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The impact of glenoid labrum thickness and modulus on labrum and glenohumeral capsule function
N.J. Drury, B.J. Ellis, J.A. Weiss, P.J. McMahon, R.E. Debski. In Journal of Biomechanical Engineering, Vol. 132, No. 12, pp. 121003--121010. 2010.
The glenoid labrum is an integral component of the glenohumeral capsule's insertion into the glenoid, and changes in labrum geometry and mechanical properties may lead to the development of glenohumeral joint pathology. The objective of this research was to determine the effect that changes in labrum thickness and modulus have on strains in the labrum and glenohumeral capsule during a simulated physical examination for anterior instability. A labrum was incorporated into a validated, subject-specific finite element model of the glenohumeral joint, and experimental kinematics were applied simulating application of an anterior load at 0 deg, 30 deg, and 60 deg of external rotation and 60 deg of glenohumeral abduction. The radial thickness of the labrum was varied to simulate thinning tissue, and the tensile modulus of the labrum was varied to simulate degenerating tissue. At 60 deg of external rotation, a thinning labrum increased the average and peak strains in the labrum, particularly in the labrum regions of the axillary pouch (increased 10.5% average strain) and anterior band (increased 7.5% average strain). These results suggest a cause-and-effect relationship between age-related decreases in labrum thickness and increases in labrum pathology. A degenerating labrum also increased the average and peak strains in the labrum, particularly in the labrum regions of the axillary pouch (increased 15.5% strain) and anterior band (increased 10.4% strain). This supports the concept that age-related labrum pathology may result from tissue degeneration. This work suggests that a shift in capsule reparative techniques may be needed in order to include the labrum, especially as activity levels in the aging population continue to increase. In the future validated, finite element models of the glenohumeral joint can be used to explore the efficacy of new repair techniques for glenoid labrum pathology.
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Finite element algorithm for frictionless contact of porous permeable media under finite deformation and sliding
G.A. Ateshian, S.A. Maas, J.A. Weiss. In Journal of Biomechanical Engineering, Vol. 132, No. 6, Note: Cover article, 2010.
This study formulates and implements a finite element contact algorithm for solid-fluid (biphasic) mixtures, accommodating both finite deformation and sliding. The finite element source code is made available to the general public. The algorithm uses a penalty method regularized with an augmented Lagrangian method to enforce the continuity of contact traction and normal component of fluid flux across the contact interface. The formulation addresses the need to automatically enforce free-draining conditions outside of the contact interface. The accuracy of the implementation is verified using contact problems, for which exact solutions are obtained by alternative analyses. Illustrations are also provided that demonstrate large deformations and sliding under configurations relevant to biomechanical applications such as articular contact. This study addresses an important computational need in the biomechanics of porous-permeable soft tissues. Placing the source code in the public domain provides a useful resource to the biomechanics community.
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Effects of idealized joint geometry on finite element predictions of cartilage contact stresses in the hip
A.E. Anderson, B.J. Ellis, S.A. Maas, J.A. Weiss. In Journal of Biomechanics, No. 43, pp. 1351--1357. 2010.
Computational models may have the ability to quantify the relationship between hip morphology, cartilage mechanics and osteoarthritis. Most models have assumed the hip joint to be a perfect ball and socket joint and have neglected deformation at the bone-cartilage interface. The objective of this study was to analyze finite element (FE) models of hip cartilage mechanics with varying degrees of simplified geometry and a model with a rigid bone material assumption to elucidate the effects on predictions of cartilage stress. A previously validated subject-specific FE model of a cadaveric hip joint was used as the basis for the models. Geometry for the bone-cartilage interface was either: (1) subject-specific (i.e. irregular), (2) spherical, or (3) a rotational conchoid. Cartilage was assigned either a varying (irregular) or constant thickness (smoothed). Loading conditions simulated walking, stair-climbing and descending stairs. FE predictions of contact stress for the simplified models were compared with predictions from the subject-specific model. Both spheres and conchoids provided a good approximation of native hip joint geometry (average fitting error ~0.5 mm). However, models with spherical/conchoid bone geometry and smoothed articulating cartilage surfaces grossly underestimated peak and average contact pressures (50% and 25% lower, respectively) and overestimated contact area when compared to the subject-specific FE model. Models incorporating subject-specific bone geometry with smoothed articulating cartilage also underestimated pressures and predicted evenly distributed patterns of contact. The model with rigid bones predicted much higher pressures than the subject-specific model with deformable bones. The results demonstrate that simplifications to the geometry of the bone-cartilage interface, cartilage surface and bone material properties can have a dramatic effect on the predicted magnitude and distribution of cartilage contact pressures in the hip joint.
