Research Papers

Deciphering the “Art” in Modeling and Simulation of the Knee Joint: Overall Strategy

[+] Author and Article Information
Ahmet Erdemir

Department of Biomedical Engineering
and Computational Biomodeling (CoBi) Core,
Lerner Research Institute,
Cleveland Clinic,
9500 Euclid Avenue (ND20),
Cleveland, OH 44195
e-mail: erdemira@ccf.org

Thor F. Besier

Department of Engineering Science,
Auckland Bioengineering Institute,
University of Auckland,
Auckland 1010, New Zealand

Jason P. Halloran

Department of Mechanical Engineering,
Center for Human Machine Systems,
Cleveland State University,
Cleveland, OH 44115

Carl W. Imhauser

Department of Biomechanics,
Hospital for Special Surgery,
New York, NY 10021

Peter J. Laz, Kevin B. Shelburne

Department of Mechanical and
Materials Engineering,
Center for Orthopaedic Biomechanics,
University of Denver,
Denver, CO 80210

Tina M. Morrison

Division of Applied Mechanics,
Office of Science and Engineering Laboratories,
Center for Devices and Radiological Health,
Food and Drug Administration,
Silver Spring, MD 20993

1Corresponding author.

Manuscript received December 4, 2018; final manuscript received March 26, 2019; published online June 5, 2019. Editor: Beth A. Winkelstein.This work is in part a work of the U.S. Government. ASME disclaims all interest in the U.S. Government's contributions.

J Biomech Eng 141(7), 071002 (Jun 05, 2019) (10 pages) Paper No: BIO-18-1516; doi: 10.1115/1.4043346 History: Received December 04, 2018; Revised March 26, 2019

Recent explorations of knee biomechanics have benefited from computational modeling, specifically leveraging advancements in finite element analysis and rigid body dynamics of joint and tissue mechanics. A large number of models have emerged with different levels of fidelity in anatomical and mechanical representation. Adapted modeling and simulation processes vary widely, based on justifiable choices in relation to anticipated use of the model. However, there are situations where modelers' decisions seem to be subjective, arbitrary, and difficult to rationalize. Regardless of the basis, these decisions form the “art” of modeling, which impact the conclusions of simulation-based studies on knee function. These decisions may also hinder the reproducibility of models and simulations, impeding their broader use in areas such as clinical decision making and personalized medicine. This document summarizes an ongoing project that aims to capture the modeling and simulation workflow in its entirety—operation procedures, deviations, models, by-products of modeling, simulation results, and comparative evaluations of case studies and applications. The ultimate goal of the project is to delineate the art of a cohort of knee modeling teams through a publicly accessible, transparent approach and begin to unravel the complex array of factors that may lead to a lack of reproducibility. This manuscript outlines our approach along with progress made so far. Potential implications on reproducibility, on science, engineering, and training of modeling and simulation, on modeling standards, and on regulatory affairs are also noted.

