SynthesisFrontiers in artificial intelligence2026
Artificial intelligence-driven preoperative CT 3D planning: a narrative review on improving the accuracy of acetabular cup angle and size in total hip arthroplasty.
Synthesis in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
3 authors.
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Abstract
Introduction: Total hip arthroplasty (THA) is a well-established treatment for end-stage hip disorders, yet its success heavily depends on precise acetabular cup positioning and sizing. Conventional planning, based on manual CT interpretation, is time-consuming, operator-dependent, and lacks standardisation, limiting its ability to achieve consistent surgical accuracy. Methods: This narrative review systematically searched PubMed, Web of Science, Cochrane Library, and IEEE Xplore for peer-reviewed studies published between January 2015 and June 2025. We included original research evaluating AI-driven preoperative CT 3D planning for THA, with quantitative outcomes on cup angle or size accuracy. Data were extracted and assessed for methodological quality using standard tools. Results: AI-assisted planning consistently improved accuracy: mean angular errors for inclination and anteversion were below 3 Discussion: Although AI planning shows clear benefits in accuracy and efficiency, several challenges remain-including limited generalisability to complex anatomies, susceptibility to image artefacts, and insufficient integration with intraoperative execution. Future research should prioritise multi-centre validation, dynamic functional planning, and seamless clinical workflow integration to translate technological potential into improved patient outcomes.
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