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Artificial intelligence serving pre-surgical digital implant planning: A scoping review
Bahaaeldeen M Elgarba1, Rocharles Cavalcante Fontenele2, Mihai Tarce3
1OMFS IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, KU Leuven & Department of Oral and Maxillofacial Surgery, University Hospitals, Campus Sint-Rafael, 3000 Leuven, Belgium & Department of Prosthodontics, Faculty of Dentistry, Tanta University, 31511 Tanta, Egypt.
Artificial intelligence (AI) enhances dental implant planning through automated segmentation and virtual patient creation. However, fully automated implant placement is not yet scientifically validated, with limited clinical validation for AI tools.
Area of Science:
- Dental implantology and digital dentistry.
- Artificial intelligence and machine learning applications.
- Surgical planning and medical imaging analysis.
Background:
- Presurgical dental implant planning relies on accurate data interpretation and workflow efficiency.
- Artificial intelligence (AI) offers potential for automating complex tasks in digital dentistry.
- The degree of automation and scientific validation of AI in implant planning requires thorough assessment.
Purpose of the Study:
- To conduct a scoping review on artificial intelligence (AI) applications in presurgical dental implant planning.
- To evaluate the level of automation in currently available pre-surgical implant planning software.
Main Methods:
- Systematic literature search across five major databases and gray literature up to November 2023.
- Inclusion of English-language studies on AI-driven tools for digital implant planning.
- Assessment of automation features in 12 commercially available implant planning software applications.
Main Results:
- 39 of 47 reviewed studies focused on AI for anatomical landmark segmentation and virtual patient creation.
- 8 studies investigated AI for virtual implant placement.
- Only 6 of 12 assessed software applications had at least one automated step; none offered a fully automated protocol.
Conclusions:
- AI significantly improves accuracy, efficiency, and consistency in anatomical segmentation for virtual patient creation.
- Current virtual implant placement systems show varying automation levels, but full automation is not yet scientifically validated.
- Clinical and scientific validation for AI applications in dental implant planning remains limited, necessitating careful clinician evaluation.
