Computational Evaluation of Patellar Dislocation in a High Risk Population
Faculty Mentor Information
Clare Fitzpatrick
Presentation Date
7-2017
Abstract
Introduction
Research has shown that knee geometry influences a person’s risk of patellar dislocation. Computational models facilitate investigation of the effects of knee geometry on dislocation in a more cost and time effective manner than is possible through cadaveric or in vivo experiments.
Methods
To analyze the effect of knee geometry on patellar dislocation, sixty patient geometries were incorporated into subject-specific computational analyses that reproduced Iranpour’s et al (2017) experimental setup. There were two distinct steps to the process: reconstruction of magnetic resonance (MR) images of knee geometries into 3D meshes (Amira, FEI, OR) and analysis of these geometry structures using finite element (FE) methods (Abaqus, Simulia, RI). Computational analyses were used to evaluate the forces resisting patellar dislocation.
Results
Forces resisting dislocation were compared between subjects, and across flexion angles. In general, restraining forces increased with increasing flexion; this was in agreement with the experimental data. Geometric features of the femur were correlated with restraining forces.
Discussion
Assumptions were made regarding muscles and tendon properties for which subject-specific information was not available. However, unlike the experiment, large number of patients were analyzed computationally; this facilitates greater understanding of the relationship between anatomy and dislocation than would be possible experimentally.
Iranpour, Farhad F et al(2017). "Femoral articular geometry and patellofemoral stability." The knee (0968-0160), 24 (3), p. 555.
Computational Evaluation of Patellar Dislocation in a High Risk Population
Introduction
Research has shown that knee geometry influences a person’s risk of patellar dislocation. Computational models facilitate investigation of the effects of knee geometry on dislocation in a more cost and time effective manner than is possible through cadaveric or in vivo experiments.
Methods
To analyze the effect of knee geometry on patellar dislocation, sixty patient geometries were incorporated into subject-specific computational analyses that reproduced Iranpour’s et al (2017) experimental setup. There were two distinct steps to the process: reconstruction of magnetic resonance (MR) images of knee geometries into 3D meshes (Amira, FEI, OR) and analysis of these geometry structures using finite element (FE) methods (Abaqus, Simulia, RI). Computational analyses were used to evaluate the forces resisting patellar dislocation.
Results
Forces resisting dislocation were compared between subjects, and across flexion angles. In general, restraining forces increased with increasing flexion; this was in agreement with the experimental data. Geometric features of the femur were correlated with restraining forces.
Discussion
Assumptions were made regarding muscles and tendon properties for which subject-specific information was not available. However, unlike the experiment, large number of patients were analyzed computationally; this facilitates greater understanding of the relationship between anatomy and dislocation than would be possible experimentally.
Iranpour, Farhad F et al(2017). "Femoral articular geometry and patellofemoral stability." The knee (0968-0160), 24 (3), p. 555.