1
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Malukhin K, Rabczuk T, Ehmann K, Verta MJ. Kirchhoff's law-based velocity-controlled motion models to predict real-time cutting forces in minimally invasive surgeries. J Mech Behav Biomed Mater 2024; 154:106523. [PMID: 38554581 DOI: 10.1016/j.jmbbm.2024.106523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 03/06/2024] [Accepted: 03/21/2024] [Indexed: 04/01/2024]
Abstract
A theoretical framework, united by a "system effect" is formulated to model the cutting/haptic force evolution at the cutting edge of a surgical cutting instrument during its penetration into soft biological tissue in minimally invasive surgery. Other cutting process responses, including tissue fracture force, friction force, and damping, are predicted by the model as well. The model is based on a velocity-controlled formulation of the corresponding equations of motion, derived for a surgical cutting instrument and tissue based on Kirchhoff's fundamental energy conservation law. It provides nearly zero residues (absolute errors) in the equations of motion balances. In addition, concurrent closing relationships for the fracture force, friction coefficient, friction force, process damping, strain rate function (a constitutive tissue model), and their implementation within the proposed theoretical framework are established. The advantage of the method is its ability to make precise real-time predictions of the aperiodic fluctuating evolutions of the cutting forces and the other process responses. It allows for the robust modeling of the interactions between a medical instrument and a nonlinear viscoelastic tissue under any physically feasible working conditions. The cutting process model was partially qualitatively verified through numerical simulations and by comparing the computed cutting forces with experimentally measured values during robotic uniaxial biopsy needle constant velocity insertion into artificial gel tissue, obtained from previous experimental research. The comparison has shown a qualitatively similar adequate trend in the evolution of the experimentally measured and numerically predicted cutting forces during insertion of the needle.
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Affiliation(s)
- Kostyantyn Malukhin
- Northwestern University, Department of Mechanical Engineering, McCormick School of Engineering, 2145 Sheridan Road, Evanston, IL, 60208, USA.
| | - Timon Rabczuk
- Bauhaus University, Department of Computational Mechanics, School of Civil Engineering, Marienstrasse 15, Weimar, 99423, Germany
| | - Kornel Ehmann
- Northwestern University, Department of Mechanical Engineering, McCormick School of Engineering, 2145 Sheridan Road, Evanston, IL, 60208, USA
| | - Michael J Verta
- Northwestern University, Feinberg School of Medicine, Department of Surgery, 420 E. Superior St., Chicago, IL, 60611, USA
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2
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Imhauser CW, Baumann AP, Liu XC, Bischoff JE, Verdonschot N, Fregly BJ, Elmasry SS, Abdollahi NN, Hume DR, Rooks NB, Schneider MTY, Zaylor W, Besier TF, Halloran JP, Shelburne KB, Erdemir A. Reproducibility in modeling and simulation of the knee: Academic, industry, and regulatory perspectives. J Orthop Res 2023; 41:2569-2578. [PMID: 37350016 DOI: 10.1002/jor.25652] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 04/23/2023] [Accepted: 05/30/2023] [Indexed: 06/24/2023]
Abstract
Stakeholders in the modeling and simulation (M&S) community organized a workshop at the 2019 Annual Meeting of the Orthopaedic Research Society (ORS) entitled "Reproducibility in Modeling and Simulation of the Knee: Academic, Industry, and Regulatory Perspectives." The goal was to discuss efforts among these stakeholders to address irreproducibility in M&S focusing on the knee joint. An academic representative from a leading orthopedic hospital in the United States described a multi-institutional, open effort funded by the National Institutes of Health to assess model reproducibility in computational knee biomechanics. A regulatory representative from the United States Food and Drug Administration indicated the necessity of standards for reproducibility to increase utility of M&S in the regulatory setting. An industry representative from a major orthopedic implant company emphasized improving reproducibility by addressing indeterminacy in personalized modeling through sensitivity analyses, thereby enhancing preclinical evaluation of joint replacement technology. Thought leaders in the M&S community stressed the importance of data sharing to minimize duplication of efforts. A survey comprised 103 attendees revealed strong support for the workshop and for increasing emphasis on computational modeling at future ORS meetings. Nearly all survey respondents (97%) considered reproducibility to be an important issue. Almost half of respondents (45%) tried and failed to reproduce the work of others. Two-thirds of respondents (67%) declared that individual laboratories are most responsible for ensuring reproducible research whereas 44% thought that journals are most responsible. Thought leaders and survey respondents emphasized that computational models must be reproducible and credible to advance knee M&S.
