Artificial intelligence–based three-dimensional templating for total joint arthroplasty planning: a scoping review

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dc.coverageDOI: 10.1007/s00264-024-06088-6
dc.creatorVelasquez Garcia, Ausberto
dc.creatorBukowiec, Lainey G.
dc.creatorYang, Linjun
dc.creatorNishikawa, Hiroki
dc.creatorFitzsimmons, James S.
dc.creatorLarson, A. Noelle
dc.creatorTaunton, Michael J.
dc.creatorSanchez-Sotelo, Joaquin
dc.creatorO’Driscoll, Shawn W.
dc.creatorWyles, Cody C.
dc.date2024
dc.date.accessioned2025-11-18T19:45:57Z
dc.date.available2025-11-18T19:45:57Z
dc.description<p>Purpose: The purpose of this review is to evaluate the current status of research on the application of artificial intelligence (AI)–based three-dimensional (3D) templating in preoperative planning of total joint arthroplasty. Methods: This scoping review followed the PRISMA, PRISMA-ScR guidelines, and five stage methodological framework for scoping reviews. Studies of patients undergoing primary or revision joint arthroplasty surgery that utilised AI-based 3D templating for surgical planning were included. Outcome measures included dataset and model development characteristics, AI performance metrics, and time performance. After AI-based 3D planning, the accuracy of component size and placement estimation and postoperative outcome data were collected. Results: Nine studies satisfied inclusion criteria including a focus on computed tomography (CT) or magnetic resonance imaging (MRI)–based AI templating for use in hip or knee arthroplasty. AI-based 3D templating systems reduced surgical planning time and improved implant size/position and imaging feature estimation compared to conventional radiographic templating. Several components of data processing and model development and testing were insufficiently covered in the studies included in this scoping review. Conclusions: AI-based 3D templating systems have the potential to improve preoperative planning for joint arthroplasty surgery. This technology offers more accurate and personalized preoperative planning, which has potential to improve functional outcomes for patients. However, deficiencies in several key areas, including data handling, model development, and testing, can potentially hinder the reproducibility and reliability of the methods proposed. As such, further research is needed to definitively evaluate the efficacy and feasibility of these systems.</p>eng
dc.identifierhttps://investigadores.uandes.cl/en/publications/7f81471c-3d0e-4b94-92bf-00495b6614d2
dc.identifier.urihttps://repositorio.uandes.cl/handle/uandes/54247
dc.languageeng
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourcevol.48 (2024) nr.4 p.997-1010
dc.subject3D imaging
dc.subject3D templating
dc.subjectArthroplasty
dc.subjectArtificial intelligence
dc.subjectSurgical planning
dc.subjectTotal hip arthroplasty
dc.titleArtificial intelligence–based three-dimensional templating for total joint arthroplasty planning: a scoping revieweng
dc.typeArticleeng
dc.typeArtículospa
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