Srinivasan Vedantham , Mohammed Salman Shazeeb , Alan Chiang , Gopal R. Vijayaraghavan
{"title":"Artificial Intelligence in Breast X-Ray Imaging","authors":"Srinivasan Vedantham , Mohammed Salman Shazeeb , Alan Chiang , Gopal R. Vijayaraghavan","doi":"10.1053/j.sult.2022.12.002","DOIUrl":null,"url":null,"abstract":"<div><p>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<span> and to a lesser extent digital breast tomosynthesis<span>; 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.</span></span></p></div>","PeriodicalId":49541,"journal":{"name":"Seminars in Ultrasound Ct and Mri","volume":"44 1","pages":"Pages 2-7"},"PeriodicalIF":1.5000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932302/pdf/","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seminars in Ultrasound Ct and Mri","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0887217122000993","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 3
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.
期刊介绍:
Seminars in Ultrasound, CT and MRI is directed to all physicians involved in the performance and interpretation of ultrasound, computed tomography, and magnetic resonance imaging procedures. It is a timely source for the publication of new concepts and research findings directly applicable to day-to-day clinical practice. The articles describe the performance of various procedures together with the authors'' approach to problems of interpretation.