A Virtual Patient-Based Workflow for Mandibular Stabilization Using a Virtual Articulator and Digital Splint

To present a fully digital workflow for mandibular stabilization that reproduces the conventional articulator-based process within a virtual environment, integrating patient-specific three-dimensional (3D) datasets and artificial intelligence (AI)-assisted alignment.

The workflow involves registration of intraoral scans, cone-beam computed tomography (CBCT), and/or facial scans to construct a unified virtual patient. Mandibular casts are mounted in centric relation on a virtual articulator using reference best-fit alignment. A virtual face-bow transfer aligns the maxillary cast to the articulator orientation plane based on anatomical landmarks from CBCT or facial scans. Stabilization splints are digitally designed with adjustable condylar guidance and anterior ramp inclination and fabricated via liquid crystal display (LCD) 3D printing with optimized orientation and post-processing. Clinical follow-up includes repeated digital centric relation bite registrations to monitor condylar position and confirm mandibular stability.

The fully digital workflow achieves mandibular stabilization while maintaining the biomechanical objectives of conventional methods. AI-assisted alignment, computer-aided design (CAD)-based splint design, and validated 3D printing parameters enhance precision, reproducibility, and clinical efficiency.

This protocol provides a reproducible and clinically feasible approach to mandibular stabilization, bridging conventional occlusal principles with digital implementation, and establishing a foundation for future AI-integrated occlusion-centered therapy.