Abstract
INTRODUCTION: Critical femoral diaphyseal defects exceeding 3 cm present significant challenges in trauma and military orthopedics, particularly in blast injury scenarios requiring rapid rehabilitation. METHODS: The purpose of this experiment was to evaluate the biomechanical in vitro performance of two personalized prostheses (Groups A and B) designed explicitly for critical femoral diaphyseal defects through integrated biomechanical testing and finite element analysis (FEA). Using fourth-generation composite femurs simulating 10 cm defects (n = 16), we compared axial compression, torsion, four-point bending stiffness, and cyclic fatigue performance against intact bones (Group D) and diaphyseal fractures without defects (Group C). RESULTS: Key findings demonstrate comparable compressive stiffness between prostheses groups (Group A: 764.12±112.63 N/mm; Group B: 693.63±136.31 N/mm) and intact femurs (808.59±18.1 N/mm, p>0.05). The torsional stiffness is comparable between prostheses groups (Group A: 2.28±0.15 Nm/°; Group B: 2.18±0.22 Nm/°) versus diaphyseal fractures without defects (2.01±0.19 Nm/°). The stiffness results comply with mobilization requirements. FEA revealed maximum von Mises stresses in prosthesis fixation systems below the yield strength of Ti6Al4V, with digital image correlation validating the stress distribution patterns. The porous scaffold design achieved optimal modulus (1,132.85 MPa) between cortical and cancellous bone, reducing the "stress shielding" effect. Both prostheses endured 1800 N cyclic loading (100,000 cycles ≈, 13.3 years of physiological use) without structural failure. DISCUSSION: These customized prostheses address critical military medical needs by enabling immediate weight-bearing, reducing surgical complexity compared to bone transport techniques, and maintaining long-term mechanical integrity. The stiffener design philosophy and additive manufacturing flexibility provide adaptable solutions for complex combat-related trauma, significantly advancing early functional recovery in resource-constrained environments.