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research-article

Deciphering the ?Art? in Modeling and Simulation of the Knee Joint

[+] Author and Article Information
Ahmet Erdemir

Department of Biomedical Engineering and Computational Biomodeling (CoBi) Core, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
erdemira@ccf.org

Thor F. Besier

Auckland Bioengineering Institute and Department of Engineering Science, University of Auckland, Auckland, New Zealand
t.besier@auckland.ac.nz

Jason P. Halloran

Department of Mechanical Engineering and the Center for Human Machine Systems, Cleveland State University, Cleveland, Ohio, USA
j.halloran64@csuohio.edu

Carl Imhauser

Department of Biomechanics, Hospital for Special Surgery, New York, New York, USA
ImhauserC@HSS.EDU

Peter J. Laz

Center for Orthopaedic Biomechanics and Department of Mechanical and Materials Engineering, University of Denver, Denver, Colorado, USA
Peter.Laz@du.edu

Tina Morrison

Division of Applied Mechanics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA
tina.morrison@fda.hhs.gov

Kevin B. Shelburne

Center for Orthopaedic Biomechanics and Department of Mechanical and Materials Engineering, University of Denver, Denver, Colorado, USA
kevin.shelburne@du.edu

1Corresponding author.

ASME doi:10.1115/1.4043346 History: Received December 04, 2018; Revised March 26, 2019

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.

Section 4: U.S. Gov Employees + Reg Authors
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