An Indirect Digital Technique to Transfer 3D Printed Casts to a Mechanical Articulator With Individual Sagittal Condylar Inclination Settings Using CBCT and Intraoral Scans

An overview of the different digital facebow methods for transferring the maxillary cast into the virtual articulator

OBJECTIVES

The purposes of this study were to classify the described digital facebow techniques for transferring the maxillary cast into the semi-adjustable virtual articulator based on the digital data acquisition technology used and to review the reported accuracy values of the different digital facebow methods described.

OVERVIEW

Digital data acquisition technologies, including digital photographs, facial scanners, cone beam computed tomography (CBCT) imaging, and jaw tracking systems, can be used to transfer the maxillary cast into the virtual articulator. The reported techniques are reviewed, as well as the reported accuracy values of the different digital facebow methods.

CONCLUSIONS

Digital photographs can be used to transfer the maxillary cast into the virtual articulator using the true horizontal reference plane, but limited studies have assessed the accuracy of this method. Facial scanning and CBCT techniques can be used to transfer the maxillary cast into the virtual articulator, in which the most frequently selected references planes are the Frankfort horizontal, axis orbital, and true horizontal planes. Studies analyzing the accuracy of the maxillary cast transfer by using facial scanning and CBCT techniques are restricted. Lastly, optical jaw trackers can be selected for transferring the maxillary cast into the virtual articulator by using the axis orbital or true horizontal planes, yet the accuracy of these systems is unknown.

CLINICAL IMPLICATIONS

Digital data acquisition technologies, including digital photographs, facial scanning methods, CBCTs, and optical jaw tracking systems, can be used to transfer the maxillary cast into the virtual articulator. Studies are needed to assess the accuracy of these digital data acquisition technologies for transferring the maxillary cast into the virtual articulator.

Intraoral scanner-based virtual facebow transferring: A chairside dental technique

Accurately mounting dental casts on an articulator is an essential step in prosthetic treatments. In digital dentistry, virtual articulator mounting procedures rely on virtual facebow records. However, virtual facebow records usually require devices like face scanners or jaw motion tracking systems that are not commonly available in most dental practices. The present technique report describes a straightforward intraoral scanner-based virtual facebow transfer approach. In this technique, a reference facebow joint support was first scanned and aligned with a virtual articulator. Then, a patient's facebow joint support and bite fork assembly were scanned chairside with an intraoral scanner and aligned with the virtual articulator by matching common features with the reference facebow joint support. After aligning the patient's intraoral scans with the patient's bite fork scan that was already superimposed on the virtual articulator, a virtual mounting process was achieved. Once the corresponding reference facebow joint supports have been generated, this technique can be easily implemented with most facebow systems and be seamlessly integrated into daily clinical practice as only an intraoral scanner and a conventional facebow were required.

Accuracy of the maxillary cast transfer into the virtual semi-adjustable articulator by using analog and digital facebow record methods

STATEMENT OF PROBLEM

Different digital methods have been described for transferring the maxillary cast into a virtual articulator; however, its accuracy remains uncertain.

PURPOSE

The purpose of this in vitro study was to compare the accuracy of the maxillary cast transfer into the virtual semi-adjustable articulator by using analog and digital methods.

MATERIAL AND METHODS

A maxillary typodont with 5 markers was positioned into a mannequin, which was digitized by using an industrial scanner (ATOS Q) and an extraoral scan of the typodont obtained (T710). Three groups were created based on the technique used to transfer the maxillary cast into the virtual articulator (Panadent PCH Articulator): conventional facebow record (CNV group), digital photograph (P group), and facial scanning (FS group) (n=10). In the CNV group, conventional facebow records (Kois Dentofacial analyzer system) were digitized (T710) and used to mount the maxillary scan into the articulator by aligning it with the reference platform (Kois adjustable platform) (DentalCAD). In the P group, photographs with the reference glasses (Kois Reference Glasses 3.0) were positioned in the mannequin. Each photograph was superimposed with the maxillary scan. Then, the maxillary scan was transferred into the virtual articulator by using the true horizontal plane information of the photograph. In the FS group, facial scans with an extraoral scan body (Kois Scan Body) were positioned in the mannequin by using a facial scanner (Instarisa). The extraoral scan body was digitized by using the same extraoral scanner. The digitized extraoral scan body provided the true horizontal plane information that was used to mount the maxillary scan into the articulator, along with the Kois disposable tray of the scan body. On the reference scan and each specimen, 15 linear measurements between the markers of the maxillary scans and the horizontal plane of the virtual articulator and 3 linear measurements between the maxillary dental midline and articulator midline were calculated. The measurements of the reference scan were used as a control to assess trueness and precision. Trueness was analyzed by using 1-way ANOVA followed by the pairwise comparison Tukey tests (α=.05). Precision was evaluated by using the Levene and pairwise comparisons Wilcoxon Rank sum tests.

