Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. EPFL thesis
  4. A patient-specific numerical musculoskeletal knee model : application to patellar resurfacing in Total Knee Arthroplasty
 
doctoral thesis

A patient-specific numerical musculoskeletal knee model : application to patellar resurfacing in Total Knee Arthroplasty

Latypova, Adeliya  
2015

Total Knee Arthroplasty (TKA) is a well-accepted surgical treatment of severe cases of osteoarthritis. Surgery is associated with improved pain level, knee function and health-related quality of life. Despite advances in surgical techniques and implant designs during the last decades, patients still face postoperative complications. Especially, patella-related complications, such as fracture and anterior knee pain (AKP), remain one of the major concerns. Several biomechanical studies suggested that the complications could be related to increased postoperative patellar strains. However, the evaluation of patellar strains after TKA is sparse, and the link with the complications is unknown. The main objective of the present PhD study was to develop a patient-specific TKA model aimed on prediction of patellar kinematics, forces and strain, for a specific interest in patellar complications after TKA. The objective was divided into three aims: development and validation of the patient-specific TKA model; identification and validation of the material law for the patellar bone; and, finally, a pilot application of the model to retrospective patients, to estimate variability of patient patellar biomechanics (kinematics, forces and strain) and potential of the model. The TKA model was based on patient preoperative data such as weight, CT, implant geometry and positioning (preoperative planning). It was decoupled into two levels: the knee and the patella. The knee model provided kinematics and forces acting on the patella, while the patella model used these values to predict bone strain. The knee model replicated a squat movement controlled by muscle elongation. It was validated with a robotic knee simulator. The originality and strength of the proposed model were a continuous recalculation of the patellar kinematics, forces and strain during the movement adapted to the patient parameters described above. The patella model was based on morphology-elasticity relationship, which was specifically identified and validated for the patellar bone. The isotropic assumption was compared to the reference anisotropic bone properties. The identification/validation was achieved by micro finite element (µFE) mechanical testing on fresh-frozen cadaveric patellar samples. As expected, anisotropy hypothesis provided more accurate stiffness, strain and stress predictions than isotropy one. After TKA, the patella model revealed a significant overestimation of patellar strains when isotropy is assumed, especially for low density and non-resurfaced patellae. The pilot application study was performed on seven retrospective patients with a minimum of one-year follow-up. The seven patient-specific TKA models were based on patient preoperative data. Since the resolution of the preoperative CT did not allow a direct measure of patellar anisotropy, we used a method based on registration with a µCT template. Peak strains were proportional to body weight and inversely proportional to average bone density multiplied by bone volume. While none of the patients suffered any complications within their follow-ups, the model predicted a complication risk for two patients. Although this patient-specific TKA model must be tested on more patients, especially pathologic ones, current results show a high potential of this model to analyze patellar biomechanics after TKA. One of the long-term targets is the implementation of patient-specific models into surgical planning software.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

EPFL_TH6822.pdf

Access type

restricted

Size

9.16 MB

Format

Adobe PDF

Checksum (MD5)

fc495f72cdcb032e3a156a3777052cc0

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés