AI-assisted Workflow to Optimize Immediate Implant Drilling Protocol with a SocketFit Static Surgical Guide: A Case...

Area of Science:

• Dental surgery
• Artificial intelligence
• Implantology

Background:

• Artificial intelligence (AI) integration has significantly advanced dental implantology.
• Static computer-aided implant surgery (sCAIS) streamlines implant placement but faces limitations with immediate implants due to complex post-extraction socket anatomy.
• Deviations in drill trajectory can compromise implant positioning, stability, and aesthetic outcomes.

Purpose of the Study:

• To introduce an AI-assisted modification to the traditional sCAIS workflow for immediate implant placement.
• To present the SocketFit Guide (SFG), an AI-driven pilot drill surgical guide designed to mitigate risks associated with immediate implant surgery.
• To enhance the accuracy and control of implant placement in challenging anatomical situations.

Main Methods:

• The study details an AI-assisted modification to the sCAIS guide design.
• The SocketFit Guide (SFG) design utilizes AI-driven virtual segmentation of anatomical structures for precise alveolar socket delineation.
• The SFG features an extended, apically positioned guide sleeve to improve pilot drill control near the planned osteotomy site.

Main Results:

• The AI algorithm enables accurate virtual delineation of alveolar socket boundaries.
• The SFG design, with its modified guide sleeve, allows for closer proximity of the pilot drill to the osteotomy site.
• This proximity enhances control over the drill trajectory, minimizing deflection and improving accuracy.

Conclusions:

• The AI-assisted SocketFit Guide (SFG) effectively addresses the limitations of traditional sCAIS in immediate implant placement.
• SFG enhances surgical accuracy and implant stability by minimizing drill deflection in complex anatomical scenarios.
• This AI-driven approach offers a promising solution for optimizing outcomes in immediate dental implant procedures.