Copyright © 2019 by ASME
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Maas, S. A. , Ateshian, G. A. , and Weiss, J. A. , 2017, “ FEBio: History and Advances,” Annu. Rev. Biomed. Eng., 19, pp. 279–299. [CrossRef] [PubMed]
Seth, A. , Hicks, J. L. , Uchida, T. K. , Habib, A. , Dembia, C. L. , Dunne, J. J. , Ong, C. F. , DeMers, M. S. , Rajagopal, A. , Millard, M. , Hamner, S. R. , Arnold, E. M. , Yong, J. R. , Lakshmikanth, S. K. , Sherman, M. A. , Ku, J. P. , and Delp, S. L. , 2018, “ OpenSim: Simulating Musculoskeletal Dynamics and Neuromuscular Control to Study Human and Animal Movement,” PLoS Comput. Biol., 14(7), p. e1006223. [CrossRef] [PubMed]
Kazemi, M. , Dabiri, Y. , and Li, L. P. , 2013, “ Recent Advances in Computational Mechanics of the Human Knee Joint,” Comput. Math. Methods Med., 2013, p. 718423. [CrossRef] [PubMed]
Peters, A. E. , Akhtar, R. , Comerford, E. J. , and Bates, K. T. , 2018, “ Tissue Material Properties and Computational Modelling of the Human Tibiofemoral Joint: A Critical Review,” PeerJ., 6, p. e4298. [CrossRef] [PubMed]
Taylor, M. , and Prendergast, P. J. , 2015, “ Four Decades of Finite Element Analysis of Orthopaedic Devices: Where are We Now and What Are the Opportunities?,” J. Biomech., 48(5), pp. 767–778. [CrossRef] [PubMed]
Erdemir, A. , Guess, T. M. , Halloran, J. , Tadepalli, S. C. , and Morrison, T. M. , 2012, “ Considerations for Reporting Finite Element Analysis Studies in Biomechanics,” J. Biomech., 45(4), pp. 625–633. [CrossRef] [PubMed]
Erdemir, A. , 2016, “ Open Knee: Open Source Modeling and Simulation in Knee Biomechanics,” J. Knee Surg., 29(2), pp. 107–116. [PubMed]
Harris, M. D. , Cyr, A. J. , Ali, A. A. , Fitzpatrick, C. K. , Rullkoetter, P. J. , Maletsky, L. P. , and Shelburne, K. B. , 2016, “ A Combined Experimental and Computational Approach to Subject-Specific Analysis of Knee Joint Laxity,” ASME J. Biomech. Eng., 138(8), p. 081004. [CrossRef]
Kia, M. , Schafer, K. , Lipman, J. , Cross, M. , Mayman, D. , Pearle, A. , Wickiewicz, T. , and Imhauser, C. , 2016, “ A Multibody Knee Model Corroborates Subject-Specific Experimental Measurements of Low Ligament Forces and Kinematic Coupling During Passive Flexion,” ASME J. Biomech. Eng., 138(5), p. 051010. [CrossRef]
Balci, O. , 2012, “ A Life Cycle for Modeling and Simulation,” Simulation, 88(7), pp. 870–883. [CrossRef]
Henak, C. R. , Anderson, A. E. , and Weiss, J. A. , 2013, “ Subject-Specific Analysis of Joint Contact Mechanics: Application to the Study of Osteoarthritis and Surgical Planning,” ASME J. Biomech. Eng., 135(2), p. 021003. [CrossRef]
Maletsky, L. , Shalhoub, S. , Fitzwater, F. , Eboch, W. , Dickinson, M. , Akhbari, B. , and Louie, E. , 2016, “ In Vitro Experimental Testing of the Human Knee: A Concise Review,” J. Knee Surg., 29(2), pp. 138–148. [PubMed]
Guan, S. , Gray, H. A. , Keynejad, F. , and Pandy, M. G. , 2016, “ Mobile Biplane X-Ray Imaging System for Measuring 3D Dynamic Joint Motion During Overground Gait,” IEEE Trans. Med. Imaging, 35(1), pp. 326–336. [CrossRef] [PubMed]
Liukkonen, M. K. , Mononen, M. E. , Tanska, P. , Saarakkala, S. , Nieminen, M. T. , and Korhonen, R. K. , 2017, “ Application of a Semi-Automatic Cartilage Segmentation Method for Biomechanical Modeling of the Knee Joint,” Comput. Methods Biomech. Biomed. Eng., 20(13), pp. 1453–1463.
