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Individualized Stem-positioning in Calcar-guided Short-stem Total Hip Arthroplasty

Individualized Stem-positioning in Calcar-guided Short-stem Total Hip Arthroplasty

Published on: February 27, 2018

AI-driven 3D virtual surgical planning in total hip arthroplasty: a machine learning approach for precision implant

Li-Cheng Xi¹, Bang-Qi Yang¹, Lin-Hua Jiang²

¹Department of Orthopaedics, Affiliated Hospital of Guilin Medical University, No. 15, Lequn Road, Xiufeng District, Guilin, 541000, Guangxi, China.

Journal of Orthopaedic Surgery and Research

|February 7, 2026

Abstract

Purpose:

To explore the clinical significance of the artificial intelligence (AI)-assisted three-dimensional (3D) planning system AI-HIP in total hip arthroplasty (THA) and evaluate its accuracy and efficacy in clinical practice.

Methods:

Preoperative planning was done using the AI-HIP system in the AI group and two-dimensional (2D) template measurements in the conventional group. The two groups were compared for postoperative radiographic results, perioperative monitoring indicators, and the degree of consistency between preoperative planning and actual implant size. Postoperative Harris scores, hip joint range of motion (ROM), and Barthel index were used to evaluate clinical effectiveness.

Results:

None of the patients who ultimately completed the 6-months follow-up experienced adverse events such as hip dislocation and infection during follow-up. Compared to the conventional group, the AI group had significantly higher Harris scores (P = 0.026), hip ROM (P = 0.018), Barthel index (P = 0.042) at 6 months postoperatively, and conformity rates of the acetabular (P = 0.001) and femoral components (P < 0.001) between intraoperative application of prosthesis model and preoperative planning. Additionally, the AI group had significantly shorter operation time (P = 0.041), less intraoperative blood loss (P = 0.012), and smaller discrepancy between bilateral acetabular offset (P = 0.032) and vertical distance of hip center of rotation (P = 0.011). However, no statistically significant intergroup differences were observed for the acetabular abduction angle, anteversion angle, femoral offset and leg length discrepancy.

Conclusion:

Preoperative planning for THA using the AI-HIP system has a high accuracy rate and allows for effective reconstruction of the rotation center and acetabular offset, reduction of surgical time, and early recovery of joint function. Further research is needed to confirm its potential clinical value.

Clinical Registration Number:

ChiCTR210004826, Date:28/03/2021, https://www.chictr.org.cn/showproj.html? proj=52846 .

Keywords:

Artificial intelligence Preoperative planning Template measurement Total hip arthroplasty

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