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Factors influencing the intraoral implant scan accuracy: a review of the literature

牙科 植入 牙种植体 口腔正畸科 医学 材料科学 外科
作者
Francesco Grande,Philippe Nuytens,Dr Sana Zahabiyoun,Oreste Iocca,Santo Catapano,Eitan Mijiritsky
出处
期刊:Journal of Dentistry [Elsevier BV]
卷期号:161: 105973-105973 被引量:12
标识
DOI:10.1016/j.jdent.2025.105973
摘要

OBJECTIVES: To review the main factors influencing the accuracy of intraoral scanners (IOSs) for implant-supported prostheses. DATA: A structured search strategy of PubMed and Scopus databases was performed to identify relevant literature published from 2013 to May 2025. Additional studies were identified through manual search. SOURCES: Eligible studies included in vitro and in vivo research evaluating IOS performance for screw-retained implant-supported restorations. Studies on removable complete dentures, orthodontics, old IOS versions, and case reports were excluded. STUDY SELECTION: A total of 1169 records were identified. After duplicate removal and title/abstract screening, 70 full-text articles were included. Quality assessment was performed using the QUIN tool for in vitro studies and the Joanna Briggs Institute checklist for in vivo studies. Articles were categorized according to six domains: intraoral scanner-related, scan body-related, operator-related, patient-related, laboratory-related and environmental factors. CONCLUSIONS: IOS accuracy is influenced by a multifactorial interplay of technological, procedural, biological, and environmental variables. ISB design, material, and library congruence significantly affect digital implant positioning. Operator experience and scanning strategy, as well as anatomical factors such as implant depth and mucosal mobility, contribute to errors. Auxiliary systems, such as splinting devices and photogrammetry, show promise in reducing inaccuracies for complete arch scans. CLINICAL SIGNIFICANCE: While digital scans are reliable for single and partial rehabilitations, complete arch implant scans remain challenging. Understanding key influencing factors can guide clinicians in selecting appropriate workflows and technologies to improve the predictability of digital implant prosthodontics.
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