Artificial Intelligence in Breast X-Ray Imaging

Srinivasan Vedantham, Mohammed Salman Shazeeb, Alan Chiang, Gopal R. Vijayaraghavan

Research output: Contribution to journalReview articlepeer-review

Abstract

This topical review is focused on the clinical breast x-ray imaging applications of the rapidly evolving field of artificial intelligence (AI). The range of AI applications is broad. AI can be used for breast cancer risk estimation that could allow for tailoring the screening interval and the protocol that are woman-specific and for triaging the screening exams. It also can serve as a tool to aid in the detection and diagnosis for improved sensitivity and specificity and as a tool to reduce radiologists’ reading time. AI can also serve as a potential second ‘reader’ during screening interpretation. During the last decade, numerous studies have shown the potential of AI-assisted interpretation of mammography and to a lesser extent digital breast tomosynthesis; however, most of these studies are retrospective in nature. There is a need for prospective clinical studies to evaluate these technologies to better understand their real-world efficacy. Further, there are ethical, medicolegal, and liability concerns that need to be considered prior to the routine use of AI in the breast imaging clinic.

Original languageEnglish (US)
Pages (from-to)2-7
Number of pages6
JournalSeminars in Ultrasound, CT and MRI
Volume44
Issue number1
DOIs
StatePublished - Feb 2023

Keywords

  • Artificial intelligence
  • Breast cancer
  • Mammography
  • Tomosynthesis
  • deep learning

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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