RESULTS

No significant trueness (P=.996) or precision (P=.430) midline discrepancies were found. Significant posterior right (P<.001), anterior (P=.005), posterior left (P<.001), and overall (P<.001) trueness discrepancies were revealed among the groups. The P group obtained the best posterior right, posterior left, and overall trueness and precision. The P and FS groups demonstrated the best anterior trueness, but no anterior precision discrepancies were found.

CONCLUSIONS

The techniques tested affected the accuracy of the maxillary cast transfer into the virtual semi-adjustable articulator. In the majority of the parameters assessed, the photography method tested showed the best trueness and precision values. However, the maxillary cast transfer accuracy ranged from 137 ±44 µm to 453 ±176 µm among the techniques tested.

Accuracy comparison of the maxillary cast transfer into the virtual semi-adjustable articulator between an analog facebow record and a digital photography technique

STATEMENT OF PROBLEM

Digital photographs can be used for transferring the maxillary cast into the virtual semi-adjustable articulator; however, its accuracy remains unknown.

PURPOSE

The purpose of the present study was to compare the accuracy of the maxillary cast transfer into the virtual semi-adjustable articulator by using an analog and a digital standardized photography technique.

MATERIAL AND METHODS

A maxillary cast was digitized (T710) and positioned into a dental mannequin. The dental midline was not coincident with the facial midline and the maxillary occlusal plane was tilted. A reference scan of the assembled mannequin was obtained by using a facial scanner (Instarisa). Two groups were created based on the technique used to transfer the maxillary cast into the articulator (Panadent PCH): conventional facebow record (CNV group) or digital photograph (Photo group) (n=10). In the CNV group, facebow records (Kois Dentofacial analyzer system) were digitized (T710) and used to transfer the maxillary scan into the articulator by aligning it with the reference platform (Kois adjustable platform). In the Photo group, photographs with a reference glasses (Kois Reference Glasses) positioned into the mannequin were acquired. Each photograph was aligned with the maxillary scan. Then, the maxillary scan was transferred into the articulator by using the true horizontal axis information contained in the photograph. On the reference scan and each specimen, 10 linear measurements between the buccal cusps of the maxillary scan and the horizontal plane of the virtual articulator and a linear measurement between the maxillary dental midline and articulator midline were calculated. The measurements of the reference scan were used as a control to compute trueness and precision. Trueness was analyzed by using 1-way ANOVA followed by the pairwise comparison Tukey test (α=.05). Precision was evaluated by using the Levene and Wilcoxon Rank sum tests (α=.05).

RESULTS

The overall discrepancy measured in the CNV group was 0.620 ±0.396 mm, while in the Photo group it was 1.282 ±0.118 mm. Significant trueness differences were found in the midline (P=.037), anterior (P=.050), posterior right (P<.001), posterior left (P=.012), and overall discrepancy (P<.001) between the CNV and Photo groups. Significant precision discrepancies were found in the midline (P=.012), posterior right (P<.001), anterior (P<.001), posterior left (P=.002), and overall discrepancy (P<.001) between the CNV and Photo groups.

CONCLUSIONS

The facebow record method impacted the accuracy of the maxillary cast transfer. The Photo group obtained better trueness in the midline transfer than the CNV group; however, the CNV group demonstrated better trueness in the anterior, posterior right, posterior left, and overall discrepancy of the maxillary cast transfer compared with the Photo group. Overall, the Photo group obtained better precision than the CNV group.

