An Alternative Digital Workflow for 3D Virtual Patient Construction Integrating Intraoral, Facial, and CBCT Data for Esthetic and Occlusal Planning

ABSTRACT

Background

Virtual patient construction integrates dental, facial, and skeletal datasets into a unified 3D model for prosthodontic diagnosis and planning. Despite advances, fully digital workflows remain limited by challenges in reproducibility and clinical validation.

Objective

To describe an alternative digital workflow for 3D virtual patient construction integrating intraoral, facial, and CBCT data, and to demonstrate its clinical applicability through direct intraoral mock‐up validation.

Methods

A patient with esthetic concerns and mild functional asymmetry was documented using full‐arch intraoral scans, facial scans, and CBCT. Craniofacial reference planes guided multimodal alignment using an Iterative Closest Point (ICP) algorithm with predefined parameters. The integrated datasets were analyzed in a virtual articulator to simulate mandibular movements. A 3D‐printed model and silicone index enabled intraoral mock‐up validation.

Results

The workflow achieved consistent multimodal alignment of hard‐ and soft‐tissue structures, eliminating the need for analog facebow transfer or mechanical mounting. The intraoral mock‐up reproduced the virtual design, confirming the clinical transferability of esthetic and functional parameters.

Conclusions

This workflow integrates virtual planning with clinical validation, thereby improving diagnostic precision, esthetic predictability, and interdisciplinary communication in prosthodontic rehabilitation.

Clinical Relevance

This approach provides a reproducible option for virtual patient construction, enabling immediate chairside validation and supporting more predictable clinical decision‐making in esthetic and occlusal rehabilitation.

1. Introduction

Advancements in digital dentistry have enabled the development of the virtual patient concept [1, 2, 3, 4], in which intraoral scans [5, 6], facial scans [7, 8, 9, 10], and cone‐beam computed tomography (CBCT) data [11, 12] are integrated to generate a unified three‐dimensional (3D) representation of the patient. This multimodal approach allows comprehensive visualization of dental morphology, facial esthetics, and craniofacial structures, supporting prosthodontic planning that is both esthetic‐driven and functionally precise [12, 13].

Virtual articulators have further expanded the capabilities of digital workflows by enabling simulation of mandibular movements [14, 15, 16]. However, important limitations remain, particularly regarding functional validation, clinical transferability, and accessibility for routine clinical use. Although semi‐adjustable articulators continue to play a role in conventional workflows [15, 17, 18, 19], current digital approaches increasingly seek to replicate mandibular dynamics within fully virtual environments [20].

Significant progress has been achieved in digital mounting techniques and in defining condylar guidance parameter [11, 18, 19]. However, a clinically applicable and standardized method that integrates intraoral, facial, and CBCT datasets into a single reproducible system while enabling functional analysis and clinical validation is still lacking.

This report presents an alternative digital workflow designed to synchronize intraoral, facial, and CBCT‐derived craniofacial data into a patient‐specific 3D virtual model [12, 16, 17, 20]. By referencing CBCT landmarks to the Frankfort horizontal plane and the terminal hinge axis, the workflow supports functional simulation and esthetic assessment within a virtual articulator environment. Its clinical accuracy is verified through direct intraoral mock‐up validation [18]. However, most existing workflows remain either partially digital or lack direct clinical validation, thereby limiting their applicability in routine prosthodontic practice [8, 9, 10].

2. Methods

A fully digital workflow was implemented to construct a 3D virtual patient [1, 2, 3] through integration of intraoral [5, 14], facial [7, 21], and CBCT datasets [11, 19]. The protocol comprised sequential steps including multimodal data acquisition, dataset fusion, virtual articulator simulation [15, 16], and clinical validation using a direct intraoral mock‐up.

2.1. Intraoral Documentation

Full‐arch maxillary and mandibular scans, along with a digital interocclusal record in maximal intercuspal position (MIP), were obtained using an intraoral scanner (Panda Smart; DeepCare Inc.) and imported into CAD software (Exocad DentalCAD; Exocad GmbH) (Figure 1A) [12, 17]. These datasets served as the primary reference for dental morphology and occlusal relationships.

FIGURE 1.

Initial digital acquisition. (A) Full‐arch intraoral scans with digital interocclusal record (MIP). (B) Three‐dimensional facial scan with natural head position.

