(P 109) FINITE ELEMENT ANALYSIS FOR FIXATION EVALUATION OF PATIENT-SPECIFIC ORTHOPEDIC IMPLANTS

Objective: Patient-specific 3D printed implants are valuable in selected pediatric and adult bone tumor patients when standard implants are not suitable, particularly for joint-sparing reconstructions. However, verification of these implants must account for anatomical variations, bone defects, and cortical bone quality for screw fixation. Conventional verification is often limited by tumor progression timelines. Finite element analysis (FEA) is an efficient alternative to mechanical testing, yet most previous models assume full bone-implant integration. This study aimed to develop a patient-specific FEA approach to simulate various clinical scenarios including the non-osteointegration phase, to predict fixation stability in complex reconstructions.

Methods: We deliberately selected two patients who underwent reconstruction using customized 3D printed implants. Inclusion criteria were: (1) minimum 3-year follow-up, (2) complex implant geometry with sufficient volume, (3) favorable bone quality, and (4) occurrence of an adverse fixation-related event to verify FEA prediction power. CT-based models were generated, and clinical boundary conditions replicating surgical fixation steps were applied. Static load analyses simulated three conditions: (1) screw pull-out during the non-osteointegration phase, (2) screw failure under cyclic loading in the same phase, and (3) fixation post-osteointegration. A cumulative fatigue damage model predicted screw fracture timing under repetitive loading.

Results: The simulation accurately predicted screw pull-out and fracture observed clinically. The estimated timing of fatigue failure closely matched the actual clinical course.

Conclusion: This study highlights the importance of screw fixation stability prior to osteointegration. The proposed FEA approach enables effective preoperative evaluation and design refinement for patient-specific implants, reducing reliance on physical testing and supporting broader clinical use.