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Research Papers

J Biomech Eng. 2018;141(1):011001-011001-10. doi:10.1115/1.4041164.

A probabilistic model predicts hip fracture probability for postflight male astronauts during lateral fall scenarios from various heights. A biomechanical representation of the hip provides impact load. Correlations relate spaceflight bone mineral density (BMD) loss and postflight BMD recovery to bone strength (BS). Translations convert fracture risk index (FRI), the ratio of applied load (AL) to BS, to fracture probability. Parameter distributions capture uncertainty and Monte Carlo simulations provide probability outcomes. The fracture probability for a 1 m fall 0 days postflight is 15% greater than preflight and remains 6% greater than pre-flight at 365 days postflight. Probability quantification provides insight into how spaceflight induced BMD loss affects fracture probability. A bone loss rate reflecting improved exercise countermeasures and dietary intake further reduces the postflight fracture probability to 6% greater than preflight at 0 days postflight and 2% greater at 365 days postflight. Quantification informs assessments of countermeasure effectiveness. When preflight BMD is one standard deviation below mean astronaut preflight BMD, fracture probability at 0 days postflight is 34% greater than the preflight fracture probability calculated with mean BMD and 28% greater at 365 days postflight. Quantification aids review of astronaut BMD fitness for duty standards. Increases in postflight fracture probability are associated with an estimated 18% reduction in postflight BS. Therefore, a 0.82 deconditioning coefficient modifies force application limits for crew vehicles.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;141(1):011002-011002-8. doi:10.1115/1.4041321.

Sex differences in the mechanical properties of different musculoskeletal tissues and their impact on tendon function and disease are becoming increasingly recognized. Tendon mechanical properties are influenced by the presence or absence of sex hormones and these effects appear to be tendon- or ligament-specific. The objective of this study was to determine how sex and hormone differences in rats affect supraspinatus tendon and muscle properties. We hypothesized that male supraspinatus tendons would have increased cross-sectional area but no differences in tendon material properties or muscle composition when compared to supraspinatus tendons from female or ovariectomized (OVX) female rats. Uninjured supraspinatus tendons and muscles from male, female, and OVX female rats were collected and mechanical and histological properties were determined. Our analysis demonstrated decreased dynamic modulus and increased hysteresis and cross-sectional area in male tendons. We found that male tendons exhibited decreased dynamic modulus (during low strain frequency sweep and high strain fatigue loading), increased hysteresis, and increased cross-sectional area compared to female and OVX female tendons. Despite robust mechanical differences, tendon cell density and shape, and muscle composition remained unchanged between groups. Interestingly, these differences were unique compared to previously reported sex differences in rat Achilles tendons, which further supports the concept that the effect of sex on tendon varies anatomically. These differences may partially provide a mechanistic explanation for the increased rate of acute supraspinatus tendon ruptures seen in young males.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;141(1):011003-011003-11. doi:10.1115/1.4041222.

Animal models offer a flexible experimental environment for studying atherosclerosis. The mouse is the most commonly used animal, however, the underlying hemodynamics in larger animals such as the rabbit are far closer to that of humans. The aortic arch is a vessel with complex helical flow and highly heterogeneous shear stress patterns which may influence where atherosclerotic lesions form. A better understanding of intraspecies flow variation and the impact of geometry on flow may improve our understanding of where disease forms. In this work, we use magnetic resonance angiography (MRA) and 4D phase contrast magnetic resonance imaging (PC-MRI) to image and measure blood velocity in the rabbit aortic arch. Measured flow rates from the PC-MRI were used as boundary conditions in computational fluid dynamics (CFD) models of the arches. Helical flow, cross flow index (CFI), and time-averaged wall shear stress (TAWSS) were determined from the simulated flow field. Both traditional geometric metrics and shape modes derived from statistical shape analysis were analyzed with respect to flow helicity. High CFI and low TAWSS were found to colocalize in the ascending aorta and to a lesser extent on the inner curvature of the aortic arch. The Reynolds number was linearly associated with an increase in helical flow intensity (R = 0.85, p < 0.05). Both traditional and statistical shape analyses correlated with increased helical flow symmetry. However, a stronger correlation was obtained from the statistical shape analysis demonstrating its potential for discerning the role of shape in hemodynamic studies.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;141(1):011004-011004-16. doi:10.1115/1.4041551.

