JOURNAL ARTICLE

Dynamic navigation system accuracy in orthodontic miniscrew insertion in the palatal vault: a prospective single-arm clinical study.

  • Published In: International Journal of Computerized Dentistry, 2026, v. 29, n. 1. P. 23 1 of 3

  • Database: Dentistry & Oral Sciences Source 2 of 3

  • Authored By: Brilli, Davide; Giansanti, Matteo; Bertoldo, Serena; Cauli, Isabella; Cassetta, Michele 3 of 3

Abstract

This article focuses on evaluating the accuracy of dynamic navigation (DN) systems in the insertion of orthodontic miniscrews in the palatal vault. In a prospective clinical study involving 23 subjects and 46 miniscrews, deviations between planned and actual miniscrew positions were measured using pre- and postoperative imaging, assessing entry point, apex point (3D and vertical), and angular deviations. Results showed mean deviations of 2.55 mm at the entry point, 3.11 mm at the apex point, 0.87 mm vertically at the apex, and an angular deviation of 8.50 degrees, with no significant correlation between accuracy and the number of surgeries performed; however, the duration of interventions decreased significantly with experience. The study concludes that DN is a viable alternative to static computer-assisted surgery for miniscrew placement in the palatal vault, despite a relatively wide range of deviations, and highlights the benefit of reduced procedure time as operator experience increases.

Additional Information

  • Source:International Journal of Computerized Dentistry. 2026/01, Vol. 29, Issue 1, p23
  • Document Type:Article
  • Subject Area:Dentistry
  • Publication Date:2026
  • ISSN:1463-4201
  • DOI:10.3290/j.ijcd.b6329377
  • Accession Number:193108754
  • Copyright Statement:Copyright of International Journal of Computerized Dentistry is the property of Quintessence Publishing Company Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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