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Soft tissue artefacts (STA) are widely considered the most critical source of error in skin-mounted marker-based biomechanics, negatively impacting the clinical usability of skin-mounted marker-based data. Amongst the numerous solutions proposed to ameliorate STA, incorporating true bone movement—acquired using adaptive constraints, projection of markers, or various imaging modalities—has been reported to improve kinematic accuracy. However, efficacy of these proposed solutions reduces for different investigated motions and participants. In this study, we propose two novel marker projection schemes, wherein a cluster of markers are projected onto the bone surface during motion. Additionally, we investigate the feasibility of applying a novel, safe and cost-effective imaging modality—microwave imaging—to detect the location of the bone from the skin surface. Our results indicate that the novel marker projection schemes reduce kinematic errors significantly (by 50%) and improve the quality of computed kinematics (95% correlation to true bone movement). In addition, our results show that microwave imaging was able to detect the bone from the skin surface in both male and female anatomical models of varying body mass index scores and poses. We believe our findings underscore the generalisability and applicability of our proposed solution to reduce STA.

Hamstring strain injury is one of the most common injuries in athletes, particularly for sports that involve high speed running. The aims of this study were to determine whether muscle activation and internal morphology influence in vivo muscle behavior and strain injury susceptibility. We measured tissue displacement and strains in the hamstring muscle injured most often, the biceps femoris long head muscle (BFLH), using cine DENSE dynamic magnetic resonance imaging. Strain measurements were used to test whether strain magnitudes are (i) larger during active lengthening than during passive lengthening and (ii) larger for subjects with a relatively narrow proximal aponeurosis than a wide proximal aponeurosis. Displacement color maps showed higher tissue displacement with increasing lateral distance from the proximal aponeurosis for both active lengthening and passive lengthening, and higher tissue displacement for active lengthening than passive lengthening. First principal strain magnitudes were averaged in a 1cm region near the myotendinous junction, where injury is most frequently observed. It was found that strains are significantly larger during active lengthening (0.19SD0.09) than passive lengthening (0.13SD0.06) (p<0.05), which suggests that elevated localized strains may be a mechanism for increased injury risk during active as opposed to passive lengthening. First principal strains were higher for subjects with a relatively narrow aponeurosis width (0.26SD 0.15) than wide (0.14SD 0.04) (p<0.05). This result suggests that athletes who have BFLH muscles with narrow proximal aponeuroses may have an increased risk for BFLH strain injuries.

The hamstring muscles frequently suffer injury during high-speed running, though the factors that make an individual more susceptible to injury remain poorly understood. The goals of this study were to measure the musculotendon dimensions of the biceps femoris long head (BFlh) muscle, the hamstring muscle injured most often, and to use computational models to assess the influence of variability in the BFlh’s dimensions on internal tissue strains during high-speed running. High-resolution magnetic resonance (MR) images were acquired over the thigh in 12 collegiate athletes, and musculotendon dimensions were measured in the proximal free tendon/aponeurosis, muscle and distal free tendon/aponeurosis. Finite element meshes were generated based on the average, standard deviation and range of BFlh dimensions. Simulation boundary conditions were defined to match muscle activation and musculotendon length change in the BFlh during high-speed running. Muscle and connective tissue dimensions were found to vary between subjects, with a coefficient of variation (CV) of 17±6% across all dimensions. For all simulations peak local strain was highest along the proximal myotendinous junction, which is where injury typically occurs. Model variations showed that peak local tissue strain increased as the proximal aponeurosis width narrowed and the muscle width widened. The aponeurosis width and muscle width variation models showed that the relative dimensions of these structures influence internal muscle tissue strains. The results of this study indicate that a musculotendon unit’s architecture influences its strain injury susceptibility during high-speed running.

Rigid body musculoskeletal models have been applied to study kinematics, moments, muscle forces, and joint reaction forces in the hip. Most often, models are driven with segment motions calculated through optical tracking of markers adhered to the skin. One limitation of optical tracking is soft tissue artifact (STA), which occurs due to motion of the skin surface relative to the underlying skeleton. The purpose of this study was to quantify differences in musculoskeletal model outputs when tracking body segment positions with skin markers as compared to bony landmarks measured by direct imaging of bone motion with dual fluoroscopy (DF). Eleven asymptomatic participants with normally developed hip anatomy were imaged with DF during level treadmill walking at a self-selected speed. Hip joint kinematics and kinetics were generated using inverse kinematics, inverse dynamics, static optimization and joint reaction force analysis. The effect of STA was assessed by comparing the difference in estimates from simulations based on skin marker positions (SM) versus virtual markers on bony landmarks from DF. While patterns were similar, STA caused underestimation of kinematics, range of motion (ROM), moments, and reaction forces at the hip, including flexion-extension ROM, maximum internal rotation joint moment and peak joint reaction force magnitude. Still, kinetic differences were relatively small, and thus they may not be relevant nor clinically meaningful.