Erdemir, A. , McLean, S. , Herzog, W. , and van den Bogert, A. J. , 2007, “ Model-Based Estimation of Muscle Forces Exerted During Movements,” Clin. Biomech., 22(2), pp. 131–154. [CrossRef]
Giambini, H. , Dragomir-Daescu, D. , Nassr, A. , Yaszemski, M. J. , and Zhao, C. , 2016, “ Quantitative Computed Tomography Protocols Affect Material Mapping and Quantitative Computed Tomography-Based Finite-Element Analysis Predicted Stiffness,” ASME J. Biomech. Eng., 138(9), p. 091003. [CrossRef]
Westover, L. M. , Sinaei, N. , Küpper, J. C. , and Ronsky, J. L. , 2016, “ Quantifying In Vivo Laxity in the Anterior Cruciate Ligament and Individual Knee Joint Structures,” Comput. Methods Biomech. Biomed. Eng., 19(14), pp. 1567–1577. [CrossRef]
Razu, S. S. , and Guess, T. M. , 2018, “ Electromyography-Driven Forward Dynamics Simulation to Estimate In Vivo Joint Contact Forces During Normal, Smooth, and Bouncy Gaits,” ASME J. Biomech. Eng., 140(7), p. 071012. [CrossRef]
Schafer, K. A. , Tucker, S. , Griffith, T. , Sheikh, S. , Wickiewicz, T. L. , Nawabi, D. H. , Imhauser, C. W. , and Pearle, A. D. , 2016, “ Distribution of Force in the Medial Collateral Ligament Complex During Simulated Clinical Tests of Knee Stability,” Am. J. Sports Med., 44(5), pp. 1203–1208. [CrossRef] [PubMed]
Bates, N. A. , Schilaty, N. D. , Nagelli, C. V. , Krych, A. J. , and Hewett, T. E. , 2018, “ Validation of Noncontact Anterior Cruciate Ligament Tears Produced by a Mechanical Impact Simulator Against the Clinical Presentation of Injury,” Am. J. Sports Med., 46(9), pp. 2113–2121. [CrossRef] [PubMed]
Ewing, J. A. , Kaufman, M. K. , Hutter, E. E. , Granger, J. F. , Beal, M. D. , Piazza, S. J. , and Siston, R. A. , 2016, “ Estimating Patient-Specific Soft-Tissue Properties in a TKA Knee,” J. Orthop. Res., 34(3), pp. 435–443. [CrossRef] [PubMed]
Kiapour, A. , Kiapour, A. M. , Kaul, V. , Quatman, C. E. , Wordeman, S. C. , Hewett, T. E. , Demetropoulos, C. K. , and Goel, V. K. , 2013, “ Finite Element Model of the Knee for Investigation of Injury Mechanisms: Development and Validation,” ASME J. Biomech. Eng., 136(1), p. 011002. [CrossRef]
Dhaher, Y. Y. , Kwon, T.-H. , and Barry, M. , 2010, “ The Effect of Connective Tissue Material Uncertainties on Knee Joint Mechanics Under Isolated Loading Conditions,” J. Biomech., 43(16), pp. 3118–3125. [CrossRef] [PubMed]
Sharifi, M. , Shirazi-Adl, A. , and Marouane, H. , 2017, “ Computational Stability of Human Knee Joint at Early Stance in Gait: Effects of Muscle Coactivity and Anterior Cruciate Ligament Deficiency,” J. Biomech., 63, pp. 110–116. [CrossRef] [PubMed]
Ali, A. A. , Harris, M. D. , Shalhoub, S. , Maletsky, L. P. , Rullkoetter, P. J. , and Shelburne, K. B. , 2017, “ Combined Measurement and Modeling of Specimen-Specific Knee Mechanics for Healthy and ACL-Deficient Conditions,” J. Biomech., 57, pp. 117–124. [CrossRef] [PubMed]
Erdemir, A. , Hunter, P. J. , Holzapfel, G. A. , Loew, L. M. , Middleton, J. , Jacobs, C. R. , Nithiarasu, P. , Löhner, R. , Wei, G. , Winkelstein, B. A. , Barocas, V. H. , Guilak, F. , Ku, J. P. , Hicks, J. L. , Delp, S. L. , Sacks, M. , Weiss, J. A. , Ateshian, G. A. , Maas, S. A. , McCulloch, A. D. , and Peng, G. C. Y. , 2018, “ Perspectives on Sharing Models and Related Resources in Computational Biomechanics Research,” ASME J. Biomech. Eng., 140(2), p. 024701. [CrossRef]
