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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  1. Elizabeth A Morris
    341 Morris
  2. Sunitha Bai Thakur
    100 Thakur
  3. Jung Hun Oh
    187 Oh
  4. Joseph Owen Deasy
    524 Deasy
  5. Aditya Apte
    203 Apte
  6. Elizabeth Jane Sutton
    70 Sutton