavicle.

14 Cadaveric clavicles were dissected by a medical doctor (MH), laser scanned (Nikon, LC60dx) and a photogrammetry was created with Agisoft photoscan (Agisoft, Russia). Subsequently a CT-scan of these bones was acquired and segmented in Mimics (Materialise, Belgium). The segmented bone was aligned with the laser scan and MAS were indicated in 3-matic (Materialise, Belgium). Next, a statistical shape model (SSM) of the 14 segmented clavicles was created. The average clavicle from the SSM was then registered to all original clavicle meshes. This registration assures correspondences between source and target mesh. Hence, MAS of individual muscles of all 14 bones were indicated on the average clavicle.

Mean area is 602 mm² ± 137 mm² for the deltoid muscle, 1022 mm² ±207 mm² for the trapezius muscle, and 683 mm² ± 132 mm² for the pectoralis major muscle. The sternocleidomastoid muscle has a mean area of 513 mm² ± 190 mm² and the subclavius muscle had the smallest mean area of 451 mm² ± 162 mm². Visualization of all MAS on the average clavicle resulted in 72% coverage of the surface, visualizing only each muscle's largest MAS led to 52% coverage.

The large differences in MAS surface areas, as shown by the standard deviation, already indicate their variability. Difference between coverage by all MAS and only the largest, shows that MAS location varies strongly as well. Therefore, design of generic plates that do not interfere with individual MAS is challenging. Hence, patient-specific clavicle fracture fixation plates should be considered to minimally interfere with MAS.

Objective

Full-thickness cartilage defects are commonly found in symptomatic knee patients, and are associated with progressive cartilage degeneration. Although the risk of defect progression to degenerative osteoarthritis is multifactorial, articular cartilage defects change contact mechanics and the mechanical response of tissue adjacent to the defect. The objective of this study was to quantify changes in intra-tissue strain patterns occurring at the defect rim and opposing tissue in an experimental model mimicking in vivo cartilage-on-cartilage contact conditions.

Introduction

Modification in joint loading, and specifically shear stress, is found to be an important mechanical factor in the development of osteoarthritis (OA). Cartilage shear stresses can be investigated using finite element (FE) modelling, where typically in vivo joint loading as measured by an instrumented hip prosthesis is used as boundary condition. However, subject-specific gait characteristics substantially affect joint loading. The goal of this study is to investigate the effect of subject-specific joint loading as calculated using a subject-specific musculoskeletal model and integrated motion capture data on acetabular shear stress.

Healthy cartilage is essential for optimal joint function. Although, articular cartilage defects are highly prevalent in the active population and might hamper joint function, the effect of articular cartilage defects on knee contact forces and pressures is not yet documented. Therefore, the present study compared knee contact forces and pressures between patients with a tibiofemoral cartilage defect and healthy controls. This might provide additional insights in movement adaptations and the role of altered loading in the progression from defect to OA. Experimental gait data was collected in 15 patients with isolated articular cartilage defects (8 medial-affected, 7 lateral-affected) and 19 healthy asymptomatic controls and was processed using a musculoskeletal model to calculate contact forces and pressures. Differences between medial-affected, lateral-affected and controls were evaluated using Kruskal-Wallis tests and individually compared using Mann-Whitney-U tests (alpha <0.05). The lateral-affected group walked significantly slower compared to the healthy controls. No adaptations in the movement pattern that resulted in decreased loading on the injured condyle were observed. Additionally, the location of loading was not significantly affected. The current results suggest that isolated cartilage defects do not induce changes in the knee joint loading pattern. Consequently, the involved condyle will be equally loaded, indicating that a similar amount of force should be distributed over the remaining cartilage surrounding the articular cartilage defect and may cause local degenerative changes in the cartilage. This in combination with inflammatory responses might play a key role in the progression from articular cartilage defect to a more severe OA phenotype.

