已发表论文

人工智能辅助的 CT 参数 3D 规划在全髋关节置换术中用于个性化选择股骨假体

 

Authors Yang TJ, Qian W

Received 19 February 2025

Accepted for publication 25 May 2025

Published 18 June 2025 Volume 2025:21 Pages 905—916

DOI https://doi.org/10.2147/TCRM.S521755

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Garry Walsh

Tian-Jiao Yang, Wei Qian

Department of Orthopedics, Renmin Hospital of Hubei University of Medicine, Shiyan, Hubei, 442000, People’s Republic of China

Correspondence: Wei Qian, Email pqw412@yeah.net

Objective: To investigate the efficacy of CT measurement parameters combined with AI-assisted 3D planning for personalized femoral prosthesis selection in total hip arthroplasty (THA).
Methods: A retrospective analysis was conducted on clinical data from 247 patients with unilateral hip or knee joint disorders treated at Renmin Hospital of Hubei University of Medicine between April 2021 and February 2024. All patients underwent preoperative full-pelvis and bilateral full-length femoral CT scans. The raw CT data were imported into Mimics 19.0 software to reconstruct a three-dimensional (3D) model of the healthy femur. Using 3-matic Research 11.0 software, the femoral head rotation center was located, and parameters including femoral head diameter (FHD), femoral neck length (FNL), femoral neck-shaft angle (FNSA), femoral offset (FO), femoral neck anteversion angle (FNAA), tip-apex distance (TAD), and tip-apex angle (TAA) were measured. AI-assisted THA 3D planning system AIJOINT V1.0.0.0 software was used for preoperative planning and design, enabling personalized selection of femoral prostheses with varying neck-shaft angles and surgical simulation. Groups were compared by gender, age, and parameters. ROC curves evaluated prediction efficacy.
Results: Females exhibited smaller FHD, FNL, FO, TAD, TAA but larger FNSA/FNAA vs males (P< 0.05). Patients > 65 years had higher FO, TAD, TAA (P< 0.05). TAD-TAA correlation was strong (r=0.954), while FNSA negatively correlated with TAD/TAA (r=− 0.773/-0.701). ROC analysis demonstrated high predictive accuracy: TAD (AUC=0.891, sensitivity=91.7%, specificity=87.6%) and TAA (AUC=0.882, sensitivity=100%, specificity=88.8%).
Conclusion: CT parameters (TAA, TAD, FNSA, FO) are interrelated and effective predictors for femoral prosthesis selection. Integration with AI-assisted planning optimizes personalized THA, reducing biomechanical mismatch risks.

Keywords: CT measurement parameters, total Hip arthroplasty, femoral prosthesis, personalized selection, impact study