1. Estrogen receptor-negative invasive breast cancer: imaging features of tumors with and without human epidermal growth factor receptor type 2 overexpression.
- Author
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Wang Y, Ikeda DM, Narasimhan B, Longacre TA, Bleicher RJ, Pal S, Jackman RJ, and Jeffrey SS
- Subjects
- Adult, Aged, Aged, 80 and over, Breast Neoplasms classification, Calcinosis classification, Female, Humans, Male, Middle Aged, Reproducibility of Results, Sensitivity and Specificity, Biomarkers, Tumor metabolism, Breast Neoplasms diagnosis, Breast Neoplasms metabolism, Calcinosis diagnosis, Calcinosis metabolism, Mammography methods, Receptor, ErbB-2 metabolism
- Abstract
Purpose: To prospectively determine if estrogen receptor (ER)-negative human epidermal growth factor receptor type 2 (HER2)-positive and ER-negative HER2-negative breast cancers have distinguishing clinical and imaging features with use of retrospectively identified patients and tissue samples., Materials and Methods: This HIPAA-compliant study was institutional review board approved. Informed consent was obtained from living patients and waived for deceased patients. Mean patient age at diagnosis was 53 years (range, 31-84 years). Clinical history; histopathologic, mammographic, and breast sonographic findings; and HER2 status as determined with immunohistochemistry or fluorescent in situ hybridization were evaluated in 56 women with ER-negative breast cancer. Imaging appearances and clinicopathologic characteristics were correlated with tumor HER2 status. P < .05 indicated a significant difference., Results: Lesion margins on mammograms (P = .028) and sonograms (P = .023), calcifications on mammograms (P = .003), and clinical cancer stage at diagnosis (P = .029) were significantly associated with HER2 status. In contrast to ER-negative HER2-negative tumors, ER-negative HER2-positive tumors were more likely to have spiculated margins (56% vs 15%), be associated with calcifications (65% vs 21%), and be detected at a higher cancer stage (74% vs 57%)., Conclusion: Biologic diversity of cancers may manifest in imaging characteristics, and, conversely, studying the range of imaging features of cancers may help refine current molecular phenotypes., ((c) RSNA, 2008.)
- Published
- 2008
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