Several studies have shown that gait kinematics[1–3] and hip contact forces (HCFs)[4, 5] of patients following total hip arthroplasty (THA) do not return to normal, although improvements in kinematics are found compared to the pre-surgery. However, the evolution of HCFs after surgery has not been investigated. The goal of this study is to evaluate HCFs during gait in OA patients before and at 2 evaluation moments post-THA.

Fourteen unilateral hip OA patients before and 3- and 12-months post-THA surgery walked at self-selected speed, as well as 18 healthy control subjects. 3D marker trajectories were captured using Vicon (Oxford Metrics, UK) and force data was measured using two AMTI force platforms (Watertown, MA). A musculoskeletal model consisting of 14 segments, 19 degrees of freedom and 88 musculotendon actuators and including wrapping surfaces around the hip joint was used[6]. All analyses were performed in OpenSim 3.1[7]. The model was scaled to the dimensions of each subject using the marker positions of a static pose. A kalman smoother procedure was used to calculate joint angles[8]. Muscle forces were calculated using static optimization, minimizing the sum of squared muscle activations. HCFs were calculated and normalized to body weight (BW). First and second peak HCFs were determined and used for statistical analysis. To determine differences between HCFs of OA patients at the different evaluation moments, a Friedman test was used. In case of a significant difference, post-hoc rank-based multiple comparison tests with a Bonferonni adjustment was used. To compare controls and patients at each evaluation moment separate Man-Whitney U tests were used. Differences in HCFs between the affected and non-affected legs were expressed by a symmetry index (SI), i.e. the ratio between the HCFs of the affected leg over the non-affected leg, averaged over the stance phase of the gait cycle.

At the first and second HCF peaks, no significant differences were found between pre-, 3- and 12-months post-surgery (first peak average HCF: 2.68, 2.72 and 2.78BW respectively; second peak average HCF: 3.21, 3.83 and 3.77BW respectively). Compared to controls, significant differences are found for all evaluation moments at the first and second HCF peaks (average HCF controls: 3.43 and 5.15BW respectively). The SI was below 1 pre- and 3-months post-surgery (0.88 and 0.85 respectively), indicating decreased loading of the affected compared to the non-affected leg. At 12-months post-surgery SI was close to 1 (0.98).

As reported before[4, 5], first or second peak HCFs do not return to normal after THA. Although HCFs increase after THA compared to pre-surgery, significant differences with controls remain. Surprisingly, no significant differences are found between the different evaluation moments of the patients, indicating no clear improvements are found after THA. Further, average HCF peaks at 3- and 12-months post-surgery are similar, indicating no further improvements are found 3-months post-surgery. However, the SI was above or close to 1 at 12-months post-surgery, indicating hip loading evolved to a more symmetrical loading 12-months post-surgery.

Children with cerebral palsy (CP) often present femoral bone deformities not accounted for in generic musculoskeletal models [1,2]. MRI-based models can be used to include subject-specific muscle paths [3,4], although this is a time-demanding process. Recently, non-rigid deformation techniques have been used to transform generic bone geometry, including muscle points, onto personalized bones [5]. However, it is still unknown to what extent such an approximation of subject-specific detail affects calculated hip contact forces (HCFs) during gait in CP children.

Seven children diagnosed with diplegic CP walked independently at self-selected speed. 3D marker trajectories were captured using Vicon (Oxford Metrics, UK) and force data was measured using two AMTI force platforms (Watertown, MA). MR-images were acquired (Philips Ingenia 1.5T) of all subjects lying supine. Firstly, a generic model [6] was scaled using the marker positions of a static pose. Secondly, a MRI-model containing the subject-specific bone structures and muscle paths of all hip and upper leg muscles was created [3]. Thirdly, the generic femur and pelvis geometries and muscle points were transformed onto the image-based femur and pelvis using an advanced non-rigid deformation procedure (Materialise N.V.). For all models, further analyses were performed in OpenSim 3.1 [7]. A kalman smoother procedure was used to calculate joint angles [8]. Muscle forces were calculated using a static optimization minimizing the sum of squared muscle activities. Next, HCFs were calculated and normalized to body weight (BW). First and second peak HCFs were determined and used for a Kruskal-Wallis test to determine differences between models. In case of a significant difference, a post-hoc rank-based multiple comparison test with Bonferonni adjustment was used. Further, average absolute differences in muscle points between the models was calculated, as well as average differences in moment arm lengths (MALs), reflecting muscle function.

