ArticleJournal of orthopaedic research : official publication of the Orthopaedic Research Society2025
Understanding the variability of the proximal femoral canal: A computational modeling study.
Article in Journal of orthopaedic research : official publication of the Orthopaedic Research Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Medullary radius as a major contributor to variance in the proximal femur: Insights from statistical shape modeling.Journal of anatomy · 2026Article
- Quantifying the anatomical variability of the proximal femur.International journal of computer assisted radiology and surgery · 2026Article
- Current Uses for Medical Imaging With Orthopaedic Implant Technology.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2026Review
- Understanding the variability of the proximal femoral canal: A computational modeling study.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2025Article
- Femoral Stem Version in Primary Hip Arthroplasty: Challenges and Advances in 3D Planning.JB & JS open accessReview
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Authors and funding
4 authors.
Funding
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Abstract
Statistical shape modeling (SSM) offers the potential to describe the morphological differences in similar shapes using a compact number of variables. Its application in orthopedics is rapidly growing. In this study, an SSM of the intramedullary canal of the proximal femur was built, with the aim to better understanding the complexity of its shape which may, in turn, enhance the preoperative planning of total hip arthroplasty (THA). This includes the prediction of the prosthetic femoral version (PFV) which is known to be highly variable amongst patients who have undergone THA. The model was built on three dimensional (3D) models of 64 femoral canals which were generated from pelvic computed tomography images including the proximal femur in the field of view. Principal component analysis (PCA) was performed on the mean shape derived from the model and each segmented canal. Five prominent modes of variations representing approximately 84% of the total 3D variations in the population of shapes were found to capture variability in size, proximal torsion, intramedullary femoral anteversion, varus/valgus orientation, and distal femoral shaft twist/torsion, respectively. It was established that the intramedullary femoral canal is highly variable in its size, shape, and orientation between different subjects. PCA-driven SSM is beneficial for identifying patterns and extracting valuable features of the femoral canal.
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