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Object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung

Historically, histopathology evaluation is performed by a pathologist generating a qualitative assessment on thin tissue sections on glass slides. In the past decade, there has been a growing interest for tools able to reduce human subjectivity and improve workload. Whole slide scanning technology c...

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Autores principales: Apfeldorfer, Coralie, Ulrich, Kristina, Jones, Gareth, Goodwin, David, Collins, Susie, Schenck, Emanuel, Richard, Virgile
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2500097/
https://www.ncbi.nlm.nih.gov/pubmed/18673504
http://dx.doi.org/10.1186/1746-1596-3-S1-S16
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author Apfeldorfer, Coralie
Ulrich, Kristina
Jones, Gareth
Goodwin, David
Collins, Susie
Schenck, Emanuel
Richard, Virgile
author_facet Apfeldorfer, Coralie
Ulrich, Kristina
Jones, Gareth
Goodwin, David
Collins, Susie
Schenck, Emanuel
Richard, Virgile
author_sort Apfeldorfer, Coralie
collection PubMed
description Historically, histopathology evaluation is performed by a pathologist generating a qualitative assessment on thin tissue sections on glass slides. In the past decade, there has been a growing interest for tools able to reduce human subjectivity and improve workload. Whole slide scanning technology combined with object orientated image analysis can offer the capacity of generating fast and reliable results. In the present study, we combined the use of these emerging technologies to characterise a mouse model for chronic asthma. We monitored the inflammatory changes over five weeks by measuring the number of neutrophils and eosinophils present in the tissue, as well as, the bronchiolar associated lymphoid tissue (BALT) area on whole lungs sections. We showed that inflammation assessment could be automated efficiently and reliably. In comparison to human evaluation performed on the same set of sections, computer generated data was more descriptive and fully quantitative. Moreover optimisation of our detection parameters allowed us to be to more sensitive and to generate data in a larger dynamic range to traditional experimental evaluation, such as bronchiolar lavage (BAL) inflammatory cell counts obtained by flow cytometry. We also took advantage of the fact that we could increase the number of samples to be analysed within a day. Such optimisation allowed us to determine the best study design and experimental conditions in order to increase statistical significance between groups. In conclusion, we showed that combination of whole slide digital scanning and image analysis could be fully automated and deliver more descriptive and biologically relevant data over traditional methods evaluating histopathological pulmonary changes observed in this mouse model of chronic asthma.
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spelling pubmed-25000972008-08-08 Object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung Apfeldorfer, Coralie Ulrich, Kristina Jones, Gareth Goodwin, David Collins, Susie Schenck, Emanuel Richard, Virgile Diagn Pathol Proceedings Historically, histopathology evaluation is performed by a pathologist generating a qualitative assessment on thin tissue sections on glass slides. In the past decade, there has been a growing interest for tools able to reduce human subjectivity and improve workload. Whole slide scanning technology combined with object orientated image analysis can offer the capacity of generating fast and reliable results. In the present study, we combined the use of these emerging technologies to characterise a mouse model for chronic asthma. We monitored the inflammatory changes over five weeks by measuring the number of neutrophils and eosinophils present in the tissue, as well as, the bronchiolar associated lymphoid tissue (BALT) area on whole lungs sections. We showed that inflammation assessment could be automated efficiently and reliably. In comparison to human evaluation performed on the same set of sections, computer generated data was more descriptive and fully quantitative. Moreover optimisation of our detection parameters allowed us to be to more sensitive and to generate data in a larger dynamic range to traditional experimental evaluation, such as bronchiolar lavage (BAL) inflammatory cell counts obtained by flow cytometry. We also took advantage of the fact that we could increase the number of samples to be analysed within a day. Such optimisation allowed us to determine the best study design and experimental conditions in order to increase statistical significance between groups. In conclusion, we showed that combination of whole slide digital scanning and image analysis could be fully automated and deliver more descriptive and biologically relevant data over traditional methods evaluating histopathological pulmonary changes observed in this mouse model of chronic asthma. BioMed Central 2008-07-15 /pmc/articles/PMC2500097/ /pubmed/18673504 http://dx.doi.org/10.1186/1746-1596-3-S1-S16 Text en Copyright © 2008 Apfeldorfer et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Apfeldorfer, Coralie
Ulrich, Kristina
Jones, Gareth
Goodwin, David
Collins, Susie
Schenck, Emanuel
Richard, Virgile
Object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung
title Object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung
title_full Object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung
title_fullStr Object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung
title_full_unstemmed Object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung
title_short Object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung
title_sort object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2500097/
https://www.ncbi.nlm.nih.gov/pubmed/18673504
http://dx.doi.org/10.1186/1746-1596-3-S1-S16
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