Computational tibial bone remodeling over a population after total knee arthroplasty: A comparative study
Thomas Anijs1, Sanne Eemers1, Yukihide Minoda2
1Orthopedic Research Laboratory, Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands.
Summary
Computational models predict bone loss after total knee arthroplasty (TKA) but underestimate proximal bone loss and inaccurately predict distal bone gain. Further research is needed to refine these models for better clinical accuracy.
Area of Science:
- Biomedical Engineering
- Orthopedic Surgery
- Computational Mechanics
Background:
- Periprosthetic bone loss is a key factor in tibial implant failure following total knee arthroplasty (TKA).
- Accurate prediction of bone remodeling is crucial for improving implant longevity and patient outcomes.
Purpose of the Study:
- To validate computational models of postoperative bone response against clinical DEXA data.
- To assess the accuracy of finite element (FE) simulations in predicting bone mineral density (BMD) changes around tibial implants.
Main Methods:
- FE simulations incorporating strain-adaptive remodeling theory were performed on 26 tibiae.
- Physiological loading conditions were applied, and BMD was analyzed in three regions of interest (ROIs) over 15 years.
- Computational BMD outcomes were compared with longitudinal clinical DEXA data from a TKA cohort.
Main Results:
- Computational and clinical models showed similar trends in proximal bone loss, with rapid initial loss followed by stabilization.
- Proximal BMD changes were underestimated computationally compared to clinical data, potentially due to higher baseline BMD in clinical subjects.
- Significant discrepancies were observed in the distal ROI, with clinical resorption contrasting with predicted bone formation in FE models.
Conclusions:
- Computational models show promise in predicting proximal periprosthetic bone loss trends after TKA but require refinement for accurate magnitude prediction.
- Current FE models exhibit limitations in accurately predicting distal bone remodeling, necessitating further research with subject-specific data and improved loading conditions.
- Optimizing computational models for bone remodeling requires incorporating subject-specific comparisons and advanced physiological knee loading parameters.
