Related Experiment Video
Updated: Sep 2, 2026

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
Published on: February 23, 2024
[Accuracy of jaw relation transfer using a digital transfer table integrated with mechanical facebow technology]
1Department of Implantology, School and Hospital of Stomatology, Fujian Medical University & Clinical Research for Oral Tissue Deficiency of Fujian Province & Fujian Key Laboratory of Oral Diseases & Fujian Provincial Engineering Research Center of Oral Biomaterial & Stomatological Key Laboratory of Fujian College and University & Institute of Oral Homeostasis, Fujian Medical University & Research Center of Dental and Craniofacial Implants, Fujian Medical University, Fuzhou 350002, China.
Abstract:
Objective: To optimize the indirect digital transfer workflow utilizing an anatomical facebow, this study proposed a modified digital transfer table (MDTT) method based on the counterweight plate structure and magnetic embedding chimeric design of a magnetic suction transfer table. Furthermore, this study evaluated the accuracy of this method in transferring the craniomaxillary relationship, providing theoretical basis and technical support for its clinical application. Methods: A total of 28 volunteers and patients (11 males, 17 females; aged 18-29 years), including student volunteers and partially edentulous patients, were retrospectively enrolled from the Department of Implantology,School and Hospital of Stomatological Fujian Medical University between July 2024 and June 2026. For each subject, the collected data included maxillary dentition plaster models of all subjects, maxillary dentition digital models obtained by scanning plaster models, craniomaxillary positional relationship data of conventional plaster-fixed transfer table-occlusal fork and magnetically fitted transfer table-occlusal fork acquired via anatomical facebow, and craniofacial cone-beam CT (CBCT) data. The maxillary dentition models with craniomaxillary spatial information were transferred to a virtual articulator through two different workflows: the conventional anatomical facebow-based indirect digital transfer method (AFB group) and the novel MDTT method (MDTT group). Seven dental cusp landmark points were marked and matched via grid registration, including the mesiobuccal cusps of bilateral maxillary first molars, the tips of bilateral maxillary canines, the distoincisal angles of bilateral maxillary central incisors, and the midpoint of the line connecting the mesioincisal angles of bilateral maxillary central incisors. Taking the three-dimensional craniomaxillary relationship reconstructed by CBCT as the gold standard, the deviations of occlusal plane angle, three-dimensional root mean square error (RMSE) of overall dentition position, three-dimensional linear RMSE of landmark points, and three-dimensional axial deviation of each landmark were calculated in both AFB and MDTT groups to evaluate the transfer trueness. For precision assessment, pairwise registration and comparison were performed based on three repeated MDTT transfer operations, and the corresponding RMSE values and intraclass correlation coefficient (ICC) were calculated. Results: Compared to the reference standard, the MDTT group exhibited a significantly smaller occlusal plane angular deviation (1.62°±1.04°) than the AFB group (1.83°±1.07°), with a statistically significant difference (t=1.00, P=0.016). No statistically significant differences were observed in the three-dimensional dentition positional RMSE values or the three-dimensional axial deviations of the dentition between the two groups. Analysis of cusp landmark deviations revealed a statistically significant intergroup difference at the 26 site; the deviation in the MDTT group [(5.03±1.89) mm] was significantly greater than that in the AFB group [(4.84±1.70) mm] (t=-2.91, P=0.007 08) (P<0.007 14). Precision analysis indicated an ICC of 0.79 for the RMSE (P=0.599). Conclusions: designed in this study can successfully achieve spatial mapping of maxillary dentition digital models onto a virtual articulator with clinically acceptable accuracy.

