Breast cancer is a complex disease characterized by many morphological, clinical, and molecular features. For many years, breast cancer has been classified according to traditional parameters, such as histological type, grade, tumor size, lymph node involvement and vascular invasion, and biomarkers (eg, estrogen receptor, progesterone receptor, and epidermal growth factor receptor 2), which are used in patient management. With emerging imaging techniques (ie, digital mammography, tomosynthesis, ultrasonography, magnetic resonance imaging, nuclear medicine, and genomic techniques, such as real-time RT-PCR and microarrays), breast cancer diagnostics is going through a significant evolution. Imaging technologies have improved breast cancer diagnosis, survival, and treatment by early detection of primary or metastatic lesions, differentiating benign from malignant lesions and promoting intraoperative surgical guidance and postoperative specimen evaluation. Genomic and transcriptomic technologies make the analysis of gene expression signatures and mutation status possible so that tumors may be classified more accurately with respect to diagnosis and prognosis. The -omic era has also made possible the identification of new biomarkers involved in breast cancer development, survival, and invasion that can be gradually incorporated into clinical testing. These advances in both imaging and genomics contribute to more personalized and predictive patient management. We review the progress made in breast cancer diagnosis and management using these new tools.
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