An elaborate data set characterizing the mechanical response of the foot

Two-team-approached free flap reconstruction for plantar malignant melanoma: An observational (STROBE-compliant) trial

Reconstructive treatments of heel defects usually involve regional flap techniques such as medial plantar flap procedures due to the limited availability of adjacent soft tissues. Although free flaps have advantages in terms of function and aesthetics, they remain challenging due to the longer operation time required than for regional flaps. Thus, we introduce an appropriate 2-team surgical protocol to reconstruct plantar defects after wide excision of malignant melanoma using free flap coverage. From 2015 to 2020, a retrospective study was performed including 21 patients who underwent free flap surgeries to reconstruct defects due to plantar malignant melanoma. Lymphoscintigraphy was performed to localize sentinel lymph nodes, and the procedure was carried out by 2 teams working together, a tumor-ablative team and a reconstructive team. The present study is adhered to the STROBE guidelines for cohort studies. The average operation time was 241.4 minutes and was not significantly different even in cases with inguinal dissection (P value: 0.641). All flaps survived after 2 cases of venous insufficiency and 1 case of hematoma were resolved by immediate revision surgery. The 2-team approach to surgically reconstruct heel defects after wide excision of malignant melanoma using free flap coverage offers favorable results and lower morbidity than regional flap approaches.

Computational methods for the investigation of ski boots ergonomics

Ski boots are known to cause vasoconstriction in the wearer’s lower limbs and, thus, cause a “cold leg” phenomenon. To address this problem, this work provides a computational framework for analysing interactions between the ski boot and the lower limb. The geometry of the lower limb was derived from magnetic resonance imaging and computed tomography techniques and anthropometric data. The geometry of the ski boot shell was obtained by means of three-dimensional computer aided design models from a manufacturer. Concerning the ski boot liner, laser scanning techniques were implemented to capture the geometry of each layer. The mechanical models of the ski boot and the lower limb were identified and validated by means of coupled experimental investigations and computational analyses. The computational models were exploited to simulate the buckling process and to investigate interaction phenomena between the boot and the lower limb. Similarly, experimental activities were performed to further analyse the buckling phenomena. The obtained computational and experimental results were compared regarding both interaction pressure and displacements between the buckle and the corresponding buckle hooks. These comparisons provided reasonable agreement (mean value of discrepancy between the model and mean experimental results in the tibial region: 20%), underlining the model’s capability to correctly interpret results from experimental measurements. Results identified the critical areas of the leg, such as the tibial region, the calcaneal region of the foot and the anterior sole, which may suffer the most due to the hydrostatic pressure and compressive strain exerted on them. The results highlight that computational methods allow investigation of the interaction phenomena between the lower leg and ski boot, potentially providing an effective framework for a more comfortable and ergonomic design of ski boots.

Postural control of a musculoskeletal model against multidirectional support surface translations

The human body is a complex system driven by hundreds of muscles, and its control mechanisms are not sufficiently understood. To understand the mechanisms of human postural control, neural controller models have been proposed by different research groups, including our feed-forward and feedback control model. However, these models have been evaluated under forward and backward perturbations, at most. Because a human body experiences perturbations from many different directions in daily life, neural controller models should be evaluated in response to multidirectional perturbations, including in the forward/backward, lateral, and diagonal directions. The objective of this study was to investigate the validity of an NC model with FF and FB control under multidirectional perturbations. We developed a musculoskeletal model with 70 muscles and 15 degrees of freedom of joints, positioned it in a standing posture by using the neural controller model, and translated its support surface in multiple directions as perturbations. We successfully determined the parameters of the neural controller model required to maintain the stance of the musculoskeletal model for each perturbation direction. The trends in muscle response magnitudes and the magnitude of passive ankle stiffness were consistent with the results of experimental studies. We conclude that the neural controller model can adapt to multidirectional perturbations by generating suitable muscle activations. We anticipate that the neural controller model could be applied to the study of the control mechanisms of patients with torso tilt and diagnosis of the change in control mechanisms from patients' behaviors.

Musculoskeletal Simulation for Determining Influences of the Magnitude of Sensory Noise and Stiffness on the Selection of Hip or Ankle Movement Strategies

While standing, the elderly exhibit different move- ment behaviors compared to young people. However, the causes of these differences remain clear. The purpose of this study was to verify a hypothesis that only the magnitude of sensory noise and stiffness can reproducibly determine trends in the hip or ankle movement strategies. Simulations of postural control of a musculoskeletal model for three noise conditions and three stiffness conditions were performed. Variations in the angles of the hip and ankle suggested that the sensory noise amplitude had no influence on the selection. However, the ankle strategy tended to be selected with the increase of stiffness. Strategy shifts of elderly may be derived from other components; muscle weakness, increase of neurological time delay, or learning based on other evaluation index.

