Improved differentiation of BI-RADS 4 breast lesions based on ultrafast dynamic contrast-enhanced MRI radiomics and artificial neural network

Improving the assessment of Breast Imaging Reporting and Data System (BI-RADS) 4 lesions can avoid unnecessary biopsies. As an emerging field, radiomics has been successfully explored as a means to aid decision-making for the diagnosis and risk stratification of several kinds of cancers1-4. In this study, we combined radiomics features extracted from ultrafast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) (using the Differential sub-sampling with cartesian ordering (DISCO) technique) with an artificial neural network (ANN) to improve diagnostic performance in assessing BI-RADS 4 lesions and evaluate the potential to avoid unnecessary biopsies.