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

BACKGROUND: Full 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) r...

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Autores principales: Rydén, T., Heydorn Lagerlöf, J., Hemmingsson, J., Marin, I., Svensson, J., Båth, M., Gjertsson, P., Bernhardt, P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5754277/
https://www.ncbi.nlm.nih.gov/pubmed/29302810
http://dx.doi.org/10.1186/s40658-017-0201-8
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author Rydén, T.
Heydorn Lagerlöf, J.
Hemmingsson, J.
Marin, I.
Svensson, J.
Båth, M.
Gjertsson, P.
Bernhardt, P.
author_facet Rydén, T.
Heydorn Lagerlöf, J.
Hemmingsson, J.
Marin, I.
Svensson, J.
Båth, M.
Gjertsson, P.
Bernhardt, P.
author_sort Rydén, T.
collection PubMed
description BACKGROUND: Full 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 (128(3) or 256(3)). 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 (177)Lu 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). RESULT: The 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 128(3) 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. CONCLUSION: The GPU-based MC code generated an MC-based SPECT/CT reconstruction within a few minutes, and reconstructed patient images of (177)Lu-DOTATATE treatments revealed clearly improved resolution and contrast.
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spelling pubmed-57542772018-01-22 Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved (177)Lu images Rydén, T. Heydorn Lagerlöf, J. Hemmingsson, J. Marin, I. Svensson, J. Båth, M. Gjertsson, P. Bernhardt, P. EJNMMI Phys Original Research BACKGROUND: Full 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 (128(3) or 256(3)). 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 (177)Lu 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). RESULT: The 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 128(3) 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. CONCLUSION: The GPU-based MC code generated an MC-based SPECT/CT reconstruction within a few minutes, and reconstructed patient images of (177)Lu-DOTATATE treatments revealed clearly improved resolution and contrast. Springer International Publishing 2018-01-04 /pmc/articles/PMC5754277/ /pubmed/29302810 http://dx.doi.org/10.1186/s40658-017-0201-8 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Research
Rydén, T.
Heydorn Lagerlöf, J.
Hemmingsson, J.
Marin, I.
Svensson, J.
Båth, M.
Gjertsson, P.
Bernhardt, P.
Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved (177)Lu images
title Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved (177)Lu images
title_full Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved (177)Lu images
title_fullStr Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved (177)Lu images
title_full_unstemmed Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved (177)Lu images
title_short Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved (177)Lu images
title_sort fast gpu-based monte carlo code for spect/ct reconstructions generates improved (177)lu images
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5754277/
https://www.ncbi.nlm.nih.gov/pubmed/29302810
http://dx.doi.org/10.1186/s40658-017-0201-8
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