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本文引用的文献

1
Impact of artificial intelligence in breast cancer screening with mammography.人工智能在乳腺 X 线摄影乳腺癌筛查中的影响。
Breast Cancer. 2022 Nov;29(6):967-977. doi: 10.1007/s12282-022-01375-9. Epub 2022 Jun 28.
2
Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis.将放射科医生和人工智能的优势相结合用于乳腺癌筛查:一项回顾性分析。
Lancet Digit Health. 2022 Jul;4(7):e507-e519. doi: 10.1016/S2589-7500(22)00070-X.
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AI-based prevention of interval cancers in a national mammography screening program.基于人工智能的全国乳腺筛查计划中间期癌的预防。
Eur J Radiol. 2022 Jul;152:110321. doi: 10.1016/j.ejrad.2022.110321. Epub 2022 Apr 20.
4
Improving the Performance of Radiologists Using Artificial Intelligence-Based Detection Support Software for Mammography: A Multi-Reader Study.利用基于人工智能的乳腺 X 线摄影检测支持软件提高放射科医生的工作表现:一项多读者研究。
Korean J Radiol. 2022 May;23(5):505-516. doi: 10.3348/kjr.2021.0476. Epub 2022 Apr 4.
5
Deep-learning-based projection-domain breast thickness estimation for shape-prior iterative image reconstruction in digital breast tomosynthesis.基于深度学习的投影域乳房厚度估计在数字乳腺断层合成中用于形状先验迭代图像重建。
Med Phys. 2022 Jun;49(6):3670-3682. doi: 10.1002/mp.15612. Epub 2022 Mar 30.
6
Interval Cancer Detection Using a Neural Network and Breast Density in Women with Negative Screening Mammograms.使用神经网络和乳腺密度对乳腺钼靶筛查阴性女性进行间期癌症检测。
Radiology. 2022 May;303(2):269-275. doi: 10.1148/radiol.210832. Epub 2022 Feb 8.
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Optimizing risk-based breast cancer screening policies with reinforcement learning.基于强化学习优化基于风险的乳腺癌筛查政策。
Nat Med. 2022 Jan;28(1):136-143. doi: 10.1038/s41591-021-01599-w. Epub 2022 Jan 13.
8
Stand-Alone Use of Artificial Intelligence for Digital Mammography and Digital Breast Tomosynthesis Screening: A Retrospective Evaluation.人工智能在数字乳腺 X 线摄影和数字乳腺断层合成筛查中的独立应用:一项回顾性评估。
Radiology. 2022 Mar;302(3):535-542. doi: 10.1148/radiol.211590. Epub 2021 Dec 14.
9
Clinical Artificial Intelligence Applications: Breast Imaging.临床人工智能应用:乳腺成像。
Radiol Clin North Am. 2021 Nov;59(6):1027-1043. doi: 10.1016/j.rcl.2021.07.010.
10
Mammography-based radiomics for predicting the risk of breast cancer recurrence: a multicenter study.基于乳腺 X 线摄影的放射组学预测乳腺癌复发风险:一项多中心研究。
Br J Radiol. 2021 Nov 1;94(1127):20210348. doi: 10.1259/bjr.20210348. Epub 2021 Sep 14.

人工智能在乳腺 X 射线成像中的应用。

Artificial Intelligence in Breast X-Ray Imaging.

机构信息

Department of Medical Imaging, University of Arizona, Tucson, AZ.

Department of Radiology, University of Massachusetts Chan Medical School, Worcester, MA.

出版信息

Semin Ultrasound CT MR. 2023 Feb;44(1):2-7. doi: 10.1053/j.sult.2022.12.002. Epub 2022 Dec 26.

DOI:10.1053/j.sult.2022.12.002
PMID:36792270
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9932302/
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.

摘要

这篇专题综述聚焦于人工智能(AI)这一快速发展领域在临床乳房 X 线摄影成像中的应用。AI 的应用范围非常广泛。它可用于乳腺癌风险评估,从而可以针对每个女性量身定制筛查间隔和方案,并对筛查检查进行分类。它还可以作为一种工具,通过提高敏感性和特异性来辅助检测和诊断,并作为一种减少放射科医生阅读时间的工具。AI 还可以作为筛查解读时潜在的第二‘读者’。在过去的十年中,许多研究表明了 AI 辅助解读乳房 X 光摄影和在较小程度上数字乳腺断层合成的潜力;然而,这些研究大多是回顾性的。需要前瞻性的临床研究来评估这些技术,以更好地了解它们在现实世界中的效果。此外,在 AI 常规用于乳房成像诊所之前,还需要考虑伦理、医疗法律和责任方面的问题。