AI-enhanced breast imaging: Where are we and where are we heading?

被引：64

作者：

Bitencourt, Almir ^{[1
,2
]}

Naranjo, Isaac Daimiel ^{[3
]}

Lo Gullo, Roberto ^{[4
]}

Saccarelli, Carolina Rossi ^{[2
,5
]}

Pinker, Katja ^{[4
]}

机构：

[1] AC Camargo Canc Ctr, Dept Imaging, Sao Paulo, SP, Brazil

[2] Dasa, Sao Paulo, SP, Brazil

[3] Guys & St ThomasNHS Trust, Breast Imaging Serv, Dept Radiol, London, England

[4] Mem Sloan Kettering Canc Ctr, Dept Radiol, New York, NY USA

[5] Hosp Sirio Libanes, Dept Radiol, Sao Paulo, SP, Brazil

来源：

EUROPEAN JOURNAL OF RADIOLOGY | 2021年 / 142卷

关键词：

Artificial Intelligence; Deep learning; Breast  neoplasms; Mammography; Ultrasound; Magnetic  reonance imaging; RADIOGENOMIC ANALYSIS; MOLECULAR SUBTYPES; NEURAL-NETWORKS; ONCOTYPE DX; CANCER; MRI; PREDICTION; RADIOMICS; FEATURES; CLASSIFICATION;

D O I：

10.1016/j.ejrad.2021.109882

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

100231 [临床病理学]; 100902 [航空航天医学];

摘要：

Significant advances in imaging analysis and the development of high-throughput methods that can extract and correlate multiple imaging parameters with different clinical outcomes have led to a new direction in medical research. Radiomics and artificial intelligence (AI) studies are rapidly evolving and have many potential applications in breast imaging, such as breast cancer risk prediction, lesion detection and classification, radiogenomics, and prediction of treatment response and clinical outcomes. AI has been applied to different breast imaging modalities, including mammography, ultrasound, and magnetic resonance imaging, in different clinical scenarios. The application of AI tools in breast imaging has an unprecedented opportunity to better derive clinical value from imaging data and reshape the way we care for our patients. The aim of this study is to review the current knowledge and future applications of AI-enhanced breast imaging in clinical practice.

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