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Published on: October 12, 2016
Integrated Study of the Distal Femur Biphasic Plate: Exploring In Vivo, In Vitro, and In Silico Methodologies
Annchristin Andres1, Kerstin Wickert2, Michael Roland2
1Applied Mechanics, Saarland University, Campus A4 2, 1. OG, 66123, Saarbrücken, Germany. annchristin.andres@uni-saarland.de.
Purpose:
An emerging concept for plate fixation of fractured bones in humans changed from absolute stability through relative stability to a new concept of a predefined range of elastic movement with mechanical amplitude limitation ("Biphasic Plate," 41 medical, Bettlach, Switzerland). As this represents a novel implant design, only a few studies have investigated it so far, particularly with respect to human cadaveric specimens and in vivo patient-specific cases. Therefore, this study aims to investigate the biphasic behavior using in vitro, in silico, and in vivo methodologies concerning stress distributions under realistic boundary conditions.
Methods:
To test this, an implantable in vivo strain measurement system ("Fracture Monitor," AO Foundation, Davos Switzerland) and a camera system are employed for experimental data acquisition, while patient monitoring captures actual boundary conditions during daily activities. Finite element simulations are performed on patient-specific 3D models generated from computed tomography imaging, allowing for detailed stress analysis. These simulations are validated through experiments on human cadaveric specimens in a custom-designed test rig by investigating the specific behavior of the biphasic plate with its two different modes (rigid and flexible).
Results:
Under axial loading, the stresses are distributed centrally; while in patient-specific cases, the stress pattern changes markedly, with maximum stresses concentrating along the lateral side of the plate.
Conclusion:
By the chosen biomechanical testing setup, the in silico simulations could be validated, demonstrating the ability to accurately replicate the postulated motion sequence of the biphasic plate. This iteration emphasizes both validation and reproducibility as the key outcomes.

