Multiparametric and Multimodality Functional Radiological Imaging for Breast Cancer Diagnosis and Early Treatment
Michael A Jacobs1, Antonio C Wolff2, Katarzyna J Macura2
1The Russell H. Morgan Department of Radiology and Radiological Science (MAJ, KJM, RO, REK, DAB, RW), Sidney Kimmel Comprehensive Cancer Center (MAJ, ACW, KJM, VS, RW), and Department of Oncology (ACW, VS), The Johns Hopkins University School of Medicine, Baltimore, MD; National Institute of Diabetes and Digestive and Kidney Diseases (not affialted, RO) and Radiology and Imaging Sciences, National Institutes of Health Clinical Center (DAB), Bethesda, MD. mikej@mri.jhu.edu.
Abstract:
Breast cancer is the second leading cause of cancer death among US women, and the chance of a woman developing breast cancer sometime during her lifetime is one in eight. Early detection and diagnosis to allow appropriate locoregional and systemic treatment are key to improve the odds of surviving its diagnosis. Emerging data also suggest that different breast cancer subtypes (phenotypes) may respond differently to available adjuvant therapies. There is a growing understanding that not all patients benefit equally from systemic therapies, and therapeutic approaches are being increasingly personalized based on predictive biomarkers of clinical benefit. Optimal use of established and novel radiological imaging methods, such as magnetic resonance imaging and positron emission tomography, which have different biophysical mechanisms can simultaneously identify key functional parameters. These methods provide unique multiparametric radiological signatures of breast cancer, that will improve the accuracy of early diagnosis, help select appropriate therapies for early stage disease, and allow early assessment of therapeutic benefit.
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