AI-enhanced breast imaging: Where are we and where are we heading?. Issue 142 (September 2021)

• Record Type: Journal Article
• Authors: Bitencourt, Almir; Daimiel Naranjo, Isaac; Lo Gullo, Roberto; Rossi Saccarelli, Carolina; Pinker, Katja
• Is Part Of: European journal of radiology. Issue 142(2021)
• Publication Date: 2021-09
• Subjects: Artificial Intelligence -- Deep learning -- Breast neoplasms -- Mammography -- Ultrasound -- Magnetic resonance imaging; AI artificial intelligence -- ADC apparent diffusion coefficient -- AUC area under the curve -- BI-RADS Breast Imaging-Reporting and Data System -- CAD computer-aided detection -- CNN convolutional neural network -- DCE-MRI dynamic contrast-enhanced magnetic resonance imaging -- DL deep learning -- DWI diffusion-weighted imaging -- ML machine learning -- MRI magnetic resonance imaging -- NAC neoadjuvant chemotherapy -- pCR pathologic complete response -- ROC receiver operating characteristic -- ROI region of interest -- US ultrasound; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2021.109882
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: AI-enhanced breast imaging extends to all imaging modalities. AI applications: risk prediction, lesion detection/classification, radiogenomics. AI applications also include prediction of treatment response and clinical outcomes. Continued study with larger sample sizes and rigorous standardization is needed. AI-enhanced breast imaging promises more effective and patient-centric cancer care. Abstract: 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.