Abstract
AbstractThere 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.
Funder
National Institute of General Medical Sciences
National Institute of Biomedical Imaging and Bioengineering
Publisher
Springer Science and Business Media LLC
Reference53 articles.
1. 3D Slicer image computing platform. 3D Slicer. https://slicer.org/ Accessed September 9, 2022
2. Assessing Credibility of Computational Modeling through Verification & Validation: Application to Medical Devices—ASME. https://www.asme.org/codes-standards/find-codes-standards/v-v-40-assessing-credibility-computational-modeling-verification-validation-application-medical-devices Accessed September 9, 2022
3. Bendjaballah, M. Z., A. Shirazi-Adl, and D. J. Zukor. Finite element analysis of human knee joint in varus-valgus. Clin. Biomech. (Bristol, Avon). 12(3):139–148, 1997. https://doi.org/10.1016/s0268-0033(97)00072-7.
4. Besier, T. F., S. Pal, C. E. Draper, et al. The role of cartilage stress in patellofemoral pain. Med. Sci. Sports Exerc. 47(11):2416–2422, 2015. https://doi.org/10.1249/MSS.0000000000000685.
5. Carniel, E. L., I. Toniolo, and C. G. Fontanella. Computational biomechanics: in-silico tools for the investigation of surgical procedures and devices. Bioengineering (Basel). 7(2):E48, 2020. https://doi.org/10.3390/bioengineering7020048.
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