Luca Lepidi

Purpose: To evaluate the accuracy of static maxillary‐facial spatial registration obtained using different virtual facebow (VF) fork designs and two facial scanning systems. Accuracy was assessed in terms of trueness and precision of linear deviations at three maxillary point references and angular deviation of the occlusal plane. The findings are intended to inform the selection of VF fork designs for improved accuracy of static maxillary‐facial spatial registration within a digital workflow. Materials and Methods: A cone‐beam computed tomography (CBCT) scan was performed on a phantom head to reconstruct a 3D facial model. The maxillary arch was separately scanned with the addition of 3 reference points: the left central incisor (#9), left first molar (#14), and right first molar (#3). This scan was aligned with the 3D facial model to create a control. Four distinct VF designs were fabricated using a 3D printer (Form 3+ 3D printer; Formlabs, Somerville, MA) with model resin (Model Resin V2; Formlabs) and sequentially attached to the phantom with blue bite material. Two scanning systems—an iPad‐based scanner (IP) and an industrial‐grade EinScan scanner (HX)—were used to obtain 3D scans of the phantom with each VF design. Each design was scanned 10 times per device, yielding 80 records. These were superimposed onto the baseline through superimpositions of common facial landmarks. The trueness and precision of linear deviations at the three reference points and the angular deviation of the occlusal plane were analyzed. Results: Overall, VF 1 demonstrated the highest average accuracy across all measured parameters, except for angular precision, whereas VF 2 exhibited the lowest accuracy among the four treatment groups evaluated. Conclusions: VF 1 demonstrated the highest accuracy when used in conjunction with the IP scanner, whereas VF 4 provided the most accurate results when paired with the HX scanner.

Purpose: Accurate maxillary positioning is critical in digital prosthodontics, particularly when transferring the spatial relationship of the maxilla to a virtual articulator. This study aimed to compare the accuracy of the two most common registration methods, three‐dimensional (3D) match and UV (landmark‐based point‐pair registration) match, for virtual facebow transfer and to investigate whether the type of facial scanner used influences the accuracy of these registration techniques. Materials and Methods: A cone beam computed tomography (CBCT) scan of a manikin was used as the reference. The maxillary arch was scanned with three anatomical landmarks and aligned to the CBCT. A computer‐aided design and computer‐aided manufacturing (CAD‐CAM)‐printed facebow fork was affixed to the arch, followed by facial scans using the EinScan HX and iPad (10 scans each). For each scan, two registration methods (3D match and UV match) were performed, generating 40 virtual alignments. Superimpositions were completed in Exocad, and accuracy was evaluated by comparing each registration to the CBCT reference using a Python script to measure linear and angular deviations. Trueness and precision were analyzed using a linear mixed model. Results: 3D match generally outperformed UV in both trueness and precision. The industrial scanner combined with 3D match yielded the highest accuracy, with linear trueness of 0.98 ± 0.67 mm and precision of 1.31 ± 0.79 mm ( p < 0.001). With the iPad, 3D registration demonstrated significantly superior angular accuracy ( p < 0.050). Conclusion: 3D registration provides higher accuracy than UV match, and 3D registration, in combination with an industrial‐grade scanner, offers higher accuracy in virtual facebow transfer than using iPad.

This clinical report introduces a novel clinical technique to create a 3D virtual patient for transferring the edentulous maxillary arch position with maxillomandibular relationship by using a facial scan device and an intraoral scanner and omitting CBCT imaging.