Skip to main content

Main menu

  • Home
  • Current issue
  • Early View
  • Archive
  • Authors/reviewers
    • Instructions for authors
    • Submit a manuscript
    • COVID-19 submission information
    • Institutional open access agreements
    • Peer reviewer login
  • Alerts
  • Subscriptions
  • ERS Publications
    • European Respiratory Journal
    • ERJ Open Research
    • European Respiratory Review
    • Breathe
    • ERS Books
    • ERS publications home

User menu

  • Log in
  • Subscribe
  • Contact Us
  • My Cart

Search

  • Advanced search
  • ERS Publications
    • European Respiratory Journal
    • ERJ Open Research
    • European Respiratory Review
    • Breathe
    • ERS Books
    • ERS publications home

Login

European Respiratory Society

Advanced Search

  • Home
  • Current issue
  • Early View
  • Archive
  • Authors/reviewers
    • Instructions for authors
    • Submit a manuscript
    • COVID-19 submission information
    • Institutional open access agreements
    • Peer reviewer login
  • Alerts
  • Subscriptions

Small airway imaging phenotypes in biomass- and tobacco smoke-exposed patients with COPD

Lalita Fernandes, Nandani Gulati, Yasmin Fernandes, Anthony Menezes Mesquita, Mahesh Sardessai, Jan-Willem J. Lammers, Firdaus A. Mohamed Hoesein, Nick H.T. ten Hacken, Maarten van den Berge, Craig J. Galbán, Salman Siddiqui
ERJ Open Research 2017 3: 00124-2016; DOI: 10.1183/23120541.00124-2016
Lalita Fernandes
1Dept of Pulmonary Medicine, Goa Medical College, Goa, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Lalita Fernandes
Nandani Gulati
1Dept of Pulmonary Medicine, Goa Medical College, Goa, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yasmin Fernandes
2Dept of Radiology, Goa Medical College, Goa, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Anthony Menezes Mesquita
1Dept of Pulmonary Medicine, Goa Medical College, Goa, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mahesh Sardessai
2Dept of Radiology, Goa Medical College, Goa, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jan-Willem J. Lammers
3University Medical Center Utrecht, Dept of Pulmonary Diseases, Utrecht, The Netherlands
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Firdaus A. Mohamed Hoesein
4University Medical Center Utrecht, Dept of Radiology, Utrecht, The Netherlands
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nick H.T. ten Hacken
5University of Groningen, University Medical Center Groningen, Dept of Pulmonary Disease, Groningen, The Netherlands
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Maarten van den Berge
5University of Groningen, University Medical Center Groningen, Dept of Pulmonary Disease, Groningen, The Netherlands
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Craig J. Galbán
6Dept of Radiology, Center for Molecular Imaging, University of Michigan, Ann Arbor, MI, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Salman Siddiqui
7University of Leicester/NIHR Respiratory Biomedical Research Unit, Leicester, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: ss338@le.ac.uk
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Biomass and functional small airway disease http://ow.ly/gXu730abpKu

To the Editor:

Chronic obstructive pulmonary disease (COPD) is currently the third most common cause of death, worldwide [1]. Tobacco smoke (TS) is the main risk factor for COPD in developed countries, but biomass smoke (BMS) exposure is the leading cause in developing countries, particularly in women [2].

Early studies evaluating BMS-induced changes in the lung parenchyma used high-resolution computed tomography (CT), which demonstrated thickening of the interlobular septae, fibrotic bands, ground glass appearance and emphysema. These findings suggest that BMS exposure is associated with pathological disease in the small airways of lung [3], and support the notion of pathological damage to the small airways in patients with BMS-exposed COPD.

Recent advances in image processing now allow accurate image registration approaches that provide functional information about the small airways [4]. Parametric response mapping (PRM) is an imaging tool that has been shown to individually quantify small airways disease and emphysema in COPD [5]. This is achieved through the spatial alignment of CT images acquired at functional residual capacity (FRC) and total lung capacity (TLC) followed by classification of individual voxels.

