Breast cancer is the utmost frequent cancer amid women. The efficiency of cancer treatments on tumor development is carried out using a most sensitive method dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Neoadjuvant chemotherapy (NAC) treatment is widely used in patients for early prediction of breast cancer. The development of extraction of high throughput of features is referred to radiomics. The purpose of this study is to determine the capability of radiomic features in the breast region respond to the treatment. Radiomic analysis was performed on 20 studies of 10 patients using DCE-MRI. A total of 94 three-dimensional radiomic features were extracted and examined statistically. Results explain that the five features 90 and 99 percentile of histogram intensity, mean 3D, variance 3D, and short-run emphasis are significant with p-value from 0.0025 to 0.0694. Hence, these radiomic features are potency to identify the ambivert changes in the breast region during the follow-ups. © 2021, Springer Nature Singapore Pte Ltd.