Validation of a virtual implantation algorithm to quantify surgeon control and optimize stem selection in total hip arthroplasty.
biomechanical · Level V
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- Record sourced from PubMed, PMID 42320305.
- Also identified by DOI 10.1016/j.jbiomech.2026.113422.
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Abstract
Accurate restoration of femoral offset (FO) and head center in total hip arthroplasty (THA) is critical for joint function, yet the intraoperative range of achievable stem positions remains unquantified. This study developed and validated a fully automated CT-based virtual implantation algorithm that maps patient- and implant-specific "feasibility spaces" of achievable postoperative femoral head center locations to identify best-fit stem-head configurations. Eight cadaveric specimens (16 hips) underwent bilateral THA with a cementless femoral stem. Preoperative CT and postoperative optical scans were used to quantify native anatomy and stem positions. The algorithm segmented the boundaries of femoral canal and probabilistically simulated valid 3D stem alignments across multiple component sizes to generate feasibility spaces. Validation was performed by comparing experimental stem positions to the closest predicted virtual alignments. Experimentally, head centers deviated 12.7 ± 4.8 mm from native targets. The algorithm predicted these placements within 1.9 ± 0.5 mm. The feasibility spaces exhibited a conical distribution with an inferior apex, and all implanted head centers clustered on the medial boundary. For each specimen, at least one stem-head option produced a feasibility space within 5 mm of the native head center. The anterior-posterior controllable ranges (11.2-35.7 mm within 10 mm superior seating) significantly exceeded medial-lateral ranges (4.2-14.4 mm), with both expanding with superior stem seating. This framework shifted single static templating to dynamic templated volumes of surgical control. By quantifying the "forgivingness" of patient-specific anatomy, this tool enables systematic risk stratification and objective implant design comparison, providing a foundation to minimize biomechanical errors and enhance surgical consistency across diverse populations.