Abnormal loading is thought to play a key role in the disease progression of cartilage, but our understanding of how cartilage compositional measurements respond to acute compressive loading in-vivo is limited. Ten healthy subjects were scanned at two timepoints (7 ± 3 days apart) with a 3 T magnetic resonance imaging (MRI) scanner. Scanning sessions included T1ρ and T2* acquisitions of each knee in two conditions: unloaded (traditional MRI setup) and loaded in compression at 40 % bodyweight as applied by an MRI-compatible loading device. T1ρ and T2* parameters were quantified for contacting cartilage (tibial and femoral) and non-contacting cartilage (posterior femoral condyle) regions. Significant effects of load were found in contacting regions for both T1ρ and T2*. The effect of load (loaded minus unloaded) in femoral contacting regions ranged from 4.1 to 6.9 ms for T1ρ, and 3.5 to 13.7 ms for T2*, whereas tibial contacting regions ranged from −5.6 to −1.7 ms for T1ρ, and −2.1 to 0.7 ms for T2*. Notably, the responses to load in the femoral and tibial cartilage revealed opposite effects. No significant differences were found in response to load between the two visits. This is the first study that analyzed the effects of acute loading on T1ρ and T2* measurements in human femoral and tibial cartilage separately. The results suggest the effect of acute compressive loading on T1ρ and T2* was: 1) opposite in the femoral and tibial cartilage; 2) larger in contacting regions than in non-contacting regions of the femoral cartilage; and 3) not different visit-to-visit.

A crucial step in understanding the onset and progression of cartilaginous disease, such as osteoarthritis, is to study how cartilage mechanics and composition relate in response to controlled loading in disease-free joints. Both knees of 10 healthy participants were imaged with a 3 T magnetic resonance imaging (MRI) scanner at two timepoints (7 ± 3 days apart). Quantitative MR images for T1ρ and T2* were acquired with the knee in two states: i) a traditional setup without load applied, and ii) while a loading device applied a 40% bodyweight load to the plantar aspect of the foot. Associations between mechanical metrics (cartilage deformation, cartilage strain, change in bone-bone distance, and change in cartilage contact area) and compositional metrics (T1ρ and T2* relaxation times) were identified. Significant decreases in bone-bone distance were seen in all compartments in response to load. Articular cartilage thickness consistently decreased, but differences were significant for only half of the medial and lateral compartments in the tibia and femur. Strains ranged from 4.9% in compression to 0.3% in tension. No significant changes were found in cartilage contact area. T1ρ and T2* relaxation times changed significantly with the application of load, with the femoral and tibial cartilage exhibiting opposite responses. No significant associations were observed between mechanical and compositional metrics for T1ρ scans, but T2* scans had three significant relationships. Results from this work demonstrate that loading can induce tibiofemoral articular cartilage composition changes, as assessed with T1ρ and T2*, even with small magnitude measurements of mechanics.

Predictions from biomechanical models of gait may be sensitive to joint center locations. Most often, the hip joint center (HJC) is derived from locations of reflective markers adhered to the skin. Here, predictive techniques use regression equations of pelvic anatomy to estimate the HJC, whereas functional methods track motion of markers placed at the pelvis and femur during a coordinated motion. Skin motion artifact may introduce errors in the estimate of HJC for both techniques. Quantifying the accuracy of these methods is an area of open investigation. In this study, we used dual fluoroscopy (DF) (a dynamic X-ray imaging technique) and three-dimensional reconstructions from computed tomography images, to measure HJC locations in vivo . Using dual fluoroscopy as the reference standard, we then assessed the accuracy of three predictive and two functional methods. Eleven non-pathologic subjects were imaged with DF and reflective skin marker motion capture. Additionally, DF-based solutions generated virtual markers placed on bony landmarks, which were input to the predictive and functional methods to determine if estimates of the HJC improved. Using skin markers, functional methods had better mean agreement with the HJC measured by DF (11.0 ± 3.3 mm) than predictive methods (18.1 ± 9.5 mm); estimates from functional and predictive methods improved when using the DF-based solutions (1.3 ± 0.9 and 17.5 ± 8.6 mm, respectively). The Harrington method was the best predictive technique using both skin markers (13.2 ± 6.5 mm) and DF-based solutions (10.6 ± 2.5 mm). The two functional methods had similar accuracy using skin makers (11.1 ± 3.6 and 10.8 ± 3.2 mm) and DF-based solutions (1.2 ± 0.8 and 1.4 ± 1.0 mm). Overall, functional methods were superior to predictive methods for HJC estimation. However, the improvements observed when using the DF-based solutions suggest that skin motion artifact is a large source of error for the functional methods.