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Affiliation(s)
- Carl W Imhauser
- Department of Biomechanics, Hospital for Special Surgery, New York, New York, USA
| | - Andrew P Baumann
- US Food and Drug Administration, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Division of Applied Mechanics, Silver Spring, Maryland, USA
| | | | | | - Nico Verdonschot
- Department of Biomechanical Engineering, Technical Medical Institute at University of Twente, Enschede, The Netherlands
- Orthopaedic Research Lab, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Benjamin J Fregly
- Department of Mechanical Engineering, Rice University, Houston, Texas, USA
| | - Shady S Elmasry
- Department of Biomechanics, Hospital for Special Surgery, New York, New York, USA
- Department of Mechanical Design and Production, Faculty of Engineering, Cairo University, Cairo, Egypt
| | - Neda N Abdollahi
- Center for Human Machine Systems, Cleveland State University, Cleveland, Ohio, USA
- Department of Mechanical Engineering, Cleveland State University, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Donald R Hume
- Department of Mechanical and Materials Engineering, University of Denver, Denver, Colorado, USA
- Center for Orthopaedic Biomechanics, University of Denver, Denver, Colorado, USA
| | - Nynke B Rooks
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Marco T-Y Schneider
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - William Zaylor
- Center for Human Machine Systems, Cleveland State University, Cleveland, Ohio, USA
- Department of Mechanical Engineering, Cleveland State University, Cleveland, Ohio, USA
| | - Thor F Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Engineering Science, Faculty of Engineering, University of Auckland, Auckland, New Zealand
| | - Jason P Halloran
- Applied Sciences Laboratory, Institute for Shock Physics, Washington State University, Spokane, Washington, USA
| | - Kevin B Shelburne
- Department of Mechanical and Materials Engineering, University of Denver, Denver, Colorado, USA
- Center for Orthopaedic Biomechanics, University of Denver, Denver, Colorado, USA
| | - Ahmet Erdemir
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
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3
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Zdziechowski A, Gluba-Sagr A, Rysz J, Woldańska-Okońska M. Why Does Rehabilitation Not (Always) Work in Osteoarthritis? Does Rehabilitation Need Molecular Biology? Int J Mol Sci 2023; 24:ijms24098109. [PMID: 37175818 PMCID: PMC10179350 DOI: 10.3390/ijms24098109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/14/2023] [Accepted: 04/20/2023] [Indexed: 05/15/2023] Open
Abstract
Osteoarthritis (OA) is a common disease among the human population worldwide. OA causes functional impairment, leads to disability and poses serious socioeconomic burden. The rehabilitation offers a function-oriented method to reduce the disability using diverse interventions (kinesiotherapy, physical therapy, occupational therapy, education, and pharmacotherapy). OA as a widespread disease among elderly patients is often treated by rehabilitation specialists and physiotherapists, however the results of rehabilitation are sometimes unsatisfactory. The understanding of molecular mechanisms activated by rehabilitation may enable the development of more effective rehabilitation procedures. Molecular biology methods may prove crucial in rehabilitation as the majority of rehabilitation procedures cannot be estimated in double-blinded placebo-controlled trials commonly used in pharmacotherapy. This article attempts to present and estimate the role of molecular biology in the development of modern rehabilitation. The role of clinicians in adequate molecular biology experimental design is also described.
