Cancer Treatment and Response to Therapy

We are developing approaches to integrate structural and functional information from multimodality images, including longitudinal data, that could be used to assess and guide personalized cancer treatment. We are also characterizing intra-tumor heterogeneity via imaging as a biomarker for evaluating therapy response and risk for recurrence. Our study was amongst the first to show that intrinsic imaging phenotypes for breast cancer tumors correlate to gene expression profiling. More recently, we have extended this work to lung cancer, where we are evaluating the integration of CT radiomic features with liquid biopsy data to characterize lung tumor heterogeneity for predicting response to targeted therapy and immunotherapy for lung cancer.

In addition, we are looking into the effect of preventative interventions for high-risk women, such as chemoprevention and lifestyle interventions that can effectively reduce the risk of developing breast cancer. Imaging biomarkers in this setting can be used to quantify the effect of treatment, assess the effectiveness of drugs in development, and identify targets for new therapeutic agents.