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A Meshing Pipeline for Biomedical Models
M. Callahan, M.J. Cole, J.F. Shepherd, J.G. Stinstra, C.R. Johnson. In Engineering with Computers, Vol. 25, No. 1, Note: DOI:10.1007/s00366-008-0106-1, SpringerLink, pp. 115-130. 2009.
Biomedical computing applications often require a computational pipeline that integrates data from experimental measurements or from image acquisition into a modeling and visualization environment. The latter process often involves segmentation, mesh generation, and numerical simulations. An important requirement of the numerical approximation and visualization methods is the need to create a discrete decomposition of the model geometry into a ‘mesh’. The meshes produced are used both as input for computational simulation and as the geometric basis for many of the resulting visualizations. Historically, the generation of these meshes has been a significant bottleneck in efforts to efficiently create complex, three-dimensional biomedical models. In this paper, we will outline a pipeline for more efficiently generating meshes suitable for biomedical simulations. Because of the wide array of geometries and phenomena encountered in biomedical computing, this pipeline, SCIRun, will incorporate a flexible suite of tools that will offer some generality to mesh generation of biomedical models. We will discuss several tools that have been successfully used in past problems and how these tools have been incorporated into SCIRun. We will demonstrate mesh generation for example problems along with methods for verifying the quality of the meshes generated. Finally, we will discuss ongoing and future efforts to bring all of these tools into a common environment to dramatically reduce the difficulty of mesh generation for biomedical simulations.
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Transversely Isotropic Distribution of Sulfated Glycosaminoglycans in Human Medial Collateral Ligament: A Quantitative Analysis
H.B. Henninger, S.A. Maas, J.H. Shepherd, S. Joshi, J.A. Weiss. In Journal of Structural Biology, Vol. 165, pp. 176-183. 2009.
Decorin and its associated glycosaminoglycan (GAG) side chain, dermatan sulfate (DS), play diverse roles in soft tissue formation and potentially aid in the mechanical integrity of the tissue. Deeper understanding of the distribution and orientation of the GAGs on a microscopic level may help elucidate the structure/function relationship of these important molecules. The hypothesis of the present study was that sulfated GAGs are aligned with transversely isotropic material symmetry in human medial collateral ligament (MCL) with the collagen acting as the axis of symmetry. To test the hypothesis, sulfated GAGs were visualized using transmission electron microscopy (TEM). Three orthogonal anatomical planes were examined to evaluate GAG distributions against symmetry criteria. GAG populations were differentiated using targeted enzyme digestion. Results suggest that sulfated GAGs including DS, chondroitin sulfates A and C, as well as other sub-populations assume transversely isotropic distributions in human MCL. Sulfated GAGs in the plane normal to the collagen axis were found to be isotropic with no preferred orientation. GAGs in the two planes along the collagen axis did not statistically differ and exhibited apparent bimodal distributions, favoring orthogonal distributions with over half at other angles with respect to collagen. A previously developed model, GAGSim3D, was used to interpret potential TEM artifacts. The data collected herein provide refined inputs to micro-scale models of the structure/function relationship of sulfated GAGs in soft tissues.
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Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees
B.M. Isaacson, J.G. Stinstra, R.S. MacLeod, J.B. Webster, J.P. Beck, R.D. Bloebaum. In JoVE, Vol. 29, 2009.
