Research Article
Differentiation of Breast Cancer Immunohistochemical Status Using Digital Mammography Radiomics Features
Author(s): Malomon Aimé Bonou*, Zouhour Ben Azouz, Khlifa Nawres, Rodrigue Sètchéou Allodji and Julien Dossou
Purpose: Discriminating breast cancer Hormonal Receptor (HR), human epidermal growth factor receptor (Her2) and Triple Negative (TN) status using mammography radiomic features. Materials and Methods: We used an open-source database enrolling 71 patients with confirmed breast cancer. It includes bilateral mammograms Craniocaudal (CC) and Mediolateral Oblique (MLO) as well as the breast cancer molecular status such as HR, Her2 and TN. We extracted a set of 486 quantitative descriptors from the original and the wavelets of the CC and the MLO mammograms. Using the training set (ntrain=48), we performed the features selection following two steps: (i) first, univariable feature selection had been implemented with correlation statistical test to eliminate redundancy between mammogram features. (ii) In second part, we used Support Vector Machine Re.. Read More»
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