Where the scaled generic muscle points differed on average 2.49cm from the MRI points, the non-rigidly deformed points differed 1.54cm from the MRI muscle points. Specifically, the tensor fascia latae differed most between the deformed and MRI models (11.7cm). When considering MALs, the gluteii muscles present an altered function for the generic and deformed models compared to the MRI model for all degrees of freedom of the hip at the time of both HCF peaks. The differences between models resulted in a significantly increased second peak HCF for the MRI models compared to the generic models (first peak average HCF: 3.88BW, 3.95BW and 4.90BW; second peak average HCF: 3.03BW, 4.89BW and 5.32BW for the generic, MRI and non-rigidly deformed models respectively). Although not significantly different, the deformed models calculated slightly increased HCFs compare to the MRI models.

The generic models underestimated HCFs compared to the MRI models, while the non-rigidly deformed models slightly overestimated HCFs. However, differences between the deformed and MRI models in terms of muscle points and MALs remain, specifically for the gluteii muscles. Therefore, further user-guided modification of the model based on MR-images will be necessary.

Four-dimensional computed tomography (4DCT: three dimensional + time) allows to measure individual bone position over a period of time usually during motion. This method has been found useful in studying the joints around the wrist as dynamic instabilities are difficult to detect during static CT scans while they can be diagnosed using a 4DCT scan [1]–[3]. For the foot, the PedCAT system (Curvebeam, Warrington, USA) has been developed to study the foot bones under full weight bearing, however its use is limited to static images. On the contrary, dynamic measurements of the foot kinematics using skin markers can only describe motion of foot segments and not of individual bones. However, the ability to measure individual bone kinematics during gait is of paramount importance as such detailed information could be used to detect instabilities, to evaluate the effect of joint degeneration, to help in pre-operative planning as well as in post-operative evaluation.

The overall gait kinematics of two healthy volunteers were measured in a gait analysis lab (Movement Analysis Lab Leuven, Belgium) using a detailed foot-model (Oxford foot model, [4]). The measured plantar-dorsiflexion and in-eversion were used to manipulate their foot during a 4D CT acquisition. The manipulation was performed through a custom made foot manipulator that controls the position and orientation of the foot bed according to input kinematics. The manipulator was compatible with the 4D CT Scanner (Aquilion One, Toshiba, JP), and a sequence of CT scans (37 CT scans over 10 seconds with 320 slices for each scan and a slice thickness of 0.5 mm) was generated over the duration of the simulation. The position of the individual bones was determined using an automatic segmentation routine after which the kinematics of individual foot bones were calculated. To do so, three landmarks were tracked on each bone over time allowing to construct bone-specific coordinate frames. The motion of the foot bed was compared against the calculated kinematics of the tibia-calcaneus as the angles between these two bones are captured with skin markers.

There is high repeatability between the imposed plantar/dorsiflexion and inversion/eversion and the calculated. Although the internal/external rotation was not imposed, the calculated kinematics follow the same pattern as the measured in the gait-analysis lab. Based on the validation of the tibia-calcaneus, the kinematics were also calculated between four other joints: tibia-talar, talar-calcaneus, calcaneus-cuboid and talar-navicular. Repeatable measurements of individual foot bone motion were obtained for both volunteers.

The use of 4D CT-scanning in combination with a foot manipulator can provide more detailed information than skin marker-based gait-analysis e.g. for the study of the the tibia-talar joint. In the future, the foot manipulator will be tested for its sensitivity for specific pathologies (e.g. metatarsal coalition) and will be further developed to better resemble a real-life stance phase of gait (i.e. to include isolated heel contact and toe off).