Biomarkers from in vivo molecular imaging of breast cancer: pretreatment (18)F-FDG PET predicts patient prognosis, and pretreatment DWI-MR predicts response to neoadjuvant chemotherapy

OBJECTIVE: Human cancers display intra-tumor phenotypic heterogeneity and recent research has focused on developing image processing methods extracting imaging descriptors to characterize this heterogeneity. This work assesses the role of pretreatment (18)F-FDG PET and DWI-MR with respect to the prognosis and prediction of neoadjuvant chemotherapy (NAC) outcomes when image features are used to characterize primitive lesions from breast cancer (BC). MATERIALS AND METHODS: A retrospective protocol included 38 adult women with biopsy-proven BC. Patients underwent a pre-therapy (18)F-FDG PET/CT whole-body study and a pre-therapy breast multi-parametric MR study. Patients were then referred for NAC treatment and then for surgical resection, with an evaluation of the therapy response. Segmentation methods were developed in order to identify functional volumes both on (18)F-FDG PET images and ADC maps. Macroscopic and histogram features were extracted from the defined functional volumes. RESULTS: Our work demonstrates that macroscopic and histogram features from (18)F-FDG PET are able to biologically characterize primitive BC, and define the prognosis. In addition, histogram features from ADC maps are able to predict the response to NAC. CONCLUSION: Our work suggests that pre-treatment (18)F-FDG PET and pre-treatment DWI-MR provide useful complementary information for biological characterization and NAC response prediction in BC.