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Algorithmic determination of femoral neck axis in Birmingham hip resurfacing: A parametric CAD-based method Cover

Algorithmic determination of femoral neck axis in Birmingham hip resurfacing: A parametric CAD-based method

Open Access
|Oct 2026

Abstract

Purpose

Birmingham hip resurfacing requires precise determination of the femoral head-neck axis to minimize risks of neck fracture, cortical notching, and component malposition. Existing methods rely on intraoperative estimation, generic guides, or semi-manual planning, all susceptible to anatomical variability. This study presents an automated parametric algorithm for determining the femoral neck axis from computed tomography (CT)-derived models to support patient-specific surgical planning.

Methods

The method utilizes segmented CT data converted to Standard for the Exchange of Product model data format. Following artifact removal, the algorithm performs iterative cross-sectional analysis along the neck axis, identifying characteristic anatomical points: the neck isthmus, head centroid, and head apex. The axis is approximated from these points and refined through rotational optimization in 5 degree and 0.5 degree increments. The algorithm was evaluated on 4 femoral models in 5 spatial orientations each (20 test cases).

Results

The algorithm achieved a mean validation score of 4.1/5.0 (82%). Three models with high-quality meshes scored 4–5, while one model with extensive artifacts scored 1–2, confirming sensitivity to input data quality. Repeatability was plus/minus 0.5 degrees in angular orientation and plus/minus 0.2 mm in isthmus position. Error propagation analysis indicated that CT-induced uncertainty (approximately 1.6 degrees upper bound) constitutes the limiting factor, not algorithmic precision. Physical prototyping confirmed viability for patient-specific instrument design.

Conclusion

The method provides reproducible, automated femoral neck axis determination with plus/minus 0.5 degrees repeatability – approximately three times smaller than CT-induced uncertainty and an order of magnitude below the 5–7 degree errors of conventional jigs. Future work should validate the method against clinical outcomes in larger cohorts.

DOI: https://doi.org/10.37190/abb/221630 | Journal eISSN: 2450-6303 | Journal ISSN: 1509-409X
Language: English
Page range: 164 - 175
Submitted on: Jan 9, 2026
Accepted on: May 8, 2026
Published on: Oct 28, 2026
Published by: Wroclaw University of Science and Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2026 Michał P. Kowalik, Dawid Knaś, Krzysztof Zawiśliński, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.