ArticleInternational orthopaedics2023
Can an artificial intelligence powered software reliably assess pelvic radiographs?
Article in International orthopaedics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 23 citations in OpenAlex.
- Large language models are comparable with commonly used statistical software: A validation of GPT 5.1 for frequentist meta-analysis in orthopaedics.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Article
- Current applications and challenges of artificial intelligence applied to diagnostics in pediatric musculoskeletal imaging.Pediatric radiology · 2026Review
- Evaluation of the reliability of novel pelvic X-ray assessment software: CalculOrther.Acta orthopaedica et traumatologica turcica · 2026Article
- Assessing deep learning accuracy in the measurement of radiographic parameters in pediatric hip X-rays.BMC medical imaging · 2025Article
- Artificial intelligence-guided assessment of the hip-knee-ankle angle shows excellent correlation with experienced human raters.Journal of experimental orthopaedics · 2025Article
- Impact of contralateral pelvic drop and femoral adduction on the femoral head acetabular coverage: A study on the reproducibility of a new radiographic measurement method.Journal of experimental orthopaedics · 2025Article
- CORR Insights®: Is Quantitative Radiographic Measurement of Acetabular Version Reliable in Anteverted and Retroverted Hips?Clinical orthopaedics and related research · 2024Article
- Evaluation of a deep learning software for automated measurements on full-leg standing radiographs.Knee surgery & related research · 2024Article
- Artificial intelligence in musculoskeletal imaging: realistic clinical applications in the next decade.Skeletal radiology · 2024Review
- Reliability and agreement of manual and automated morphological radiographic hip measurements.Osteoarthritis and cartilage open · 2024Article
- Automated radiographic hip morphology measurements: An open-access method.Osteoarthritis imaging · 2024Article
- Development of a diagnostic support system for distal humerus fracture using artificial intelligence.International orthopaedics · 2024Article
- Artificial intelligence-based three-dimensional templating for total joint arthroplasty planning: a scoping review.International orthopaedics · 2024Article
- What happened to 'bedside manner'?International orthopaedics · 2024Article
- Predicting Outcomes in Hip Arthroscopy for Femoroacetabular Impingement Syndrome.Current reviews in musculoskeletal medicine · 2024Review
- Fully automated assessment of the knee alignment on long leg radiographs following corrective knee osteotomies in patients with valgus or varus deformities.Archives of orthopaedic and trauma surgery · 2024Article
- Advancements in artificial intelligence for pelvic floor ultrasound analysis.American journal of translational research · 2024Review
- Gender-specific distribution of knee morphology according to CPAK and functional phenotype classification: analysis of 8739 osteoarthritic knees prior to total knee arthroplasty using artificial intelligence.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2023Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeDespite advances of three-dimensional imaging pelvic radiographs remain the cornerstone in the evaluation of the hip joint. However, large inter- and intra-rater variabilities were reported due to subjective landmark setting. Artificial intelligence (AI)-powered software applications could improve the reproducibility of pelvic radiograph evaluation by providing standardized measurements. The aim of this study was to evaluate the reliability and agreement of a newly developed AI algorithm for the evaluation of pelvic radiographs.
methodsThree-hundred pelvic radiographs from 280 patients with different degrees of acetabular coverage and osteoarthritis (Tönnis Grade 0 to 3) were evaluated. Reliability and agreement between manual measurements and the outputs of the AI software were assessed for the lateral-center-edge (LCE) angle, neck-shaft angle, sharp angle, acetabular index, as well as the femoral head extrusion index.
resultsThe AI software provided reliable results in 94.3% (283/300). The ICC values ranged between 0.73 for the Acetabular Index to 0.80 for the LCE Angle. Agreement between readers and AI outputs, given by the standard error of measurement (SEM), was good for hips with normal coverage (LCE-SEM: 3.4°) and no osteoarthritis (LCE-SEM: 3.3°) and worse for hips with undercoverage (LCE-SEM: 5.2°) or severe osteoarthritis (LCE-SEM: 5.1°).
conclusionAI-powered applications are a reliable alternative to manual evaluation of pelvic radiographs. While being accurate for patients with normal acetabular coverage and mild signs of osteoarthritis, it needs improvement in the evaluation of patients with hip dysplasia and severe osteoarthritis.
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