We report our investigation of system designs and 3D reconstruction for a dedicated brain-imaging SPECT system using multiple square or square and hexagonal detector modules. The system employs shuttering to vary which of multiple pinhole apertures are enabled to pass photons through to irradiate the detectors. Both multiplexed and nonmultiplexed irradiation by the pinholes are investigated. Sampling is assessed by simulated imaging of a uniform activity concentration in a spherical tub filling the VOI and a tailored Defrise phantom consisting of a series of activity containing slabs aligned axially. Potential image quality for clinical imaging is assessed through simulated imaging of an XCAT brain phantom with an activity distribution simulating perfusion imaging.
KEYWORDS: Monte Carlo methods, Systems modeling, Single photon emission computed tomography, Reconstruction algorithms, Data acquisition, Data modeling, Computer simulations
We introduce a generic analytic simulation and image reconstruction software platform for multi-pinhole (MPH) SPECT systems. The platform is capable of modeling common or sophisticated MPH designs as well as complex data acquisition schemes. Graphics processing unit (GPU) acceleration was utilized to make a high-performance computing software. Herein, we describe the software platform and provide verification studies of the simulation and image reconstruction software.
The use of accurate system response modeling has been proven to be an essential key of SPECT image reconstruction, with its usage leading to overall improvement of image quality. The aim of this work was to investigate the imaging performance using an XCAT brain perfusion phantom of two modeling strategies, one based on analytic techniques and the other one based on GATE Monte-Carlo simulation. In addition, an efficient forced detection approach to improve the overall simulation efficiency was implemented and its performance was evaluated. We demonstrated that accurate modeling of the system matrix generated by Monte-Carlo simulation for iterative reconstruction leads to superior performance compared to analytic modeling in the case of clinical 123I brain imaging. It was also shown that the use of the forced detection approach provided a quantitative and qualitative enhancement of the reconstruction.
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