An exploratory radiomics analysis on digital breast tomosynthesis in women with mammographically negative dense breasts. (August 2018) - Tagliafico, Alberto Stefano; Valdora, Francesca; Mariscotti, Giovanna; Durando, Maunela; Nori, Jacopo; La Forgia, Daniele; Rosenberg, Ilan; Caumo, Francesca; Gandolfo, Nicoletta; Houssami, Nehmat; Calabrese, Massimo
Abstract: Purpose: To compare Digital Breast Tomosynthesis (DBT) for cancers and normal screens in women with dense breasts and negative mammography using a Radiomics approach. Materials and Methods: A substudy (N = 40) of the 'Adjunct Screening With Tomosynthesis or Ultrasound in Women With Mammography-Negative Dense Breasts (ASTOUND)' trial was done based on 20 women who had DBT-detected, histology-proven, breast cancer and 20 controls matched for age and density. Using a Radiomics approach normal and pathological breast parenchyma were evaluated, and correlations among Radiomics features and clinical and prognostic parameters were investigated. Results: The median age of the patients was 50 years (range 39–70 years). After Radiomics feature number reduction, 3 of 6 (50%) selected features differed between controls and cancers (Skewness (0.002); Entropy (p.004); 90percentile (p.006)). Three Radiomics features (Energy, Entropy and Dissimilarity) significantly correlated to tumor size (r = −0.15, r = 0.49, r = 0.51), but not with prognostic factors. Entropy correlated with Estrogen Receptor status (r = −0, 46; p.004). Conclusion: Radiomics features in patients with dense breasts and negative mammography appear to differ between cancerous and normal breast tissue, with evidence of correlation with tumor size and estrogen receptors. This new information warrants further evaluation in larger studies and could contribute to improved understanding of breast cancer through imaging, and may support tailored screening and treatments. Highlights: Radiomicsis explored in breast cancer research. Some Radiomics features differes between normal and pathologic breast tissue. Specific Radiomics features correlated with tumor size. One Radiomics feature (Entropy) correlated with Estrogen Receptor. Radiomics could improve our understanding of breast cancer through imaging.