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Method to determine the statistical technical variability of SUV metrics

BACKGROUND: The Standardized Uptake Value (SUV) Max, SUVMean, and SUVPeak are metrics used to quantify positron emission tomography (PET) images. In order to assess the significance of a change in these metrics for diagnostic purposes, it is relevant to know their variation. The sources of variation...

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Autores principales: De Luca, Giulia M. R., Habraken, Jan B. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170854/
https://www.ncbi.nlm.nih.gov/pubmed/35666316
http://dx.doi.org/10.1186/s40658-022-00470-2
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author De Luca, Giulia M. R.
Habraken, Jan B. A.
author_facet De Luca, Giulia M. R.
Habraken, Jan B. A.
author_sort De Luca, Giulia M. R.
collection PubMed
description BACKGROUND: The Standardized Uptake Value (SUV) Max, SUVMean, and SUVPeak are metrics used to quantify positron emission tomography (PET) images. In order to assess the significance of a change in these metrics for diagnostic purposes, it is relevant to know their variation. The sources of variation can be biological or technical. In this study, we present a method to determine the statistical technical variation of SUV in PET images. RESULTS: This method was tested on a NEMA quality phantom with spheres of various diameters with a full-length acquisition time of 150 s per bed position and foreground-to-background activity ratio of F(18)-2-fluoro-2-deoxy-d-glucose (FDG) of 10:1. Our method divides the 150 s acquisition into subsets with statistically independent frames of shorter reconstruction length. SUVMax, Mean and Peak were calculated for each reconstructed image in a subset. The coefficient of variation of SUV within each subset has been used to estimate the expected coefficient of variation at 150 s reconstruction length. We report the largest coefficient of variation of the SUV metrics for the smallest sphere and the smallest variation for the largest sphere. The expected variation at 150 s reconstruction length does not exceed 6% for the smallest sphere and 2% for the largest sphere. CONCLUSIONS: With the presented method, we aim to determine the statistical technical variation of SUV. The method enables the evaluation of the effect of SUV metric choice (Max, Mean, Peak) and lesion size on the technical variation and, therefore, to evaluate its relevance on the total variation of the SUV value between clinical studies.
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spelling pubmed-91708542022-06-08 Method to determine the statistical technical variability of SUV metrics De Luca, Giulia M. R. Habraken, Jan B. A. EJNMMI Phys Original Research BACKGROUND: The Standardized Uptake Value (SUV) Max, SUVMean, and SUVPeak are metrics used to quantify positron emission tomography (PET) images. In order to assess the significance of a change in these metrics for diagnostic purposes, it is relevant to know their variation. The sources of variation can be biological or technical. In this study, we present a method to determine the statistical technical variation of SUV in PET images. RESULTS: This method was tested on a NEMA quality phantom with spheres of various diameters with a full-length acquisition time of 150 s per bed position and foreground-to-background activity ratio of F(18)-2-fluoro-2-deoxy-d-glucose (FDG) of 10:1. Our method divides the 150 s acquisition into subsets with statistically independent frames of shorter reconstruction length. SUVMax, Mean and Peak were calculated for each reconstructed image in a subset. The coefficient of variation of SUV within each subset has been used to estimate the expected coefficient of variation at 150 s reconstruction length. We report the largest coefficient of variation of the SUV metrics for the smallest sphere and the smallest variation for the largest sphere. The expected variation at 150 s reconstruction length does not exceed 6% for the smallest sphere and 2% for the largest sphere. CONCLUSIONS: With the presented method, we aim to determine the statistical technical variation of SUV. The method enables the evaluation of the effect of SUV metric choice (Max, Mean, Peak) and lesion size on the technical variation and, therefore, to evaluate its relevance on the total variation of the SUV value between clinical studies. Springer International Publishing 2022-06-06 /pmc/articles/PMC9170854/ /pubmed/35666316 http://dx.doi.org/10.1186/s40658-022-00470-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Research
De Luca, Giulia M. R.
Habraken, Jan B. A.
Method to determine the statistical technical variability of SUV metrics
title Method to determine the statistical technical variability of SUV metrics
title_full Method to determine the statistical technical variability of SUV metrics
title_fullStr Method to determine the statistical technical variability of SUV metrics
title_full_unstemmed Method to determine the statistical technical variability of SUV metrics
title_short Method to determine the statistical technical variability of SUV metrics
title_sort method to determine the statistical technical variability of suv metrics
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170854/
https://www.ncbi.nlm.nih.gov/pubmed/35666316
http://dx.doi.org/10.1186/s40658-022-00470-2
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