Enhancing Precision in Pelvic Tumor Reconstruction: Early Experience and Iterative Design of Custom 3D-Printed Implants.

Abstract

Pelvic tumor resections with custom 3D-printed implant reconstruction have become the benchmark in limb-salvage surgery. However, evidence regarding reconstructive precision is limited, and adaptive prosthetic design is rarely discussed. This study reports our early experience, highlighting iterative design modifications and lessons learned to optimize fit and accuracy. We also evaluated implant positioning comparing preoperative plans with postoperative imaging. We retrospectively reviewed seven patients with primary bone malignancy who underwent periacetabular resection and reconstruction with custom 3D-printed implants. Patient-specific plans and postoperative imaging were analyzed. Implant design was iteratively refined based on early intraoperative challenges, with modifications implemented in later cases. Outcomes were assessed descriptively, and statistical analyses were conducted to compare implant version, acetabular version, and implant frame overlap. Early challenges, including open-book pelvic migration, joint instability, and implant malpositioning, prompted design modifications, such as modular implant splitting, angle-stable locking screws, novel constrained cup, and clamp-like pubic fixation plates, which improved fit and stability. Minor discrepancies between planned and actual implant positions were observed overall, with median differences in implant version, acetabular version, and implant frame overlap of 1.6° (IQR 1.2-2.4), 2.7° (IQR 2.4-6.3), and 87.0% (IQR 80.0-88.0), respectively. Comparisons between initial and modified implants demonstrated markedly improved positioning, and learning curves showed progressive improvements in placement and intraoperative performance. Patient-specific instruments combined with iterative prosthetic design enable precise pelvic reconstructions and enhance short-term results. Early experience demonstrates how adaptive modifications and surgical learning curves can address challenges, laying the foundation for improved long-term functional outcomes.