Mechanics of bone graft and implant choices for spino-pelvic reconstruction following combined hemipelvectomy, sacrectomy and L5 vertebrectomy

Abstract

Spino-pelvic reconstruction following extended hemipelvectomy is a highly complex surgical procedure with significant variability in biomechanics between patients due to differences in surgical techniques. Despite its clinical significance, experimentally identifying the key biomechanical factors that govern the integrity of the reconstructed pelvis remains challenging. To address this, we developed a multiscale computational modeling framework, ranging from 1D beam theory and 2D composite trusses to anatomically accurate 3D reconstructions, to systematically evaluate the biomechanical trade-offs of bone graft selection in spino-pelvic reconstructions. Anatomically accurate, three-dimensional finite element models, reconstructed from postoperative CT imaging, were developed to simulate stress distributions in both bone and implant components of the reconstructed pelvis under quasi-static sitting conditions, representing the postoperative recovery phase. Two key choices were systematically evaluated: bone graft selection and implant material properties. Comparative analysis of tibial, femoral, and fibular grafts demonstrates that the femoral graft provides superior mechanical performance due to its larger cross-sectional area. The tibial graft exhibits approximately twice the stress level of the femur, while the fibular graft experiences stresses nearly three times higher, indicating limited suitability for structural reconstruction. Implant material analysis reveals that titanium and stainless steel minimize stress accumulation and reduce the risk of mechanical failure, making them preferable under high-load conditions. In contrast, polymer-based implants mitigate stress shielding and may be advantageous when bone remodeling is a priority. Together, these findings offer new insight into spino-pelvic reconstruction strategies and support simulation-driven design optimization to improve future outcomes for patients undergoing these complex procedures.