We aimed to determine the degree of emphysematous, functional small airway and non-emphysematous airflow obstruction from a cohort of BMS- and TS-exposed female COPD patients with matched levels of spirometric airflow limitation. We hypothesised that BMS-exposed patients would demonstrate a distinct profile of small airways disease when compared to TS exposed patients.

We performed a prospective observational study based in the respiratory hospital outpatient clinic of Goa Medical College, Goa, India. The study was approved by the institutional ethics committee (IEC/CR/GMC/2012/024), and all subjects gave informed consent. A total of 57 patients aged ≥40 years, with stable COPD, were enrolled between November 2012 and April 2014. From this cohort, all 17 BMS-exposed female COPD patients were included in the study, and 2 were excluded for failed image registration. As most Indian women are exposed to BMS and the prevalence of smoking among women is low, we did not have women with exclusive TS-associated COPD. Accordingly, a comparator group of TS-exposed women (N=20) was evaluated, taken from the TI Pharma cohort [6] from a secondary care COPD population in the Netherlands. The comparator group was matched to the Goa cohort for age, sex, post-bronchodilator forced expiratory volume in 1 s % predicted (FEV1 % pred) and FEV1/forced vital capacity (FVC).

COPD was diagnosed according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines [7]. All patients underwent detailed COPD characterisation. Spirometry was performed according to American Thoracic Society (ATS)/European Respiratory Society (ERS) 2005 guidelines [8]. Exposures were evaluated using the Burden of Obstructive Lung Disease (BOLD) Core and BOLD biomass and fuel questionnaires [9]. Exposure to BMS was reported in hour-years, which are the product of the average number of hours the patient has spent cooking daily and the number of years of cooking using biomass fuel. The cumulative exposure to TS was quantified as pack-years.

Computed tomography of the lung was performed using a Somatom Definition AS multi-detector CT (MDCT) (Siemens Healthcare GmbH, Erlangen, Germany). We used a low-dose radiation protocol, with 140 kVp tube voltage and with the milli-amperes (mA) tube current set according to body mass index.

The lung was scanned in the supine position from apex to base in deep inspiration (total lung capacity) and expiration (functional residual capacity). For the TI Pharma cohort, CT scans were performed using a 64-multidetector scanner (Somatom Definition, Siemens, Forchheim, Germany). Scans were performed at full inspiration and expiration (near residual volume). Scanning was performed with 20 mA·s. The kV setting was adjusted to weight. Acquired imaging data were reconstructed using a standard soft kernel (B30f), with 1.0 mm slice thickness and 0.7 mm increment.

PRM is a unique quantitative assessment method for investigating COPD that, when applied to paired CT images, allows quantification of emphysema and functional small airway disease. This analysis was performed using Lung Density Analysis software (Imbio, Minneapolis, MN, USA). There are three fundamental steps: inspiratory and expiratory image acquisition, image processing (which involves lung parenchyma segmentation and co-registration of inspiratory and expiratory scans) and classification of voxels in terms of Hounsfield values (HU), where green represents normal lung parenchyma [PRMNormal], yellow is functional small airway disease [PRMfSAD] and red is emphysema [PRMEmph]. Voxels of lungs with inspiration and expiration CT attenuation less than −950 HU and −856 HU, respectively, were defined as emphysema, voxels greater than −950 HU on inspiration, but less than −865 HU on expiration are areas of gas trapping due to functional small airway disease, and voxels with inspiration and expiration greater than −950 HU and −856 HU, respectively, were classified as normal parenchyma.

Variables were expressed as mean and standard deviation or median and interquartile range. Mann–Whitney U-test, t-tests and linear regression were applied. Statistical analysis was performed using the statistical software package SPSS 23 (IBM Corp., Armonk, NY, USA).

Clinical and spirometry data were well matched: mean±sd age 60.60±5.28 and 64.20±7.97 years, post-bronchodilator FEV1 61.42±27.02% and 62.33±20.27%, and FEV1/FVC 48.35±14.92 and 55.86±12.49, in the TS- and BMS-exposed populations, respectively.