Preparatory co-activation of the ankle muscles may prevent ankle inversion injuries

Ankle inversion sprains are the most frequent acute musculoskeletal injuries occurring in physical activity. Interventions that retrain muscle coordination have helped rehabilitate injured ankles, but it is unclear which muscle coordination strategies, if any, can prevent ankle sprains. The purpose of this study was to determine whether coordinated activity of the ankle muscles could prevent excessive ankle inversion during a simulated landing on a 30° incline. We used a set of musculoskeletal simulations to evaluate the efficacy of two strategies for coordinating the ankle evertor and invertor muscles during simulated landing scenarios: planned co-activation and stretch reflex activation with physiologic latency (60-ms delay). A full-body musculoskeletal model of landing was used to generate simulations of a subject dropping onto an inclined surface with each coordination condition. Within each condition, the intensity of evertor and invertor co-activity or stretch reflexes were varied systematically. The simulations revealed that strong preparatory co-activation of the ankle evertors and invertors prior to ground contact prevented ankle inversion from exceeding injury thresholds by rapidly generating eversion moments after initial contact. Conversely, stretch reflexes were too slow to generate eversion moments before the simulations reached the threshold for inversion injury. These results suggest that training interventions to protect the ankle should focus on stiffening the ankle with muscle co-activation prior to landing. The musculoskeletal models, controllers, software, and simulation results are freely available online at http://simtk.org/home/ankle-sprains, enabling others to reproduce the results and explore new injury scenarios and interventions.

Material properties of the heel fat pad across strain rates

The complex structural and material behaviour of the human heel fat pad determines the transmission of plantar loading to the lower limb across a wide range of loading scenarios; from locomotion to injurious incidents. The aim of this study was to quantify the hyper-viscoelastic material properties of the human heel fat pad across strains and strain rates. An inverse finite element (FE) optimisation algorithm was developed and used, in conjunction with quasi-static and dynamic tests performed to five cadaveric heel specimens, to derive specimen-specific and mean hyper-viscoelastic material models able to predict accurately the response of the tissue at compressive loading of strain rates up to 150 s⁻¹. The mean behaviour was expressed by the quasi-linear viscoelastic (QLV) material formulation, combining the Yeoh material model (C10=0.1MPa, C30=7MPa, K=2GPa) and Prony׳s terms (A1=0.06, A2=0.77, A3=0.02 for τ1=1ms, τ2=10ms, τ3=10s). These new data help to understand better the functional anatomy and pathophysiology of the foot and ankle, develop biomimetic materials for tissue reconstruction, design of shoe, insole, and foot and ankle orthoses, and improve the predictive ability of computational models of the foot and ankle used to simulate daily activities or predict injuries at high rate injurious incidents such as road traffic accidents and underbody blast.

A stereologic study of the plantar fat pad in young and aged rats

Plantar fat pad (PFP) is a tissue structure that absorbs the initial impact of walking and running and ultimately bears body weight at standing. This study was designed to quantify the histomorphological changes of the PFP in aged rats. The most medial PFP was dissected from the hind feet of young rats (4 months old, n = 6) and aged rats (24 months old, n = 6). Histological structure and cellular senescence of PFP were analyzed stereologically and histomorphometrically. Immunohistochemistry of matrix metalloproteinase 9 (MMP9) was also performed on PFP tissue sections. Compared with young rats, the thickness of epidermis, dermis and septa of the PFP were significantly reduced in the aged rats. The total volume of adipose tissue in the PFP of aged rats was only about 65% of that in the young rats. The microvascular density and the number of fat pad units (FPU), a cluster of adipocytes enclosed by elastin septa, in the PFP were unchanged in the aged rats. In the aged rats, the number of adipocytes per FPU was reduced but the number of simple adipocyte clusters, without surrounding septa, was increased. The shift of the types of adipocyte clusters in the aged PFP was accompanied by degradation of elastin fibers and increased expression of MMP9. In conclusion, the PFP, particularly the elastic septa, degenerates significantly in aged rats and this may contribute to the pathology of PFP-related diseases.