Sibole, S. C. , and Erdemir, A. , 2012, “ Chondrocyte Deformations as a Function of Tibiofemoral Joint Loading Predicted by a Generalized High-Throughput Pipeline of Multi-Scale Simulations,” PLoS One, 7(5), p. e37538. [CrossRef] [PubMed]
Mesfar, W. , and Shirazi-Adl, A. , 2006, “ Biomechanics of Changes in ACL and PCL Material Properties or Prestrains in Flexion Under Muscle Force-Implications in Ligament Reconstruction,” Comput. Methods Biomech. Biomed. Eng., 9(4), pp. 201–209. [CrossRef]
Shirazi, R. , and Shirazi-Adl, A. , 2009, “ Analysis of Partial Meniscectomy and ACL Reconstruction in Knee Joint Biomechanics Under a Combined Loading,” Clin. Biomech., 24(9), pp. 755–761. [CrossRef]
Bates, N. A. , McPherson, A. L. , Nesbitt, R. J. , Shearn, J. T. , Myer, G. D. , and Hewett, T. E. , 2017, “ Robotic Simulation of Identical Athletic-Task Kinematics on Cadaveric Limbs Exhibits a Lack of Differences in Knee Mechanics Between Contralateral Pairs,” J. Biomech., 53, pp. 36–44. [CrossRef] [PubMed]
Rao, C. , Fitzpatrick, C. K. , Rullkoetter, P. J. , Maletsky, L. P. , Kim, R. H. , and Laz, P. J. , 2013, “ A Statistical Finite Element Model of the Knee Accounting for Shape and Alignment Variability,” Med. Eng. Phys., 35(10), pp. 1450–1456. [CrossRef] [PubMed]
Nuño, N. , and Ahmed, A. M. , 2001, “ Sagittal Profile of the Femoral Condyles and Its Application to Femorotibial Contact Analysis,” ASME J. Biomech. Eng., 123(1), pp. 18–26. [CrossRef]
Guo, H. , Santner, T. J. , Lerner, A. L. , and Maher, S. A. , 2017, “ Reducing Uncertainty When Using Knee-Specific Finite Element Models by Assessing the Effect of Input Parameters,” J. Orthop. Res., 35(10), pp. 2233–2242. [CrossRef] [PubMed]
Galbusera, F. , Freutel, M. , Dürselen, L. , D'Aiuto, M. , Croce, D. , Villa, T. , Sansone, V. , and Innocenti, B. , 2014, “ Material Models and Properties in the Finite Element Analysis of Knee Ligaments: A Literature Review,” Front Bioeng. Biotechnol., 2, p. 54. [CrossRef] [PubMed]
Rachmat, H. H. , Janssen, D. , Zevenbergen, W. J. , Verkerke, G. J. , Diercks, R. L. , and Verdonschot, N. , 2014, “ Generating Finite Element Models of the Knee: How Accurately Can We Determine Ligament Attachment Sites From MRI Scans?,” Med. Eng. Phys., 36(6), pp. 701–707. [CrossRef] [PubMed]
Donahue, T. L. H. , Hull, M. L. , Rashid, M. M. , and Jacobs, C. R. , 2002, “ A Finite Element Model of the Human Knee Joint for the Study of Tibio-Femoral Contact,” ASME J. Biomech. Eng., 124(3), pp. 273–280. [CrossRef]
Halloran, J. P. , Petrella, A. J. , and Rullkoetter, P. J. , 2005, “ Explicit Finite Element Modeling of Total Knee Replacement Mechanics,” J. Biomech., 38(2), pp. 323–331. [CrossRef] [PubMed]
Li, G. , Gil, J. , Kanamori, A. , and Woo, S. L. , 1999, “ A Validated Three-Dimensional Computational Model of a Human Knee Joint,” ASME J. Biomech. Eng., 121(6), pp. 657–662. [CrossRef]
Erdemir, A. , Mulugeta, L. , and Lytton, W. W. , 2015, “ Ten ‘Not So’ Simple Rules for Credible Practice of Modeling and Simulation in Healthcare: A Multidisciplinary Committee Perspective,” Biomedical Engineering Society/Food and Drug Administration Frontiers in Medical Devices Conference: Innovations in Modeling and Simulation, Washington, DC, May 18–20, 2015.
