Implementation of angular response function modeling in SPECT simulations with GATE

Descourt, Patrice; Carlier, Thomas; Du, Yong; Song, Xiyun; Buvat, Irène; Frey, Eric; Bardiès, Manuel; Tsui, B.M.W.; Visvikis, Dimitris

doi:10.1088/0031-9155/55/9/n04

Cited by 23 publications

(23 citation statements)

References 19 publications

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“…Our collimator-detector response model includes both attenuation correction and variable polar and azimuthal angle septal penetrations—which are important for high energetic photons such as the 364 keV photons emitted from 131 I. However, accurate ARF requires a substantial simulation of all parameter values, which are not always easily implemented in the simulations, e.g., the commonly used energy resolution model might not be useful for high-energy photons and the complex structure of the backscattering components makes the simulation challenging [ 36 , 37 ]. Despite the complexity of simulating ARF correctly, the polar and azimuthal angular-dependent ARF are important for high energetic photons, and it would be valuable to further study their impact on simulation times and image quality, which can be performed effectively by using the fast simulation performance of SARec.…”

Section: Discussionmentioning

confidence: 99%

Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177Lu images

et al. 2018

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BackgroundFull Monte Carlo (MC)-based SPECT reconstructions have a strong potential for correcting for image degrading factors, but the reconstruction times are long. The objective of this study was to develop a highly parallel Monte Carlo code for fast, ordered subset expectation maximum (OSEM) reconstructions of SPECT/CT images. The MC code was written in the Compute Unified Device Architecture language for a computer with four graphics processing units (GPUs) (GeForce GTX Titan X, Nvidia, USA). This enabled simulations of parallel photon emissions from the voxels matrix (1283 or 2563). Each computed tomography (CT) number was converted to attenuation coefficients for photo absorption, coherent scattering, and incoherent scattering. For photon scattering, the deflection angle was determined by the differential scattering cross sections. An angular response function was developed and used to model the accepted angles for photon interaction with the crystal, and a detector scattering kernel was used for modeling the photon scattering in the detector. Predefined energy and spatial resolution kernels for the crystal were used. The MC code was implemented in the OSEM reconstruction of clinical and phantom 177Lu SPECT/CT images. The Jaszczak image quality phantom was used to evaluate the performance of the MC reconstruction in comparison with attenuated corrected (AC) OSEM reconstructions and attenuated corrected OSEM reconstructions with resolution recovery corrections (RRC).ResultThe performance of the MC code was 3200 million photons/s. The required number of photons emitted per voxel to obtain a sufficiently low noise level in the simulated image was 200 for a 1283 voxel matrix. With this number of emitted photons/voxel, the MC-based OSEM reconstruction with ten subsets was performed within 20 s/iteration. The images converged after around six iterations. Therefore, the reconstruction time was around 3 min. The activity recovery for the spheres in the Jaszczak phantom was clearly improved with MC-based OSEM reconstruction, e.g., the activity recovery was 88% for the largest sphere, while it was 66% for AC-OSEM and 79% for RRC-OSEM.ConclusionThe GPU-based MC code generated an MC-based SPECT/CT reconstruction within a few minutes, and reconstructed patient images of 177Lu-DOTATATE treatments revealed clearly improved resolution and contrast.

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Section: Discussionmentioning

confidence: 99%

Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177Lu images

et al. 2018

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“…Over the years, the features of the platform have been enhanced and new versions of the software have been regularly released, to incorporate well-validated upgrades and to stay consistent with regular GEANT4 public releases. Compared to the functionalities of the platform described in the initial paper of the OpenGATE collaboration (Jan et al 2004), the major enhancements consist of additional options for speeding up simulations (Taschereau and Chatziioannou 2008, Rehfeld et al 2009, Descourt et al 2010, facilities to use GATE for dose calculations in internal dosimetry (Visvikis et al 2006a, Taschereau and Chatziioannou 2007, Thiam et al 2008, Grevillot et al 2010b, and inclusion of optical physics models for accurate modelling of the detector response (van Der Laan et al 2010). All these developments have been incorporated in the new GATE V6 release presented here, but are not described in this paper as they have been explained in the articles listed above.…”

