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Quantification of [(11)C]PBR28 data after systemic lipopolysaccharide challenge
BACKGROUND: Lipopolysaccharide (LPS) is a classic immune stimulus. LPS combined with positron emission tomography (PET) 18 kDa translocator protein (TSPO) brain imaging provides a robust human laboratory model to study neuroimmune signaling. To evaluate optimal analysis of these data, this work comp...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067964/ https://www.ncbi.nlm.nih.gov/pubmed/32166497 http://dx.doi.org/10.1186/s13550-020-0605-7 |
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author | Woodcock, Eric A. Schain, Martin Cosgrove, Kelly P. Hillmer, Ansel T. |
author_facet | Woodcock, Eric A. Schain, Martin Cosgrove, Kelly P. Hillmer, Ansel T. |
author_sort | Woodcock, Eric A. |
collection | PubMed |
description | BACKGROUND: Lipopolysaccharide (LPS) is a classic immune stimulus. LPS combined with positron emission tomography (PET) 18 kDa translocator protein (TSPO) brain imaging provides a robust human laboratory model to study neuroimmune signaling. To evaluate optimal analysis of these data, this work compared the sensitivity of six quantification approaches. METHODS: [(11)C]PBR28 data from healthy volunteers (N = 8) were collected before and 3 h after LPS challenge (1.0 ng/kg IV). Quantification approaches included total volume of distribution estimated with two tissue, and two tissue plus irreversible uptake in whole blood, compartment models (2TCM and 2TCM-1k, respectively) and multilinear analysis-1 (MA-1); binding potential estimated with simultaneous estimation (SIME); standardized uptake values (SUV); and SUV ratio (SUVR). RESULTS: The 2TCM, 2TCM-1k, MA-1, and SIME approaches each yielded substantive effect sizes for LPS effects (partial η(2) = 0.56–0.89, ps <. 05), whereas SUV and SUVR did not. CONCLUSION: These findings highlight the importance of incorporating AIF measurements to quantify LPS-TSPO studies. |
format | Online Article Text |
id | pubmed-7067964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-70679642020-03-23 Quantification of [(11)C]PBR28 data after systemic lipopolysaccharide challenge Woodcock, Eric A. Schain, Martin Cosgrove, Kelly P. Hillmer, Ansel T. EJNMMI Res Short Communication BACKGROUND: Lipopolysaccharide (LPS) is a classic immune stimulus. LPS combined with positron emission tomography (PET) 18 kDa translocator protein (TSPO) brain imaging provides a robust human laboratory model to study neuroimmune signaling. To evaluate optimal analysis of these data, this work compared the sensitivity of six quantification approaches. METHODS: [(11)C]PBR28 data from healthy volunteers (N = 8) were collected before and 3 h after LPS challenge (1.0 ng/kg IV). Quantification approaches included total volume of distribution estimated with two tissue, and two tissue plus irreversible uptake in whole blood, compartment models (2TCM and 2TCM-1k, respectively) and multilinear analysis-1 (MA-1); binding potential estimated with simultaneous estimation (SIME); standardized uptake values (SUV); and SUV ratio (SUVR). RESULTS: The 2TCM, 2TCM-1k, MA-1, and SIME approaches each yielded substantive effect sizes for LPS effects (partial η(2) = 0.56–0.89, ps <. 05), whereas SUV and SUVR did not. CONCLUSION: These findings highlight the importance of incorporating AIF measurements to quantify LPS-TSPO studies. Springer Berlin Heidelberg 2020-03-12 /pmc/articles/PMC7067964/ /pubmed/32166497 http://dx.doi.org/10.1186/s13550-020-0605-7 Text en © The Author(s). 2020 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 | Short Communication Woodcock, Eric A. Schain, Martin Cosgrove, Kelly P. Hillmer, Ansel T. Quantification of [(11)C]PBR28 data after systemic lipopolysaccharide challenge |
title | Quantification of [(11)C]PBR28 data after systemic lipopolysaccharide challenge |
title_full | Quantification of [(11)C]PBR28 data after systemic lipopolysaccharide challenge |
title_fullStr | Quantification of [(11)C]PBR28 data after systemic lipopolysaccharide challenge |
title_full_unstemmed | Quantification of [(11)C]PBR28 data after systemic lipopolysaccharide challenge |
title_short | Quantification of [(11)C]PBR28 data after systemic lipopolysaccharide challenge |
title_sort | quantification of [(11)c]pbr28 data after systemic lipopolysaccharide challenge |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7067964/ https://www.ncbi.nlm.nih.gov/pubmed/32166497 http://dx.doi.org/10.1186/s13550-020-0605-7 |
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