Digital cross-mounting of intraoral scan casts from a virtual articulator to a mechanical articulator by using a custom transfer plate: A dental technique

With the development of digital dental technologies, a complete digital workflow without using physical casts has become possible. However, for certain clinical and dental laboratory procedures, especially in complex rehabilitation treatments, physically mounted casts in an ideal location in a mechanical articulator are still necessary for treatment planning and restoration fabrication. This technique report describes a digital approach to fabricating a custom transfer plate to cross mount intraoral scan casts from a virtual articulator to the corresponding mechanical articulator. This technique eliminates the need for conventional physical facebow transfer processes and offers a straightforward approach to integrating virtual procedures with analog workflows.

Digital diagnostic occlusal equilibration combining an intraoral scanner, optical jaw tracking system, and dental design program: A dental technique

Patients with aberrant occlusal patterns, including constricted mastication patterns or occlusal dysfunction, may require occlusal equilibration. Conventional diagnostic procedures involve diagnostic stone casts mounted in the articulator. During diagnostic procedures, occlusal equilibration methods are simulated on mounted stone casts to analyze the amount of dental structure that may need to be removed. A technique to virtually simulate an occlusal equilibration procedure is described. Digital data acquisition procedures include diagnostic casts acquired using an intraoral scanner and the repeatable reference position of the mandible or centric relation, excursive movements, and the mastication pattern captured using an optical jaw tracking system. The jaw tracker and dental design programs are used to simulate the occlusal equilibration.

The Role of Digital Facebow for CAD/CAM Implant-Supported Crowns Workflow

Recent advancements in digital technologies have transformed clinical workflows in dentistry, ensuring precise restorations. Custom-made crowns and fixed partial dentures (FPDs) now rely on virtual articulation. The digital facebow provides individualized data for CAD settings, streamlining the fabrication via digital workflow. For the purpose of demonstrating the differences observed during fabrication, we present a case report involving a 68-year-old patient seeking a replacement for missing teeth 24, 25, 26, and 27. The treatment plan involved the fabrication of an implant-supported FPD using monolithic zirconia (ZrO2). However, technical hurdles emerged during the planning phase, primarily due to spatial limitations posing a risk of mechanical failure over time. Consequently, we pivoted approach towards a porcelain fused to metal (PFM) FPD. For the PFM FPD, individual values from the digital facebow adjusted both virtual and conventional articulators. For comparison, two ZrO2 FPDs were milled-individual settings and average settings. All restorations underwent assessment for occlusion in maximal intercuspal position and eccentric mandible movements. In conclusion, the case report showed that individualized PFM FPD required minimal adjustments compared to milled ZrO2 restorations, whether using individual or average values. Utilizing individual values from the digital facebow reduced operator working time and minimized the intraoral adjustments.

Novel Procedure for Automatic Registration between Cone-Beam Computed Tomography and Intraoral Scan Data Supported with 3D Segmentation

In contemporary practice, intraoral scans and cone-beam computed tomography (CBCT) are widely adopted techniques for tooth localization and the acquisition of comprehensive three-dimensional models. Despite their utility, each dataset presents inherent merits and limitations, prompting the pursuit of an amalgamated solution for optimization. Thus, this research introduces a novel 3D registration approach aimed at harmonizing these distinct datasets to offer a holistic perspective. In the pre-processing phase, a retrained Mask-RCNN is deployed on both sagittal and panoramic projections to partition upper and lower teeth from the encompassing CBCT raw data. Simultaneously, a chromatic classification model is proposed for segregating gingival tissue from tooth structures in intraoral scan data. Subsequently, the segregated datasets are aligned based on dental crowns, employing the robust RANSAC and ICP algorithms. To assess the proposed methodology's efficacy, the Euclidean distance between corresponding points is statistically evaluated. Additionally, dental experts, including two orthodontists and an experienced general dentist, evaluate the clinical potential by measuring distances between landmarks on tooth surfaces. The computed error in corresponding point distances between intraoral scan data and CBCT data in the automatically registered datasets utilizing the proposed technique is quantified at 0.234 ± 0.019 mm, which is significantly below the 0.3 mm CBCT voxel size. Moreover, the average measurement discrepancy among expert-identified landmarks ranges from 0.368 to 1.079 mm, underscoring the promise of the proposed method.

