Qualitative and quantitative image-based biomarkers of therapeutic response in triple-negative breast cancer. AMIA Summits on Translational Science proceedings AMIA Summit on Translational Science Golden, D. I., Lipson, J. A., Telli, M. L., Ford, J. M., Rubin, D. L. 2013; 2013: 62-?


Experimental targeted treatments for neoadjuvant chemotherapy for triple-negative breast cancer are currently underway, and a current challenge is predicting which patients will respond to these therapies. In this study, we use data from dynamic contrast-enhanced MRI (DCE-MRI) images to predict whether patients with triple negative breast cancer will respond to an experimental neoadjuvant chemotherapy regimen. Using pre-therapy image-based features that are both qualitative (e.g., morphological BI-RADS categories) and quantitative (e.g., lesion texture), we built a model that was able to predict whether patients will have residual invasive cancer with lymph nodes metastases following therapy (receiver operating characteristic area under the curve of 0.83, sensitivity=0.73, specificity=0.83). This model's performance is at a level that is potentially clinically valuable for predicting which patients may or may not benefit from similar treatments in the future.

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