Tumors that are oxygen-starved (hypoxic) and exhibit cycling hypoxia (where regions within a tumor fluctuate between normoxic and hypoxic levels) have been shown to be resistant to treatment. While knowledge of the hypoxic status of tumors could inform an improved therapeutic course, quantitative assessment of hypoxia (both static and cycling) via in vivo imaging is difficult. Electron paramagnetic resonance imaging (EPRI) has been shown to provide direct quantification of tissue oxygenation (pO2) in small animals. EPRI is advantageous in being low cost and highly specific to image tumor oxygenation. While both chronic and intermittent hypoxia can be visualized within solid tumors using existing techniques, the spatial and temporal resolution is currently sub-optimal. The technical aim of this project is to develop new image acquisition strategies for EPRI to improve spatial resolution and reconstructed image framerate. Key to the implementation of these ideas will be the incorporation of radial data sampling techniques. These techniques, when combined with iterative image reconstruction, have been shown to provide good results for dynamic imaging in spite of relaxed data sampling requirements, thus providing significant acceleration compared to previous techniques. These new methods will enable improved spatial and temporal resolution and allow novel insights into study of the tumor microenvironment with a pharmcokinetic assessment of hypoxic tumors that is currently not possible with any other imaging technique. These improvements will be demonstrated in dynamic imaging of SCCVII solid tumors implanted in the legs of mice by using accelerated EPR imaging to characterize chronic and intermittent hypoxia in response to breathing different gas mixtures.
Knowledge of oxygen-starved (hypoxic) regions of tumors, which are known to be treatment-resistant, could suggest the selection of optimal therapy, however, quantitative assessments of hypoxia are difficult to obtain non-invasively. Quantification of tissue oxygenation (pO2) with dynamic imaging is possible with electron paramagnetic resonance imaging (EPRI), and this developing modality has been successfully demonstrated in in vivo. Unfortunately, current EPRI techniques are limited in spatial and temporal resolution;thus, this proposal will develop methods to allow substantial improvements in EPR imaging, which has the promise to become a low cost and highly specific modality to spatially and temporally characterize tumor hypoxia.
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