Breast cancer disorders are leading cause of morbidity and mortality worldwide. Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is the most common method of assessing the response to chemotherapy in breast cancer treatment monitoring. Radiomic features obtained from MR images have potential in reflecting the tumor biology. In this work, an attempt has been made to investigate the clinical potential of breast DCE-MRI derived radiomic features and its response to Neoadjuvant Chemotherapy (NAC). The data used in this study (10 Patients with 20 studies (Visit-1 Visit-2) were obtained from public domain Quantitative Imaging Network (QIN) Breast DCE-MRI database. Using Mazda software, the radiomic features were extracted from whole breast region to quantify the pathological variations during visit-1 and visit-2. Totally, 176 texture and shape features were extracted and analyzed statistically using student's t test. Result shows that, the radiomic features were able to differentiate the variations in the tumor biology during visit-1 and visit-2 due to NAC. The features such as GeoW2, GeoW3, GeoW4, GeoRs, GeoRc, GeoRm, 50 percentile of histogram intensity and Theta1 were found to be statistically significant with p values ranging from 0.03 to 0.08. Hence it appears that, the radiomic features could be used as adjunct measure in reflecting the pathological response during NAC and thus this study seems to be clinically significant. © 2019 IEEE.