Research On Key Technologies Of PET/DOT Hybrid Imaging

Positron emission tomography (PET) and diffuse optical tomography (DOT) are quantitative functional medical imaging modalities. The former employs radio isotope labeled tracers and track their distribution and concentration in living tissues to get information about physiological metabolisms; the later utilizes the transmitting band of tissue to near infrared light to get optical parameter’s distribution image and oxygen saturation.Hybrid imaging is thoroughly researched all over the world recently. Different imaging modalities are combined to supply more information for research and clinical applications. Among them, the system of PET and DOT can be easily corporated, PET image with high resolution can be adopted as a priory information for DOT image reconstruction; moreover, the images of the two modalities are complementary in some cases, and can also validate each other in certain applications. This paper workes on the two modalities and tries to combine them. The main content and contributions of this paper are as followed.System construction and experiments:1. Construct planar PET system which is proper for hybrid imaging. BGO crystal is employed with flat panel position sensitive photo multiplier tube to construct the gamma ray detection unit. Initial tests are held, including point source test, line source test and mouse experiments.2. Develop high speed coincidence detection and data acquisition unit basing on FPGA and fiber communication modules. The system is designed with circle shaped protocol, which can be easily corporate with new units.3. For the purpose of hybrid imaging, use Hamamatsu TRS system to get time domain signals measured from self made solid phantoms, transform the data into frequency domain for reconstruction.Reconstruction algorithms:4. The consumption that the system probability matrix is exactly known in most statistical PET image reconstruction algorithms are not true and may influence the quality of reconstructed images. We propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts. Finely reconstructed images can be used as a priory information for DOT image reconstruction.5. Employ element free Galerkin method (EFG, one of mesh free methods) to simulate photon transport process in tissues, discretize imaging domain with a set of nodes, avoid the burdensome mesh generation and adjusting work in finite element method (FEM) and the node set can be easily adjusted. The forward calculation results are validated with Green’s function.6. Basing on mesh free representation of imaging domain, employ self-adopted sparse node set as reconstruction basis for DOT image reconstruction. The state space reconstruction formulas are given. Self-adopted algorithm promises the reconstruction quality and calculation consumption proper for contemporary computer servers. Compare FEM and EFG method in calculation consumption and image quality aspects, give advices on the choice of numerical methods in future applications.