2.2. Facial Acquisition

A 3D facial scan was acquired using a facial scanner (Rayface; Ray Co. Ltd.) with the patient positioned in natural head posture (Figure 1B). Scans were obtained in repose and light smile to capture perioral soft‐tissue dynamics. The facial dataset (STL) was aligned to the maxillary intraoral scan using reference points on the canines and central incisors, while overlapping dental regions were excluded to minimize registration artifacts [7, 8, 9, 10, 13].

2.3. CBCT Acquisition and Landmark Identification

A large field‐of‐view CBCT scan (Planmeca ProMax 3D Mid; Planmeca Oy; field of view 20.1 × 16.9 cm; voxel size 300 μm; 90 kVp; 10 mA) was acquired to capture the complete maxillofacial complex. Cheek retractors were used during acquisition to minimize soft‐tissue superimposition and improve dentition visibility.

DICOM volumes were thresholded to isolate hard tissues and exported as STL files representing dentition, alveolar bone, and condyles (Figure 2A). Regions affected by scattering or metallic artifacts were excluded to enhance segmentation accuracy.

FIGURE 2.

Dataset integration. (A) Large field‐of‐view CBCT converted into STL files of dentition, alveolar bone, and condyles. (B) Alignment and superimposition of intraoral, facial, and CBCT datasets in CAD software (Exocad, Exocad GmbH) to generate a unified virtual patient.

The Frankfort horizontal (FH) plane and a CBCT‐derived terminal hinge axis were established using a modified Bergström approach. The geometric centers of both condyles were identified on axial and sagittal CBCT views, and a virtual hinge axis was defined by connecting these points. This axis was used to position the digital patient within the virtual articulator, ensuring spatial alignment of the condylar centers with the articulator reference system [16, 18].

This hinge‐axis determination corresponds to a CBCT‐based kinematic approximation described in previous digital mounting protocols, in which condylar centers are identified in multiplanar views and validated through anatomical symmetry and consistency rather than direct functional mandibular tracking [11, 14, 18, 19].

2.4. Multimodal Alignment and Validation

The CBCT‐derived skeletal model was aligned to the maxillary intraoral scan using Exocad's automatic mesh‐alignment tool, with the CBCT model defined as the floating mesh and the intraoral scan as the fixed mesh. Bilateral first molars and lateral incisors were selected as initial alignment landmarks, and marked tooth regions were excluded to minimize distortion (Figure 2B). This approach is supported by previous studies demonstrating reliable multimodal registration using dental landmarks and triangulation strategies [1, 7, 8, 12].

Alignment was further refined using an Iterative Closest Point (ICP) algorithm with predefined parameters to enhance reproducibility. For CBCT‐to‐intraoral alignment, stable anatomical landmarks including the mesiobuccal cusp tips of the maxillary first molars and the cusp tips of the canines were used to establish initial correspondence. For facial scan integration, a triangulation approach based on the cusp tips of both maxillary canines and the distoincisal angles of the maxillary central incisors was applied [2, 16].

ICP refinement was performed using a matching parts ratio of 5% and a maximum influence distance of 0.5 mm to control point cloud correspondence. Iterations were conducted until convergence was achieved without introducing geometric distortion [1, 12].

The integrated datasets were subsequently visualized and verified, confirming spatial correspondence among skeletal, dental, and facial structures (Figure 3A,B). This process resulted in a unified virtual patient with consistent multimodal alignment, balancing accuracy and computational efficiency while minimizing overfitting of local geometries.

FIGURE 3.

Multimodal fusion for virtual diagnostic wax‐up. (A) CBCT volume superimposed with intraoral scan. (B) Integration of intraoral, facial, and CBCT datasets. (C) Full‐face view of the facially generated diagnostic wax‐up. (D) Intraoral view of virtual diagnostic wax‐up.

2.5. Digital Design and Articulator Simulation

A facially guided virtual diagnostic wax‐up was created to harmonize symmetry, incisal edge position, gingival contours, and smile arc relative to facial reference lines [21, 22] (Figure 3C,D). The integrated model was transferred to Exocad's virtual articulator (Figure 4A).

FIGURE 4.

Simulation of mandibular movements in a virtual articulator. (A) Frontal view of maxillomandibular mounting based on CBCT‐derived landmarks. (B) Frontal alignment of the integrated digital model simulating the terminal hinge axis. (C) Lateral view showing articulator positioning referenced to the Frankfort horizontal plane.

