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Updated: Aug 19, 2026

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
Published on: February 23, 2024
Nationwide registry-based automated dose monitoring for dental CBCT: a feasibility study
Gyu-Dong Jo1,2, Jung Su Kim3, Ah-Young Kwon4
1Department of Oral and Maxillofacial Radiology, Seoul National University Dental Hospital, 101 Daehak-ro, 03080, Seoul, Korea.
Objectives:
To develop and evaluate the feasibilityof a nationwide registry-based automated dose monitoring system for dental cone-beam computed tomography (CBCT).
Methods:
A CBCT dose monitoring system was developed to automatically extract dose-related parameters from Digital Imaging and Communications in Medicine (DICOM) headers. The system was implemented at participating dental institutions across the Republic of Korea, and data were collected from CBCT examinations performed between March and November 2025. Device-reported dose-area product (DAP) values were categorized according to field-of-view (FOV) size, patient age group, and institution type. Category-specific DAP distributions were summarized using the minimum, 25th percentile, median, 75th percentile, and maximum values.
Results:
A total of 22,781 CBCT examinations from 120 participating dental institutions were included. Medium FOV examinations were the most common (21,390; 93.9%), followed by small FOV (1,338; 5.9%) and large FOV examinations (53; 0.2%). The 75th percentile DAP values were 1,898, 2,089, and 1,045 mGy·cm² for large, medium, and small FOV examinations, respectively. Age-specific and institution-type-specific DAP distributions were also generated. Pediatric examinations showed lower 75th percentile DAP values than adult examinations across FOV categories, whereas university hospitals showed higher values than clinics.
Conclusions:
This study demonstrates that nationwide, registry-based monitoring of dental CBCT doses is feasible using routine DICOM data. While providing initial large-scale dose reference estimates, future efforts must focus on external validation, standardized metadata reporting, and tailored classification strategies to establish robust, longitudinal dose surveillance and optimization.