Section: Introductionmentioning

confidence: 99%

GATE V6: a major enhancement of the GATE simulation platform enabling modelling of CT and radiotherapy

Benoit²,

et al. 2011

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GATE (Geant4 Application for Emission Tomography) is a Monte Carlo simulation platform developed by the OpenGATE collaboration since 2001 and first publicly released in 2004. Dedicated to the modelling of planar scintigraphy, single photon emission computed tomography (SPECT) and positron emission tomography (PET) acquisitions, this platform is widely used to assist PET and SPECT research. A recent extension of this platform, released by the OpenGATE collaboration as GATE V6, now also enables modelling of x-ray computed tomography and radiation therapy experiments. This paper presents an overview of the main additions and improvements implemented in GATE since the publication of the initial GATE paper (Jan et al 2004 Phys. Med. Biol. 49 4543-61). This includes new models available in GATE to simulate optical and hadronic processes, novelties in modelling tracer, organ or detector motion, new options for speeding up GATE simulations, examples illustrating the use of GATE V6 in radiotherapy applications and CT simulations, and preliminary results regarding the validation of GATE V6 for radiation therapy applications. Upon completion of extensive validation studies, GATE is expected to become a valuable tool for simulations involving both radiotherapy and imaging.

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“…In this work, we only considered iterative reconstruction and all simulations were performed within the GATE (Geant4 Application in Emission Tomography) platform (Jan et al 2004(Jan et al , 2011). The fictitious interaction tracking algorithm (Rehfeld et al 2009) was used to speed up the MC computation, as well as the angular response function option (Descourt et al 2010) for the SPECT simulations.…”

Section: Methodsmentioning

confidence: 99%

Monte Carlo simulations of clinical PET and SPECT scans: impact of the input data on the simulated images

Stute¹,

Carlier²,

Cristina³

et al. 2011

Phys. Med. Biol.

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Monte Carlo simulations of emission tomography have proven useful to assist detector design and optimize acquisition and processing protocols. The more realistic the simulations, the more straightforward the extrapolation of conclusions to clinical situations. In emission tomography, accurate numerical models of tomographs have been described and well validated under specific operating conditions (collimator, radionuclide, acquisition parameters, count rates, etc). When using these models under these operating conditions, the realism of simulations mostly depends on the activity distribution used as an input for the simulations. It has been proposed to derive the input activity distribution directly from reconstructed clinical images, so as to properly model the heterogeneity of the activity distribution between and within organs. However, reconstructed patient images include noise and have limited spatial resolution. In this study, we analyse the properties of the simulated images as a function of the properties of the reconstructed images used to define the input activity distributions in (18)F-FDG PET and (131)I SPECT simulations. The propagation through the simulation/reconstruction process of the noise and spatial resolution in the input activity distribution was studied using simulations. We found that the noise properties of the images reconstructed from the simulated data were almost independent of the noise in the input activity distribution. The spatial resolution in the images reconstructed from the simulations was slightly poorer than that in the input activity distribution. However, using high-noise but high-resolution patient images as an input activity distribution yielded reconstructed images that could not be distinguished from clinical images. These findings were confirmed by simulated highly realistic (131)I SPECT and (18)F-FDG PET images from patient data. In conclusion, we demonstrated that (131)I SPECT and (18)F-FDG PET images indistinguishable from real scans can be simulated using activity maps with spatial resolution higher than that used in routine clinical applications.

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Implementation of angular response function modeling in SPECT simulations with GATE

Cited by 23 publications

References 19 publications

Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177Lu images

Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177Lu images

GATE V6: a major enhancement of the GATE simulation platform enabling modelling of CT and radiotherapy

Monte Carlo simulations of clinical PET and SPECT scans: impact of the input data on the simulated images

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