Initial positioning was based on the maxillary central incisor edge and the mesiobuccal cusp tips of both first molars. The FH plane was oriented parallel to the articulator frame, and the hinge axis was aligned using CBCT‐derived condylar coordinates (Figure 4B). A digital semi‐adjustable articulator (BioArt A7 Plus; BioArt) was used with standard parameters (30° condylar inclination, 15° Bennett angle), which were adjusted as required [14, 15] (Figure 4C).

Simulated mandibular movements, including protrusive and laterotrusive excursions, were performed to evaluate occlusal contacts, functional pathways, and potential interferences (Figure 5A–C).

FIGURE 5.

Functional evaluation of simulated mandibular movements. (A) Right laterotrusive movement. (B) Maximal intercuspal position (MIP). (C) Left laterotrusive movement.

2.6. Smile Visualization and Interdisciplinary Verification

A simulated smile was generated by superimposing the virtual wax‐up onto the facial scan, enabling evaluation of esthetic outcomes in both static and dynamic expressions and facilitating interdisciplinary planning [13, 22] (Figure 6A,B).

FIGURE 6.

Virtual smile design for interdisciplinary communication. (A) Baseline facial scan with natural smile. (B) Simulated smile with facially generated virtual diagnostic wax‐up.

2.7. Clinical Validation With a Direct Intraoral Mock‐Up

The final digital wax‐up was designed using dental CAD software (Exocad DentalCAD, version 3.2 Elefsina; Exocad GmbH, Darmstadt, Germany) and fabricated using a stereolithography 3D printer (Phrozen Sonic Mini 8 K S; Phrozen Technology, Taipei, Taiwan) with a model resin (Prizma Wide; Makertech Labs) [17].

Baseline clinical conditions prior to mock‐up transfer are shown in (Figure 7A). A silicone index was fabricated over the printed model and loaded with flowable bis‐acrylic resin, which was positioned intraorally to transfer the virtual design directly onto the dentition (Figure 7B).

FIGURE 7.

Clinical validation. (A) Baseline. (B) Direct intraoral mock‐up derived from the facially guided digital wax‐up, used for esthetic verification.

This mock‐up provided immediate chairside verification of esthetic proportions, midline alignment, smile arc, and preliminary occlusal contacts, serving as the final clinical validation step prior to definitive rehabilitation.

3. Results

Virtual occlusal relationships, including intercuspal, protrusive, and laterotrusive contacts, were successfully evaluated within the virtual articulator. This enabled early identification of functional pathways and potential occlusal interferences prior to clinical intervention, supporting a more controlled and predictive treatment planning process [14, 15].

Integration of intraoral, facial, and CBCT datasets resulted in a coherent three‐dimensional virtual patient, maintaining spatial consistency among dental, skeletal, and soft‐tissue structures. This multimodal alignment allowed stable visualization of key esthetic parameters, including symmetry, incisal display, and smile arc, thereby facilitating comprehensive interdisciplinary assessment within a unified digital environment [2, 12, 16].

The virtual wax‐up was directly translated into an intraoral mock‐up, enabling immediate chairside validation of esthetic integration, occlusal contacts, and phonetic performance. Clinical evaluation demonstrated a high level of concordance with the virtual design, confirming the accuracy of tooth proportions, midline position, and functional occlusion without the need for intermediate analog procedures [21, 22].

Overall, the workflow enabled a predictable transfer of the digital plan to the clinical setting, reducing reliance on conventional mounting techniques, and minimizing iterative adjustments during mock‐up verification. This contributed to a more efficient and reliable chairside decision‐making process [15, 17, 19].

4. Discussion

This report presents a fully digital workflow integrating intraoral, facial, and CBCT datasets for virtual patient construction, building upon previously described digital mounting and articulation strategies [1, 2, 14, 15, 16]. Its main clinical contribution lies in combining CBCT‐derived craniofacial positioning for functional simulation with direct intraoral mock‐up validation, enabling immediate verification of esthetic parameters and preliminary occlusal contacts prior to definitive rehabilitation. This validation step establishes a direct link between virtual planning and clinical execution, strengthening translational reliability compared with previously reported workflows [2, 16].

The use of predefined ICP parameters and standardized anatomical landmarks improves reproducibility and reduces operator‐dependent variability, addressing a major limitation of multimodal workflows [1, 12]. In addition, STL‐based superimposition combined with CBCT‐derived reference planes enables stable mandibular positioning, eliminating the need for facebow transfer and mechanical mounting [14, 18, 19].

