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Register a new userMonte Carlo tomographic reconstruction in SPECT impact of bootstrapping and number of generated events
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Z. El Bitar
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In Single Photon Emission Computed Tomography (SPECT), 3D images usually reconstructed by performing a set of bidimensional (2D) analytical or iterative reconstructions can also be reconstructed using an iterative reconstruction algorithm involving a 3D projector. Accurate Monte Carlo (MC) simulations modeling all the physical effects that affect the imaging process can be used to estimate this projector. However, the accuracy of the projector is affected by the stochastic nature of MC simulations. In this paper, we study the accuracy of the reconstructed images with respect to the number of simulated histories used to estimate the MC projector. Furthermore, we study the impact of applying the bootstrapping technique when estimating the projector
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Image reconstruction in Single Photon Emission Computed Tomography (SPECT) is affected by physical effects such as photon attenuation, Compton scatter and detector response. These effects can be compensated for by modeling the corresponding spread of photons in 3D within the system matrix used for tomographic reconstruction. The fully 3D Monte Carlo (F3DMC) reconstruction technique consists in calculating this system matrix using Monte Carlo simulations. The inverse problem of tomographic reconstruction is then solved using conventional iterative algorithms such as maximum likelihood expectation maximization (MLEM). Although F3DMC has already shown promising results, its use is currently limited by two major issues: huge size of the fully 3D system matrix and long computation time required for calculating a robust and accurate system matrix. To address these two issues, we propose to calculate the F3DMC system matrix using a spatial sampling matching the functional regions to be reconstructed. In this approach, different regions of interest can be reconstructed with different spatial sampling. For instance, a single value is reconstructed for a functional region assumed to contain uniform activity. To assess the value of this approach, Monte Carlo simulations have been performed using GATE. Results suggest that F3DMC reconstruction using functional regions improves quantitative accuracy compared to the F3DMC reconstruction method proposed so far. In addition, it considerably reduces disk space requirement and duration of the simulations needed to estimate the system matrix. The concept of functional regions might therefore make F3DMC reconstruction practically feasible.
Monte Carlo algorithms have a growing impact on nuclear medicine reconstruction processes. One of the main limitations of myocardial perfusion imaging (MPI) is the effective mitigation of the scattering component, which is particularly challenging in Single Photon Emission Computed Tomography (SPECT). In SPECT, no timing information can be retrieved to locate the primary source photons. Monte Carlo methods allow an event-by-event simulation of the scattering kinematics, which can be incorporated into a model of the imaging system response. This approach was adopted since the late Nineties by several authors, and recently took advantage of the increased computational power made available by high-performance CPUs and GPUs. These recent developments enable a fast image reconstruction with an improved image quality, compared to deterministic approaches. Deterministic approaches are based on energy-windowing of the detector response, and on the cumulative estimate and subtraction of the scattering component. In this paper, we review the main strategies and algorithms to correct for the scattering effect in SPECT and focus on Monte Carlo developments, which nowadays allow the three-dimensional reconstruction of SPECT cardiac images in a few seconds.
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