Breast cancer subtype intertumor heterogeneity: MRI-based features predict results of a genomic assay Journal Article
| Authors: | Sutton, E. J.; Oh, J. H.; Dashevsky, B. Z.; Veeraraghavan, H.; Apte, A. P.; Thakur, S. B.; Deasy, J. O.; Morris, E. A. |
| Article Title: | Breast cancer subtype intertumor heterogeneity: MRI-based features predict results of a genomic assay |
| Abstract: | Purpose To investigate the association between a validated, gene-expression-based, aggressiveness assay, Oncotype Dx RS, and morphological and texture-based image features extracted from magnetic resonance imaging (MRI). Materials and Methods This retrospective study received Internal Review Board approval and need for informed consent was waived. Between 2006-2012, we identified breast cancer patients with: 1) ER+, PR+, and HER2- invasive ductal carcinoma (IDC); 2) preoperative breast MRI; and 3) Oncotype Dx RS test results. Extracted features included morphological, histogram, and gray-scale correlation matrix (GLCM)-based texture features computed from tumors contoured on pre- and three postcontrast MR images. Linear regression analysis was performed to investigate the association between Oncotype Dx RS and different clinical, pathologic, and imaging features. P<0.05 was considered statistically significant. Results Ninety-five patients with IDC were included with a median Oncotype Dx RS of 16 (range: 0-45). Using stepwise multiple linear regression modeling, two MR-derived image features, kurtosis in the first and third postcontrast images and histologic nuclear grade, were found to be significantly correlated with the Oncotype Dx RS with P=0.0056, 0.0005, and 0.0105, respectively. The overall model resulted in statistically significant correlation with Oncotype Dx RS with an R-squared value of 0.23 (adjusted R-squared=0.20; P=0.0002) and a Spearman?s rank correlation coefficient of 0.49 (P<0.0001). Conclusion A model for IDC using imaging and pathology information correlates with Oncotype Dx RS scores, suggesting that image-based features could also predict the likelihood of recurrence and magnitude of chemotherapy benefit. © 2015 Wiley Periodicals, Inc. |
| Keywords: | adult; aged; major clinical study; clinical feature; histopathology; preoperative care; nuclear magnetic resonance imaging; preoperative evaluation; disease association; image analysis; epidermal growth factor receptor 2; cohort analysis; genotype; retrospective study; prediction; quantitative analysis; contrast enhancement; breast carcinoma; estrogen receptor; progesterone receptor; imaging and display; correlational study; nuclear magnetic resonance scanner; computer analysis; invasive ductal carcinoma; data extraction; human; female; priority journal; article; gene expression assay; breast cancer subtypes; gray scale correlation matrix based second order texture; histogram based first order texture; morphology based feature; oncotype dx recurrence score |
| Journal Title: | Journal of Magnetic Resonance Imaging |
| Volume: | 42 |
| Issue: | 5 |
| ISSN: | 1053-1807 |
| Publisher: | Wiley Blackwell |
| Date Published: | 2015-11-01 |
| Start Page: | 1398 |
| End Page: | 1406 |
| Language: | English |
| DOI: | 10.1002/jmri.24890 |
| PROVIDER: | scopus |
| PUBMED: | 25850931 |
| PMCID: | PMC4784421 |
| DOI/URL: | |
| Notes: | Export Date: 2 December 2015 -- Source: Scopus |
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