This project advances the use of two novel technologies to image tissue in experimental cancer models and in patients, and will test hypothesis that these can be used to image tissue biophysical parameters, photosensitizer concentration and blood flow in tumors. The central theme in this project is that optical spectroscopy can be used in vivo to accurately measure bulk tissue values, but must be used in a way, which is image-guided. Image-guided spectroscopy utilizes transmission or remission measurements for their superior signal to noise in measuring molecular concentration in vivo, yet also allows integration of the measurement into existing medical imaging technologies, such as magnetic resonance imaging (MRI), high frequency ultrasound (HFUS), and optical coherence tomography (OCT).
Aim 1 utilizes a commercial prototype system for combined MRI-NIR tomography of experimental rodent models, to study the biophysical changes in hemoglobin, oxygen saturation, water and sub-cellular granularity which can be assessed by NIR tomography. The changes in response to chemotherapy and receptor signaling can be measured by longitudinal imaging studies using this new imaging system. The pancreas cancer model will also be used to validate the imaging, by systematic and quantitative comparison to ex vivo measurements.
In Aim 2, the ability to combine fluorescence optical tomography with structural imaging systems such as OCT and HFUS will be tested, as a way to quantify the photosensitizer concentrations in skin. These unique hybrid systems will be validated in phantoms and tissue cultures, and then used to study skin cancer tumors in vivo. Finally Aim 3 will advance the concept of using photosensitizer imaging as a way to individualize dosimetry treatment planning, using the systems described above. The uptake rate in the tissue can be quantified using image-guided absorbance imaging. This work will also involve modeling of the parenchyma versus vascular partitioning of the drug in a pancreas tumor model, to aid in the related studies of clinical pancreas cancer PDT. The project will translate key developments to Core C, for eventual distribution to other projects, and will use software tools developed in the core. The project uses microscopy analysis and knowledge from Core B to analyze the histology sections, to validate the in vivo imaging with ex vivo quantitative pathology. The project uses common tumor models from the other projects and Core B, and also leverages considerable imaging resources from ongoing work in tools for optical imaging, Potential benefit to public health: this project provides new tools for basic PDT dosimetry and translated into clinical PDT dosimetry thus enhancing treatment outcomes.
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