ReviewCureus2025
Accuracy of AI-Assisted Methods in Preoperative Templating Compared to the Standard X-Ray-Based Surgeon-Performed Templating in Total Hip Replacement Surgery: A Systematic Review and Meta-Analysis.
Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Artificial Intelligence in Orthopaedics: Clinical Performance, Limitations, and Translational Readiness-A Review.Journal of clinical medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate preoperative templating in total hip arthroplasty (THA) improves the procedure's precision, shortens its duration, and reduces complications such as instability and dislocations, prosthesis loosening, and loss of bone stock, among others. The current standard method uses X-ray images to manually determine implant size; however, the emergence of artificial intelligence (AI) is gaining increasing interest in its use for preoperative templating. This systematic review and meta-analysis aims to assess the difference in accuracy between the standard and AI methods for preoperative templating in regards to implant size. A systematic search of electronic databases identified 36 papers related to AI in preoperative planning in THA. Of these, 9 studies met the inclusion criteria and cumulatively yielded 1049 patient for comparison. Statistical analysis was performed using OpenMetaAnalysis software, utilising a random effects model with reported results at 95% confidence intervals. Results showed the odds for exact size match using an AI-assisted method were 4.163 times higher than the standard manual method in predicting an acetabular cup component (OR=4.163, P<0.001) and 3.672 times higher in predicting a femoral stem component (OR=3.672, P<0.001). Moreover, operative time following the use of the AI-assisted method was 9.2 minutes less than operations following the surgeon-performed method (MD=-9.2, P=0.027), although this was reduced to 4.35 minutes when the source of heterogeneity was removed (MD=-4.35, P=0.025). A key limitation of this study is that all the papers identified in the literature and included in this meta-analysis originated from China, thus limiting generalisability to other healthcare systems and populations. It was concluded that AI-assisted preoperative templating is significantly more accurate than the standard templating method currently used in clinical practice in predicting implant size in total hip arthroplasty and it helps to reduce operating time, although a high level of evidence from different centres worldwide is still lacking to validate its use in clinical practice.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.