Jeffrey E. Bischoff

Deformation Measurements and Material Property Estimation of Mouse Carotid Artery Using a Microstructure-Based Constitutive Model

A series of pressurization and tensile loading experiments on mouse carotid arteries is performed with deformation measurements acquired during each experiment using three-dimensional digital image correlation. Using a combination of finite element analysis and a microstructure-based constitutive model to describe the response of biological tissue, the measured surface strains during pressurization, and the average axial strains during tensile loading, an inverse procedure is used to identify the optimal constitutive parameters for the mouse carotid artery. The results demonstrate that surface strain measurements can be combined with computational methods to identify material properties in a vascular tissue. Additional computational studies using the optimal material parameters for the mouse carotid artery are discussed with emphasis on the significance of the qualitative trends observed.

Comprehensive assessment of tibial plateau morphology in total knee arthroplasty: Influence of shape and size on anthropometric variability

Better understanding of proximal tibia morphology can lead to improvements in total knee arthroplasty (TKA) through development of tibial tray families that adequately reflect the diversity of global anatomy using an appropriate number of components. We quantified variations in proximal tibial morphology at the TKA level and characterized differences attributable to gender and ethnicity. Virtual TKA was performed on digital models of 347 tibiae, spanning both genders and multiple ethnicities. The geometry of the resection profile was quantified using both a comprehensive set of morphological measurements (reflecting size and shape) and principal component analysis (PCA). The dominant statistical modes of variation were associated primarily with size (plateau dimensions, radii, and area), with lesser contributions associated with asymmetry and aspect ratios. Medial and lateral AP dimensions were strongly correlated with plateau ML width, with minimal differences in correlations due to gender or ethnicity. In conclusion, clinically relevant differences in proximal tibia morphology at the level of TKA resections across genders and multiple ethnicities can be attributed largely to variations in overall proximal tibial size, not gender‐ or ethnic‐specific shape variations.

Quantifying nonlinear anisotropic elastic material properties of biological tissue by use of membrane inflation

Determination of material parameters for soft tissue frequently involves regression of material parameters for nonlinear, anisotropic constitutive models against experimental data from heterogeneous tests. Here, parameter estimation based on membrane inflation is considered. A four parameter nonlinear, anisotropic hyperelastic strain energy function was used to model the material, in which the parameters are cast in terms of key response features. The experiment was simulated using finite element (FE) analysis in order to predict the experimental measurements of pressure versus profile strain. Material parameter regression was automated using inverse FE analysis; parameter values were updated by use of both local and global techniques, and the ability of these techniques to efficiently converge to a best case was examined. This approach provides a framework in which additional experimental data, including surface strain measurements or local structural information, may be incorporated in order to quantify heterogeneous nonlinear material properties.

Incorporating Population-Level Variability in Orthopedic Biomechanical Analysis: A Review

Effectively addressing population-level variability within orthopedic analyses requires robust data sets that span the target population and can be greatly facilitated by statistical methods for incorporating such data into functional biomechanical models. Data sets continue to be disseminated that include not just anatomical information but also key mechanical data including tissue or joint stiffness, gait patterns, and other inputs relevant to analysis of joint function across a range of anatomies and physiologies. Statistical modeling can be used to establish correlations between a variety of structural and functional biometrics rooted in these data and to quantify how these correlations change from health to disease and, finally, to joint reconstruction or other clinical intervention. Principal component analysis provides a basis for effectively and efficiently integrating variability in anatomy, tissue properties, joint kinetics, and kinematics into mechanistic models of joint function. With such models, bioengineers are able to study the effects of variability on biomechanical performance, not just on a patient-specific basis but in a way that may be predictive of a larger patient population. The goal of this paper is to demonstrate the broad use of statistical modeling within orthopedics and to discuss ways to continue to leverage these techniques to improve biomechanical understanding of orthopedic systems across populations.

Influence of Crosslinking on the Wear Performance of Polyethylene Within Total Ankle Arthroplasty

Background: Wear debris of polyethylene within joint replacement systems can result in clinical complications including osteolysis and component loosening. Highly crosslinked polyethylene (HXPE) was introduced to improve these outcomes, and has been shown to result in improved wear performance in several joint replacement systems. However, bearing couples within total ankle replacement (TAR) systems have historically used conventional polyethylene (CPE) articulating on metal. The extent to which HXPE would result in a reduction of polyethylene wear compared to CPE in the ankle has not been studied. The hypothesis motivating this study was that use of HXPE within TAR will result in significantly lower wear rate than CPE. Methods: HXPE and CPE inserts within a semiconstrained, bicondylar TAR system were manufactured for this study. Samples were subjected to 5.0 million cycles of wear on an in vitro wear simulator. Testing was performed within a physiological environment, using kinematic and kinetic loading profiles characteristic of walking gait. Samples were weighed at regular intervals to determine gravimetric mass loss, and the morphology of wear particles was analyzed. Results: The wear rates for CPE and HXPE samples were 7.4 ± 1.3 and 1.9 ± 0.3 mg/Mc (mean ± SD), respectively. HXPE samples exhibited a significant (P < .01) wear rate reduction of 74% when compared with the CPE. Debris morphology trends between HXPE and CPE were consistent with what has been observed in other joint systems. Conclusion: Use of HXPE significantly reduces wear of TAR as compared to CPE, based on in vitro wear testing. Clinical Relevance: Highly crosslinked polyethylene may reduce clinical complications of total ankle replacement that are linked to polyethylene wear.