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Affiliation(s)
- Adam Zdziechowski
- Department of Internal Diseases, Rehabilitation and Physical Medicine, Medical University, 90-700 Łódź, Poland
| | - Anna Gluba-Sagr
- Department of Nephrology, Hypertension and Family Medicine, Medical University of Lodz, 90-549 Łódź, Poland
| | - Jacek Rysz
- Department of Nephrology, Hypertension and Family Medicine, Medical University of Lodz, 90-549 Łódź, Poland
| | - Marta Woldańska-Okońska
- Department of Internal Diseases, Rehabilitation and Physical Medicine, Medical University, 90-700 Łódź, Poland
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4
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Halloran JP, Abdollahi Nohouji N, Hafez MA, Besier TF, Chokhandre SK, Elmasry S, Hume DR, Imhauser CW, Rooks NB, Schneider MTY, Schwartz A, Shelburne KB, Zaylor W, Erdemir A. Assessment of reporting practices and reproducibility potential of a cohort of published studies in computational knee biomechanics. J Orthop Res 2023; 41:325-334. [PMID: 35502762 PMCID: PMC9630164 DOI: 10.1002/jor.25358] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 03/22/2022] [Accepted: 04/20/2022] [Indexed: 02/04/2023]
Abstract
Reproducible research serves as a pillar of the scientific method and is a foundation for scientific advancement. However, estimates for irreproducibility of preclinical science range from 75% to 90%. The importance of reproducible science has not been assessed in the context of mechanics-based modeling of human joints such as the knee, despite this being an area that has seen dramatic growth. Framed in the context of five experienced teams currently documenting knee modeling procedures, the aim of this study was to evaluate reporting and the perceived potential for reproducibility across studies the teams viewed as important contributions to the literature. A cohort of studies was selected by polling, which resulted in an assessment of nine studies as opposed to a broader analysis across the literature. Using a published checklist for reporting of modeling features, the cohort was evaluated for both "reporting" and their potential to be "reproduced," which was delineated into six major modeling categories and three subcategories. Logistic regression analysis revealed that for individual modeling categories, the proportion of "reported" occurrences ranged from 0.31, 95% confidence interval (CI) [0.23, 0.41] to 0.77, 95% CI: [0.68, 0.86]. The proportion of whether a category was perceived as "reproducible" ranged from 0.22, 95% CI: [0.15, 0.31] to 0.44, 95% CI: [0.35, 0.55]. The relatively low ratios highlight an opportunity to improve reporting and reproducibility of knee modeling studies. Ongoing efforts, including our findings, contribute to a dialogue that facilitates adoption of practices that provide both credibility and translation possibilities.
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Affiliation(s)
- Jason P Halloran
- Applied Sciences Laboratory, Institute for Shock Physics, Washington State University, Spokane, WA, USA,Corresponding author: Applied Sciences Laboratory, Institute for Shock Physics, 412 E Spokane Falls Blvd, Spokane, WA 99202, Phone: 509-358-7713,
| | - Neda Abdollahi Nohouji
- Center for Human Machine Systems, Cleveland State University, Cleveland, OH, USA,Department of Mechanical Engineering, Cleveland State University, Cleveland, OH, USA,Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OHIO, USA
| | - Mhd Ammar Hafez
- Center for Human Machine Systems, Cleveland State University, Cleveland, OH, USA,Department of Civil Engineering, Cleveland State University, Cleveland, OH, USA
| | - Thor F Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland, NZ,Department of Engineering Science, Faculty of Engineering, University of Auckland, Auckland, NZ
| | - Snehal K Chokhandre
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OHIO, USA,Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, USA
| | - Shady Elmasry
- Department of Biomechanics, Hospital for Special Surgery, New York, NY, USA
| | - Donald R Hume
- Department of Mechanical and Materials Engineering, University of Denver, Denver, CO, USA,Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA
| | - Carl W Imhauser
- Department of Biomechanics, Hospital for Special Surgery, New York, NY, USA
| | - Nynke B Rooks
- Auckland Bioengineering Institute, University of Auckland, Auckland, NZ
| | | | - Ariel Schwartz
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OHIO, USA,Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, USA
| | - Kevin B Shelburne
- Department of Mechanical and Materials Engineering, University of Denver, Denver, CO, USA,Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, USA
| | - William Zaylor
- Center for Human Machine Systems, Cleveland State University, Cleveland, OH, USA,Department of Mechanical Engineering, Cleveland State University, Cleveland, OH, USA
| | - Ahmet Erdemir
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OHIO, USA,Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, USA