Global models for the dynamics of coupled fluid compartments of the central nervous system (CNS) require simplified representations of the individual components which are both accurate and computationally efficient. This paper presents a one-dimensional model for computing the flow of cerebrospinal fluid (CSF) within the spinal subarachnoid space (SSAS) under the simplifying assumption that it consists of two coaxial tubes representing the spinal cord and the dura. A rigorous analysis of the first-order nonlinear system demonstrates that the system is elliptic-hyperbolic, and hence ill-posed, for some values of parameters, being hyperbolic otherwise. In addition, the system cannot be written in conservation-law form, and thus, an appropriate numerical approach is required, namely the path conservative approach. The designed computational algorithm is shown to be second-order accurate in both space and time, capable of handling strongly nonlinear discontinuities, and a method of coupling it with an unsteady inflow condition is presented. Such an approach is sufficiently rapid to be integrated into a global, closed-loop model for computing the dynamics of coupled fluid compartments of the CNS.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;141(1):011005-011005-10. doi:10.1115/1.4041046.

Adhesion of carrier particles to the luminal surface of endothelium under hemodynamic flow conditions is critical for successful vascular drug delivery. Endothelial cells (ECs) line the inner surface of blood vessels. The effect of mechanical behavior of this compliant surface on the adhesion of blood-borne particles is unknown. In this contribution, we use a phase-plane method, first developed by Hammer and Lauffenburger (1987, “A Dynamical Model for Receptor-Mediated Cell Adhesion to Surfaces,” Biophys. J., 52(3), p. 475), to analyze the stability of specific adhesion of a spherical particle to a compliant interface layer. The model constructs a phase diagram and predicts the state of particle adhesion, subjected to an incident simple shear flow, in terms of interfacial elasticity, shear rate, binding affinity of cell adhesive molecules, and their surface density. The main conclusion is that the local deformation of the flexible interface inhibits the stable adhesion of the particle. In comparison with adhesion to a rigid substrate, a greater ligand density is required to establish a stable adhesion between a particle and a compliant interface.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;141(1):011006-011006-12. doi:10.1115/1.4041522.

This paper aims to develop a data-driven model for glucose dynamics taking into account the effects of physical activity (PA) through a numerical study. It intends to investigate PA's immediate effect on insulin-independent glucose variation and PA's prolonged effect on insulin sensitivity. We proposed a nonlinear model with PA (NLPA), consisting of a linear regression of PA and a bilinear regression of insulin and PA. The model was identified and evaluated using data generated from a physiological PA-glucose model by Dalla Man et al. integrated with the uva/padova Simulator. Three metrics were computed to compare blood glucose (BG) predictions by NLPA, a linear model with PA (LPA), and a linear model with no PA (LOPA). For PA's immediate effect on glucose, NLPA and LPA showed 45–160% higher mean goodness of fit (FIT) than LOPA under 30 min-ahead glucose prediction (P < 0.05). For the prolonged PA effect on glucose, NLPA showed 87% higher FIT than LPA (P < 0.05) for simulations using no previous measurements. NLPA had 25–37% and 31–54% higher sensitivity in predicting postexercise hypoglycemia than LPA and LOPA, respectively. This study demonstrated the following qualitative trends: (1) for moderate-intensity exercise, accuracy of BG prediction was improved by explicitly accounting for PA's effect; and (2) accounting for PA's prolonged effect on insulin sensitivity can increase the chance of early prediction of postexercise hypoglycemia. Such observations will need to be further evaluated through human subjects in the future.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;141(1):011007-011007-13. doi:10.1115/1.4040944.

There is a scant biomechanical literature that tests, in a laboratory setting, whether or not determinants of helmet fit affect biomechanical parameters associated with injury. Using conventional cycling helmets and repeatable models of the human head and neck, integrated into a guided drop impact experiment at speeds up to 6 m/s, this study tests the hypothesis that fit affects head kinematics, neck kinetics, and the extent to which the helmet moves relative to the underlying head (an indicator of helmet positional stability). While there were a small subset of cases where head kinematics were statistically significantly altered by fit, when viewed as a whole our measures of head kinematics suggest that fit does not systematically alter kinematics of the head secondary to impact. Similarly, when viewed as a whole, our data suggest that fit does not systematically alter resultant neck compression and resultant moment and associated biomechanical measures. Our data suggest that backward fit helmets exhibit the worst dynamic stability, in particular when the torso is impacted before the helmeted head is impacted, suggesting that the typical certification method of dynamical loading of a helmet to quantify retention may not be representative of highly plausible cycling incident scenarios where impact forces are first applied to the torso leading to loading of the neck prior to the head. Further study is warranted so that factors of fit that affect injury outcome are uncovered in both laboratory and real-world settings.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;141(1):011008-011008-11. doi:10.1115/1.4041526.

