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Computed Tomography

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

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Published on: February 23, 2024

Clinically applicable artificial intelligence system for dental diagnosis with CBCT.

Matvey Ezhov¹, Maxim Gusarev¹, Maria Golitsyna¹

¹Diagnocat Inc, San Francisco, CA, USA.

Scientific Reports

|July 23, 2021

Summary

A novel artificial intelligence (AI) system significantly improved dentists' diagnostic accuracy in real-time Cone Beam Computed Tomography (CBCT) imaging. The AI system enhanced both sensitivity and specificity in identifying dental conditions.

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Area of Science:

Dentistry
Artificial Intelligence
Medical Imaging

Background:

Cone Beam Computed Tomography (CBCT) is crucial for dental diagnostics.
Accurate interpretation of CBCT scans requires specialized expertise.
AI offers potential to enhance diagnostic capabilities in dentistry.

Purpose of the Study:

To evaluate the real-time performance and clinical effectiveness of a novel AI system for CBCT imaging diagnosis.
To assess the impact of the AI system on diagnostic accuracy when used by dentists.
To determine the safety and clinical utility of the AI system in a dental setting.

Main Methods:

A deep learning-based AI system with five modules (ROI-localization, tooth-localization/numeration, periodontitis, caries, periapical-lesion localization) was developed.
The AI system was trained on 1346 CBCT scans using Convolutional Neural Networks (CNNs).
A clinical evaluation involved 24 dentists examining 30 CBCT scans, with one group aided by the AI system and the other unaided.

Main Results:

The AI-assisted group showed higher overall sensitivity (0.8537) compared to the unaided group (0.7672).
Specificity was also higher in the AI-assisted group (0.9672) versus the unaided group (0.9616).
The difference in diagnostic performance between the aided and unaided groups was statistically significant (p=0.032).

Conclusions:

The novel AI system significantly enhances dentists' diagnostic capabilities in CBCT imaging.
The AI system demonstrates real-time performance, clinical effectiveness, and safety.
AI integration in dentistry holds promise for improving diagnostic accuracy and patient care.