Computerized Textural Analysis Of Dce-Mri To Enable Identification Of Her2-Enriched Breast Cancers.

598Background: HER2+ breast cancer is biologically and clinically heterogeneous. PAM50 profiling of HER2+ breast cancer reliably identifies the HER2-Enriched (HER2-E) subtype as most responsive to HER2-targeted antibody therapy (trastuzumab). As this subtype is currently only identifiable using molecular profiling of breast tumor tissue, a non-invasive HER2-E identification method could reduce future patient morbidity. We present initial findings involving a new computational imaging feature (CIF) that captures the disorder among pixel level gradient directions on dynamic contrast-enhanced (DCE) MRI. We show that this CIF is able to discriminate between HER2-E and other HER2+ breast cancer subtypes on DCE-MRI. Methods: 25 baseline DCE-MRI HER2+ breast cancer cases were split into two cohorts by PAM50-confirmed subtype (10 HER2-E, 15 non-HER2-E). 13 CIFs were computed on peak contrast image within expert-annotated lesions. This feature set was narrowed down to the 8 most differentially expressed features. ...