Cryosurgery is a rapidly developing discipline, alternative to conventional surgical techniques, used to destroy cancer cells by the action of low temperatures. Currently, the refrigeration is obtained via the adiabatic expansion of gases in probes used for surgeries, with the need of inherently dangerous pressurized vessels. The proposed innovative prototypal apparatus aims to reach the cryosurgical temperatures exploiting a closed-loop refrigeration system, avoiding the hazardous presence of pressurized vessels in the operating room. This study preliminarily examines the technical feasibility of the cryoablation with this machine focusing the attention on the cryoprobe design. Cryoprobe geometry and materials are assessed and the related heat transfer taking place during the cryoablation process is simulated with the aid of the computational fluid dynamics software ANSYS®Fluent. Parametric analyses are carried out varying the length of the collecting tubes and the inlet velocity of the cold carrier fluid in the cryoprobe. The values obtained for physical quantities such as the temperature reached in the treated tissue, the width of the obtained cold front, and the maximum pressure required for the cold carrier fluid are calculated and discussed in order to prove the effectiveness of the experimental apparatus and develop the machine further.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;141(1):011009-011009-11. doi:10.1115/1.4041524.

To better understand the disorders in the pelvic cavity associated with the pelvic floor muscles (PFM) using computational models, it is fundamental to identify the biomechanical properties of these muscles. For this purpose, we implemented an optimization scheme, involving a genetic algorithm (GA) and an inverse finite element analysis (FEA), in order to estimate the material properties of the pubovisceralis muscle (PVM). The datasets of five women were included in this noninvasive analysis. The numerical models of the PVM were built from static axial magnetic resonance (MR) images, and the hyperplastic Mooney–Rivlin constitutive model was used. The material parameters obtained were compared with the ones established through a similar optimization scheme, using Powell's algorithm. To validate the values of the material parameters that characterize the passive behavior of the PVM, the displacements obtained via the numerical models with both methods were compared with dynamic MR images acquired during Valsalva maneuver. The material parameters (c1 and c2) were higher for the GA than for Powell's algorithm, but when comparing the magnitude of the displacements in millimeter of the PVM, there was only a 5% difference, and 4% for the principal logarithmic strain. The GA allowed estimating the in vivo biomechanical properties of the PVM of different subjects, requiring a lower number of simulations when compared to Powell's algorithm.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2018;141(1):011010-011010-11. doi:10.1115/1.4041576.

Quantifying dynamic strain fields from time-resolved volumetric medical imaging and microscopy stacks is a pressing need for radiology and mechanobiology. A critical limitation of all existing techniques is regularization: because these volumetric images are inherently noisy, the current strain mapping techniques must impose either displacement regularization and smoothing that sacrifices spatial resolution, or material property assumptions that presuppose a material model, as in hyperelastic warping. Here, we present, validate, and apply the first three-dimensional (3D) method for estimating mechanical strain directly from raw 3D image stacks without either regularization or assumptions about material behavior. We apply the method to high-frequency ultrasound images of mouse hearts to diagnose myocardial infarction. We also apply the method to present the first ever in vivo quantification of elevated strain fields in the heart wall associated with the insertion of the chordae tendinae. The method shows promise for broad application to dynamic medical imaging modalities, including high-frequency ultrasound, tagged magnetic resonance imaging, and confocal fluorescence microscopy.

Commentary by Dr. Valentin Fuster

Technical Brief

J Biomech Eng. 2018;141(1):014501-014501-4. doi:10.1115/1.4041619.

While previous research has assessed the validity of the OptoGait system to the GAITRite walkway and an instrumented treadmill, no research to date has assessed this system against a traditional three-dimensional motion analysis system. Additionally, previous research has shown that the OptoGait system shows systematic bias when compared to other systems due to the configuration of the system's hardware. This study examined the agreement between the spatiotemporal gait parameters calculated from the OptoGait system and a three-dimensional motion capture (14 camera Vicon motion capture system and 2 AMTI force plates) in healthy adults. Additionally, a range of filter settings for the OptoGait were examined to determine if it was possible to eliminate any systematic bias between the OptoGait and the three-dimensional motion analysis system. Agreement between the systems was examined using 95% limits of agreement by Bland and Altman and the intraclass correlation coefficient. A repeated measure ANOVA was used to detect any systematic differences between the systems. Findings confirm the validity of the OptoGait system for the evaluation of spatiotemporal gait parameters in healthy adults. Furthermore, recommendations on filter settings which eliminate the systematic bias between the OptoGait and the three-dimensional motion analysis system are provided.

Commentary by Dr. Valentin Fuster

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