Figure 1 depicts typical PRM classification images in representative BMS-exposed and TS-exposed patients with GOLD stage 3 COPD.

FIGURE 1
  • Download figure
  • Open in new tab
  • Download powerpoint
FIGURE 1

Composite PRM image (PRM∑) in two exemplar patients with tobacco smoke (TS) exposure and chronic obstructive pulmonary disease (COPD) (top left) and biomass smoke (BMS) exposure and COPD (bottom left). The colours in the two-dimensional image (top and bottom left) and three-dimensional image reconstructions (left to right) represent PRMNormal (normal healthy and deforming lung voxels; green), PRMfSAD (functional small airways disease voxels; yellow) and PRMEmph (emphysema voxels; red).

PRM analysis of CT images demonstrated that COPD patients with BMS exposure had similar healthy lung voxels (49.95±14.11%) when compared to TS-exposed patients (43.50±13.5%), p=0.185. In addition, both TS- and BMS-exposed patients had similar levels of PRMfSAD (33.41±8.33% versus 39.43±12.95%, p=0.11).

In contrast, TS-exposed patients had significantly more emphysema (i.e. PRMEmph) than BMS-exposed patients; median 9.85% (2.40–16.34%) compared to 1.84% (0.69±3.72%) (p=0.001).

Stepwise linear regression identified that PRMEmph (model R2=0.607, β= −0.79; p=0.001) and PRMfSAD (model R2=0.461, β= −0.70; p=0.003) were significant independent predictors of post bronchodilator FEV1/FVC in TS- and BMS-exposed COPD patients, respectively.

We have identified, for the first time, that BMS-exposed COPD patients have a distinct pattern of small airway disease characterised by functional small airways disease in the absence of significant emphysema. Our results support and extend the findings of previous reports. Specifically, Camp et al. [10] have demonstrated significant gas trapping in BMS-exposed COPD (via qualitative assessment) and significant emphysema in TS-exposed COPD (via quantitative assessment). This latter report demonstrated, in two female cohorts, that BMS exposure was preferentially associated with CT low-attenuation areas and gas trapping, in contrast to TS exposure, which was associated with emphysema in a cohort of Mexican women. In contrast, we identified functional small airways disease using image registration and PRM in both BMS- and TS-exposed females within our Indian cohort. Our observations may suggest that the PRM imaging approach, which allows the differentiation of voxels associated with gas trapping and low CT attenuation due to emphysema and small airways dysfunction, is more specific for small airways disease than the approach in the Camp et al. paper [10]. Further validation of this concept comes from the observation that emphysema, which does not require image registration for quantification, was associated only with TS exposure in both our cohorts.

Our observations suggest that the nature of small airways disease in COPD may be related to specific prototypes of environmental/extrinsic exposures. In addition, our report suggests that spirometric airflow obstruction may be differentially regulated by functional small airways disease and emphysema in BMS- and TS-exposed patients, respectively.

Our report has a number of limitations, including the small sample size and ethnicity imbalance in the two exposure groups. Due to the low prevalence of female smokers without BMS exposure in rural Indian female communities, we identified a comparator population of Caucasians with TS-exposed COPD in the Netherlands. Furthermore the impact of using FRC and near residual volume expiratory imaging in the Goa and T1 Pharma cohorts, respectively, may have introduced bias into the imaging quantification. Additionally, it is possible that differences in diet, lifestyle and environmental exposure between the two study cohorts may have been attributable for some of the observed differences in quantitative PRM imaging features.

Nonetheless, we have shown for the first time that BMS-exposed COPD patients have a distinct pattern of small airways disease when compared to TS-exposed patients. These observations now need to be validated in larger population studies.

