ArticleThe Journal of international medical research2021
Value of preoperative three-dimensional planning software (AI-HIP) in primary total hip arthroplasty: a retrospective study.
Article in The Journal of international medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Comparison of Artificial Intelligence and Traditional Methods in Preoperative Planning for Primary Total Hip Arthroplasty: A Systematic Review and Meta-Analysis.Orthopaedic surgery · 2025Pooled it
- The role of artificial intelligence in preoperative planning for Total Hip Arthroplasty: a systematic review.Frontiers in artificial intelligence · 2024Pooled it
- Artificial Intelligence in Arthroplasty: A Comprehensive Structured Critical Review and Descriptive Evidence Map of Validation, Uncertainty, and Workflow Integration.Bioengineering (Basel, Switzerland) · 2026Review
- Automated Femoral, Acetabular, and Global Offset Measurements on Pelvis Radiograph Using Deep Learning.Hip & pelvis · 2026Article
- Three-dimensional and artificial intelligence-assisted preoperative templating in total hip arthroplasty: a systematic review and meta-analysis.Arthroplasty (London, England) · 2026Review
- Optimizing preoperative planning for total hip arthroplasty using random forest models to predict stem size and compatibility.BMC musculoskeletal disorders · 2026Article
- Artificial Intelligence Applications in Implant Positioning, Dislocation Risk Prediction, and Surgical Indications in Orthopaedic Surgery.Bioengineering (Basel, Switzerland) · 2026Review
- Artificial Intelligence in Orthopaedics: Clinical Performance, Limitations, and Translational Readiness-A Review.Journal of clinical medicine · 2026Review
- The accuracy of artificial intelligence in 3D preoperative planning for total hip arthroplasty: A systematic review and meta-analysis.Journal of experimental orthopaedics · 2026Review
- Development of a Deep Learning Model for Hip Arthroplasty Templating Using Anteroposterior Hip Radiograph.Journal of clinical medicine · 2025Article
- Review
- AI-assisted direct anterior approachFrontiers in bioengineering and biotechnology · 2025Article
- Total hip arthroplasty preoperative planning for childhood hip disorders' sequelae: Focus on developmental dysplasia of the hip.World journal of orthopedics · 2024Article
- Reliable prediction of implant size and axial alignment in AI-based 3D preoperative planning for total knee arthroplasty.Scientific reports · 2024Article
- Artificial intelligence-based three-dimensional templating for total joint arthroplasty planning: a scoping review.International orthopaedics · 2024Article
- Application and evaluation of artificial intelligence 3D preoperative planning software in developmental dysplasia of the hip.Journal of orthopaedic surgery and research · 2024Article
- Artificial intelligence in planned orthopaedic care.SICOT-J · 2024Article
- Determining the accuracy of preoperative total hip replacement 2D templating using the mediCADJournal of orthopaedic surgery and research · 2022Observational
- The role of artificial intelligence in surgical simulation.Frontiers in medical technology · 2022Article
- Ortho-digital dynamics: Exploration of advancing digital health technologies in musculoskeletal disease management.Digital healthArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe performed a retrospective study to compare the accuracy of preoperative planning using three-dimensional AI-HIP software and traditional two-dimensional manual templating to predict the size and position of prostheses. The purpose of this study was to evaluate the accuracy of AI-HIP in preoperative planning for primary total hip arthroplasty.
methodsIn total, 316 hips treated from April 2019 to June 2020 were retrospectively reviewed. A typical preoperative planning process for patients was implemented to compare the accuracy of the two preoperative planning methods with respect to prosthetic size and position. Intraclass correlation coefficients (ICCs) were used to evaluate the homogeneity between the actual prosthetic size and position and the preoperative planning method.
resultsWhen AI-HIP software and manual templating were used for preoperative planning, the stem agreement was 87.7% and 58.9%, respectively, and the cup agreement was 94.0% and 65.2%, respectively. The results showed that when AI-HIP software was used, an extremely high level of consistency (ICC > 0.95) was achieved for the femoral stem size, cup size, and femoral osteotomy level (ICC = 0.972, 0.962, and 0.961, respectively).
conclusionAI-HIP software showed excellent reliability for predicting the component size and implant position in primary total hip arthroplasty.
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