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Updated: Aug 5, 2026
The Use of Mixed Reality in Custom-Made Revision Hip Arthroplasty: A First Case Report
Published on: August 4, 2022
Development and Application of Automated Preoperative Planning System for Developmental Dysplasia of the Hip via
Jinghui Yao1, Xiaoyou Fan2, Yijian Wang1
1Department of Pediatric Orthopedics, Center for Orthopedic Surgery, The Third Affiliated Hospital, Southern Medical University, The Third School of Clinical Medicine, Southern Medical University, Orthopedic Hospital of Guangdong Province, Academy of Orthopedics, Guangzhou, China.
Abstract:
This study developed and prospectively validated a deep learning-based automated preoperative planning system for developmental dysplasia of the hip (DDH) to guide osteotomy. Using 3544 anteroposterior pelvic radiographs, a selective keypoint integration strategy combining YOLOv11-Pose, YOLOv11, and YOLOv13 models achieved a mean pixel error of 9.68 pixels with 100% keypoint recall. The system automatically calculates acetabular index, neck-shaft angle, and center-edge angle, and recommends PHP plates based on predefined geometric rules and patient weight. In a multicenter randomized controlled trial with 30 DDH patients and six surgeons, AI planning reduced time from 170.5 ± 4.7 s (manual) to 0.0606 s (P < 0.001), matched expert acetabular index accuracy (P = 0.327), showed slightly higher but clinically acceptable neck-shaft angle error (P < 0.001), and achieved 92.3% plate recommendation concordance (P = 0.106). This first prospective RCT demonstrates expert-level DDH planning in seconds, advancing AI toward surgical guidance. Clinical trial registration: ChiCTR2600119719 (registered on 2026-03-03).