Korean J Fam Pract.  2023 Dec;13(4):196-210. 10.21215/kjfp.2023.13.4.196.

Application of Artificial Intelligence in Breast Imaging: Current Landscape and Prospects

• Kim HJ
• Kim HH

• KMID: 2549642
• DOI: http://doi.org/10.21215/kjfp.2023.13.4.196

Abstract

Breast cancer stands as a pervasive and life-threatening disease affecting women worldwide. Early detection of the disease is critical, and mammography has conventionally been a primary screening modality. However, mammography has some limitations, such as false-positives and difficulties in detecting lesions in dense breasts. To address these challenges, artificial intelligence-based computer-aided detection (AI-CAD) systems have been developed to assist radiologists in interpreting mammograms. These systems identify suspicious patterns indicative of breast cancer. Studies have shown that AI-CAD exhibits high sensitivity and specificity in breast cancer detection, at times even surpassing the performance of radiologists. Radiologists utilizing AI-CAD achieved enhanced diagnostic accuracy, especially in complex cases. Notably, AI’s role extends beyond cancer detection. It can streamline workflow, help radiologists prioritize images, objectively evaluate breast density, and predict individual breast cancer risk. While AI shows promise in breast imaging, challenges still persist. Large-scale clinical validation is needed to establish generalizability, consistency, and efficiency. Ethical and legal considerations are essential for integrating AI into clinical practice. Collaborations between radiologists and AI is important for maximizing the technology’s potential in breast imaging. In conclusion, AI has shown significant promise in enhancing breast cancer detection and improving radiologists’ performance in breast imaging. Further research, clinical validation, ethical considerations, and collaborations between radiologists and AI are crucial for its widespread adoption in breast imaging.

Keyword

Artificial Intelligence; Computer-Aided Detection; Breast Imaging; Mammography