Patellofemoral interactions in walking, stair ascent, and stair descent using a virtual patella model

Restoration of normal patella kinematics is an important clinical outcome of total knee arthroplasty. Failure of the patella within total knee systems has been documented and, upon occurrence, often necessitates revision surgery. It is thus important to understand patella mechanics following implantation, subject to load states that are typically realized during walking and other gaits. Here, a computational model of the patella is developed and used to examine the effects of walking, stair ascent, and stair descent on the development of stress and contact pressure in the patella throughout the gait cycle. Motion of the patella was governed by a combination of kinematic and force control, based on knee flexion and patellofemoral joint reaction force data from the literature. Unlike most previous analyses of full gait, quasi-static equilibrium was enforced throughout the cycle. Results indicate that, though peak forces vary greatly between the three gaits, maximum contact pressure and von Mises stress are roughly equivalent. However, contact area is larger in stair ascent and descent than walking, as patellofemoral loading, implant geometry, and polyethylene yield increase conformity between the femoral component and patella. Additionally, maximum contact pressure does not coincide with maximum load except for the case of walking. Though specific to the implant design considered here, this result has important ramifications for patella testing and emphasizes the need to characterize patella mechanics throughout gait.

Metatarsal Loading During Gait-A Musculoskeletal Analysis.

Detailed knowledge of the loading conditions within the human body is essential for the development and optimization of treatments for disorders and injuries of the musculoskeletal system. While loads in the major joints of the lower limb have been the subject of extensive study, relatively little is known about the forces applied to the individual bones of the foot. The objective of this study was to use a detailed musculoskeletal model to compute the loads applied to the metatarsal bones during gait across several healthy subjects. Motion-captured gait trials and computed tomography (CT) foot scans from four healthy subjects were used as the inputs to inverse dynamic simulations that allowed the computation of loads at the metatarsal joints. Low loads in the metatarsophalangeal (MTP) joint were predicted before terminal stance, however, increased to an average peak of 1.9 times body weight (BW) before toe-off in the first metatarsal. At the first tarsometatarsal (TMT) joint, loads of up to 1.0 times BW were seen during the early part of stance, reflecting tension in the ligaments and muscles. These loads subsequently increased to an average peak of 3.0 times BW. Loads in the first ray were higher compared to rays 2-5. The joints were primarily loaded in the longitudinal direction of the bone.

Influence of landmark and surgical variability on virtual assessment of total knee arthroplasty

Given advances in recent years in imaging modalities and computational hardware/software, virtual analyses are increasingly valuable and practical for evaluating total knee arthroplasty (TKA). However, the influence of variabilities at each step in computational analyses on predictions of TKA performance for a population has not yet been thoroughly investigated, nor the relationship between these variabilities and expected variations in surgical practice. Understanding these influences is nevertheless essential for ensuring the clinical relevance of theoretical predictions. Here, a morphological analysis of proximal tibial resections within TKA is proposed and investigated. The goals of this analysis are to quantify the influence of variability in landmark detection on resection parameters and to evaluate this sensitivity relative to expected clinical variability in TKA resections. Results here are directly applicable to population-level computational analyses of morphological and functional TKA performance.

Verification and Validation of an Open Source–Based Morphology Analysis Platform to Support Implant Design

Availability of medical image data and ongoing advancement of image-processing and mathematical-modeling techniques are increasingly enabling device manufacturers to conduct clinically relevant morphological and mechanical analyses across populations to support device development. Gaps in the ability of contemporary commercial codes to fully realize these analytical goals frequently requires some amount of in-house code development and deployment. Verification and validation (V&V) of these custom modules or platforms is an essential requirement for deployment of the software within a medical device design controls system. One such software platform to support orthopedic morphological analysis, zibra, has been successfully developed through a collaborative relationship between Zimmer, Inc. and Kitware, Inc. The development process involved configuration of commercial code, open-source toolkits, and custom code. Here, the V&V strategy to support deployment of zibra is described.

Nonlinear Material Parameter Estimation Using Inverse Finite Element Analysis

Constitutive parameters for biological materials are ideally regressed against data from well-designed experiments in which the loading and boundary conditions give rise to a homogeneous region of deformation. Such conditions may exist for healthy tissue within the context of in vitro tests, but rarely are met when attempting to measure parameters physiologically or noninvasively, due to complex boundary conditions or heterogeneous material structure and properties. The ability to estimate parameters in these situations is essential in many clinically relevant studies, including determination of tendon/ligament parameters in whole knee studies, non-destructive evaluation of evolving material parameters in laboratory studies, and estimation of heterogeneous parameters due to local normal or pathologic disruptions in tissue microstructure. In such cases, computational algorithms must be used to regress material parameters for a given constitutive model against the available data, in which the experimental conditions are modeled as accurately as possible without significant regard to complexity. The work presented here is focused on development of an iterative, inverse finite element (FE) algorithm for estimation of material parameters from experimental data obtained from tests with nonlinear complexities from contact, large deformations, and constitutive models.Copyright