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5
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Chokhandre S, Schwartz A, Klonowski E, Landis B, Erdemir A. Open Knee(s): A Free and Open Source Library of Specimen-Specific Models and Related Digital Assets for Finite Element Analysis of the Knee Joint. Ann Biomed Eng 2023; 51:10-23. [PMID: 36104640 PMCID: PMC9832097 DOI: 10.1007/s10439-022-03074-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 09/04/2022] [Indexed: 01/28/2023]
Abstract
There is a growing interest in the use of virtual representations of the knee for musculoskeletal research and clinical decision making, and to generate digital evidence for design and regulation of implants. Accessibility to previously developed models and related digital assets can dramatically reduce barriers to entry to conduct simulation-based studies of the knee joint and therefore help accelerate scientific discovery and clinical innovations. Development of models for finite element analysis is a demanding process that is both time consuming and resource intensive. It necessitates expertise to transform raw data to reliable virtual representations. Modeling and simulation workflow has many processes such as image segmentation, surface geometry generation, mesh generation and finally, creation of a finite element representation with relevant loading and boundary conditions. The outcome of the workflow is not only the end-point knee model but also many other digital by-products. When all of these data, derivate assets, and tools are freely and openly accessible, researchers can bypass some or all the steps required to build models and focus on using them to address their research goals. With provenance to specimen-specific anatomical and mechanical data and traceability of digital assets throughout the whole lifecycle of the model, reproducibility and credibility of the modeling practice can be established. The objective of this study is to disseminate Open Knee(s), a cohort of eight knee models (and relevant digital assets) for finite element analysis, that are based on comprehensive specimen-specific imaging data. In addition, the models and by-products of modeling workflows are described along with model development strategies and tools. Passive flexion served as a test simulation case, demonstrating an end-user application. Potential roadmaps for reuse of Open Knee(s) are also discussed.
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Affiliation(s)
- Snehal Chokhandre
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH USA
| | - Ariel Schwartz
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH USA
| | - Ellen Klonowski
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH USA
| | - Benjamin Landis
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH USA
| | - Ahmet Erdemir
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH USA
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6
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Rooks NB, Schneider MTY, Erdemir A, Halloran JP, Laz PJ, Shelburne KB, Hume DR, Imhauser CW, Zaylor W, Elmasry S, Schwartz A, Chokhandre SK, Abdollahi Nohouji N, Besier TF. Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Variations in Model Development. J Biomech Eng 2021; 143:061002. [PMID: 33537727 PMCID: PMC8086182 DOI: 10.1115/1.4050028] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 01/19/2021] [Indexed: 11/08/2022]
Abstract
The use of computational modeling to investigate knee joint biomechanics has increased exponentially over the last few decades. Developing computational models is a creative process where decisions have to be made, subject to the modelers' knowledge and previous experiences, resulting in the "art" of modeling. The long-term goal of the KneeHub project is to understand the influence of subjective decisions on the final outcomes and the reproducibility of computational knee joint models. In this paper, we report on the model development phase of this project, investigating model development decisions and deviations from initial modeling plans. Five teams developed computational knee joint models from the same dataset, and we compared each teams' initial uncalibrated models and their model development workflows. Variations in the software tools and modeling approaches were found, resulting in differences such as the representation of the anatomical knee joint structures in the model. The teams consistently defined the boundary conditions and used the same anatomical coordinate system convention. However, deviations in the anatomical landmarks used to define the coordinate systems were present, resulting in a large spread in the kinematic outputs of the uncalibrated models. The reported differences and similarities in model development and simulation presented here illustrate the importance of the "art" of modeling and how subjective decision-making can lead to variation in model outputs. All teams deviated from their initial modeling plans, indicating that model development is a flexible process and difficult to plan in advance, even for experienced teams.
