Paper
10 March 2017 Can BI-RADS features on mammography be used as a surrogate for expensive genomic testing in breast cancer patients?
Michael R. Harowicz, Jeffrey R. Marks, P. Kelly Marcom, Maciej A. Mazurowski
Author Affiliations +
Abstract
Medical oncologists increasingly rely on expensive genomic analysis to stratify patients for different treatment. The genomic markers are able to divide patients into groups that behave differently in terms of tumor presentation, likelihood of metastatic spread, and response to chemotherapy and radiation therapy. In recent years there has been a rapid increase in the number of genomic tests available, like the Oncotype DX test, which provides the risk of cancer recurrence for a subset of patients. Radiogenomics, a new field that investigates the relationship between imaging phenotypes and genomic characteristics, may offer a less expensive and less invasive imaging surrogate for molecular subtype and Oncotype DX recurrence score (ODRS). This retrospective study analyzes the relationship between Breast Imaging-Reporting and Data System (BI-RADS) features as assessed by radiologists on mammograms with molecular subtype and ODRS. We used data from patients with BI-RADS features (shape or margin) and a genomic feature (subtype or ODRS) for the following cohort: shape vs. subtype (n=69), margin vs. subtype (n=78), shape vs. ODRS (n=20), and margin vs. ODRS (n=18). The association between features was assessed using a Fisher’s exact test. Our results show that shape assessed by radiologists according to the BI-RADS lexicon is associated with molecular subtype (p=0.0171), while BI-RADS features of shape and margin were not significantly associated with ODRS (p=0.7839, p=0.6047 respectively).
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Michael R. Harowicz, Jeffrey R. Marks, P. Kelly Marcom, and Maciej A. Mazurowski "Can BI-RADS features on mammography be used as a surrogate for expensive genomic testing in breast cancer patients?", Proc. SPIE 10136, Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment, 101361N (10 March 2017); https://doi.org/10.1117/12.2255866
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KEYWORDS
Mammography

Breast cancer

Tumors

Medicine

Receptors

Breast

Cancer

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