Anderson, A. E. , Ellis, B. J. , and Weiss, J. A. , 2007, “ Verification, Validation and Sensitivity Studies in Computational Biomechanics,” Comput. Methods Biomech. Biomed. Eng., 10(3), pp. 171–184. [CrossRef]
Fregly, B. J. , Besier, T. F. , Lloyd, D. G. , Delp, S. L. , Banks, S. A. , Pandy, M. G. , and D'Lima, D. D. , 2012, “ Grand Challenge Competition to Predict In Vivo Knee Loads,” J. Orthop. Res., 30(4), pp. 503–513. [CrossRef] [PubMed]
SimTK, 2018, “ SimTK: Reproducibility in Simulation-Based Prediction of Natural Knee Mechanics: Project Home,” SimTK, accessed Dec. 1, 2018, https://simtk.org/projects/kneehub
NIH, 2018, “ Project Information—NIH RePORTER—NIH Research Portfolio Online Reporting Tools Expenditures and Results,” National Institutes of Health, Bethesda, MD, accessed Dec. 1, 2018, https://projectreporter.nih.gov/project_info_description.cfm?aid=9366122&icde=41076822
SimTK, 2018, “ SimTK: Open Knee(s): Virtual Biomechanical Representations of the Knee Joint: Project Home,” SimTK, accessed Dec. 1, 2018, https://simtk.org/projects/openknee
University of Denver, 2018, “Natural Knee Data,” Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, accessed Dec. 1, 2018, https://digitalcommons.du.edu/natural_knee_data/
SimTK, 2018, “ Specifications/ExperimentationAnatomicalImaging—Openknee,” SimTK, accessed Dec. 1, 2018, https://simtk.org/plugins/moinmoin/openknee/Specifications/ExperimentationAnatomicalImaging
SimTK, 2018, “ Specifications/ExperimentationJointMechanics—Openknee,” SimTK, accessed Dec. 1, 2018, https://simtk.org/plugins/moinmoin/openknee/Specifications/ExperimentationJointMechanics
Ali, A. A. , Shalhoub, S. S. , Cyr, A. J. , Fitzpatrick, C. K. , Maletsky, L. P. , Rullkoetter, P. J. , and Shelburne, K. B. , 2016, “ Validation of Predicted Patellofemoral Mechanics in a Finite Element Model of the Healthy and Cruciate-Deficient Knee,” J. Biomech., 49(2), pp. 302–309. [CrossRef] [PubMed]
Henninger, H. B. , Reese, S. P. , Anderson, A. E. , and Weiss, J. A. , 2010, “ Validation of Computational Models in Biomechanics,” Proc. Inst. Mech. Eng. H, 224(7), pp. 801–812. [CrossRef] [PubMed]
Wilson, D. R. , Feikes, J. D. , Zavatsky, A. B. , and O'Connor, J. J. , 2000, “ The Components of Passive Knee Movement are Coupled to Flexion Angle,” J. Biomech., 33(4), pp. 465–473. [CrossRef] [PubMed]
Arilla, F. V. , Yeung, M. , Bell, K. , Rahnemai-Azar, A. A. , Rothrauff, B. B. , Fu, F. H. , Debski, R. E. , Ayeni, O. R. , and Musahl, V. , 2015, “ Experimental Execution of the Simulated Pivot-Shift Test: A Systematic Review of Techniques,” Arthroscopy, 31(12), pp. 2445–2454. [CrossRef] [PubMed]
Felson, D. T. , Nevitt, M. C. , Yang, M. , Clancy, M. , Niu, J. , Torner, J. C. , Lewis, C. E. , Aliabadi, P. , Sack, B. , McCulloch, C. , and Zhang, Y. , 2008, “ A New Approach Yields High Rates of Radiographic Progression in Knee Osteoarthritis,” J. Rheumatol., 35(10), pp. 2047–2054. http://www.jrheum.org/content/35/10/2047.long [PubMed]
