期刊
ACADEMIC RADIOLOGY
卷 27, 期 1, 页码 39-46出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.acra.2019.09.012
关键词
breast cancer; radiogenomics; MRI; deep learning
Radiogenomics is an area of research that aims to identify associations between imaging phenotypes (radio-) and tumor genome (-genomics). Breast cancer radiogenomics research in particular has been an especially prolific area of investigation in recent years as evidenced by the wide number and variety of publications and conferences presentations. To date, research has primarily been focused on dynamic contrast enhanced pre-operative breast MRI and breast cancer molecular subtypes, but investigations have extended to all breast imaging modalities as well as multiple additional genetic markers including those that are commercially available. Furthermore, both human and computer-extracted features as well as deep learning techniques have been explored. This review will summarize the specific imaging modalities used in radiogenomics analysis, describe the methods of extracting imaging features, and present the types of genomics, molecular, and related information used for analysis. Finally, the limitations and future directions of breast cancer radiogenomics research will be discussed.
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