title: Qualitative and quantitative image-based biomarkers of therapeutic response in triple-negative breast cancer.
abstract: 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.
authors.affiliation: Department of Radiology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, CA 94305, USA.
authors.forename: Daniel I
authors.initials: DI
authors.lastname: Golden
authors.forename: Jafi A
authors.initials: JA
authors.lastname: Lipson
authors.forename: Melinda L
authors.initials: ML
authors.lastname: Telli
authors.forename: James M
authors.initials: JM
authors.lastname: Ford
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Rubin