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Proceedings Paper

Mammographic parenchymal texture as an imaging marker of hormonal activity: a comparative study between pre- and post-menopausal women
Author(s): Dania Daye; Ezra Bobo; Bethany Baumann; Antonios Ioannou; Emily F. Conant; Andrew D. A. Maidment; Despina Kontos
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Paper Abstract

Mammographic parenchymal texture patterns have been shown to be related to breast cancer risk. Yet, little is known about the biological basis underlying this association. Here, we investigate the potential of mammographic parenchymal texture patterns as an inherent phenotypic imaging marker of endogenous hormonal exposure of the breast tissue. Digital mammographic (DM) images in the cranio-caudal (CC) view of the unaffected breast from 138 women diagnosed with unilateral breast cancer were retrospectively analyzed. Menopause status was used as a surrogate marker of endogenous hormonal activity. Retroareolar 2.5cm2 ROIs were segmented from the post-processed DM images using an automated algorithm. Parenchymal texture features of skewness, coarseness, contrast, energy, homogeneity, grey-level spatial correlation, and fractal dimension were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance in distinguishing between 72 pre- and 66 post-menopausal women. Logistic regression was performed to assess the independent effect of each texture feature in predicting menopause status. ROC analysis showed that texture features have inherent capacity to distinguish between pre- and post-menopausal statuses (AUC>0.5, p<0.05). Logistic regression including all texture features yielded an ROC curve with an AUC of 0.76. Addition of age at menarche, ethnicity, contraception use and hormonal replacement therapy (HRT) use lead to a modest model improvement (AUC=0.78) while texture features maintained significant contribution (p<0.05). The observed differences in parenchymal texture features between pre- and post- menopausal women suggest that mammographic texture can potentially serve as a surrogate imaging marker of endogenous hormonal activity.

Paper Details

Date Published: 8 March 2011
PDF: 8 pages
Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79631N (8 March 2011); doi: 10.1117/12.878924
Show Author Affiliations
Dania Daye, The Univ. of Pennsylvania Health System (United States)
Ezra Bobo, The Univ. of Pennsylvania Health System (United States)
Bethany Baumann, The Univ. of Pennsylvania Health System (United States)
Antonios Ioannou, The Univ. of Pennsylvania Health System (United States)
Emily F. Conant, The Univ. of Pennsylvania Health System (United States)
Andrew D. A. Maidment, The Univ. of Pennsylvania Health System (United States)
Despina Kontos, The Univ. of Pennsylvania Health System (United States)

Published in SPIE Proceedings Vol. 7963:
Medical Imaging 2011: Computer-Aided Diagnosis
Ronald M. Summers; Bram van Ginneken, Editor(s)

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