Caruthers, E. J. , Thompson, J. A. , Chaudhari, A. M. W. , Schmitt, L. C. , Best, T. M. , Saul, K. R. , and Siston, R. A. , 2016, “ Muscle Forces and Their Contributions to Vertical and Horizontal Acceleration of the Center of Mass During Sit-to-Stand Transfer in Young, Healthy Adults,” J. Appl. Biomech., 32(5), pp. 487–503. [CrossRef] [PubMed]
Bland, J. M. , and Altman, D. G. , 2007, “ Agreement Between Methods of Measurement With Multiple Observations per Individual,” J. Biopharm. Stat., 17(4), pp. 571–582. [CrossRef] [PubMed]
Taha, A. A. , and Hanbury, A. , 2015, “ An Efficient Algorithm for Calculating the Exact Hausdorff Distance,” IEEE Trans. Pattern Anal. Mach. Intell., 37(11), pp. 2153–2163. [CrossRef] [PubMed]
NASA, 2016, “ NASA Technical Standards System (NTSS),” National Aeronautics and Space Administration, Washington, DC, Document No. NASA-STD-7009. https://standards.nasa.gov/standard/nasa/nasa-std-7009
ASME, 2018, “ Assessing Credibility of Computational Modeling Through Verification and Validation: Application to Medical Devices,” American Society of Mechanical Engineers, New York, Standard No. V V 40 - 2018. https://www.asme.org/products/codes-standards/vv-40-2018-assessing-credibility-computational
U.S. FDA, 2018, “ Reporting of Computational Modeling Studies in Medical Device Submissions—Guidance for Industry and Food and Drug Administration Staff,” U.S. Food & Drug Administration, Silver Spring, MD, accessed Dec. 1, 2018, https://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM381813.pdf
SimTK, 2018, “ ModelDevelopment—Kneehub,” SimTK, accessed Dec. 1, 2018, https://simtk.org/plugins/moinmoin/kneehub/ModelDevelopment
SimTK, 2018, “ SimTK: Reproducibility in Simulation-Based Prediction of Natural Knee Mechanics: Documents,” SimTK, accessed Dec. 1, 2018, https://simtk.org/docman/?group_id=1061
3D Slicer, 2018, “ 3D Slicer,” accessed Dec. 1, 2018, https://www.slicer.org/
MeshLab, 2018, “ MeshLab,” accessed Dec. 1, 2018, http://www.meshlab.net/
Synopsis, 2018, “ Simpleware ScanIP,” Synopsis, Mountain View, CA, accessed Dec. 1, 2018, https://www.synopsys.com/simpleware/products/software/scanip.html
MathWorks, 2018, “ MATLAB—MathWorks—MATLAB & Simulink,” The Mathworks, Natick, MA, accessed Dec. 1, 2018, https://www.mathworks.com/products/matlab.html
Materialise, 2018, “3 D Medical Image Processing Software | Materialise Mimics,” Materialise NV, Leuven, Belgium, accessed Dec. 1, 2018, https://www.materialise.com/en/medical/software/mimics
3D Systems, 2018, “ Software,” 3D Systems, Rock Hill, SC, accessed Dec. 1, 2018, https://www.3dsystems.com/software
SALOME, 2018, “ Welcome to the www.Salome-Platform.Org—SALOME Platform,” SALOME, accessed Dec. 1, 2018, http://www.salome-platform.org/
Altair, 2018, “ Large Model Finite Element Preprocessing—Altair HyperMesh,” Altair, Troy, MI, accessed Dec. 1, 2018, https://altairhyperworks.com/product/hypermesh
MAP, 2018, “ Musculoskeletal Atlas Project (MAP) Client Documentation—Latest—MAP Client Latest Documentation,” accessed Dec. 1, 2018, https://map-client.readthedocs.io/en/latest/
CCAD, 2018, “IA-FEMesh,” Center for Computer Aided Design, The University of Iowa, Iowa City, IA, accessed Dec. 1, 2018, https://www.ccad.uiowa.edu/MIMX/projects/IA-FEMesh
FEBio, 2018, “ FEBio Software Suite,” accessed Dec. 1, 2018, https://febio.org/
