Peri-prosthetic fractures (PPF) are a major concern in Total Hip Arthroplasty (THA), with intraoperative-PPF occurring more frequently than postoperative-PPF. Although finite element analysis (FEA) has been used to assess THA, it often inadequately models surgical steps like implantation. This study develops a novel FEA framework to simulate the surgical steps of uncemented THA, aiming to predict IOPPF risk. Bone geometry was segmented, a neck osteotomy was performed in-silico, and a mesh convergence study was conducted. The femur was modelled with a 10-node-tetrahedral mesh, using an isotropic-bilinear-heterogeneous material with a plastic-strain-based-failure-criterion and element deactivation to mimic fracture. Boundary conditions included fixation of the distal femur and implant path with local-adaptive remeshing. The FEA model was subsequently verified through a cadaver experiment. The FEA model successfully simulated the surgical process, with no high-strain regions observed during implantation with the surgeon-selected implant size. However, when a larger implant size was used in the simulation, high-strain regions indicative of IOPPF risk were identified, confirming the model’s ability to predict fracture risk based on implant size. The developed FEA framework can assist surgeons in pre-surgical planning, particularly in implant selection, positioning, and predicting PPF risk. Future improvements will aim to refine and validate the model.

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Towards Prediction of Peri-Prosthetic Fractures: A Comprehensive Finite Element Model of Uncemented Total Hip Arthroplasty

  • Vineet Seemala,
  • Mark A. Williams,
  • Richard King,
  • Arnab Palit

摘要

Peri-prosthetic fractures (PPF) are a major concern in Total Hip Arthroplasty (THA), with intraoperative-PPF occurring more frequently than postoperative-PPF. Although finite element analysis (FEA) has been used to assess THA, it often inadequately models surgical steps like implantation. This study develops a novel FEA framework to simulate the surgical steps of uncemented THA, aiming to predict IOPPF risk. Bone geometry was segmented, a neck osteotomy was performed in-silico, and a mesh convergence study was conducted. The femur was modelled with a 10-node-tetrahedral mesh, using an isotropic-bilinear-heterogeneous material with a plastic-strain-based-failure-criterion and element deactivation to mimic fracture. Boundary conditions included fixation of the distal femur and implant path with local-adaptive remeshing. The FEA model was subsequently verified through a cadaver experiment. The FEA model successfully simulated the surgical process, with no high-strain regions observed during implantation with the surgeon-selected implant size. However, when a larger implant size was used in the simulation, high-strain regions indicative of IOPPF risk were identified, confirming the model’s ability to predict fracture risk based on implant size. The developed FEA framework can assist surgeons in pre-surgical planning, particularly in implant selection, positioning, and predicting PPF risk. Future improvements will aim to refine and validate the model.