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Variability in quantitative analysis of atherosclerotic plaque inflammation using (18)F-FDG PET/CT
BACKGROUND: (18)F-FDG-PET(/CT) is increasingly used in studies aiming at quantifying atherosclerotic plaque inflammation. Considerable methodological variability exists. The effect of data acquisition and image analysis parameters on quantitative uptake measures, such as standardized uptake value (S...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5553940/ https://www.ncbi.nlm.nih.gov/pubmed/28800625 http://dx.doi.org/10.1371/journal.pone.0181847 |
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author | Lensen, Karel-Jan D. F. van Sijl, Alper M. Voskuyl, Alexandre E. van der Laken, Conny J. Heymans, Martijn W. Comans, Emile F. I. Nurmohamed, Mike T. Smulders, Yvo M. Boellaard, Ronald |
author_facet | Lensen, Karel-Jan D. F. van Sijl, Alper M. Voskuyl, Alexandre E. van der Laken, Conny J. Heymans, Martijn W. Comans, Emile F. I. Nurmohamed, Mike T. Smulders, Yvo M. Boellaard, Ronald |
author_sort | Lensen, Karel-Jan D. F. |
collection | PubMed |
description | BACKGROUND: (18)F-FDG-PET(/CT) is increasingly used in studies aiming at quantifying atherosclerotic plaque inflammation. Considerable methodological variability exists. The effect of data acquisition and image analysis parameters on quantitative uptake measures, such as standardized uptake value (SUV) and target-to-background ratio (TBR) has not been investigated extensively. OBJECTIVE: The goal of this study was to explore the effect of several data acquisition and image analysis parameters on quantification of vascular wall (18)F-FDG uptake measures, in order to increase awareness of potential variability. METHODS: Three whole-body emission scans and a low-dose CT scan were acquired 38, 60 and 90 minutes after injection of (18)F-FDG in six rheumatoid arthritis patients with high cardiovascular risk profiles.Data acquisition (1 and 2) and image analysis (3, 4 and 5) parameters comprised:1. (18)F-FDG uptake time, 2. SUV normalisation, 3. drawing regions/volumes of interest (ROI’s/VOI’s) according to: a. hot-spot (HS), b. whole-segment (WS) and c. most-diseased segment (MDS), 4. Background activity, 5. Image matrix/voxel size.Intraclass correlation coefficients (ICC’s) and Bland Altman plots were used to assess agreement between these techniques and between observers. A linear mixed model was used to determine the association between uptake time and continuous outcome variables. RESULTS: 1. Significantly higher TBRmax values were found at 90 minutes (1,57 95%CI 1,35–1,80) compared to 38 minutes (1,30 95%CI 1,21–1,39) (P = 0,024) 2. Normalising SUV for BW, LBM and BSA significantly influences average SUVmax (2,25 (±0,60) vs 1,67 (±0,37) vs 0,058 (±0,013)). 3. Intraclass correlation coefficients were high in all vascular segments when SUVmax HS was compared to SUVmax WS. SUVmax HS was consistently higher than SUVmax MDS in all vascular segments. 4. Blood pool activity significantly decreases in all (venous and arterial) segments over time, but does not differ between segments. 5. Image matrix/voxel size does not influence SUVmax. CONCLUSION: Quantitative measures of vascular wall (18)F-FDG uptake are affected mainly by changes in data acquisition parameters. Standardization of methodology needs to be considered when studying atherosclerosis and/or vasculitis. |
format | Online Article Text |
id | pubmed-5553940 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-55539402017-08-25 Variability in quantitative analysis of atherosclerotic plaque inflammation using (18)F-FDG PET/CT Lensen, Karel-Jan D. F. van Sijl, Alper M. Voskuyl, Alexandre E. van der Laken, Conny J. Heymans, Martijn W. Comans, Emile F. I. Nurmohamed, Mike T. Smulders, Yvo M. Boellaard, Ronald PLoS One Research Article BACKGROUND: (18)F-FDG-PET(/CT) is increasingly used in studies aiming at quantifying atherosclerotic plaque inflammation. Considerable methodological variability exists. The effect of data acquisition and image analysis parameters on quantitative uptake measures, such as standardized uptake value (SUV) and target-to-background ratio (TBR) has not been investigated extensively. OBJECTIVE: The goal of this study was to explore the effect of several data acquisition and image analysis parameters on quantification of vascular wall (18)F-FDG uptake measures, in order to increase awareness of potential variability. METHODS: Three whole-body emission scans and a low-dose CT scan were acquired 38, 60 and 90 minutes after injection of (18)F-FDG in six rheumatoid arthritis patients with high cardiovascular risk profiles.Data acquisition (1 and 2) and image analysis (3, 4 and 5) parameters comprised:1. (18)F-FDG uptake time, 2. SUV normalisation, 3. drawing regions/volumes of interest (ROI’s/VOI’s) according to: a. hot-spot (HS), b. whole-segment (WS) and c. most-diseased segment (MDS), 4. Background activity, 5. Image matrix/voxel size.Intraclass correlation coefficients (ICC’s) and Bland Altman plots were used to assess agreement between these techniques and between observers. A linear mixed model was used to determine the association between uptake time and continuous outcome variables. RESULTS: 1. Significantly higher TBRmax values were found at 90 minutes (1,57 95%CI 1,35–1,80) compared to 38 minutes (1,30 95%CI 1,21–1,39) (P = 0,024) 2. Normalising SUV for BW, LBM and BSA significantly influences average SUVmax (2,25 (±0,60) vs 1,67 (±0,37) vs 0,058 (±0,013)). 3. Intraclass correlation coefficients were high in all vascular segments when SUVmax HS was compared to SUVmax WS. SUVmax HS was consistently higher than SUVmax MDS in all vascular segments. 4. Blood pool activity significantly decreases in all (venous and arterial) segments over time, but does not differ between segments. 5. Image matrix/voxel size does not influence SUVmax. CONCLUSION: Quantitative measures of vascular wall (18)F-FDG uptake are affected mainly by changes in data acquisition parameters. Standardization of methodology needs to be considered when studying atherosclerosis and/or vasculitis. Public Library of Science 2017-08-11 /pmc/articles/PMC5553940/ /pubmed/28800625 http://dx.doi.org/10.1371/journal.pone.0181847 Text en © 2017 Lensen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lensen, Karel-Jan D. F. van Sijl, Alper M. Voskuyl, Alexandre E. van der Laken, Conny J. Heymans, Martijn W. Comans, Emile F. I. Nurmohamed, Mike T. Smulders, Yvo M. Boellaard, Ronald Variability in quantitative analysis of atherosclerotic plaque inflammation using (18)F-FDG PET/CT |
title | Variability in quantitative analysis of atherosclerotic plaque inflammation using (18)F-FDG PET/CT |
title_full | Variability in quantitative analysis of atherosclerotic plaque inflammation using (18)F-FDG PET/CT |
title_fullStr | Variability in quantitative analysis of atherosclerotic plaque inflammation using (18)F-FDG PET/CT |
title_full_unstemmed | Variability in quantitative analysis of atherosclerotic plaque inflammation using (18)F-FDG PET/CT |
title_short | Variability in quantitative analysis of atherosclerotic plaque inflammation using (18)F-FDG PET/CT |
title_sort | variability in quantitative analysis of atherosclerotic plaque inflammation using (18)f-fdg pet/ct |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5553940/ https://www.ncbi.nlm.nih.gov/pubmed/28800625 http://dx.doi.org/10.1371/journal.pone.0181847 |
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