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Acoustic Prediction and Biomechanical Validation of Primary Stability in Uncemented Short-Stem Hip Prostheses: An
Alexander Jahnke1, Simon Schreynemackers1, Ahmed Tawous1,2
1Laboratory of Biomechanics, Justus-Liebig-University Gießen, Giessen, Germany.
None:
In uncemented hip arthroplasty, achieving sufficient primary stability is essential for long-term implant success. However, objective intraoperative assessment of fixation quality remains challenging. Acoustic analysis of stem impaction sounds offers a promising tool for real-time evaluation, but its diagnostic accuracy and biomechanical correlation require further validation. Twelve formalin-fixed human femora were implanted with cementless Metha short stems under three predefined anchorage conditions: loose, optimal (fit), and fracture-inducing press-fit. Impaction sounds were recorded using calibrated microphones and processed via frequency-domain analysis. Relative micromotions were quantified under torsional loading to biomechanically assess primary stability. Spectral markers reliably differentiated between anchorage states. The transition from loose to fit showed minimal spectral change, yet emerged as statistically significant across multiple frequency clusters, while fit-to-fracture was characterized by a significant increase in low-frequency energy (< 2.5 kHz) and pronounced attenuation in high-frequency bands (> 15 kHz). These acoustic signatures closely correlated with biomechanically measured micromotions, which showed a distinct hierarchy: fracture < fit < loose. Cluster permutation analysis confirmed statistically significant differences between all groups, particularly in the fracture condition. This in vitro study demonstrates that frequency-based acoustic analysis can distinguish between stable, insufficient, and over-press-fit conditions during stem implantation. The findings support the feasibility of intraoperative acoustic monitoring as a real-time, objective tool to enhance implant safety and detect cortical compromise at an early stage, before clinical manifestation. However, translation into a clinical product will require further algorithmic development, integration into a surgical interface, and prospective in vivo validation.
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