Using MARS Spectral CT for Identifying Biomedical Nanoparticles
Thesis DisciplineMedical Physics
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosphy
The goal of this research is to contribute to the development of MARS spectral CT and to demonstrate the feasibility of molecular imaging using the technology. MARS is a newly developed micro CT scanner, incorporating the latest spectroscopic Medipix photon counting detector. I show that the scanner can identify both drug markers and stenosis of atherosclerosis labelled with non-toxic nanoparticles. I also show that spectral computed tomography using Medipix x-ray detectors can give quantitative measurements of concentrations of gold nanoparticles in phantoms, mice and excised atheroma. The characterisation of the Medipix2 assemblies with Si and CdTe x-ray sensors using poly-energetic x-ray sources has been performed. I measure the inhomogeneities within the sensors; individual pixel sensitivity response; and their saturation effects at higher photon fluxes. The effects of charge sharing on the performance of Medipix2 have been assessed, showing that it compromises energy resolution much more than spatial resolution. I have commissioned several MARS scanners incorporating several different Medipix2 and Medipix3 cameras. After the characterization of x-ray detectors and the geometrical assessment of MARS-CT, spectral CT data has been acquired, using x-ray energies that are appropriate for human imaging. The outcome shows that MARS scanner has the ability to discriminate among low atomic number materials, and from various concentrations of heavy atoms. This new imaging modality, used with functionalized gold nanoparticles, gives a new tool to assess plaque vulnerability. I demonstrated this by using gold nanoparticles, attached to antibodies, which targeted to thrombotic events in excised plaque. Likewise, the imaging modality can be used to track drugs labelled with any heavy atoms to assess how much drug gets into a target organ. Thus the methodology could be used to accelerate development of new drug treatments for cancers and inflammatory diseases.