Disclosures

Supplementary Material

Galban 00124-2016_Galban

Siddiqui 00124-2016_Siddiqui

van den Berge 00124-2016_van_den_Berge

Acknowledgements

L. Fernandes developed the study protocol, performed statistical analysis, interpreted data and wrote the manuscript. N. Gulati undertook patient recruitment, co-supervised CT acquisition, performed statistical analysis and interpreted data. Y. Fernandes supervised CT acquisition and assisted with quantitative CT standardisation. A.M. Mesquita co-developed the protocol, co-wrote the manuscript and acted as scientific advisor. M. Sardessai co-developed the protocol and acted as scientific advisor. J-W.J. Lammers critically reviewed the manuscript and provided a scientific critique of the data. F.A. Mohamed Hoesein provided PRM data and CT scans from female patients in the Netherlands cohort, critically reviewed the manuscript and provided a scientific critique of the data. N.H.T. ten Hacken critically reviewed the manuscript and provided a scientific critique of the data. M. van den Berge provided PRM data and CT scans from female patients in the Netherlands cohort, critically reviewed the manuscript and provided a scientific critique of the data. C.J. Galbán developed the PRM algorithm, analysed CT images using the PRM approach and provided a scientific critique of the data. S. Siddiqui helped L. Fernandes prepare the manuscript, influenced the study design (addition of the Groningen cohort), analysed the data with L. Fernandes and provided a scientific critique of the data. All authors read and approved the final manuscript.

Footnotes

  • Support statement: This study was supported by the Dept of Pulmonary Medicine, Goa Medical College, India, and by the National Institute for Health Research (NIHR) Leicester Respiratory Biomedical Research Unit. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR or the Dept of Health. The cohort from the Netherlands was supported by Top Institute Pharma project T1-108 “Acute and chronic inflammatory responses – COPD and smoking”, with partners University Medical Center Groningen, University of Groningen, GRIAC Research Institute Groningen, University Medical Center Utrecht, Nycomed BV, GlaxoSmithKline and Foundation TI Pharma. Funding information for this article has been deposited with the Crossref Funder Registry.

  • Conflict of interest: Disclosures can be found alongside this article at openres.ersjournals.com

  • Received November 14, 2016.
  • Accepted February 19, 2017.
  • Copyright ©ERS 2017

This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0.

References

  1. ↵
    1. Lozano R,
    2. Naghavi M,
    3. Foreman K, et al.
    Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380: 2095–2128.
    OpenUrlCrossRefPubMed
  2. ↵
    1. Pérez-Padilla R,
    2. Regalado J,
    3. Vedal S, et al.
    Exposure to biomass smoke and chronic airway disease in Mexican women. A case-control study. Am J Respir Crit Care Med 1996; 154: 701–706.
    OpenUrlCrossRefPubMed
  3. ↵
    1. Arslan M,
    2. Akkurt I,
    3. Egilmez H, et al.
    Biomass exposure and the high resolution computed tomographic and spirometric findings. Eur J Radiol 2004; 52: 192–199.
    OpenUrlCrossRefPubMed
  4. ↵
    1. Boes JL,
    2. Hoff BA,
    3. Hylton N, et al.
    Image registration for quantitative parametric response mapping of cancer treatment response. Transl Oncol 2014; 7: 101–110.
    OpenUrl
  5. ↵
    1. Galbán CJ,
    2. Han MK,
    3. Boes JL, et al.
    Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression. Nat Med 2012; 18: 1711–1715.
    OpenUrlCrossRefPubMed
  6. ↵
    1. Lo Tam Loi AT,
    2. Hoonhorst SJ,
    3. Franciosi L, et al.
    Acute and chronic inflammatory responses induced by smoking in individuals susceptible and non-susceptible to development of COPD: from specific disease phenotyping towards novel therapy. Protocol of a cross-sectional study. BMJ Open 2013; 3: 002178.
    OpenUrl
  7. ↵
    Global Initiative for Chronic Obstructive Lung Disease. Global Strategy for Diagnosis, Management, and Prevention of COPD. www.goldcopd.org Date last accessed: December 24, 2015.
  8. ↵
    1. Miller MR,
    2. Hankinson J,
    3. Brusasco V, et al.
    Standardisation of spirometry. Eur Respir J 2005; 26: 319–338.
    OpenUrlAbstract/FREE Full Text
  9. ↵
    1. Buist AS,
    2. Vollmer WM,
    3. Sullivan SD, et al.
    The Burden of Obstructive Lung Disease Initiative (BOLD): rationale and design. COPD 2005; 2: 277–283.
    OpenUrl
  10. ↵
    1. Camp PG,
    2. Ramirez-Venegas A,
    3. Sansores RH, et al.
    COPD phenotypes in biomass smoke- versus tobacco smoke-exposed Mexican women. Eur Respir J 2014; 43: 725–734.
    OpenUrlAbstract/FREE Full Text
PreviousNext
Back to top
Vol 3 Issue 2 Table of Contents
ERJ Open Research: 3 (2)
  • Table of Contents
  • Index by author
Email

