Title: “Diffuse and Nonlinear Imaging for in vivo Monitoring of Tumor Structure and Function”
Darren Roblyer, PhD – BME (Advisor)
Hadi Nia, PhD – BME (Chair)
Muhammad Zaman, PhD – BME
Thomas Bifano, PhD – ME
David Waxman, PhD – Biology
Diffuse Optical Imaging (DOI) technologies provide metabolic and hemodynamic information in tissue in a label-free manner using non-harmful near infrared light. Recently, DOI techniques have received significant interest as a non-invasive functional imaging tool for monitoring patient response to cancer therapies in the clinic. A number of reports have demonstrated that DOI can determine response within hours to weeks from the start of treatment. Despite these promising results, the potential impact, and ultimately adoption of DOI for cancer therapy monitoring in the clinic is limited in part by the lack of knowledge of the cellular, molecular, and biological origins of these clinical observations. Knowledge of the biological underpinnings of DOI response markers is likely to provide clinically relevant insights that can be used to manage and personalize cancer treatment strategies. To this end, the work presented in this dissertation was focused on developing methodology and instrumentation for a novel preclinical imaging technique called Diffuse and Nonlinear Imaging (DNI). DNI combines functional measurements of tumors obtained by wide-field DOI with the underlying tumor biology captured with intravital Multiphoton Microscopy (MPM). Specifically, DNI combines MPM with the DOI technique Spatial Frequency Domain Imaging (SFDI) to provide multiscale datasets of tumor microvascular architecture coregistered within wide-field hemodynamic maps. A procedure was developed to image small animal tumor models with high x-y spatial coregistration accuracy and precision between SFDI and MPM, along with a novel method to match the imaging depths of both modalities by utilizing informed SFDI spatial frequency selection. A preliminary in vivo DNI study of murine mammary tumors revealed multiscale relationships between tumor oxygen saturation and microvessel diameter, and tumor oxygen saturation and microvessel length. Based on these encouraging results, an integrated DNI instrument was then designed and fabricated to acquire tumor vascular structure and function datasets in an inherently spatially coregistered manner from a single system, while simultaneously increasing the sampling resolution of functional spatial heterogeneity. Finally, a small longitudinal study was conducted with the DNI system, demonstrating multiscale relationships between tumor vascular structure and function over space and time, with differences in tumor models and treatment regimens presented. In summary, the work described in this dissertation resulted in a new method to investigate the relationships between clinically translational DOI hemodynamic markers and MPM metrics of vascular architecture. Ultimately, this work will help to pave a path towards DOI for personalized and precision medicine to significantly impact and inform adaptive therapy strategies tailored to the in vivo state of each patient’s tumor.