Femoroacetabular impingement syndrome (FAIS) is a motion-related pathology of the hip characterized by pain, morphological abnormalities of the proximal femur, and an elevated risk of joint deterioration and hip osteoarthritis. Activities that require deep flexion are understood to induce impingement in cam FAIS patients, however, less demanding activities such as walking and pivoting may induce pain as well as alterations in kinematics and joint stability. Still, the paucity of quantitative descriptions of cam FAIS has hindered understanding underlying hip joint mechanics during such activities. Previous in silico studies have employed generalized model geometry or kinematics to simulate impingement between the femur and acetabulum, which may not accurately capture the interplay between morphology and motion. In this study, we utilized models with participant-specific bone and articular soft tissue anatomy and kinematics measured by dual-fluoroscopy to compare hip contact mechanics of cam FAIS patients to controls during four activities of daily living (internal/external pivoting and level/incline walking). Averaged across the gait cycle during incline walking, patients displayed increased strain in the anterior joint (labrum strain: p-value = 0.038, patients: 11.7 ± 6.7 %, controls: 5.0 ± 3.6 %; cartilage strain: p-value = 0.029, patients: 9.1 ± 3.3 %, controls: 4.2 ± 2.3). Patients also exhibited increased average anterior cartilage strains during external pivoting (p-value = 0.039; patients: 13.0 ± 9.2 %, controls: 3.9 ± 3.2 %]). No significant differences between patient and control contact area and strain were found for level walking and internal pivoting. Our study provides new insights into the biomechanics of cam FAIS, including spatiotemporal hip joint contact mechanics during activities of daily living.

Use of subject-specific axes of rotation may improve predictions generated by kinematic models, especially for joints with complex anatomy, such as the tibiotalar and subtalar joints of the ankle. The objective of this study was twofold. First, we compared the axes of rotation between generic and subject-specific ankle models for ten control subjects. Second, we quantified the accuracy of generic and subject-specific models for predicting tibiotalar and subtalar joint motion during level walking using inverse kinematics. Here, tibiotalar and subtalar joint kinematics measured in vivo by dual-fluoroscopy served as the reference standard. The generic model was based on a cadaver study, while the subject-specific models were derived from each subject’s talus reconstructed from computed tomography images. The subject-specific and generic axes of rotation were significantly different. The average angle between the modeled axes was 12.9° ± 4.3° and 24.4° ± 5.9° at the tibiotalar and subtalar joints, respectively. However, predictions from both models did not agree well with dynamic dual-fluoroscopy data, where errors ranged from 1.0° to 8.9° and 0.6° to 7.6° for the generic and subject-specific models, respectively. Our results suggest that methods that rely on talar morphology to define subject-specific axes may be inadequate for accurately predicting tibiotalar and subtalar joint kinematics.

Category: Ankle Introduction/Purpose: Measurements of joint angles and translations (i.e. kinematics) are essential to understand the pathomechanics of ankle disease and functional changes following treatment. Traditional motion capture techniques, which track the positions of reflective markers adhered to the skin, cannot measure motion of the tibiotalar and subtalar joints independent of one another. To overcome this limitation, we used high-speed dual fluoroscopy (DF), an x-ray videography technique, to quantify in-vivo kinematics of healthy asymptomatic ankles during activities of daily living. Using these kinematics as baseline data, our secondary objective was to assess preliminary kinematic differences between chronic ankle instability (CAI) patients and asymptomatic control subjects. Methods: High-speed DF images of the hindfoot of ten healthy, asymptomatic adults and four adults with CAI were acquired during treadmill walking at 0.5 m/s and 1.0 m/s and during a single-leg, balanced heel-rise. Three-dimensional (3D) CT models of the calcaneus, tibia, and talus and DF images served as input to the validated model-based markerless tracking software that quantified in vivo kinematics for the tibiotalar and subtalar joints. Dynamic joint kinematics and mean range of motion (ROM) were calculated and reported as dorsi/plantarflexion (D/P), inversion/eversion (In/Ev) and internal/external rotation (IR/ER) angles or translations along the medial/lateral (ML), anterior/posterior (AP), and superior/inferior (SI) directions. Results: During gait, the tibiotalar joint had significantly greater D/P ROM than the subtalar joint (0.5 m/s: p=0.004; 1.0 m/s: p=0.003). The subtalar joint had significantly greater In/Ev (0.5 m/s: p < 0.001; 1.0 m/s: p < 0.001) and IR/ER (0.5 m/s: p=0.01; 1.0 m/s: p=0.02) ROM than the tibiotalar joint. However, during balanced heel-rise, D/P and In/Ev were significantly different between the two joints (p < 0.001; p < 0.001). For AP translation, subtalar ROM was significantly greater than tibiotalar ROM during walking at 0.5m/s (p=0.002). CAI patients often demonstrated rotational profiles with dynamic trends that fell outside the 95% confidence intervals of the asymptomatic subjects (Figure 1). CAI patients exhibited smaller ROM than asymptomatic subjects. However, only 0.5 m/s tibiotalar SI translational (p=0.049) and 1.0 m/s subtalar In/Ev (p=0.03) ROM were significant. Conclusion: To our knowledge, this is the first study to quantify in-vivo joint angles and translations in asymptomatic and CAI subjects. Our results support the belief that the tibiotalar joint is primarily responsible for D/P, while the subtalar joint facilitates In/Ev and IR/ER. Secondary rotational contributions suggest that both joints undergo complex, 3D motion. Our comparison of CAI and asymptomatic subjects is not conclusive, yet suggests that a larger sample size will detect significant differences. With a larger sample size, dual-fluoroscopy may provide insight into the clinical relevance of altered kinematics and the pathomechanics responsible for ankle instability and other pathologies.