Almadi, D. and Benington, P. and Ju, X. and Ayoub, A. (2023) Reproducibility and reliability of digital occlusal planning for orthognathic surgery. International Journal of Oral and Maxillofacial Surgery, 52 (10). pp. 1074-1080. ISSN 0901-5027
AI Summary:
The study compared the accuracy and reproducibility of free-hand articulation of digital and physical dental models. The results showed that despite a steep learning curve, digital occlusal planning is accurate enough for clinical applications.AI Topics:
The digital articulation of dental models is gradually replacing the conventional physical approach for occlusal prediction planning. This study was performed to compare the accuracy and reproducibility of free-hand articulation of two groups of digital and physical dental models, 12 Class I (group 1) and 12 Class III (group 2). The models were scanned using an intraoral scanner. The physical and digital models were independently articulated 2 weeks apart by three orthodontists to achieve the maximum inter-digitation, with coincident midlines and a positive overjet and overbite. The occlusal contacts provided by the software color-coded maps were assessed and the differences in the pitch, roll, and yaw were measured. The reproducibility of the achieved occlusion of both the physical and digital articulation was excellent. The z-axis displayed the smallest absolute mean differences of 0.10 ± 0.08 mm and 0.27 ± 0.24 mm in the repeated physical and repeated digital articulations, respectively, both in group 2. The largest discrepancies between the two methods of articulation were in the y-axis (0.76 ± 0.60 mm, P = 0.010) and in roll (1.83° ± 1.72°, P = 0.005). The overall measured differences were< 0.8 mm and< 2°. Despite the steep learning curve, digital occlusal planning is accurate enough for clinical applications.
Title | Reproducibility and reliability of digital occlusal planning for orthognathic surgery |
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Creators | Almadi, D. and Benington, P. and Ju, X. and Ayoub, A. |
Identification Number | 10.1016/j.ijom.2023.03.001 |
Date | October 2023 |
Divisions | College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing > Dental School |
Publisher | Elsevier |
URI | https://pub.demo35.eprints-hosting.org/id/eprint/489 |
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Item Type | Article |
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Depositing User | Unnamed user with email ejo1f20@soton.ac.uk |
Date Deposited | 11 Jun 2025 16:38 |
Revision | 34 |
Last Modified | 12 Jun 2025 09:09 |
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