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Affiliation(s)
- Nynke B. Rooks
- Auckland Bioengineering Institute, University of Auckland, Level 6/70 Symonds Street, Grafton, Auckland 1010, New Zealand
| | - Marco T. Y. Schneider
- Auckland Bioengineering Institute, University of Auckland, Level 6/70 Symonds Street, Grafton, Auckland 1010, New Zealand
| | - Ahmet Erdemir
- Department of Biomedical Engineering & Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue (ND20), Cleveland, OH 44195
| | - Jason P. Halloran
- Applied Sciences Laboratory, Institute for Shock Physics, Washington State University, 1455 E. College Avenue, Spokane, Pullman, WA 99164
| | - Peter J. Laz
- Department of Mechanical and Materials Engineering, Center for Orthopaedic Biomechanics, University of Denver, 2155 E. Wesley Avenue, Denver, CO 80210
| | - Kevin B. Shelburne
- Department of Mechanical and Materials Engineering, Center for Orthopaedic Biomechanics, University of Denver, 2155 E. Wesley Avenue, Denver, CO 80210
| | - Donald R. Hume
- Department of Mechanical and Materials Engineering, Center for Orthopaedic Biomechanics, University of Denver, 2155 E. Wesley Avenue, Denver, CO 80210
| | - Carl W. Imhauser
- Department of Biomechanics, Hospital for Special Surgery, 535 E. 70th Street, New York, NY 10021
| | - William Zaylor
- Department of Mechanical Engineering, Center for Human Machine Systems, Cleveland State University, 1960 E 24th Street, Cleveland, OH 44115
| | - Shady Elmasry
- Department of Biomechanics, Hospital for Special Surgery, 535 E. 70th Street, New York, NY 10021
| | - Ariel Schwartz
- Department of Biomedical Engineering & Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue (ND20), Cleveland, OH 44195
| | - Snehal K. Chokhandre
- Department of Biomedical Engineering & Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue (ND20), Cleveland, OH 44195
| | - Neda Abdollahi Nohouji
- Department of Mechanical Engineering, Center for Human Machine Systems, Cleveland State University, 1960 E 24th Street, Cleveland, OH 44115; Department of Biomedical Engineering & Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue (ND20), Cleveland, OH 44195
| | - Thor F. Besier
- Department of Engineering Science, Faculty of Engineering, Auckland Bioengineering Institute, University of Auckland, Level 6/70 Symonds Street, Grafton, Auckland 1010, New Zealand
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7
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A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11052037] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The ultimate goal of most neuromusculoskeletal modeling research is to improve the treatment of movement impairments. However, even though neuromusculoskeletal models have become more realistic anatomically, physiologically, and neurologically over the past 25 years, they have yet to make a positive impact on the design of clinical treatments for movement impairments. Such impairments are caused by common conditions such as stroke, osteoarthritis, Parkinson’s disease, spinal cord injury, cerebral palsy, limb amputation, and even cancer. The lack of clinical impact is somewhat surprising given that comparable computational technology has transformed the design of airplanes, automobiles, and other commercial products over the same time period. This paper provides the author’s personal perspective for how neuromusculoskeletal models can become clinically useful. First, the paper motivates the potential value of neuromusculoskeletal models for clinical treatment design. Next, it highlights five challenges to achieving clinical utility and provides suggestions for how to overcome them. After that, it describes clinical, technical, collaboration, and practical needs that must be addressed for neuromusculoskeletal models to fulfill their clinical potential, along with recommendations for meeting them. Finally, it discusses how more complex modeling and experimental methods could enhance neuromusculoskeletal model fidelity, personalization, and utilization. The author hopes that these ideas will provide a conceptual blueprint that will help the neuromusculoskeletal modeling research community work toward clinical utility.
