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The role of quantitative CT image analysis in understanding COPD

The role of quantitative CT image analysis in understanding COPD
The role of quantitative CT image analysis in understanding COPD
COPD is a heterogeneous disease with multiple clinical phenotypes and biological endotypes and the association between these are poorly understood. Novel quantitative analysis techniques permit objective measurements of pulmonary and extra-pulmonary manifestations of the disease. This thesis examines the role of quantitative CT analysis in exploring COPD, with the aim of showing that these techniques can potentially give important insights into the disease and explore the heterogeneity and underlying biology of the condition.

CT image analysis was performed on two different cohorts of COPD subjects, which included quantification of emphysema, small airways disease and bronchial wall dimensions. Furthermore, novel analysis was also performed to quantify emphysema sub-types and body composition parameters. One of the cohorts was a small cross-sectional study of mild-moderate COPD subjects involving CT imaging and bronchoscopic sampling of the airways. BAL samples were analysed for inflammatory cytokines, white cell differential, matrix-metalloproteinases (MMPs) and microbiology. The other cohort was a larger 2 year longitudinal study of moderate-very severe COPD subjects who had CT imaging at enrolment and at 2 years. They also had careful characterisation with pulmonary function testing, exercise testing, sputum and blood analysis and clinical follow-up.

The findings confirmed that CT image analysis could successfully measure emphysema and small airways disease with both having significant relationships with pulmonary function. Using these measures, I demonstrated a novel relationship between multiple MMPs and CT measured small airways disease, suggesting these proteases play an important role in the small airway remodelling that occurs in COPD. There were also associations between emphysema and MMPs, providing further evidence for their role in parenchymal destruction. In the larger cohort emphysema was independently associated with desaturation on exertion, but neither emphysema nor small airways disease had significant associations with blood or sputum inflammatory markers, sputum bacterial detection or exacerbation rate. On longitudinal analysis, emphysema progressed over a two period, although the causes for this were not apparent in my study. Quantification of airway dimensions were variable and unreliable and did not provide significant information about disease in either of my two cohorts.

The findings from this study suggest that CT image analysis can be used to explore the disease and provides further rationale for future investigation into the use of image analysis in assessing different features of COPD.
University of Southampton
Ostridge, Kristoffer
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Ostridge, Kristoffer
d2271bae-b078-4390-8919-8f8c0e20542c
Wilkinson, Thomas
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Bourne, Simon
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Howarth, Peter
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Ostridge, Kristoffer (2017) The role of quantitative CT image analysis in understanding COPD. University of Southampton, Doctoral Thesis, 335pp.

Record type: Thesis (Doctoral)

Abstract

COPD is a heterogeneous disease with multiple clinical phenotypes and biological endotypes and the association between these are poorly understood. Novel quantitative analysis techniques permit objective measurements of pulmonary and extra-pulmonary manifestations of the disease. This thesis examines the role of quantitative CT analysis in exploring COPD, with the aim of showing that these techniques can potentially give important insights into the disease and explore the heterogeneity and underlying biology of the condition.

CT image analysis was performed on two different cohorts of COPD subjects, which included quantification of emphysema, small airways disease and bronchial wall dimensions. Furthermore, novel analysis was also performed to quantify emphysema sub-types and body composition parameters. One of the cohorts was a small cross-sectional study of mild-moderate COPD subjects involving CT imaging and bronchoscopic sampling of the airways. BAL samples were analysed for inflammatory cytokines, white cell differential, matrix-metalloproteinases (MMPs) and microbiology. The other cohort was a larger 2 year longitudinal study of moderate-very severe COPD subjects who had CT imaging at enrolment and at 2 years. They also had careful characterisation with pulmonary function testing, exercise testing, sputum and blood analysis and clinical follow-up.

The findings confirmed that CT image analysis could successfully measure emphysema and small airways disease with both having significant relationships with pulmonary function. Using these measures, I demonstrated a novel relationship between multiple MMPs and CT measured small airways disease, suggesting these proteases play an important role in the small airway remodelling that occurs in COPD. There were also associations between emphysema and MMPs, providing further evidence for their role in parenchymal destruction. In the larger cohort emphysema was independently associated with desaturation on exertion, but neither emphysema nor small airways disease had significant associations with blood or sputum inflammatory markers, sputum bacterial detection or exacerbation rate. On longitudinal analysis, emphysema progressed over a two period, although the causes for this were not apparent in my study. Quantification of airway dimensions were variable and unreliable and did not provide significant information about disease in either of my two cohorts.

The findings from this study suggest that CT image analysis can be used to explore the disease and provides further rationale for future investigation into the use of image analysis in assessing different features of COPD.

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The Role of Quantitative CT Image Analysis in Understanding COPD Thesis K. Ostridge - Version of Record
Available under License University of Southampton Thesis Licence.
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Submitted date: March 2017

Identifiers

Local EPrints ID: 427142
URI: http://eprints.soton.ac.uk/id/eprint/427142
PURE UUID: 1eb580bb-a0d4-4172-9d72-4d458f621f0f

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Date deposited: 03 Jan 2019 17:30
Last modified: 13 Mar 2019 17:42

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Contributors

Author: Kristoffer Ostridge
Thesis advisor: Thomas Wilkinson
Thesis advisor: Simon Bourne
Thesis advisor: Peter Howarth

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