SIMULIA, 2018, “ Abaqus Unified FEA—SIMULIATM by Dassault Systèmes®,” SIMULIA, Johnston, RI, accessed Dec. 1, 2018, https://www.3ds.com/products- services/simulia/products/abaqus/
MSC, 2018, “ Adams—The Multibody Dynamics Simulation Solution,” MSC Software, Newport Beach, CA, accessed Dec. 1, 2018, http://www.mscsoftware.com/product/adams
Naghibi Beidokhti, H. , Janssen, D. , van de Groes, S. , Hazrati, J. , Van den Boogaard, T. , and Verdonschot, N. , 2017, “ The Influence of Ligament Modelling Strategies on the Predictive Capability of Finite Element Models of the Human Knee Joint,” J. Biomech., 65, pp. 1–11. [CrossRef] [PubMed]
Collins, F. S. , and Tabak, L. A. , 2014, “ Policy: NIH Plans to Enhance Reproducibility,” Nature, 505(7485), pp. 612–613. [CrossRef] [PubMed]
Dreischarf, M. , Zander, T. , Shirazi-Adl, A. , Puttlitz, C. M. , Adam, C. J. , Chen, C. S. , Goel, V. K. , Kiapour, A. , Kim, Y. H. , Labus, K. M. , Little, J. P. , Park, W. M. , Wang, Y. H. , Wilke, H. J. , Rohlmann, A. , and Schmidt, H. , 2014, “ Comparison of Eight Published Static Finite Element Models of the Intact Lumbar Spine: Predictive Power of Models Improves When Combined Together,” J. Biomech., 47(8), pp. 1757–1766. [CrossRef] [PubMed]
Britten, R. D. , Christie, G. R. , Little, C. , Miller, A. K. , Bradley, C. , Wu, A. , Yu, T. , Hunter, P. , and Nielsen, P. , 2013, “ FieldML, A Proposed Open Standard for the Physiome Project for Mathematical Model Representation,” Med. Biol. Eng. Comput., 51(11), pp. 1191–1207. [CrossRef] [PubMed]
Meng, Q. , Jin, Z. , Fisher, J. , and Wilcox, R. , 2013, “ Comparison Between FEBio and Abaqus for Biphasic Contact Problems,” Proc. Inst. Mech. Eng. H, 227(9), pp. 1009–1019. [CrossRef] [PubMed]
Erdemir, A. , Guess, T. M. , Halloran, J. P. , Modenese, L. , Reinbolt, J. A. , Thelen, D. G. , and Umberger, B. R. , 2016, “ Commentary on the Integration of Model Sharing and Reproducibility Analysis to Scholarly Publishing Workflow in Computational Biomechanics,” IEEE Trans. Biomed. Eng., 63(10), pp. 2080–2085. [CrossRef] [PubMed]
U.S. FDA, 2011, “ Advancing Regulatory Science at FDA: A Strategic Plan, August 2011,” U.S. Food & Drug Administration, Silver Spring, MD, accessed Dec. 1, 2018, https://www.fda.gov/downloads/ScienceResearch/SpecialTopics/RegulatoryScience/UCM268225.pdf
U.S. FDA, 2017, “ CDRH Regulatory Science Priorities (FY 2017),” U.S. Food & Drug Administration, Silver Spring, MD, accessed Dec. 1, 2018, https://www.fda.gov/downloads/medicaldevices/scienceandresearch/ucm521503. pdf
U.S. FDA, 2018, “ Medical Device Development Tools (MDDT),” U.S. Food & Drug Administration, Silver Spring, MD, accessed Dec. 1, 2018, https://www.fda.gov/medicaldevices/scienceandresearch/medicaldevicedevelopment toolsmddt/
Morrison, T. M. , Pathmanathan, P. , Adwan, M. , and Margerrison, E. , 2018, “ Advancing Regulatory Science With Computational Modeling for Medical Devices at the FDA's Office of Science and Engineering Laboratories,” Front. Med., 5, p. 241. [CrossRef]
ASME, 2018, “ Committee Pages—V & V 40 Verification and Validation in Computational Modeling of Medical Devices,” American Society of Mechanical Engineers, New York, accessed Dec. 1, 2018, https://cstools.asme.org/csconnect/CommitteePages.cfm?Committee= 100108782