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8
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Erdemir A, Mulugeta L, Ku JP, Drach A, Horner M, Morrison TM, Peng GCY, Vadigepalli R, Lytton WW, Myers JG. Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective. J Transl Med 2020; 18:369. [PMID: 32993675 PMCID: PMC7526418 DOI: 10.1186/s12967-020-02540-4] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 09/21/2020] [Indexed: 11/10/2022] Open
Abstract
The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the development and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder community survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing implementations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.
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Affiliation(s)
- Ahmet Erdemir
- Department of Biomedical Engineering and Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue (ND20), Cleveland, OH, 44195, USA.,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA
| | - Lealem Mulugeta
- InSilico Labs LLC, 2617 Bissonnet St. Suite 435, Houston, TX, 77005, USA.,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA
| | - Joy P Ku
- Department of Bioengineering, Clark Center, Stanford University, 318 Campus Drive, Stanford, CA, 94305-5448, USA.,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA
| | - Andrew Drach
- Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, 201 E. 24th st, Austin, TX, 78712, USA.,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA
| | - Marc Horner
- ANSYS, Inc, 1007 Church Street, Suite 250, Evanston, IL, 60201, USA.,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA
| | - Tina M Morrison
- Division of Applied Mechanics, United States Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA.,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA
| | - Grace C Y Peng
- National Institute of Biomedical Imaging & Bioengineering, Suite 200, MSC 6707 Democracy Blvd5469, Bethesda, MD, 20892, USA.,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA
| | - Rajanikanth Vadigepalli
- Department of Pathology, Anatomy and Cell Biology, Daniel Baugh Institute for Functional Genomics/Computational Biology, Thomas Jefferson University, 1020 Locust St, Philadelphia, PA, 19107, USA.,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA
| | - William W Lytton
- State University of New York, Kings County Hospital, 450 Clarkson Ave., MSC 31, Brooklyn, NY, 11203, USA.,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA
| | - Jerry G Myers
- Human Research Program, Cross-Cutting Computational Modeling Project, National Aeronautics and Space Administration - John H. Glenn Research Center, 21000 Brookpark Road, Cleveland, OH, 44135, USA. .,Committee on Credible Practice of Modeling, & Simulation in Healthcare, Interagency Modeling and Analysis Group and Multiscale Modeling Consortium, Bethesda, MD, USA.
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9
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Erdemir A, Besier TF, Halloran JP, Imhauser CW, Laz PJ, Morrison TM, Shelburne KB. Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Overall Strategy. J Biomech Eng 2020; 141:2730179. [PMID: 31166589 DOI: 10.1115/1.4043346] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Indexed: 12/26/2022]
Abstract
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.
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Affiliation(s)
- 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:
| | - 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
- 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
| | - Kevin B Shelburne
- Department of Mechanical and Materials Engineering, Center for Orthopaedic Biomechanics, University of Denver, Denver, CO 80210
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10
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Cooper RJ, Wilcox RK, Jones AC. Finite element models of the tibiofemoral joint: A review of validation approaches and modelling challenges. Med Eng Phys 2019; 74:1-12. [DOI: 10.1016/j.medengphy.2019.08.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 08/05/2019] [Accepted: 08/21/2019] [Indexed: 12/20/2022]
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11
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A modeling algorithm for exploring the architecture and construction of bird nests. Sci Rep 2019; 9:14772. [PMID: 31611582 PMCID: PMC6791838 DOI: 10.1038/s41598-019-51478-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 09/30/2019] [Indexed: 11/20/2022] Open
Abstract
The wide variety of nest architectural designs exhibited by passerine birds allowed them to diversify into a wide variety of ecological niches and terrestrial habitats. At present, very little is known about the mechanics of building these structures. Digitizing natural biological structures such as bird nests provides the opportunity to explore their structural properties and behavior under specific conditions by means of computational manipulations, simulations, and analyses. This study describes a generic algorithm for the digitization and exploration of complex interlocked bird nests, and validates it on nests built by the Dead-Sea Sparrow (Passer moabiticus) in branches of trees using stiff dry branches. This algorithm takes as input computerized tomographic scans of the nest, identifies and isolates each branch entity within the three-dimensional data, and finally extracts the characteristics of each branch. The result is a reliable three-dimensional digital model of the nest that contains a complete geometric dataset per each of its components, e.g. dimensions and contact points with neighboring components, as well as global properties, e.g. density distribution and network structure. Based on these, we were able to simulate various models of the nest construction process. Altogether, the described algorithm and possible derivatives thereof could be a valuable tool in studying the structure-function relationships of similarly complex biological objects, and may provide further insights into the potential selective mechanisms underlying historical evolution of this distinct nest form.
