Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Overall Strategy
Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Overall Strategy
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DOI：
10.1115/1.4043346
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发表时间：
2019-07-01
影响因子：
1.7
通讯作者：
Shelburne, Kevin B.
中科院分区：
文献类型：
--
作者：
Erdemir, Ahmet;Besier, Thor F.;Shelburne, Kevin B.
膝关节生物力学的最新探索受益于计算建模，特别是利用关节和组织力学的有限元分析和刚体动力学的进步。出现了大量的模型，在解剖和机械表示方面具有不同程度的保真度。根据与模型预期用途相关的合理选择，适应性建模和模拟过程差异很大。然而，在某些情况下，建模者的决策似乎是主观的、武断的，并且难以合理化。无论基于何种基础，这些决策都构成了建模的“艺术”，这会影响基于模拟的膝关节功能研究的结论。这些决定还可能阻碍模型和模拟的可重复性，阻碍它们在临床决策和个性化医疗等领域的更广泛应用。本文总结了一个正在进行的项目，旨在捕捉建模和仿真工作流程的整体操作程序，偏差，模型，建模的副产品，仿真结果，案例研究和应用的比较评估。该项目的最终目标是通过一种公开、透明的方法来描绘一组膝关节建模团队的艺术，并开始解开可能导致缺乏可重复性的复杂因素。这份手稿概述了我们的方法沿着迄今取得的进展。潜在的影响，再现性，对科学，工程和培训的建模和模拟，建模标准，和监管事务也注意到。
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.