3D Oxygenation Imaging of Bone Marrow Using X-ray Luminescence Micro-CT
 

Imaging oxygenation distribution at high spatial resolution in deep tissues, such as bone marrow, is essential for understanding its role in stem cell proliferation and differentiation. Current techniques are limited by low resolution when imaging deep targets. This dissertation focuses on improving XLCT imaging and its applications in imaging the oxygenation concentrations of deep tissues.
   At first, the XLCT imaging system was improved to include the capability of measurements at multiple wavelengths, through which it is possible to sense the oxygenation concentration by measuring the emission optical photons at two different wavelengths.
   Secondly, the XLCT imaging was improved by introducing a new reconstruction algorithm, weighted sinogram based filtered back projection (wsFBP). With this new reconstruction algorithm, we can perform XLCT imaging quantitatively and straightforwardly. Furthermore, the sensitivity of XLCT imaging system was studied to investigate how to obtain the XLCT imaging of targets with very low concentrations.
   Lastly, two oxygenation biosensors, 𝑌_2 𝑂_2 𝑆:𝑇𝑏_𝑃𝑡𝑇𝐹𝑃𝑃 and 〖𝐿𝑢〗_2 〖𝑆𝑖𝑂〗_5:𝐶𝑒_𝑃𝑡𝑇𝐹𝑃𝑃 were developed and applied for oxygenation imaging by measuring the emitted optical photons at two different wavelengths. It was found that the ratio of the emission intensity at the two wavelengths (600 nm and 650 nm) is the indicator of the oxygenation concentrations. We have performed both phantom and ex vivo experiments to verify this approach. Our results have demonstrated that XLCT with the oxygenation biosensors is able to achieve the 3D oxygenation concentration images at a high spatial resolution up to 150 µm for targets at depths up to 1.2 cm, representing the first application of XLCT for visualizing oxygen concentration changes in deep tissues.

Yibing Zhang obtained her Master's degree in Electrical Engineering at the University of South Carolina. Currently, she is a Ph.D. candidate in the Department of Bioengineering at the University of California, Merced, working under the supervision of Prof. Changqing Li. Her dissertation focuses on the X-ray Luminescence Computed Tomography (XLCT) imaging system.