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12
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Franssen FME, Alter P, Bar N, Benedikter BJ, Iurato S, Maier D, Maxheim M, Roessler FK, Spruit MA, Vogelmeier CF, Wouters EFM, Schmeck B. Personalized medicine for patients with COPD: where are we? Int J Chron Obstruct Pulmon Dis 2019; 14:1465-1484. [PMID: 31371934 PMCID: PMC6636434 DOI: 10.2147/copd.s175706] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2019] [Accepted: 06/05/2019] [Indexed: 12/19/2022] Open
Abstract
Chronic airflow limitation is the common denominator of patients with chronic obstructive pulmonary disease (COPD). However, it is not possible to predict morbidity and mortality of individual patients based on the degree of lung function impairment, nor does the degree of airflow limitation allow guidance regarding therapies. Over the last decades, understanding of the factors contributing to the heterogeneity of disease trajectories, clinical presentation, and response to existing therapies has greatly advanced. Indeed, diagnostic assessment and treatment algorithms for COPD have become more personalized. In addition to the pulmonary abnormalities and inhaler therapies, extra-pulmonary features and comorbidities have been studied and are considered essential components of comprehensive disease management, including lifestyle interventions. Despite these advances, predicting and/or modifying the course of the disease remains currently impossible, and selection of patients with a beneficial response to specific interventions is unsatisfactory. Consequently, non-response to pharmacologic and non-pharmacologic treatments is common, and many patients have refractory symptoms. Thus, there is an ongoing urgency for a more targeted and holistic management of the disease, incorporating the basic principles of P4 medicine (predictive, preventive, personalized, and participatory). This review describes the current status and unmet needs regarding personalized medicine for patients with COPD. Also, it proposes a systems medicine approach, integrating genetic, environmental, (micro)biological, and clinical factors in experimental and computational models in order to decipher the multilevel complexity of COPD. Ultimately, the acquired insights will enable the development of clinical decision support systems and advance personalized medicine for patients with COPD.
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Affiliation(s)
- Frits ME Franssen
- Department of Research and Education, CIRO, Horn, The Netherlands
- Department of Respiratory Medicine, Maastricht University Medical Centre, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht, The Netherlands
| | - Peter Alter
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Nadav Bar
- Department of Chemical Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Birke J Benedikter
- Institute for Lung Research, Universities of Giessen and Marburg Lung Centre, Philipps-University Marburg, Member of the German Center for Lung Research (DZL), Marburg, Germany
- Department of Medical Microbiology, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands
| | | | | | - Michael Maxheim
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Fabienne K Roessler
- Department of Chemical Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Martijn A Spruit
- Department of Research and Education, CIRO, Horn, The Netherlands
- Department of Respiratory Medicine, Maastricht University Medical Centre, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht, The Netherlands
- REVAL - Rehabilitation Research Center, BIOMED - Biomedical Research Institute, Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, Belgium
| | - Claus F Vogelmeier
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Emiel FM Wouters
- Department of Research and Education, CIRO, Horn, The Netherlands
- Department of Respiratory Medicine, Maastricht University Medical Centre, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht, The Netherlands
| | - Bernd Schmeck
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps University of Marburg (UMR), Member of the German Center for Lung Research (DZL), Marburg, Germany
- Institute for Lung Research, Universities of Giessen and Marburg Lung Centre, Philipps-University Marburg, Member of the German Center for Lung Research (DZL), Marburg, Germany
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