Thank you for your interest in spreading the word on European Respiratory Society .

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Small airway imaging phenotypes in biomass- and tobacco smoke-exposed patients with COPD
(Your Name) has sent you a message from European Respiratory Society
(Your Name) thought you would like to see the European Respiratory Society web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Print
Citation Tools
Small airway imaging phenotypes in biomass- and tobacco smoke-exposed patients with COPD
Lalita Fernandes, Nandani Gulati, Yasmin Fernandes, Anthony Menezes Mesquita, Mahesh Sardessai, Jan-Willem J. Lammers, Firdaus A. Mohamed Hoesein, Nick H.T. ten Hacken, Maarten van den Berge, Craig J. Galbán, Salman Siddiqui
ERJ Open Research Apr 2017, 3 (2) 00124-2016; DOI: 10.1183/23120541.00124-2016

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Small airway imaging phenotypes in biomass- and tobacco smoke-exposed patients with COPD
Lalita Fernandes, Nandani Gulati, Yasmin Fernandes, Anthony Menezes Mesquita, Mahesh Sardessai, Jan-Willem J. Lammers, Firdaus A. Mohamed Hoesein, Nick H.T. ten Hacken, Maarten van den Berge, Craig J. Galbán, Salman Siddiqui
ERJ Open Research Apr 2017, 3 (2) 00124-2016; DOI: 10.1183/23120541.00124-2016
del.icio.us logo Digg logo Reddit logo Technorati logo Twitter logo CiteULike logo Connotea logo Facebook logo Google logo Mendeley logo
Full Text (PDF)

Jump To

  • Article
    • Abstract
    • Disclosures
    • Acknowledgements
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF

Subjects

  • COPD and smoking
  • Lung imaging
  • Tweet Widget
  • Facebook Like
  • Google Plus One

More in this TOC Section

  • rs2070600 SNP regulates AGER splicing and sputum sRAGE
  • Procoagulant microparticles and COVID-19
  • Cancer referral and interventional pulmonology during COVID-19
Show more Original research letters

Related Articles

Navigate

  • Home
  • Current issue
  • Archive

About ERJ Open Research

  • Editorial board
  • Journal information
  • Press
  • Permissions and reprints
  • Advertising

The European Respiratory Society

  • Society home
  • myERS
  • Privacy policy
  • Accessibility

ERS publications

  • European Respiratory Journal
  • ERJ Open Research
  • European Respiratory Review
  • Breathe
  • ERS books online
  • ERS Bookshop

Help

  • Feedback

For authors

  • Instructions for authors
  • Publication ethics and malpractice
  • Submit a manuscript

For readers

  • Alerts
  • Subjects
  • RSS

Subscriptions

  • Accessing the ERS publications

Contact us

European Respiratory Society
442 Glossop Road
Sheffield S10 2PX
United Kingdom
Tel: +44 114 2672860
Email: journals@ersnet.org

ISSN

Online ISSN: 2312-0541

Copyright © 2023 by the European Respiratory Society