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Research Papers

J Biomech Eng. 2019;141(10):101001-101001-9. doi:10.1115/1.4043869.

The anthropometries of elite wheelchair racing athletes differ from the generic, able-bodied anthropometries commonly used in computational biomechanical simulations. The impact of using able-bodied parameters on the accuracy of simulations involving wheelchair racing is currently unknown. In this study, athlete-specific mass segment inertial parameters of the head and neck, torso, upper arm, forearm, hand, thigh, shank, and feet for five elite wheelchair athletes were calculated using dual-energy X-ray absorptiometry (DXA) scans. These were compared against commonly used anthropometrics parameters of data presented in the literature. A computational biomechanical simulation of wheelchair propulsion using the upper extremity dynamic model in opensim assessed the sensitivity of athlete-specific mass parameters using Kruskal–Wallis analysis and Spearman correlations. Substantial between-athlete body mass distribution variances (thigh mass between 7.8% and 22.4% total body mass) and between-limb asymmetries (<62.4% segment mass; 3.1 kg) were observed. Compared to nonathletic able-bodied anthropometric data, wheelchair racing athletes demonstrated greater mass in the upper extremities (up to 3.8% total body mass) and less in the lower extremities (up to 9.8% total body mass). Computational simulations were sensitive to individual body mass distribution, with joint torques increasing by up to 31.5% when the scaling of segment masses (measured or generic) differed by up to 2.3% total body mass. These data suggest that nonathletic, able-bodied mass segment inertial parameters are inappropriate for analyzing elite wheelchair racing motion.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2019;141(10):101002-101002-9. doi:10.1115/1.4043664.

Prosthetic valve thrombosis (PVT) is a serious complication affecting prosthetic heart valves. The transvalvular mean pressure gradient (MPG) derived by Doppler echocardiography is a crucial index to diagnose PVT but may result in false negatives mainly in case of bileaflet mechanical valves (BMVs) in mitral position. This may happen because MPG estimation relies on simplifying assumptions on the transvalvular fluid dynamics or because Doppler examination is manual and operator dependent. A deeper understanding of these issues may allow for improving PVT diagnosis and management. To this aim, we used in vitro and fluid–structure interaction (FSI) modeling to simulate the function of a real mitral BMV in different configurations: normally functioning and stenotic with symmetric and completely asymmetric leaflet opening, respectively. In each condition, the MPG was measured in vitro, computed directly from FSI simulations and derived from the corresponding velocity field through a Doppler-like postprocessing approach. Following verification versus in vitro data, MPG computational data were analyzed to test their dependency on the severity of fluid-dynamic derangements and on the measurement site. Computed MPG clearly discriminated between normally functioning and stenotic configurations. They did not depend markedly on the site of measurement, yet differences below 3 mmHg were found between MPG values at the central and lateral orifices of the BMV. This evidence suggests a mild uncertainty of the Doppler-based evaluation of the MPG due to probe positioning, which yet may lead to false negatives when analyzing subjects with almost normal MPG.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2019;141(10):101003-101003-6. doi:10.1115/1.4043969.

As the use of glenoid suture anchors in arthroscopic and open reconstruction, for instability after Bankart lesions of the shoulder, increases, an emerging problem has been the incidence of glenoid rim fractures through suture drill holes. Very little is known regarding the effect of the Hill–Sachs lesion on the glenoid's susceptibility to fracture and how drill hole location can further affect this. This study used finite element modeling techniques to investigate the risk of fracture of the glenoid rim in relation to variable sized Hill–Sachs defects impacting on the anterior glenoid edge with suture anchor holes placed in varying positions. The distribution of Von Mises (VM) stresses and the factor of safety (FOS) for each of the configurations were calculated. The greatest peak in VM stresses was generated when the glenoid was loaded with a small Hill–Sachs lesion. The VM stresses were lessened and the FOS increased (reducing likelihood of failure) with increasing size of the Hill–Sachs lesion. Placement of the suture drill holes at 2 mm from the glenoid rim showed the highest risk of failure; and when combined with a medium sized Hill–Sachs lesion, which matched the central line of the drill holes, a potentially clinically significant configuration was presented. The results of this study are useful in assisting the surgeon in understanding the interaction between the Hill–Sachs lesion size and the placement of suture anchors with the purpose of minimizing the risk of subsequent rim fracture with new injury.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2019;141(10):101004-101004-10. doi:10.1115/1.4043259.

