Investigation of cellular microenvironments and heterogeneity with biodynamic imaging

Imaging of biological tissue in a relevant environment is critical to accurately assessing the effectiveness of chemotherapeutic agents in combatting cancer. Though many three-dimensional (3D) culture models exist, conventional in vitro assays continue to use two-dimensional (2D) cultures because of the difficulty in imaging through deep tissue. 3D tomographic imaging techniques exist and are being used in the development of 3D efficacy assays. However, most of these assays look at therapy endpoint (dead or living cancer cell count) and do not capture the dynamics of tissue response. Biodynamic imaging (BDI) is a 3D tomographic imaging and assay technique that uses the dynamics of scattered coherent light, or speckle, to measure dynamic response of tissue to perturbations. Dynamic measurements allow BDI to not only assess overall efficacy, but to also measure phenotypic changes in cancer tissue as it responds to therapy. Because BDI captures the phenotypic response of tissue, it naturally accounts for genetic and microenvironmental factors, and shows promise as an accurate predictor of in vivo chemotherapeutic response. This thesis presents the development of BDI into a predictive assay for assisting in chemotherapy selection. It shows how microenvironmental factors alter BDI response measurements. It reports how different BDI biomarkers can accurately assess sensitivity to platinum treatment in xenograpft models of ovarian cancer. Changes in sensitivity during metastasis are observed, and a method for addressing sample variability and heterogeneity is presented. A predictive model for chemotherapeutic selection is developed and applied retrospectively to primary esophageal cancer. Finally, a new imaging modality called tissue dynamic spectroscopic imaging (TDSI) is presented, which is capable of directly assessing spatial functional patterns in patient samples