The University of Southampton
University of Southampton Institutional Repository

Using novel computed tomography analysis to describe the contribution and distribution of emphysema and small airways disease in COPD

Using novel computed tomography analysis to describe the contribution and distribution of emphysema and small airways disease in COPD
Using novel computed tomography analysis to describe the contribution and distribution of emphysema and small airways disease in COPD

Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitation, caused by emphysema and small airways disease (SAD). Computed tomography (CT) coupled with image analysis enables the quantification of these abnormalities; however, the optimum method for doing so has not been determined.

Objectives: This study aims to compare two CT quantitative analysis techniques, disease probability measure (DPM) and parametric response mapping (PRM), and assess their relationship with specific physiological measures of SAD.

Methods: Subjects with mild to moderate COPD, never smokers, and healthy ex-smokers were recruited. Each had airway oscillometry and multiple-breath nitrogen washout, measuring peripheral airway resistance, peripheral airway reactance, and acinar airway inhomogeneity. Subjects also had an inspiratory and expiratory chest CT, with DPM and PRM analysis performed by coregistering images and classifying each voxel as normal, emphysema, or nonemphysematous gas trapping related to SAD.

Results: Thirty-eight subjects with COPD, 18 never smokers, and 23 healthy ex-smokers were recruited. There were strong associations between DPM and PRM analysis when measuring gas trapping (ρ = 0.87; P < 0.001) and emphysema (ρ = 0.99; P < 0.001). DPM assigned significantly more voxels as emphysema and gas trapped than PRM (P < 0.001). Both techniques showed significantly greater emphysema and gas trapping in subjects with COPD than in never smokers and ex-smokers (P < 0.001). All CT measures had significant associations with peripheral airway resistance and reactance, with disease probability measure of nonemphysematous gas trapping related to SAD having the strongest independent association with peripheral airway resistance (β = 0.42; P = 0.001) and peripheral airway reactance (β = 0.41; P = 0.001). Emphysema measures had the strongest associations with acinar airway inhomogeneity (β = 0.35–0.38).

Conclusions: These results provide further validation for the use of DPM/PRM analysis in COPD by demonstrating significant relationships with specific physiological measures of SAD.

imaging, Quantitative CT analysis
2329-6933
990-997
Ostridge, Kristoffer
d2271bae-b078-4390-8919-8f8c0e20542c
Gove, Kerry
8f043bbb-080d-49b3-9ee5-046f3a636ee0
Paas, Karlien
1b27f435-780c-47a5-b877-dfdf907a7376
Burke, Hannah
a9bb9391-4704-4584-aeb7-e69fe0acbdb8
Freeman, Anna, Teresa
3d83f907-e7ce-4649-a018-a7a31b19f934
Harden, Stephen
f53e511e-df8b-451f-aa1e-e8e80e1a4e46
Kirby, Miranda
faef6ffa-8e1b-4eb7-bc17-21e16adab8cc
Peterson, Sam
4c7038fb-444b-4390-8680-166cbbad9a2c
Sieren, Jared
2273f4ab-0569-482a-ade4-b20a2f0ed056
McCrae, Chris
ff867925-ff4c-4cd0-bfb5-5e639e66b464
Vaarala, Outi
35ea8119-e804-402c-bb79-cfac625e71f5
Staples, Karl J.
e0e9d80f-0aed-435f-bd75-0c8818491fee
Wilkinson, Tom MA
8c55ebbb-e547-445c-95a1-c8bed02dd652
Ostridge, Kristoffer
d2271bae-b078-4390-8919-8f8c0e20542c
Gove, Kerry
8f043bbb-080d-49b3-9ee5-046f3a636ee0
Paas, Karlien
1b27f435-780c-47a5-b877-dfdf907a7376
Burke, Hannah
a9bb9391-4704-4584-aeb7-e69fe0acbdb8
Freeman, Anna, Teresa
3d83f907-e7ce-4649-a018-a7a31b19f934
Harden, Stephen
f53e511e-df8b-451f-aa1e-e8e80e1a4e46
Kirby, Miranda
faef6ffa-8e1b-4eb7-bc17-21e16adab8cc
Peterson, Sam
4c7038fb-444b-4390-8680-166cbbad9a2c
Sieren, Jared
2273f4ab-0569-482a-ade4-b20a2f0ed056
McCrae, Chris
ff867925-ff4c-4cd0-bfb5-5e639e66b464
Vaarala, Outi
35ea8119-e804-402c-bb79-cfac625e71f5
Staples, Karl J.
e0e9d80f-0aed-435f-bd75-0c8818491fee
Wilkinson, Tom MA
8c55ebbb-e547-445c-95a1-c8bed02dd652

