DCE-MRI Pharmacokinetic-Based Phenotyping of Invasive Ductal Carcinoma: A Radiomic Study for Prediction of Histological Outcomes

Breast cancer is a disease afecting an increasing number of women worldwide. Several eforts have been made in the last years to identify imaging biomarker and to develop noninvasive diagnostic tools for breast tumor characterization and monitoring, which could help in patients’ stratifcation, outcome prediction, and treatment personalization. In particular, radiomic approaches have paved the way to the study of the cancer imaging phenotypes. In this work, a group of 49 patients with diagnosis of invasive ductal carcinoma was studied. The purpose of this study was to select radiomic features extracted from a DCE-MRI pharmacokinetic protocol, including quantitative maps of Ktrans, Kep, Ve, iAUC, and 1R of molecular receptor status (ER+/ER−, PR+/PR−, and HER2+/HER2−), triple negative (TN)/non-triple negative (NTN), ki67 levels, and tumor grade. A total of 163 features were obtained and, after feature set reduction step, followed by feature selection and prediction performance estimations, the predictive model coefcients were computed for each classifcation task. The AUC values obtained were 0.826 ± 0.006 for ER+/ER−, 0.875 ± 0.009 for PR+/PR−, 0.838 ± 0.006 for HER2+/HER2−, 0.876 ± 0.007 for TN/NTN, 0.811 ± 0.005 for ki67+/ki67−, and 0.895 ± 0.006 for lowGrade/highGrade. In conclusion, DCE-MRI pharmacokineticbased phenotyping shows promising for discrimination of the histological outcomes.