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 2.5cm<sup>2</sup> 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&gt;0.5, p&lt;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&lt;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.

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