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Quantitative analysis of dynamic (18)F-FDG PET/CT for measurement of lung inflammation
BACKGROUND: An inflammatory reaction in the airways and lung parenchyma, comprised mainly of neutrophils and alveolar macrophages, is present in some patients with chronic obstructive pulmonary disease (COPD). Thoracic fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET) has been propos...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445063/ https://www.ncbi.nlm.nih.gov/pubmed/28547129 http://dx.doi.org/10.1186/s13550-017-0291-2 |
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author | Coello, Christopher Fisk, Marie Mohan, Divya Wilson, Frederick J. Brown, Andrew P. Polkey, Michael I. Wilkinson, Ian Tal-Singer, Ruth Murphy, Philip S. Cheriyan, Joseph Gunn, Roger N. |
author_facet | Coello, Christopher Fisk, Marie Mohan, Divya Wilson, Frederick J. Brown, Andrew P. Polkey, Michael I. Wilkinson, Ian Tal-Singer, Ruth Murphy, Philip S. Cheriyan, Joseph Gunn, Roger N. |
author_sort | Coello, Christopher |
collection | PubMed |
description | BACKGROUND: An inflammatory reaction in the airways and lung parenchyma, comprised mainly of neutrophils and alveolar macrophages, is present in some patients with chronic obstructive pulmonary disease (COPD). Thoracic fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET) has been proposed as a promising imaging biomarker to assess this inflammation. We sought to introduce a fully quantitative analysis method and compare this with previously published studies based on the Patlak approach using a dataset comprising (18)F-FDG PET scans from COPD subjects with elevated circulating inflammatory markers (fibrinogen) and matched healthy volunteers (HV). Dynamic (18)F-FDG PET scans were obtained for high-fibrinogen (>2.8 g/l) COPD subjects (N = 10) and never smoking HV (N = 10). Lungs were segmented using co-registered computed tomography images and subregions (upper, middle and lower) were semi-automatically defined. A quantitative analysis approach was developed, which corrects for the presence of air and blood in the lung (qABL method), enabling direct estimation of the metabolic rate of FDG in lung tissue. A normalised Patlak analysis approach was also performed to enable comparison with previously published results. Effect sizes (Hedge’s g) were used to compare HV and COPD groups. RESULTS: The qABL method detected no difference (Hedge’s g = 0.15 [−0.76 1.04]) in the tissue metabolic rate of FDG in the whole lung between HV (μ = 6.0 ± 1.9 × 10(−3) ml cm(−3) min(−1)) and COPD (μ = 5.7 ± 1.7 × 10(−3) ml cm(−3) min(−1)). However, analysis with the normalised Patlak approach detected a significant difference (Hedge’s g = −1.59 [−2.57 −0.48]) in whole lung between HV (μ = 2.9 ± 0.5 × 10(−3) ml cm(−3) min(−1)) and COPD (μ = 3.9 ± 0.7 × 10(−3) ml cm(−3) min(−1)). The normalised Patlak endpoint was shown to be a composite measure influenced by air volume, blood volume and actual uptake of (18)F-FDG in lung tissue. CONCLUSIONS: We have introduced a quantitative analysis method that provides a direct estimate of the metabolic rate of FDG in lung tissue. This work provides further understanding of the underlying origin of the (18)F-FDG signal in the lung in disease groups and helps interpreting changes following standard or novel therapies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13550-017-0291-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5445063 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-54450632017-06-13 Quantitative analysis of dynamic (18)F-FDG PET/CT for measurement of lung inflammation Coello, Christopher Fisk, Marie Mohan, Divya Wilson, Frederick J. Brown, Andrew P. Polkey, Michael I. Wilkinson, Ian Tal-Singer, Ruth Murphy, Philip S. Cheriyan, Joseph Gunn, Roger N. EJNMMI Res Original Research BACKGROUND: An inflammatory reaction in the airways and lung parenchyma, comprised mainly of neutrophils and alveolar macrophages, is present in some patients with chronic obstructive pulmonary disease (COPD). Thoracic fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET) has been proposed as a promising imaging biomarker to assess this inflammation. We sought to introduce a fully quantitative analysis method and compare this with previously published studies based on the Patlak approach using a dataset comprising (18)F-FDG PET scans from COPD subjects with elevated circulating inflammatory markers (fibrinogen) and matched healthy volunteers (HV). Dynamic (18)F-FDG PET scans were obtained for high-fibrinogen (>2.8 g/l) COPD subjects (N = 10) and never smoking HV (N = 10). Lungs were segmented using co-registered computed tomography images and subregions (upper, middle and lower) were semi-automatically defined. A quantitative analysis approach was developed, which corrects for the presence of air and blood in the lung (qABL method), enabling direct estimation of the metabolic rate of FDG in lung tissue. A normalised Patlak analysis approach was also performed to enable comparison with previously published results. Effect sizes (Hedge’s g) were used to compare HV and COPD groups. RESULTS: The qABL method detected no difference (Hedge’s g = 0.15 [−0.76 1.04]) in the tissue metabolic rate of FDG in the whole lung between HV (μ = 6.0 ± 1.9 × 10(−3) ml cm(−3) min(−1)) and COPD (μ = 5.7 ± 1.7 × 10(−3) ml cm(−3) min(−1)). However, analysis with the normalised Patlak approach detected a significant difference (Hedge’s g = −1.59 [−2.57 −0.48]) in whole lung between HV (μ = 2.9 ± 0.5 × 10(−3) ml cm(−3) min(−1)) and COPD (μ = 3.9 ± 0.7 × 10(−3) ml cm(−3) min(−1)). The normalised Patlak endpoint was shown to be a composite measure influenced by air volume, blood volume and actual uptake of (18)F-FDG in lung tissue. CONCLUSIONS: We have introduced a quantitative analysis method that provides a direct estimate of the metabolic rate of FDG in lung tissue. This work provides further understanding of the underlying origin of the (18)F-FDG signal in the lung in disease groups and helps interpreting changes following standard or novel therapies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13550-017-0291-2) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2017-05-25 /pmc/articles/PMC5445063/ /pubmed/28547129 http://dx.doi.org/10.1186/s13550-017-0291-2 Text en © The Author(s). 2017 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 Coello, Christopher Fisk, Marie Mohan, Divya Wilson, Frederick J. Brown, Andrew P. Polkey, Michael I. Wilkinson, Ian Tal-Singer, Ruth Murphy, Philip S. Cheriyan, Joseph Gunn, Roger N. Quantitative analysis of dynamic (18)F-FDG PET/CT for measurement of lung inflammation |
title | Quantitative analysis of dynamic (18)F-FDG PET/CT for measurement of lung inflammation |
title_full | Quantitative analysis of dynamic (18)F-FDG PET/CT for measurement of lung inflammation |
title_fullStr | Quantitative analysis of dynamic (18)F-FDG PET/CT for measurement of lung inflammation |
title_full_unstemmed | Quantitative analysis of dynamic (18)F-FDG PET/CT for measurement of lung inflammation |
title_short | Quantitative analysis of dynamic (18)F-FDG PET/CT for measurement of lung inflammation |
title_sort | quantitative analysis of dynamic (18)f-fdg pet/ct for measurement of lung inflammation |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445063/ https://www.ncbi.nlm.nih.gov/pubmed/28547129 http://dx.doi.org/10.1186/s13550-017-0291-2 |
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