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Fig. 1

Number of publications focusing on knee modeling or simulation reaches up to 1000 per year. Total number of publications (up to year 2018) is 10,895 (data from PubMed2). With the increased fidelity of simulation software and computing hardware, use of finite element analysis in computational knee mechanics has gained traction. Annual number of studies are approaching 100 (total up to year 2018 is 882).

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Fig. 2

Fundamental abstraction of modeling in knee biomechanics. Required input parameters include anatomical (geometry, mesh, etc.) and mechanical representations (stiffness, material properties, etc.) of joint components (bones, cartilage, ligaments, menisci, muscles, etc.), and loading and boundary conditions (external loads, muscular forces, etc.). Simulations look for predictions of mechanical response, e.g., joint movements, tissue stresses, and strains.

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Fig. 3

Even visually, computational models of the knee joint exhibit large variations in anatomical and mechanical representations of tissue structures. Shown are samples of work by teams collaborating in a comprehensive study to understand the art of modeling and simulation in knee biomechanics: (a) open knee(s)—generation 1 from Cleveland Clinic team (Reproduced from [7]), (b) a model from the group at University of Denver (Reproduced from [8]), (c) work by researchers at Auckland Bioengineering Institute, (d) a current model from Cleveland State University, and (e) recent modeling by the team at Hospital for Special Surgery (Reproduced from [9]).

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Fig. 4

Starting with the same data sets, each modeling and simulation (M & S) team goes through a sequence of modeling and simulation phases to come up with their own flavor of models representing the knee specimens of the data sets. The overarching goal of this study is to understand if the decisions of the modeling teams influence simulation predictions, and their interpretation to reach scientific and clinically relevant conclusions. Dissemination of all modeling and simulation outcomes and documentation of the whole lifecycle of the models will provide the opportunity to understand the source of variations in modeling decisions and the motivations behind them.

Grahic Jump Location
Fig. 5

Sample images from proposed model development specifications in regard to segmentation of ligaments: (a) the team from the University of Denver proposes to segment the posterior cruciate ligament using the paint tool in Simpleware ScanIP [63]. The segmentation will be used to determine insertion locations of springs, which will be refined using probed point data and (b) the team from the Cleveland Clinic proposes to use 3D Slicer [61] to manually segment the same ligament in order to generate a full continuum representation of its volume. It is interesting to note that both groups independently and unknowingly chose the same ligament approximately at the same image location to provide an example of ligament segmentation. Image from University of Denver documentation was cropped to match the bounds of the image from Cleveland Clinic documentation.



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