J Korean Soc Radiol.
2025 Mar;86(2):205-215. 10.3348/jksr.2025.0011.
Clinical Application of Artificial Intelligence in Digital Breast Tomosynthesis
- Affiliations
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- 1Department of Radiology, Seoul National University Hospital, Seoul, Korea
- 2Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- 3Lunit, Seoul, Korea
- 4Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
- KMID: 2566617
- DOI: http://doi.org/10.3348/jksr.2025.0011
Abstract
- Digital breast tomosynthesis (DBT) provides improved cancer detection and lower recall rates when compared with full-field digital mammography (DM) and has been widely adopted for breast cancer screening. However, adopting DBT presents new challenges such as an increased number of acquired images resulting in longer interpretation times. Artificial intelligence (AI) offers numerous opportunities to enhance the advantages of DBT and mitigate its shortcomings. Research in the DBT AI domain has grown significantly and AI algorithms play a key role in the screening and diagnostic phases of breast cancer detection and characterization. The application of AI may streamline the workflow and reduce the time required for radiologists to interpret images. In addition, AI can minimize radiation exposure and enhance lesion visibility in synthetic two-dimensional DM images. This review provides an overview of AI technology in DBT, its clinical applications, and future considerations.
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