Development and validation of a computational model of the knee joint for the evaluation of surgical treatments for osteoarthritis. Academic Article uri icon

Overview

MeSH

  • Algorithms
  • Biomechanical Phenomena
  • Cartilage
  • Finite Element Analysis
  • Humans
  • Magnetic Resonance Imaging
  • Male
  • Middle Aged
  • Pressure
  • Range of Motion, Articular
  • Rotation
  • Weight-Bearing

MeSH Major

  • Computer Simulation
  • Knee Joint
  • Models, Anatomic
  • Osteoarthritis

abstract

  • A three-dimensional (3D) knee joint computational model was developed and validated to predict knee joint contact forces and pressures for different degrees of malalignment. A 3D computational knee model was created from high-resolution radiological images to emulate passive sagittal rotation (full-extension to 65°-flexion) and weight acceptance. A cadaveric knee mounted on a six-degree-of-freedom robot was subjected to matching boundary and loading conditions. A ligament-tuning process minimised kinematic differences between the robotically loaded cadaver specimen and the finite element (FE) model. The model was validated by measured intra-articular force and pressure measurements. Percent full scale error between FE-predicted and in vitro-measured values in the medial and lateral compartments were 6.67% and 5.94%, respectively, for normalised peak pressure values, and 7.56% and 4.48%, respectively, for normalised force values. The knee model can accurately predict normalised intra-articular pressure and forces for different loading conditions and could be further developed for subject-specific surgical planning.

publication date

  • 2014

has subject area

  • Algorithms
  • Biomechanical Phenomena
  • Cartilage
  • Computer Simulation
  • Finite Element Analysis
  • Humans
  • Knee Joint
  • Magnetic Resonance Imaging
  • Male
  • Middle Aged
  • Models, Anatomic
  • Osteoarthritis
  • Pressure
  • Range of Motion, Articular
  • Rotation
  • Weight-Bearing

Research

keywords

  • Journal Article
  • Validation Studies

Identity

Language

  • eng

PubMed Central ID

  • PMC4047624

Digital Object Identifier (DOI)

  • 10.1080/10255842.2014.899588

PubMed ID

  • 24786914

Additional Document Info

start page

  • 1502

end page

  • 1517

volume

  • 17

number

  • 13