A three-dimensional inverse finite element analysis of the heel pad

Quantification of plantar tissue behavior of the heel pad is essential in developing computational models for predictive analysis of preventive treatment options such as footwear for patients with diabetes. Simulation based studies in the past have generally adopted heel pad properties from the literature, in return using heel-specific geometry with material properties of a different heel. In exceptional cases, patient-specific material characterization was performed with simplified two-dimensional models, without further evaluation of a heel-specific response under different loading conditions. The aim of this study was to conduct an inverse finite element analysis of the heel in order to calculate heel-specific material properties in situ. Multidimensional experimental data available from a previous cadaver study by Erdemir et al. ("An Elaborate Data Set Characterizing the Mechanical Response of the Foot," ASME J. Biomech. Eng., 131(9), pp. 094502) was used for model development, optimization, and evaluation of material properties. A specimen-specific three-dimensional finite element representation was developed. Heel pad material properties were determined using inverse finite element analysis by fitting the model behavior to the experimental data. Compression dominant loading, applied using a spherical indenter, was used for optimization of the material properties. The optimized material properties were evaluated through simulations representative of a combined loading scenario (compression and anterior-posterior shear) with a spherical indenter and also of a compression dominant loading applied using an elevated platform. Optimized heel pad material coefficients were 0.001084 MPa (μ), 9.780 (α) (with an effective Poisson's ratio (ν) of 0.475), for a first-order nearly incompressible Ogden material model. The model predicted structural response of the heel pad was in good agreement for both the optimization (<1.05% maximum tool force, 0.9% maximum tool displacement) and validation cases (6.5% maximum tool force, 15% maximum tool displacement). The inverse analysis successfully predicted the material properties for the given specimen-specific heel pad using the experimental data for the specimen. The modeling framework and results can be used for accurate predictions of the three-dimensional interaction of the heel pad with its surroundings.

Adaptive surrogate modeling for expedited estimation of nonlinear tissue properties through inverse finite element analysis

Simulation-based prediction of specimen-specific biomechanical behavior commonly requires inverse analysis using geometrically consistent finite element (FE) models. Optimization drives such analyses but previous studies have highlighted a large computational cost dictated by iterative use of nonlinear FE models. The goal of this study was to evaluate the performance of a local regression-based adaptive surrogate modeling approach to decrease computational cost for both global and local optimization approaches using an inverse FE application. Nonlinear elastic material parameters for patient-specific heel-pad tissue were found, both with and without the surrogate model. Surrogate prediction replaced a FE simulation using local regression of previous simulations when the corresponding error estimate was less than a given tolerance. Performance depended on optimization type and tolerance value. The surrogate reduced local optimization expense up to 68%, but achieved accurate results for only 1 of 20 initial conditions. Conversely, up to a tolerance value of 20 N(2), global optimization with the surrogate yielded consistent parameter predictions with a concurrent decrease in computational cost (up to 77%). However, the local optimization method without the surrogate, although sensitive to the initial conditions, was still on average seven times faster than the global approach. Our results help establish guidelines for setting acceptable tolerance values while using an adaptive surrogate model for inverse FE analysis. Most important, the study demonstrates the benefits of a surrogate modeling approach for intensive FE-based iterative analysis.

Concurrent musculoskeletal dynamics and finite element analysis predicts altered gait patterns to reduce foot tissue loading

Current computational methods for simulating locomotion have primarily used muscle-driven multibody dynamics, in which neuromuscular control is optimized. Such simulations generally represent joints and soft tissue as simple kinematic or elastic elements for computational efficiency. These assumptions limit application in studies such as ligament injury or osteoarthritis, where local tissue loading must be predicted. Conversely, tissue can be simulated using the finite element method with assumed or measured boundary conditions, but this does not represent the effects of whole body dynamics and neuromuscular control. Coupling the two domains would overcome these limitations and allow prediction of movement strategies guided by tissue stresses. Here we demonstrate this concept in a gait simulation where a musculoskeletal model is coupled to a finite element representation of the foot. Predictive simulations incorporated peak plantar tissue deformation into the objective of the movement optimization, as well as terms to track normative gait data and minimize fatigue. Two optimizations were performed, first without the strain minimization term and second with the term. Convergence to realistic gait patterns was achieved with the second optimization realizing a 44% reduction in peak tissue strain energy density. The study demonstrated that it is possible to alter computationally predicted neuromuscular control to minimize tissue strain while including desired kinematic and muscular behavior. Future work should include experimental validation before application of the methodology to patient care.