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SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool

BACKGROUND: Positron-emission tomography (PET) simulators are frequently used for development and performance evaluation of segmentation methods or quantitative uptake metrics. To date, most PET simulation tools are based on Monte Carlo simulations, which are computationally demanding. Other analyti...

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Autores principales: Pfaehler, Elisabeth, De Jong, Johan R., Dierckx, Rudi A. J. O., van Velden, Floris H. P., Boellaard, Ronald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141406/
https://www.ncbi.nlm.nih.gov/pubmed/30225675
http://dx.doi.org/10.1186/s40658-018-0215-x
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author Pfaehler, Elisabeth
De Jong, Johan R.
Dierckx, Rudi A. J. O.
van Velden, Floris H. P.
Boellaard, Ronald
author_facet Pfaehler, Elisabeth
De Jong, Johan R.
Dierckx, Rudi A. J. O.
van Velden, Floris H. P.
Boellaard, Ronald
author_sort Pfaehler, Elisabeth
collection PubMed
description BACKGROUND: Positron-emission tomography (PET) simulators are frequently used for development and performance evaluation of segmentation methods or quantitative uptake metrics. To date, most PET simulation tools are based on Monte Carlo simulations, which are computationally demanding. Other analytical simulation tools lack the implementation of time of flight (TOF) or resolution modelling (RM). In this study, a fast and easy-to-use PET simulation-reconstruction package, SiMulAtion and ReconsTruction (SMART)-PET, is developed and validated, which includes both TOF and RM. SMART-PET, its documentation and instructions to calibrate the tool to a specific PET/CT system are available on Zenodo. SMART-PET allows the fast generation of 3D PET images. As input, it requires one image representing the activity distribution and one representing the corresponding CT image/attenuation map. It allows the user to adjust different parameters, such as reconstruction settings (TOF/RM), noise level or scan duration. Furthermore, a random spatial shift can be included, representing patient repositioning. To evaluate the tool, simulated images were compared with real scan data of the NEMA NU 2 image quality phantom. The scan was acquired as a 60-min list-mode scan and reconstructed with and without TOF and/or RM. For every reconstruction setting, ten statistically equivalent images, representing 30, 60, 120 and 300 s scan duration, were generated. Simulated and real-scan data were compared regarding coefficient of variation in the phantom background and activity recovery coefficients (RCs) of the spheres. Furthermore, standard deviation images of each of the ten statistically equivalent images were compared. RESULTS: SMART-PET produces images comparable to actual phantom data. The image characteristics of simulated and real PET images varied in similar ways as function of reconstruction protocols and noise levels. The change in image noise with variation of simulated TOF settings followed the theoretically expected behaviour. RC as function of sphere size agreed within 0.3–11% between simulated and actual phantom data. CONCLUSIONS: SMART-PET allows for rapid and easy simulation of PET data. The user can change various acquisition and reconstruction settings (including RM and TOF) and noise levels. The images obtained show similar image characteristics as those seen in actual phantom data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40658-018-0215-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-61414062018-09-28 SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool Pfaehler, Elisabeth De Jong, Johan R. Dierckx, Rudi A. J. O. van Velden, Floris H. P. Boellaard, Ronald EJNMMI Phys Original Research BACKGROUND: Positron-emission tomography (PET) simulators are frequently used for development and performance evaluation of segmentation methods or quantitative uptake metrics. To date, most PET simulation tools are based on Monte Carlo simulations, which are computationally demanding. Other analytical simulation tools lack the implementation of time of flight (TOF) or resolution modelling (RM). In this study, a fast and easy-to-use PET simulation-reconstruction package, SiMulAtion and ReconsTruction (SMART)-PET, is developed and validated, which includes both TOF and RM. SMART-PET, its documentation and instructions to calibrate the tool to a specific PET/CT system are available on Zenodo. SMART-PET allows the fast generation of 3D PET images. As input, it requires one image representing the activity distribution and one representing the corresponding CT image/attenuation map. It allows the user to adjust different parameters, such as reconstruction settings (TOF/RM), noise level or scan duration. Furthermore, a random spatial shift can be included, representing patient repositioning. To evaluate the tool, simulated images were compared with real scan data of the NEMA NU 2 image quality phantom. The scan was acquired as a 60-min list-mode scan and reconstructed with and without TOF and/or RM. For every reconstruction setting, ten statistically equivalent images, representing 30, 60, 120 and 300 s scan duration, were generated. Simulated and real-scan data were compared regarding coefficient of variation in the phantom background and activity recovery coefficients (RCs) of the spheres. Furthermore, standard deviation images of each of the ten statistically equivalent images were compared. RESULTS: SMART-PET produces images comparable to actual phantom data. The image characteristics of simulated and real PET images varied in similar ways as function of reconstruction protocols and noise levels. The change in image noise with variation of simulated TOF settings followed the theoretically expected behaviour. RC as function of sphere size agreed within 0.3–11% between simulated and actual phantom data. CONCLUSIONS: SMART-PET allows for rapid and easy simulation of PET data. The user can change various acquisition and reconstruction settings (including RM and TOF) and noise levels. The images obtained show similar image characteristics as those seen in actual phantom data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40658-018-0215-x) contains supplementary material, which is available to authorized users. Springer International Publishing 2018-09-18 /pmc/articles/PMC6141406/ /pubmed/30225675 http://dx.doi.org/10.1186/s40658-018-0215-x 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
Pfaehler, Elisabeth
De Jong, Johan R.
Dierckx, Rudi A. J. O.
van Velden, Floris H. P.
Boellaard, Ronald
SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool
title SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool
title_full SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool
title_fullStr SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool
title_full_unstemmed SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool
title_short SMART (SiMulAtion and ReconsTruction) PET: an efficient PET simulation-reconstruction tool
title_sort smart (simulation and reconstruction) pet: an efficient pet simulation-reconstruction tool
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141406/
https://www.ncbi.nlm.nih.gov/pubmed/30225675
http://dx.doi.org/10.1186/s40658-018-0215-x
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