This paper presents in vivo mechanical characterization of the muscularis, submucosa, and mucosa of the porcine stomach wall under large deformation loading. This is particularly important for the development of gastrointestinal pathology-specific surgical intervention techniques. The study is based on testing the cardiac and fundic glandular stomach regions using a custom-developed compression ultrasound elastography system. Particular attention has been paid to elucidate the heterogeneity and anisotropy of tissue response. A Fung hyperelastic material model has been used to model the mechanical response of each tissue layer. A univariate analysis comparing the initial shear moduli of the three layers indicates that the muscularis (5.69 ± 4.06 kPa) is the stiffest followed by the submucosa (3.04 ± 3.32 kPa) and the mucosa (0.56 ± 0.28 kPa). The muscularis is found to be strongly distinguishable from the mucosa tissue in the cardiac and fundic regions based on a multivariate discriminant analysis. The cardiac muscularis is observed to be stiffer than the fundic muscularis tissue (shear moduli of 7.96 ± 3.82 kPa versus 3.42 ± 2.96 kPa), more anisotropic (anisotropic parameter of 2.21 ± 0.77 versus 1.41 ± 0.38), and strongly distinguishable from its fundic counterpart. The results are consistent with the tissue morphology and are in accordance with our previous ex vivo tissue study. Finally, a univariate comparison of the in vivo and ex vivo initial shear moduli for each layer shows that the muscularis and submucosa tissues are softer while in vivo, but the mucosa tissue is stiffer while in vivo. The results concerning the mechanical properties highlight the inhomogeneity and anisotropy of multilayer stomach tissue.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2019;141(10):101005-101005-10. doi:10.1115/1.4043441.

Multibody kinematic optimization is frequently used to assess shoulder kinematics during manual wheelchair (MWC) propulsion, but multiple kinematics chains are available. It is hypothesized that these different kinematic chains affect marker tracking, shoulder kinematics, and resulting musculotendon (MT) lengths. In this study, shoulder kinematics and MT lengths obtained from four shoulder kinematic chains (open-loop thorax-clavicle-scapula-humerus (M1), closed-loop with contact ellipsoid (M2), scapula rhythm from regression equations (M3), and a single ball-and- socket joint between the thorax and the humerus (M4) were compared. Right-side shoulder kinematics from seven subjects were obtained with 34 reflective markers and a scapula locator using an optoelectronic motion capture system while propelling on a MWC simulator. Data were processed based on the four models. The results showed the impact of shoulder kinematic chains on all studied variables. Marker reconstruction errors were found to be similar between M1 and M2 and lower than for M3 and M4. Few degrees-of-freedom (DoF) were noticeably different between M1 and M2, but all shoulder DoFs were significantly affected between M1 and M4. As a consequence of differences in joint kinematics, MT lengths were affected by the kinematic chain definition. The contact ellipsoid (M2) was found as a good trade-off between marker tracking and penetration avoidance of the scapula. The regression-based model (M3) was less efficient due to limited humerus elevation during MWC propulsion, as well as the ball-and-socket model (M4) which appeared not suitable for upper limbs activities, including MWC propulsion.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2019;141(10):101006-101006-10. doi:10.1115/1.4043755.

Currently available knee joint kinematic tracking systems fail to nondestructively capture the subtle variation in joint and soft tissue kinematics that occur in native, injured, and reconstructed joint states. Microcomputed tomography (CT) imaging has the potential as a noninvasive, high-resolution kinematic tracking system, but no dynamic simulators exist to take advantage of this. The purpose of this work was to develop and assess a novel micro-CT compatible knee joint simulator to quantify the knee joint's kinematic and kinetic response to clinically (e.g., pivot shift test) and functionally (e.g., gait) relevant loading. The simulator applies closed-loop, load control over four degrees-of-freedom (DOF) (internal/external rotation, varus/valgus rotation, anterior/posterior translation, and compression/distraction), and static control over a fifth degree-of-freedom (flexion/extension). Simulator accuracy (e.g., load error) and repeatability (e.g., coefficient of variation) were assessed with a cylindrical rubber tubing structure and a human cadaveric knee joint by applying clinically and functionally relevant loads along all active axes. Micro-CT images acquired of the joint at a loaded state were then used to calculate joint kinematics. The simulator loaded both the rubber tubing and the cadaveric specimen to within 0.1% of the load target, with an intertrial coefficient of variation below 0.1% for all clinically relevant loading protocols. The resultant kinematics calculated from the acquired images agreed with previously published values, and produced errors of 1.66 mm, 0.90 mm, 4.41 deg, and 1.60 deg with respect to anterior translation, compression, internal rotation, and valgus rotation, respectively. All images were free of artifacts and showed knee joint displacements in response to clinically and functionally loading with isotropic CT image voxel spacing of 0.15 mm. The results of this study demonstrate that the joint-motion simulator is capable of applying accurate, clinically and functionally relevant loads to cadaveric knee joints, concurrent with micro-CT imaging. Nondestructive tracking of bony landmarks allows for the precise calculation of joint kinematics with less error than traditional optical tracking systems.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2019;141(10):101007-101007-12. doi:10.1115/1.4043832.

