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Development of artificial intelligence model for supporting implant drilling protocol decision making.

Takahiko Sakai^1,2, Hefei Li¹, Tatsuki Shimada¹

¹Department of Biomaterials Science, Osaka University Graduate School of Dentistry, Osaka, Japan.

Journal of Prosthodontic Research

|August 24, 2022

Summary

An artificial intelligence (AI) model accurately predicts dental implant drilling protocols using cone-beam computed tomography (CBCT) images. This AI tool can aid surgeons in planning procedures for improved primary stability.

Keywords:

Artificial intelligence Computed tomography Deep learning/machine learning Dental implant(s)Prosthodontic dentistry/prosthodontics

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Area of Science:

Dental Implantology
Artificial Intelligence in Medicine
Medical Imaging Analysis

Background:

Determining appropriate implant drilling protocols is crucial for achieving primary stability in dental implantology.
Cone-beam computed tomography (CBCT) provides detailed anatomical information essential for surgical planning.

Purpose of the Study:

To develop and validate an artificial intelligence (AI) model for predicting dental implant drilling protocols.
To utilize cone-beam computed tomography (CBCT) images for AI-driven surgical planning.

Main Methods:

An AI model based on LeNet-5 architecture was developed using 1,200 anonymized CBCT image slices from 60 patients.
CBCT images were classified into three drilling protocols (A, B, C) based on actual surgical procedures.
The model was trained and validated on 960 images and tested on 240 images, evaluating accuracy, sensitivity, precision, F-value, and AUC.

Main Results:

The AI model achieved an overall accuracy of 93.8% in predicting drilling protocols.
High sensitivity, precision, and F-value scores were observed for all three protocols (A, B, C).
Area Under the Curve (AUC) values ranged from 98.6% to 99.4%, indicating excellent predictive performance.

Conclusions:

The developed AI model demonstrates high efficacy in predicting dental implant drilling protocols from CBCT images prior to surgery.
This AI tool shows potential as a decision-making support system to enhance primary implant stability.
AI-assisted analysis of CBCT images can significantly improve the precision of implant drilling protocol selection.