Validating subject-specific knee models from in vivo measurements

Despite the documented consequences of modeling decisions on the performance of computational models in orthopaedics and biomechanics, the influence of the input data has largely been ignored. Modeling the living knee is limited by methods to measure in vivo the quantities needed for ligament calibr...

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Main Authors: Thor E. Andreassen, Donald R. Hume, Landon D. Hamilton, Stormy L. Hegg, Sean E. Higinbotham, Kevin B. Shelburne
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Bioengineering and Biotechnology
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Online Access:https://www.frontiersin.org/articles/10.3389/fbioe.2025.1554836/full
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author Thor E. Andreassen
Thor E. Andreassen
Donald R. Hume
Landon D. Hamilton
Stormy L. Hegg
Sean E. Higinbotham
Kevin B. Shelburne
author_facet Thor E. Andreassen
Thor E. Andreassen
Donald R. Hume
Landon D. Hamilton
Stormy L. Hegg
Sean E. Higinbotham
Kevin B. Shelburne
author_sort Thor E. Andreassen
collection DOAJ
description Despite the documented consequences of modeling decisions on the performance of computational models in orthopaedics and biomechanics, the influence of the input data has largely been ignored. Modeling the living knee is limited by methods to measure in vivo the quantities needed for ligament calibration; yet, this may be possible with new devices focused on non-invasive measurement of knee laxity. These devices offer measurements similar to those commonly obtained from cadaveric specimens but are limited by what can be practically and safely obtained from a living subject. Validation of models calibrated with in vivo data is crucial and increasingly important as personalized modeling becomes the basis for proposed digital twins, and in silico clinical trial workflows. To support our overall goal of building subject-specific models of the living knee, we aimed to show that subject-specific computational models calibrated using in vivo measurements would have accuracy comparable to models calibrated using in vitro measurements. Two cadaveric knee specimens were imaged using a combination of computed tomography (CT) and surface scans. Knee laxity measurements were made with a custom apparatus used for the living knee and from a robotic knee simulator. Models of the knees were built following previous methods and then calibrated with either laxity data from the in vitro robotic knee simulator (RKS) or from the in vivo knee laxity apparatus (KLA). Model performance was compared by simulation of various activities and found to be similar between models calibrated with laxity targets from the RKS and the KLA. Model predictions during simulated anterior-posterior laxity tests differed by less than 2.5 mm and within 2.6° and 2.8 mm during a simulated pivot shift. Still, differences in the predicted ligament loads and calibrated material properties emerged, highlighting a need for methods to include ligament load as part of the calibration process. Overall, the results showed that currently available methods of measuring knee laxity in vivo are sufficient to calibrate models comparable with existing in vitro techniques, and the workflows described here may provide a basis for modeling the living knee. The experimental data, models, results, and tools are publicly available.
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issn 2296-4185
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spelling doaj-art-203ce76eabc842fc80034b276a67b6932025-08-20T04:00:56ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852025-08-011310.3389/fbioe.2025.15548361554836Validating subject-specific knee models from in vivo measurementsThor E. Andreassen0Thor E. Andreassen1Donald R. Hume2Landon D. Hamilton3Stormy L. Hegg4Sean E. Higinbotham5Kevin B. Shelburne6Center for Orthopaedic Biomechanics, Department of Mechanical and Materials Engineering, University of Denver, Denver, CO, United StatesAssistive and Restorative Technology Laboratory, Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, United StatesCenter for Orthopaedic Biomechanics, Department of Mechanical and Materials Engineering, University of Denver, Denver, CO, United StatesCenter for Orthopaedic Biomechanics, Department of Mechanical and Materials Engineering, University of Denver, Denver, CO, United StatesCenter for Orthopaedic Biomechanics, Department of Mechanical and Materials Engineering, University of Denver, Denver, CO, United StatesCenter for Orthopaedic Biomechanics, Department of Mechanical and Materials Engineering, University of Denver, Denver, CO, United StatesCenter for Orthopaedic Biomechanics, Department of Mechanical and Materials Engineering, University of Denver, Denver, CO, United StatesDespite the documented consequences of modeling decisions on the performance of computational models in orthopaedics and biomechanics, the influence of the input data has largely been ignored. Modeling the living knee is limited by methods to measure in vivo the quantities needed for ligament calibration; yet, this may be possible with new devices focused on non-invasive measurement of knee laxity. These devices offer measurements similar to those commonly obtained from cadaveric specimens but are limited by what can be practically and safely obtained from a living subject. Validation of models calibrated with in vivo data is crucial and increasingly important as personalized modeling becomes the basis for proposed digital twins, and in silico clinical trial workflows. To support our overall goal of building subject-specific models of the living knee, we aimed to show that subject-specific computational models calibrated using in vivo measurements would have accuracy comparable to models calibrated using in vitro measurements. Two cadaveric knee specimens were imaged using a combination of computed tomography (CT) and surface scans. Knee laxity measurements were made with a custom apparatus used for the living knee and from a robotic knee simulator. Models of the knees were built following previous methods and then calibrated with either laxity data from the in vitro robotic knee simulator (RKS) or from the in vivo knee laxity apparatus (KLA). Model performance was compared by simulation of various activities and found to be similar between models calibrated with laxity targets from the RKS and the KLA. Model predictions during simulated anterior-posterior laxity tests differed by less than 2.5 mm and within 2.6° and 2.8 mm during a simulated pivot shift. Still, differences in the predicted ligament loads and calibrated material properties emerged, highlighting a need for methods to include ligament load as part of the calibration process. Overall, the results showed that currently available methods of measuring knee laxity in vivo are sufficient to calibrate models comparable with existing in vitro techniques, and the workflows described here may provide a basis for modeling the living knee. The experimental data, models, results, and tools are publicly available.https://www.frontiersin.org/articles/10.3389/fbioe.2025.1554836/fullfinite element modelvalidationsubject-specifickneecomputational modeling and simulationin vivo
spellingShingle Thor E. Andreassen
Thor E. Andreassen
Donald R. Hume
Landon D. Hamilton
Stormy L. Hegg
Sean E. Higinbotham
Kevin B. Shelburne
Validating subject-specific knee models from in vivo measurements
Frontiers in Bioengineering and Biotechnology
finite element model
validation
subject-specific
knee
computational modeling and simulation
in vivo
title Validating subject-specific knee models from in vivo measurements
title_full Validating subject-specific knee models from in vivo measurements
title_fullStr Validating subject-specific knee models from in vivo measurements
title_full_unstemmed Validating subject-specific knee models from in vivo measurements
title_short Validating subject-specific knee models from in vivo measurements
title_sort validating subject specific knee models from in vivo measurements
topic finite element model
validation
subject-specific
knee
computational modeling and simulation
in vivo
url https://www.frontiersin.org/articles/10.3389/fbioe.2025.1554836/full
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AT landondhamilton validatingsubjectspecifickneemodelsfrominvivomeasurements
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