Atrial fibrillation (AF) is the most common irregular heartbeat among the world's population and is a major contributor to cardiogenic embolisms and acute ischemic stroke (AIS). However, the role AF flow plays in the trajectory paths of cardiogenic emboli has not been experimentally investigated. A physiological simulation system was designed to analyze the trajectory patterns of bovine embolus analogs (EAs) (n = 720) through four patient-specific models, under three flow conditions: steady flow, normal pulsatile flow, and AF pulsatile flow. It was seen that EA trajectory paths were proportional to the percentage flowrate split of 25–31% along the branching vessels. Overall, AF flow conditions increased trajectories through the left- (LCCA) and right (RCCA)-common carotid artery by 25% with respect to normal pulsatile flow. There was no statistical difference in the distribution of clot trajectories when the clot was released from the right, left, or anterior positions. Significantly, more EAs traveled through the brachiocephalic trunk (BCT) than through the LCCA or the left subclavian. Yet of the EAs that traveled through the common carotid arteries, there was a greater affiliation toward the LCCA compared to the RCCA (p < 0.05).

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2019;141(10):101008-101008-10. doi:10.1115/1.4043520.

Inelastic behaviors, such as softening, a progressive decrease in modulus before failure, occur in tendon and are important aspects in degeneration and tendinopathy. These inelastic behaviors are generally attributed to two potential mechanisms: plastic deformation and damage. However, it is not clear which is primarily responsible. In this study, we evaluated these potential mechanisms of tendon inelasticity by using a recently developed reactive inelasticity model (RIE), which is a structurally inspired continuum mechanics framework that models tissue inelasticity based on the molecular bond kinetics. Using RIE, we formulated two material models, one specific to plastic deformation and the other to damage. The models were independently fit to published macroscale experimental tensile tests of rat tail tendons. We quantified the inelastic effects and compared the performance of the two models in fitting the mechanical response during loading, relaxation, unloading, and reloading phases. Additionally, we validated the models by using the resulting fit parameters to predict an independent set of experimental stress–strain curves from ramp-to-failure tests. Overall, the models were both successful in fitting the experiments and predicting the validation data. However, the results did not strongly favor one mechanism over the other. As a result, to distinguish between plastic deformation and damage, different experimental protocols will be needed. Nevertheless, these findings suggest the potential of RIE as a comprehensive framework for studying tendon inelastic behaviors.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2019;141(10):101009-101009-13. doi:10.1115/1.4043561.

Understanding the pressure distributions at the limb-socket interface is essential to the design and evaluation of prosthetic components for lower limb prosthesis users. Force sensing resistors (FSRs) are employed in prosthetics research to measure pressure at this interface due to their low cost, thin profile, and ease of use. While FSRs are known to be sensitive to many sources of error, few studies have systematically quantified these errors using test conditions relevant to lower limb prosthetics. The purpose of this study was to evaluate FSR accuracy for the measurement of lower limb prosthetics interface pressures. Two FSR models (Flexiforce A201 and Interlink 402) were subjected to a series of prosthetic-relevant tests. These tests included: (1) static compression, (2) cyclic compression, and (3) a combined static and cyclic compression protocol mimicking a variable activity (walk–sit–stand) procedure. Flexiforce sensors outperformed Interlink sensors and were then subjected to two additional tests: (4) static curvature and (5) static shear stress. Results demonstrated that FSRs experienced significant errors in all five tests. We concluded that: (1) if used carefully, FSRs can provide an estimate of prosthetic interface pressure, but these measurements should be interpreted within the expected range of possible measurement error given the setup; (2) FSRs should be calibrated in a setup that closely matches how they will be used for taking measurements; and (3) both Flexiforce and Interlink sensors can be used to estimate interface pressures; however, in most cases Flexiforce sensors are likely to provide more accurate measurements.

Commentary by Dr. Valentin Fuster

Technical Brief

J Biomech Eng. 2019;141(10):104501-104501-8. doi:10.1115/1.4043076.

The arterial input function (AIF)—time-density curve (TDC) of contrast at the coronary ostia—plays a central role in contrast enhanced computed tomography angiography (CTA). This study employs computational modeling in a patient-specific aorta to investigate mixing and dispersion of contrast in the aortic arch (AA) and to compare the TDCs in the coronary ostium and the descending aorta. Here, we examine the validity of the use of TDC in the descending aorta as a surrogate for the AIF. Computational fluid dynamics (CFD) was used to study hemodynamics and contrast dispersion in a CTA-based patient model of the aorta. Variations in TDC between the aortic root, through the AA and at the descending aorta and the effect of flow patterns on contrast dispersion was studied via postprocessing of the results. Simulations showed complex unsteady patterns of contrast mixing and dispersion in the AA that are driven by the pulsatile flow. However, despite the relatively long intra-aortic distance between the coronary ostia and the descending aorta, the TDCs at these two locations were similar in terms of rise-time and up-slope, and the time lag between the two TDCs was 0.19 s. TDC in the descending aorta is an accurate analog of the AIF. Methods that use quantitative metrics such as rise-time and slope of the AIF to estimate coronary flowrate and myocardial ischemia can continue with the current practice of using the TDC at the descending aorta as a surrogate for the AIF.

Commentary by Dr. Valentin Fuster

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