The objectives of this proposal are to create a multi-scale, finite element (FE) model of the human body that combines dynamic muscle modeling and structural FE analysis into a single framework, to validate the model at multiple scales by comparison to in vitro and in vivo data, and to apply the modeling framework to subject- specific analyses of the natural and TKR implanted knee during activities of daily living. The FE framework allows for interchangeable rigid and deformable representations of the tissues, which enables stress and strain evaluation in muscle, ligament and cartilage structures. Current computational models of the musculoskeletal system do not incorporate into a single framework the multi-scale complexity of the musculoskeletal system, the force and redundancy of the many muscles spanning the joints, and the deformability of the tissues. Due in part to these limitations, computer models and simulations are not widely applied in orthopedics and musculoskeletal research.
The specific aims of this proposal will address these limitations and accelerate innovation in human modeling and simulation by opening a new path for more realistic representation of human tissue. For the first time, muscle forces for test subjects will e predicted by optimization within a single multi-scale deformable modeling framework. Significantly, accurate knowledge of the forces, stresses and strains transmitted to the tissues cuts across many scales and disciplines. This ground-breaking initiative will help engineers, clinicians, and researchers to create and improve the design of surgical procedures, rehabilitation protocols, prosthetics and implants, and improve understanding of injury and disease.

Public Health Relevance

The objectives of this proposal are to create a multi-scale, finite element (FE) model of the human body that combines dynamic muscle modeling and structural FE analysis into a single framework, to validate the model at multiple scales by comparison to in vitro and in vivo data, and to apply the modeling framework to subject-specific analyses of the natural and TKR implanted knee during activities of daily living. The FE framework allows for interchangeable rigid and deformable representations of the tissues, which enables stress and strain evaluation in muscle, ligament and cartilage structures. This ground-breaking initiative will help engineers, clinicians, and researchers to create and improve the design of surgical procedures, rehabilitation protocols, prosthetics and implants, and improve understanding of injury and disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
1R01EB015497-01
Application #
8350729
Study Section
Special Emphasis Panel (ZRG1-SBIB-Q (80))
Program Officer
Peng, Grace
Project Start
2012-08-01
Project End
2016-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
1
Fiscal Year
2012
Total Cost
$321,870
Indirect Cost
$75,270
Name
University of Denver
Department
Type
Other Domestic Higher Education
DUNS #
007431760
City
Denver
State
CO
Country
United States
Zip Code
80208
Ali, Azhar A; Mannen, Erin M; Rullkoetter, Paul J et al. (2018) In vivo comparison of medialized dome and anatomic patellofemoral geometries using subject-specific computational modeling. J Orthop Res 36:1910-1918
Navacchia, Alessandro; Kefala, Vasiliki; Shelburne, Kevin B (2017) Dependence of Muscle Moment Arms on In Vivo Three-Dimensional Kinematics of the Knee. Ann Biomed Eng 45:789-798
Smoger, Lowell M; Shelburne, Kevin B; Cyr, Adam J et al. (2017) Statistical shape modeling predicts patellar bone geometry to enable stereo-radiographic kinematic tracking. J Biomech 58:187-194
Ali, Azhar A; Harris, Michael D; Shalhoub, Sami et al. (2017) Combined measurement and modeling of specimen-specific knee mechanics for healthy and ACL-deficient conditions. J Biomech 57:117-124
Ali, Azhar A; Shalhoub, Sami S; Cyr, Adam J et al. (2016) Validation of predicted patellofemoral mechanics in a finite element model of the healthy and cruciate-deficient knee. J Biomech 49:302-9
Navacchia, Alessandro; Myers, Casey A; Rullkoetter, Paul J et al. (2016) Prediction of In Vivo Knee Joint Loads Using a Global Probabilistic Analysis. J Biomech Eng 138:4032379
Navacchia, Alessandro; Rullkoetter, Paul J; Schütz, Pascal et al. (2016) Subject-specific modeling of muscle force and knee contact in total knee arthroplasty. J Orthop Res 34:1576-87
Gaffney, Brecca M; Harris, Michael D; Davidson, Bradley S et al. (2016) Multi-Joint Compensatory Effects of Unilateral Total Knee Arthroplasty During High-Demand Tasks. Ann Biomed Eng 44:2529-41
Harris, Michael D; Cyr, Adam J; Ali, Azhar A et al. (2016) A Combined Experimental and Computational Approach to Subject-Specific Analysis of Knee Joint Laxity. J Biomech Eng 138:
Myers, Casey A; Laz, Peter J; Shelburne, Kevin B et al. (2015) A probabilistic approach to quantify the impact of uncertainty propagation in musculoskeletal simulations. Ann Biomed Eng 43:1098-111

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