Virtual facebow techniques: A scoping review

STATEMENT OF PROBLEM

Although advances in technology continue to improve the acquisition of patient data and the manufacturing of different oral rehabilitations, the method of transferring clinical information to a virtual environment has not yet been consolidated in the literature.

PURPOSE

The purpose of this scoping review was to map the existing literature on different techniques of transferring information from virtual facebows for oral rehabilitation.

MATERIAL AND METHODS

This scoping review was structured using a 5-step methodology based on guidelines proposed by Arksey and O'Malley: (1) characterization of the research question, (2) identification of relevant studies, (3) selection of studies, (4) mapping of results, and (5) selection, summary and reporting of the data. The Joanna Briggs Manual for Evidence Synthesis was followed and the review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The guiding question for the development of this review was, "What virtual facebow techniques are being used to transfer anatomic data to the virtual environment?"

RESULTS

A total of 1745 articles were found during the search, and 20 were included in this review. Nineteen of the included articles had positive results with the described techniques of registration and transfer of anatomic references to the virtual environment; however, 1 study indicated that the technique was negative.

CONCLUSIONS

Based on the findings, facial scanning, 2-dimensional photographs, and cone beam computed tomography are feasible methods of acquiring extraoral anatomic landmarks. The use of a device that allows the convergence of intraoral and extraoral images by superimposing data was revealed to be a promising option.

Comparison of the performance of various virtual articulator mounting procedures: a self-controlled clinical study

OBJECTIVES

This clinical study aimed to compare the performance of various virtual articulator (VA) mounting procedures in the participants' natural head position (NHP).

MATERIALS AND METHODS

Fourteen participants with acceptable dentitions and jaw relationships were recruited in this study registered in the Clinical Trials Registry (#NCT05512455; August 2022). A virtual facebow was designed for virtual mounting and hinge axis measurement. Intraoral scans were obtained, and landmarks were placed on each participant's face to register the horizontal plane in NHP. Six virtual mounting procedures were performed for each participant. The average facebow group (AFG) used an indirect digital procedure by using the average facebow record. The average mounting group (AMG) aligned virtual arch models to VA's average occlusal plane. The smartphone facial scan group (SFG) and professional facial scan group (PFG) used facial scan images with Beyron points and horizontal landmarks, respectively. The cone-beam computed tomography (CBCT) scan group (CTG) used the condyle medial pole, and horizontal landmarks were applied. The kinematic facebow group (KFG) served as the control group, and a direct digital procedure was applied using a kinematic digital facebow and the 3D skull model. Deviations of the reference plane and the hinge axis between the KFG and other groups were calculated. The inter-observer variability in virtual mounting software operation was then evaluated using the interclass correlation coefficient (ICC) test.

RESULTS

In virtual condylar center deviations, the CTG had the lowest condylar deviations. The AFG showed larger condylar deviations than PFG, SFG, and CTG. There was no statistically significant difference between the AFG and the AMG and between the PFG and the SFG. In reference plane deviations, the AMG showed the largest angular deviation (8.23 ± 3.29°), and the AFG was 3.89 ± 2.25°. The angular deviations of PFG, SFG, and CTG were very small (means of each group < 1.00°), and there was no significant difference among them. There was no significant difference between the researchers, and the ICC test showed moderate to excellent reliability for the virtual condylar center and good to excellent reliability for the reference plane in the operation of the virtual mounting software.

CONCLUSIONS

CBCT scan provided the lowest hinge axis deviation in virtual mounting compared to average mounting, facebow record, and facial scans. The performance of the smartphone facial scanner in virtual mounting was similar to that of the professional facial scanner. Direct virtual mounting procedures using horizontal landmarks in NHP accurately recorded the horizontal plane.

CLINICAL RELEVANCE

Direct digital procedures can be reliably used for virtual articulator mounting. The use of a smartphone facial scanner provides a suitable and radiation-free option for clinicians.