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Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC)

BACKGROUND: [(18)F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) has been widely used in oncologic procedures such as tumor diagnosis and staging. However, false-positive rates have been high, unacceptable and mainly caused by inflammatory lesions. Misinterpretations take place esp...

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Autores principales: Yang, Zhen, Zan, Yunlong, Zheng, Xiujuan, Hai, Wangxi, Chen, Kewei, Huang, Qiu, Xu, Yuhong, Peng, Jinliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4589399/
https://www.ncbi.nlm.nih.gov/pubmed/26421925
http://dx.doi.org/10.1371/journal.pone.0139089
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author Yang, Zhen
Zan, Yunlong
Zheng, Xiujuan
Hai, Wangxi
Chen, Kewei
Huang, Qiu
Xu, Yuhong
Peng, Jinliang
author_facet Yang, Zhen
Zan, Yunlong
Zheng, Xiujuan
Hai, Wangxi
Chen, Kewei
Huang, Qiu
Xu, Yuhong
Peng, Jinliang
author_sort Yang, Zhen
collection PubMed
description BACKGROUND: [(18)F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) has been widely used in oncologic procedures such as tumor diagnosis and staging. However, false-positive rates have been high, unacceptable and mainly caused by inflammatory lesions. Misinterpretations take place especially when non-subcutaneous inflammations appear at the tumor site, for instance in the lung. The aim of the current study is to evaluate the use of dynamic PET imaging procedure to differentiate in situ and subcutaneous non-small cell lung carcinoma (NSCLC) from inflammation, and estimate the kinetics of inflammations in various locations. METHODS: Dynamic FDG-PET was performed on 33 female mice inoculated with tumor and/or inflammation subcutaneously or inside the lung. Standardized Uptake Values (SUVs) from static imaging (SUVmax) as well as values of influx rate constant (Ki) of compartmental modeling from dynamic imaging were obtained. Static and kinetic data from different lesions (tumor and inflammations) or different locations (subcutaneous, in situ and spontaneous group) were compared. RESULTS: Values of SUVmax showed significant difference in subcutaneous tumor and inflammation (p<0.01), and in inflammations from different locations (p<0.005). However, SUVmax showed no statistical difference between in situ tumor and inflammation (p = 1.0) and among tumors from different locations (subcutaneous and in situ, p = 0.91). Values of Ki calculated from compartmental modeling showed significant difference between tumor and inflammation both subcutaneously (p<0.005) and orthotopically (p<0.01). Ki showed also location specific values for inflammations (subcutaneous, in situ and spontaneous, p<0.015). However, Ki of tumors from different locations (subcutaneous and in situ) showed no significant difference (p = 0.46). CONCLUSION: In contrast to static PET based SUVmax, both subcutaneous and in situ inflammations and malignancies can be differentiated via dynamic FDG-PET based Ki. Moreover, Values of influx rate constant Ki from compartmental modeling can offer an assessment for inflammations at different locations of the body, which also implies further validation is necessary before the replacement of in situ inflammation with its subcutaneous counterpart in animal experiments.
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spelling pubmed-45893992015-10-02 Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC) Yang, Zhen Zan, Yunlong Zheng, Xiujuan Hai, Wangxi Chen, Kewei Huang, Qiu Xu, Yuhong Peng, Jinliang PLoS One Research Article BACKGROUND: [(18)F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) has been widely used in oncologic procedures such as tumor diagnosis and staging. However, false-positive rates have been high, unacceptable and mainly caused by inflammatory lesions. Misinterpretations take place especially when non-subcutaneous inflammations appear at the tumor site, for instance in the lung. The aim of the current study is to evaluate the use of dynamic PET imaging procedure to differentiate in situ and subcutaneous non-small cell lung carcinoma (NSCLC) from inflammation, and estimate the kinetics of inflammations in various locations. METHODS: Dynamic FDG-PET was performed on 33 female mice inoculated with tumor and/or inflammation subcutaneously or inside the lung. Standardized Uptake Values (SUVs) from static imaging (SUVmax) as well as values of influx rate constant (Ki) of compartmental modeling from dynamic imaging were obtained. Static and kinetic data from different lesions (tumor and inflammations) or different locations (subcutaneous, in situ and spontaneous group) were compared. RESULTS: Values of SUVmax showed significant difference in subcutaneous tumor and inflammation (p<0.01), and in inflammations from different locations (p<0.005). However, SUVmax showed no statistical difference between in situ tumor and inflammation (p = 1.0) and among tumors from different locations (subcutaneous and in situ, p = 0.91). Values of Ki calculated from compartmental modeling showed significant difference between tumor and inflammation both subcutaneously (p<0.005) and orthotopically (p<0.01). Ki showed also location specific values for inflammations (subcutaneous, in situ and spontaneous, p<0.015). However, Ki of tumors from different locations (subcutaneous and in situ) showed no significant difference (p = 0.46). CONCLUSION: In contrast to static PET based SUVmax, both subcutaneous and in situ inflammations and malignancies can be differentiated via dynamic FDG-PET based Ki. Moreover, Values of influx rate constant Ki from compartmental modeling can offer an assessment for inflammations at different locations of the body, which also implies further validation is necessary before the replacement of in situ inflammation with its subcutaneous counterpart in animal experiments. Public Library of Science 2015-09-30 /pmc/articles/PMC4589399/ /pubmed/26421925 http://dx.doi.org/10.1371/journal.pone.0139089 Text en © 2015 Yang 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Yang, Zhen
Zan, Yunlong
Zheng, Xiujuan
Hai, Wangxi
Chen, Kewei
Huang, Qiu
Xu, Yuhong
Peng, Jinliang
Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC)
title Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC)
title_full Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC)
title_fullStr Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC)
title_full_unstemmed Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC)
title_short Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC)
title_sort dynamic fdg-pet imaging to differentiate malignancies from inflammation in subcutaneous and in situ mouse model for non-small cell lung carcinoma (nsclc)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4589399/
https://www.ncbi.nlm.nih.gov/pubmed/26421925
http://dx.doi.org/10.1371/journal.pone.0139089
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