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This project aims for understanding the influence of modelers’ approaches and decisions (essentially their art) throughout the lifecycle of modeling and simulation. It will demonstrate the uncertainty of delivering consistent simulation predictions when the founding data to feed into models remain the same. The project site also aims to be a hub to provide an overview of resources for modeling & simulation of the knee joint. Funding is provided by the National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health (Grant No. R01EB024573).

License: Data for MB - DU02, Data for MB - oks003, Data for MC - DU02, Data for MC - oks003, Data for MD - DU02, Data for MD - oks003, Outcomes for MC, Outcomes for MD, Reproducibility Paper Data

Modeling and simulation offers a cost-effective and prompt path to respond to the pressing medical needs for restoration of knee function. However, the reproducibility of simulation results, to inform scientific and clinical decision making, is questionable. Reproducibility is a pressing issue in scientific conduct. For modeling and simulation, there is added scrutiny particularly with the desire to repurpose and reuse virtual specimens for prospective solutions of diverse scientific and clinical problems. A significant portion of the modeling and simulation workflow includes development, evaluation, and simulation. This workflow, while based on objective scientific principles, commonly requires intuition during implementation; therefore relies on the knowledge and expertise of the modeler. This ‘art of modeling’ can be a fundamental source of diminished reproducibility. The goal of this study is to understand how modelers’ choices to build models, even when using the same data, may influence predictions and therefore the reproducibility of simulation results. Five modeling and simulation teams will independently develop, calibrate and benchmark computational models of knees based on the same data sets and reuse these models to simulate the same scientifically and clinically relevant scenarios. Ideally, predicted joint and tissue mechanics will be the same. In practice, the skills and experiences of model developers will reflect upon their modeling choices; and as a result, discrepancies will exist. The proposed activity will document the magnitude and potential sources of such discrepancies through comparisons of model components and simulation results. This project will examine and critique the current state of model development and simulation reproducibility in joint and tissue mechanics. This will translate into reliable models of the knee joint for simulation-based discoveries and in silico design and evaluation of medical devices and interventions. The required exchange of data, model components, and simulation results among the teams and with the public will also impact developers and users of such resources. Specifications, to facilitate data and model exchange and to develop data and modeling standards, and guidance, to inform modeling and simulation workflows, will likely emerge as by-products of the research activity. Subsequently, this project aims to curate various modeling & simulation and data resources for scientific and clinical investigations of knee biomechanics. An additional goal of the project site is to be a discussion platform among investigators who collect data and build models for the knee joint.