The projected number of American amputees is expected to rise to 3.6 million by 2050. Many of these individuals depend on artificial limbs to perform routine activities, but prosthetic suspensions using traditional socket technology can prove to be cumbersome and uncomfortable for a person with limb loss. Moreover, for those with high proximal amputations, limited residual limb length may prevent exoprosthesis attachment all together. Osseointegrated implant technology is a novel operative procedure which allow firm skeletal attachment between the host bone and an implant. Preliminary results in European amputees with osseointegrated implants have shown improved clinical outcomes by allowing direct transfer of loads to the bone-implant interface. Despite the apparent advantages of osseointegration over socket technology, the current rehabilitation procedures require long periods of restrictive load bearing prior which may be reduced with expedited skeletal attachment via electrical stimulation. The goal of the osseointegrated intelligent implant design (OIID) system is to make the implant part of an electrical system to accelerate skeletal attachment and help prevent periprosthetic infection. To determine optimal electrode size and placement, we initiated proof of concept with computational modeling of the electric fields and current densities that arise during electrical stimulation of amputee residual limbs. In order to provide insure patient safety, subjects with retrospective computed tomography scans were selected and three dimensional reconstructions were created using customized software programs to ensure anatomical accuracy (Seg3D and SCIRun) in an IRB and HIPAA approved study. These software packages supported the development of patient specific models and allowed for interactive manipulation of electrode position and size. Preliminary results indicate that electric fields and current densities can be generated at the implant interface to achieve the homogenous electric field distributions required to induce osteoblast migration, enhance skeletal fixation and may help prevent periprosthetic infections. Based on the electrode configurations experimented with in the model, an external two band configuration will be advocated in the future.
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Accuracy and run-time comparison for different potential approaches and iterative solvers in finite element method based EEG source analysis
S. Lew, C.H. Wolters, T. Dierkes, C. Röer, R.S. MacLeod. In Applied Numerical Mathematics, Vol. 59, pp. 1970--1988. 2009.
Accuracy and run-time play an important role in medical diagnostics and research as well as in the field of neuroscience. In Electroencephalography (EEG) source reconstruction, a current distribution in the human brain is reconstructed noninvasively from measured potentials at the head surface (the EEG inverse problem). Numerical modeling techniques are used to simulate head surface potentials for dipolar current sources in the human cortex, the so-called EEG forward problem.
In this paper, the efficiency of algebraic multi-grid (AMG), incomplete Cholesky (IC) and Jacobi preconditioners for the conjugate gradient (CG) method are compared for iteratively solving the finite element (FE) method based EEG forward problem. The interplay of the three solvers with a full subtraction approach and two direct potential approaches, the Venant and the partial integration method for the treatment of the dipole singularity is examined. The examination is performed in a four-compartment sphere model with anisotropic skull layer, where quasi-analytical solutions allow for an exact quantification of computational speed versus numerical error. Specifically-tuned constrained Delaunay tetrahedralization (CDT) FE meshes lead to high accuracies for both the full subtraction and the direct potential approaches. Best accuracies are achieved by the full subtraction approach if the homogeneity condition is fulfilled. It is shown that the AMG-CG achieves an order of magnitude higher computational speed than the CG with the standard preconditioners with an increasing gain factor when decreasing mesh size. Our results should broaden the application of accurate and fast high-resolution FE volume conductor modeling in source analysis routine.
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Improved EEG Source Analysis Using Low-Resolution Conductivity Estimation in a Four-Compartment Finite Element Head Model
S. Lew, C.H. Wolters, A. Anwander, S. Makeig, R.S. MacLeod. In Human Brain Mapping, Vol. 30, pp. 2862--2878. 2009.
Bioelectric source analysis in the human brain from scalp electroencephalography (EEG) signals is sensitive to geometry and conductivity properties of the different head tissues. We propose a low-resolution conductivity estimation (LRCE) method using simulated annealing optimization on high-resolution finite element models that individually optimizes a realistically shaped four-layer volume conductor with regard to the brain and skull compartment conductivities. As input data, the method needs T1- and PD-weighted magnetic resonance images for an improved modeling of the skull and the cerebrospinal fluid compartment and evoked potential data with high signal-to-noise ratio (SNR). Our simulation studies showed that for EEG data with realistic SNR, the LRCE method was able to simultaneously reconstruct both the brain and the skull conductivity together with the underlying dipole source and provided an improved source analysis result. We have also demonstrated the feasibility and applicability of the new method to simultaneously estimate brain and skull conductivity and a somatosensory source from measured tactile somatosensory-evoked potentials of a human subject. Our results show the viability of an approach that computes its own conductivity values and thus reduces the dependence on assigning values from the literature and likely produces a more robust estimate of current sources. Using the LRCE method, the individually optimized four-compartment volume conductor model can, in a second step, be used for the analysis of clinical or cognitive data acquired from the same subject.
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Muskuloskeletal Research Laboratory
