The Emergence Clone concept. Optimizing the implant emergence profile using artificial segmentation

Area of Science:

• Dental implantology
• Digital dentistry
• Artificial intelligence in healthcare

Background:

• Achieving a natural emergence profile is crucial for dental implant success, transitioning from implant neck to cervical tooth area.
• The anterior edentulous region presents challenges for soft tissue reference, complicating surgical and prosthetic phases.
• Digital workflows, including 3D modeling and segmentation, are vital for accurate diagnosis, virtual planning, and outcome prediction in implant dentistry.

Purpose of the Study:

• To develop and evaluate a novel artificial intelligence-convolutional neural network system for automatic segmentation of CBCT images.
• To utilize AI for replicating natural tooth contours and soft tissue architecture in delayed implant placement cases.
• To streamline the fabrication of temporary restorations by mimicking contralateral natural teeth.

Main Methods:

• Development of a new artificial intelligence-convolutional neural network system for automated CBCT image segmentation.
• Application of a digital workflow involving segmentation, copy-pasting of natural tooth contours via a mirror effect, and CAD/CAM fabrication.
• Sequential modification of the critical contour to shape peri-implant soft tissue in delayed implant placement.

Main Results:

• The AI system successfully segmented CBCT images, enabling precise isolation of anatomical structures.
• CAD/CAM temporization using the AI application consistently reproduced the natural critical contour of contralateral teeth.
• The technique allowed for accurate, mimetic recreation of soft tissue architecture and tooth contour, eliminating the need for adjustments.

Conclusions:

• AI-powered digital workflows offer a predictable and efficient method for restoring natural tooth contours and soft tissue architecture in implant dentistry.
• This innovative technique significantly improves the aesthetic outcomes of delayed implant placements, particularly in the anterior region.
• The AI-driven approach facilitates the precise fabrication of temporary restorations, ensuring a natural appearance and optimal fit.