ArticleJournal of orthopaedic surgery and research2026
AI-driven 3D virtual surgical planning in total hip arthroplasty: a machine learning approach for precision implant positioning and improved clinical outcomes.
Article in Journal of orthopaedic surgery and research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Artificial Intelligence in Arthroplasty: A Comprehensive Structured Critical Review and Descriptive Evidence Map of Validation, Uncertainty, and Workflow Integration.Bioengineering (Basel, Switzerland) · 2026Review
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5 authors.
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Abstract
purposeTo 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.
methodsPreoperative 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.
resultsNone 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.
conclusionPreoperative 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 .
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