Ostridge, Kristoffer, Gove, Kerry, Paas, Karlien, Burke, Hannah, Freeman, Anna, Teresa, Harden, Stephen, Kirby, Miranda, Peterson, Sam, Sieren, Jared, McCrae, Chris, Vaarala, Outi, Staples, Karl J. and Wilkinson, Tom MA (2019) Using novel computed tomography analysis to describe the contribution and distribution of emphysema and small airways disease in COPD. Annals of the American Thoracic Society, 16 (8), 990-997. (doi:10.1513/AnnalsATS.201810-669OC).

Record type: Article

Abstract

Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitation, caused by emphysema and small airways disease (SAD). Computed tomography (CT) coupled with image analysis enables the quantification of these abnormalities; however, the optimum method for doing so has not been determined.

Objectives: This study aims to compare two CT quantitative analysis techniques, disease probability measure (DPM) and parametric response mapping (PRM), and assess their relationship with specific physiological measures of SAD.

Methods: Subjects with mild to moderate COPD, never smokers, and healthy ex-smokers were recruited. Each had airway oscillometry and multiple-breath nitrogen washout, measuring peripheral airway resistance, peripheral airway reactance, and acinar airway inhomogeneity. Subjects also had an inspiratory and expiratory chest CT, with DPM and PRM analysis performed by coregistering images and classifying each voxel as normal, emphysema, or nonemphysematous gas trapping related to SAD.

Results: Thirty-eight subjects with COPD, 18 never smokers, and 23 healthy ex-smokers were recruited. There were strong associations between DPM and PRM analysis when measuring gas trapping (ρ = 0.87; P < 0.001) and emphysema (ρ = 0.99; P < 0.001). DPM assigned significantly more voxels as emphysema and gas trapped than PRM (P < 0.001). Both techniques showed significantly greater emphysema and gas trapping in subjects with COPD than in never smokers and ex-smokers (P < 0.001). All CT measures had significant associations with peripheral airway resistance and reactance, with disease probability measure of nonemphysematous gas trapping related to SAD having the strongest independent association with peripheral airway resistance (β = 0.42; P = 0.001) and peripheral airway reactance (β = 0.41; P = 0.001). Emphysema measures had the strongest associations with acinar airway inhomogeneity (β = 0.35–0.38).

Conclusions: These results provide further validation for the use of DPM/PRM analysis in COPD by demonstrating significant relationships with specific physiological measures of SAD.

Text
Using Novel CT analysis to describe the contribution and distribution of emphysema and Small Airways Disease in COPD_resubmission whole - Accepted Manuscript
Restricted to Repository staff only until 6 March 2020.
Request a copy

More information

Accepted/In Press date: 6 March 2019
Published date: 1 August 2019
Keywords: imaging, Quantitative CT analysis

Identifiers

Local EPrints ID: 429033
URI: https://eprints.soton.ac.uk/id/eprint/429033
ISSN: 2329-6933
PURE UUID: 8824668d-3575-4ba9-a2bc-1dcda43a5cec
ORCID for Karl J. Staples: ORCID iD orcid.org/0000-0003-3844-6457

Catalogue record

Date deposited: 19 Mar 2019 17:30
Last modified: 13 Nov 2019 01:35

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×