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Proximal femoral osteotomy (PFO) is a surgical intervention, typically performed on paediatric population, that aims to correct femoral deformities caused by different pathologies (e.g., slipped capital femoral epiphysis). A PFO involves introduction of an implant to fix the proximal and distal sections of femur following the surgical corrections. The femoral neck-shaft angle (NSA) and anteversion angle (AVA) are key geometric parameters that influence PFO outcomes. To date, the effects of NSA and AVA on bone-implant system mechanics in paediatric populations have not been examined. This study used an established neuromusculoskeletal modelling process paired with finite element analysis to determine the sensitivity of the implanted femur's mechanics to variations in NSA and AVA during the stance phase of walking. Three male patients aged 9–12 years with different pathology (Spastic diplegia, Perthes disease and Slipped Capital Femoral Epiphysis), weight (377, 747, 842 N), height (1.39, 1.55, 1.71 m) and femur lengths (34.1, 39.4, 43.7 cm) and geometries (NSA: 143, 102, 111 deg; AVA: 29, 17, -22 deg) were examined. For each patient, a three-dimensional bone model was created from computed tomography imaging and digital surgical corrections were applied to systematically vary the NSA and AVA. Personalized motion and loading conditions driven from a neuromusculoskeletal modelling process were applied to each model and its associated permutations of NSA and AVA. Results indicated significant intra-participant variability in post-PFO bone-implant micromotion and peak von Mises stress on implant. For models with a post-surgery NSA of 135° and AVA of 12°, the averaged micromotion increased by 87 % and the peak von Mises stress decreased by 63% between patient 1 and 2. Between patient 2 and 3, the averaged micromotion decreased by 55% while the peak von Mises stress increased by 84%. Furthermore, post-PFO bone-implant mechanics were sensitive to variation in NSA and AVA in a subject-specific manner. Optimization of PFO planning is recommended based on patient-specific characteristics. • Patient Modelling: Neuromusculoskeletal modelling with finite element analysis for patient-specific surgical simulations. • Automated Virtual Surgery: Developed a custom toolbox to automate surgeries, ensuring precise corrections across patients. • Surgical Parameters: Systematically varied key angles (NSA and AVA) to understand their impact on system mechanics. • Loosening Risk: Adjusting NSA can reduce bone-implant micromotion, highlighting the importance of personalized surgery. • Post-op mechanics are patient-specific, emphasizing the need for individualized models for optimal outcomes.
Bavil et al. (Sun,) studied this question.