Monte Carlo tomographic reconstruction in SPECT impact of bootstrapping and number of generated events

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 projectorComment: 15 pages, 9 figures, 2 table

Effect of noise and modeling errors on the reliability of fully 3D Monte Carlo reconstruction in SPECT

We recently demonstrated the value of reconstructing SPECT data with fully 3D Monte Carlo reconstruction (F3DMC), in terms of spatial resolution and quantification. This was shown on a small cubic phantom (64 projections 10 x 10) in some idealistic configurations. The goals of the present study were to assess the effect of noise and modeling errors on the reliability of F3DMC, to propose and evaluate strategies for reducing the noise in the projector, and to demonstrate the feasibility of F3DMC for a dataset with realistic dimensions. A small cubic phantom and a realistic Jaszczak phantom dataset were considered. Projections and projectors for both phantoms were calculated using the Monte Carlo simulation code GATE. Projectors with different statistics were considered and two methods for reducing noise in the projector were investigated: one based on principal component analysis (PCA) and the other consisting in setting small probability values to zero. Energy and spatial shifts in projection sampling with respect to projector sampling were also introduced to test F3DMC in realistic conditions. Experiments with the cubic phantom showed the importance of using simulations with high statistics for calculating the projector, and the value of filtering the projector using a PCA approach. F3DMC was shown to be robust with respect to energy shift and small spatial sampling off-set between the projector and the projections. Images of the Jaszczak phantom were successfully reconstructed and also showed promising results in terms of spatial resolution recovery and quantitative accuracy in small structures. It is concluded that the promising results of F3DMC hold on realistic data set

Execution of the SimSET Monte Carlo PET/SPECT Simulator in the Condor Distributed Computing Environment

SimSET is a package for simulation of emission tomography data sets. Condor is a popular distributed computing environment. Simple C/C++ applications and shell scripts are presented which allow the execution of SimSET on the Condor environment. This is accomplished without any modification to SimSET by executing multiple instances and using its combinebin utility. This enables research facilities without dedicated parallel computing systems to utilize the idle cycles of desktop workstations to greatly reduce the run times of their SimSET simulations. The necessary steps to implement this approach in other environments are presented along with sample results

Reconstruction tri-dimensionnelle complete d'images en spect-ct par modelisation Monte-Carlo

présenté par Z. El Bitar, proceedings sous forme de CDEn tomographie d'émission monophotonique (SPECT), les images 3D normalement reconstruites par des algorithmes de reconstruction analytiques ou itératives bidimensionnelles (2D) pourraient aussi bien être reconstruites avec des algorithmes de reconstruction itérative (3D) qui permettent de compenser les effets physiques perturbant le processus de formation de l'image notamment l'atténuation et la diffusion. Nous avons étudié une technique de reconstruction 3D complète (F3DMC) (Lazaro et al. NIM 2004), dans laquelle le projecteur 3D impliqué dans la reconstruction est estimé par des simulations Monte-Carlo effectuées à partir de données tomodensitométriques du patient

Targeted fully 3D Monte Carlo reconstruction in SPECT

PCSV, présenté par Z. El Bitar, soumis aux proceedingsFully 3D Monte-Carlo (F3DMC) reconstruction consists in calculating a fully 3D object-specific system matrix using Monte-Carlo simulations and inverting it using an iterative approach. To reduce the large amount of disk space required by this approach, we derived a targeted F3DMC approach (TF3DMC) in which the volume to be reconstructed is irregularly sampled, so that pre-identified functional regions of interest are reconstructed using fine sampling while regions with non-specific activity or without any particular interest are coarsely sampled. This method was assessed using simulated and real SPECT data of a phantom filled with Tc99m. The GATE Monte-Carlo simulator was considered to simulate the phantom data and to calculate the system matrices needed for the reconstruction of the simulated and of the real SPECT data. Activity ratios measured in TF3DMC images were compared with those measured on F3DMC and OSEM images corrected for scatter, attenuation and detector response function. TF3DLMC yielded errors less than 10% in activity ratio estimates in hot regions, while errors with quantitative OSEM were between -21% and -3%. The space needed to store the system matrix was divided by a factor from 3.5 to 9.4 compared to F3DMC, for similar or even better accuracy in activity ratio estimates. These results suggest that TF3DMC can be made practical and outperforms F3DMC and OSEM in terms of quantitative accuracy

Validation of the GATE Monte Carlo simulation platform for modelling a CsI(Tl) scintillation camera dedicated to small animal imaging

Monte Carlo simulations are increasingly used in scintigraphic imaging to model imaging systems and to develop and assess tomographic reconstruction algorithms and correction methods for improved image quantitation. GATE (GEANT 4 Application for Tomographic Emission) is a new Monte Carlo simulation platform based on GEANT4 dedicated to nuclear imaging applications. This paper describes the GATE simulation of a prototype of scintillation camera dedicated to small animal imaging and consisting of a CsI(Tl) crystal array coupled to a position sensitive photomultiplier tube. The relevance of GATE to model the camera prototype was assessed by comparing simulated 99mTc point spread functions, energy spectra, sensitivities, scatter fractions and image of a capillary phantom with the corresponding experimental measurements. Results showed an excellent agreement between simulated and experimental data: experimental spatial resolutions were predicted with an error less than 100 mu m. The difference between experimental and simulated system sensitivities for different source-to-collimator distances was within 2%. Simulated and experimental scatter fractions in a [98-182 keV] energy window differed by less than 2% for sources located in water. Simulated and experimental energy spectra agreed very well between 40 and 180 keV. These results demonstrate the ability and flexibility of GATE for simulating original detector designs. The main weakness of GATE concerns the long computation time it requires: this issue is currently under investigation by the GEANT4 and the GATE collaboration

Monte Carlo Simulation With The GATE Software Using Grid Computing

DémonstrationInternational audienceMonte Carlo simulations needing many replicates to obtain good statistical results can be easily executed in parallel using the "Multiple Replications In Parallel" approach. However, several precautions have to be taken in the generation of the parallel streams of pseudo-random numbers. In this paper, we present the distribution of Monte Carlo simulations performed with the GATE software using local clusters and grid computing. We obtained very convincing results with this large medical application, thanks to the EGEE Grid (Enabling Grid for E-sciencE), achieving in one week computations that could have taken more than 3 years of processing on a single computer. This work has been achieved thanks to a generic object-oriented toolbox called DistMe which we designed to automate this kind of parallelization for Monte Carlo simulations. This toolbox, written in Java is freely available on SourceForge and helped to ensure a rigorous distribution of pseudo-random number streams. It is based on the use of a documented XML format for random numbers generators statuses

Spectral factor analysis for multi-isotope imaging in nuclear medicine

Abstract. In nuclear medicine, simultaneous dual-isotope imaging is used to determine the distribution of two radiotracers from a single acquisition and for emission/transmission (E/T) imaging in SPECT. However, no general solution to the cross-talk problem caused by scattered and unscattered photons has been found yet and accurate quantification cannot be performed. We describe a general method of spectral factor analysis (SFA) for multi-isotope acquisitions. SFA corrects for cross-talk due to unscattered and scattered photons in planar or SPECT imaging involving two or more radiotracers and for E/T scans. A Tc-99m/I-123 phantom study shows that quantitative accuracy is within 10% with SFA, while errors up to 170% are observed using conventional spectral windows