Facial scans provide reliable information on soft‐tissue morphology and smile dynamics [7, 8, 9, 10, 12, 13], while intraoral scans capture high‐resolution dental anatomy and occlusal relationships [5, 17]. When integrated with CBCT‐derived skeletal orientation and hinge‐axis estimation, these datasets form a coherent three‐dimensional model that supports esthetic‐ and function‐driven prosthodontic planning [2, 12]. The use of standardized landmarks and algorithm‐based alignment further supports reproducibility when acquisition protocols are controlled [1].

Compared with workflows based on partial digital integration or isolated virtual articulation, this protocol enables dynamic mandibular simulation within a unified environment, improving diagnostic precision, occlusal predictability, and interdisciplinary communication (Table 1) [15, 18, 19, 20]. However, this report is limited to a single clinical case without quantitative validation or comparison with conventional workflows. Therefore, it should be interpreted as a structured clinical protocol rather than a validated analytical model, highlighting the need for controlled studies.

TABLE 1.

Comparison of digital and conventional workflows for virtual patient construction.

Workflow	Data integration	Functional simulation	Clinical validation	Main limitation
Conventional articulator [15, 17]	No	Limited	Indirect	Analog transfer steps and cumulative errors
IOS + virtual articulator [17, 19]	Partial (dental)	Moderate	Limited	Lack of facial and skeletal reference
Facial + IOS [7, 8, 9, 10]	Partial (esthetic)	Moderate	Limited	Absence of hinge‐axis definition
CBCT + IOS [1, 11, 18]	Partial (skeletal)	High	Limited	Radiation exposure requirement
Proposed workflow [2, 15, 16]	Full (dental, facial, and skeletal; dynamic)	High (dynamic simulation)	Direct (intraoral mock‐up validation)	Increased technical complexity and computational demand

Although CBCT acquisition may be considered a limitation, its use is justified when clinically indicated. It should not be prescribed solely for virtual articulation due to radiation exposure. In such cases, CBCT‐free alternatives, including facial scan alignment combined with digital protrusive records, may provide functional mapping with reduced radiation [14, 18, 19]. Additionally, multimodal integration may require substantial computational resources, potentially affecting processing time, memory demand, and software performance.

Previous studies have evaluated digital alignment using CBCT or facial scans independently [11, 18, 19], and more recent approaches have demonstrated fully digital mounting integrating multiple datasets [2, 16]. The present workflow differs by integrating all modalities within a structured protocol and incorporating direct intraoral mock‐up validation, enabling chairside assessment of esthetic and functional outcomes before definitive treatment. However, facial scanning remains sensitive to motion artifacts, particularly in patients with limited neuromuscular control [8, 13].

The reproducibility of this workflow depends on scan quality, segmentation accuracy, and operator experience during multimodal integration [2, 5, 12]. Although this may limit initial adoption, once implemented the protocol reduces analog steps, preserves anatomical fidelity, and provides a scalable approach for digital prosthodontic planning [15, 17].

Future studies should include quantitative comparisons with conventional workflows, evaluating efficiency, accuracy, error rates, and inter‐operator variability, as well as longitudinal assessment of esthetic and functional outcomes.

This workflow enabled predictable transfer of the digital plan to the clinical setting, reducing chairside adjustments, and improving treatment efficiency. Therefore, it should be interpreted not only as a digital integration protocol, but as a clinically translatable strategy that enhances predictability and reliability in virtual patient‐based prosthodontic planning [2, 15].

5. Conclusions

This report demonstrates that a fully digital workflow integrating intraoral, facial, and CBCT datasets can generate a reproducible and clinically applicable virtual patient for prosthodontic planning. The integration of CBCT‐derived craniofacial references with direct intraoral mock‐up validation enables functional simulation and real‐time clinical verification within a unified digital environment.

By directly linking virtual design with chairside validation, this approach enhances diagnostic precision, improves esthetic and functional predictability, and supports more efficient interdisciplinary communication. Therefore, this workflow should be considered a clinically translatable strategy that strengthens the reliability and predictability of virtual patient–based prosthodontic rehabilitation.

Author Contributions

Milton Villanueva Valenzuela: conceptualization, investigation, resources, clinical execution, project administration. Consuelo Marroquín‐Soto: methodology, clinical interpretation, visualization, writing – original draft. César‐Augusto Padilla‐Avalos: methodology, supervision, writing – review and editing, final approval.

Funding

The authors have nothing to report.

Consent

Written informed consent was obtained from the patient prior to the publication of this report.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.