BMC Musculoskeletal Disorders (May 2024)

3D-Printed custom-made hemipelvic endoprosthetic reconstruction following periacetabular tumor resection: utilizing a novel classification system

  • Xin Hu,
  • Minxun Lu,
  • Yitian Wang,
  • Yi Luo,
  • Yong Zhou,
  • Xiao Yang,
  • Li Min,
  • Chongqi Tu

DOI
https://doi.org/10.1186/s12891-024-07509-8
Journal volume & issue
Vol. 25, no. 1
pp. 1 – 13

Abstract

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Abstract Background Customized 3D-printed pelvic implants with a porous structure have revolutionized periacetabular pelvic defect reconstruction after tumor resection, offering improved osteointegration, long-term stability, and anatomical fit. However, the lack of an established classification system hampers implementation and progress. Methods We formulated a novel classification system based on pelvic defect morphology and 3D-printed hemipelvis endoprostheses. It integrates surgical approach, osteotomy guide plate and prosthesis design, postoperative rehabilitation plans, and perioperative processes. Results Retrospectively analyzing 60 patients (31 males, 29 females), we classified them into Type A (15 patients: Aa = 6, Ab = 9), Type B (27 patients: Ba = 15, Bb = 12), Type C (17 patients). All underwent customized osteotomy guide plate-assisted tumor resection and 3D-printed hemipelvic endoprosthesis reconstruction. Follow-up duration was median 36.5 ± 15.0 months (range, 6 to 74 months). The mean operating time was 430.0 ± 106.7 min, intraoperative blood loss 2018.3 ± 1305.6 ml, transfusion volume 2510.0 ± 1778.1 ml. Complications occurred in 13 patients (21.7%), including poor wound healing (10.0%), deep prosthesis infection (6.7%), hip dislocation (3.3%), screw fracture (1.7%), and interface loosening (1.7%). VAS score improved from 5.5 ± 1.4 to 1.7 ± 1.3, MSTS-93 score from 14.8 ± 2.5 to 23.0 ± 5.6. Implant osseointegration success rate was 98.5% (128/130), with one Type Ba patient experiencing distal prosthesis loosening. Conclusion The West China classification may supplement the Enneking and Dunham classification, enhancing interdisciplinary communication and surgical outcomes. However, further validation and wider adoption are required to confirm clinical effectiveness.

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