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Phantom validation of a novel RSA-based impingement metric to assess component-on-component impingement risk.

Shahnaz TalebJordan S BrobergBrent A LantingMatthew G Teeter
Published in: Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine (2024)
Component-on-component impingement in total hip arthroplasty may lead to post-operative complications including dislocation. Despite numerous clinical studies focusing on reducing this risk, assessment methods remain limited to qualitative radiography, finite element analysis, and cadaver studies. There is a need for more precise measurements of impingement in the research setting. We aimed to validate a novel RSA-based impingement metric to measure component-on-component impingement in vivo. A phantom experiment of a standard metal-on-polyethylene total hip system was performed. RSA examinations were performed as typical for a traditional weight-bearing RSA exam for large joints. The phantom was placed in 10 possible impinged positions and one neutral position. Double exposure radiographs were taken to measure repeatability. The closest distance between the skirt of the head and the inner circumference of the acetabular cup liner was measured to assess impingement risk. Distances between the closest point of the hood to the edge of the cup in 10 impinged positions ranged from 0.05 to 1.03 mm, with the average being 0.67 mm. In the neutral position, the distance measured is 11.02 mm. Excellent repeatability was observed, with a standard deviation of 0.03 mm with an r value of 0.09. A validated RSA-based risk metric was established to evaluate in vivo hip impingement. A 1 mm threshold may be proposed to define impingement where distances approaching 1.00 mm are at a greater risk of impingement. This simplified metric holds promise for upcoming clinical studies on component-on-component impingement.
Keyphrases
  • total hip
  • total hip arthroplasty
  • risk assessment
  • body mass index
  • total knee arthroplasty
  • systematic review
  • magnetic resonance
  • image quality
  • weight loss
  • computed tomography
  • machine learning
  • human health