Noninvasive Imaging Biomarker Identifies Small Airway Damage in Severe Chronic Obstructive Pulmonary Disease
Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography densitometry has been demonstrated to identify emphysema, but no such studies have been performed linking an imaging metric to small airway abnormality. To correl...
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Published in | American journal of respiratory and critical care medicine Vol. 200; no. 5; pp. 575 - 581 |
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Main Authors | , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Thoracic Society
01.09.2019
|
Subjects | |
Online Access | Get full text |
ISSN | 1073-449X 1535-4970 1535-4970 |
DOI | 10.1164/rccm.201811-2083OC |
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Abstract | Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography densitometry has been demonstrated to identify emphysema, but no such studies have been performed linking an imaging metric to small airway abnormality.
To correlate
parametric response mapping (PRM) analysis to
lung tissue measurements of patients with severe COPD treated by lung transplantation and control subjects.
Resected lungs were inflated, frozen, and systematically sampled, generating 33 COPD (
= 11 subjects) and 22 control tissue samples (
= 3 subjects) for micro-computed tomography analysis of terminal bronchioles (TBs; last generation of conducting airways) and emphysema.
PRM analysis was conducted to differentiate functional small airways disease (PRM
) from emphysema (PRM
). In COPD lungs, TB numbers were reduced (
= 0.01); surviving TBs had increased wall area percentage (
< 0.001), decreased circularity (
< 0.001), reduced cross-sectional luminal area (
< 0.001), and greater airway obstruction (
= 0.008). COPD lungs had increased airspace size (
< 0.001) and decreased alveolar surface area (
< 0.001). Regression analyses demonstrated unique correlations between PRM
and TBs, with decreased circularity (
< 0.001), decreased luminal area (
< 0.001), and complete obstruction (
= 0.008). PRM
correlated with increased airspace size (
< 0.001), decreased alveolar surface area (
= 0.003), and fewer alveolar attachments per TB (
= 0.01).
PRM
identifies areas of lung tissue with TB loss, luminal narrowing, and obstruction. This is the first confirmation that an imaging biomarker can identify terminal bronchial pathology in established COPD and provides a noninvasive imaging methodology to identify small airway damage in COPD. |
---|---|
AbstractList | Rationale: Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography densitometry has been demonstrated to identify emphysema, but no such studies have been performed linking an imaging metric to small airway abnormality.Objectives: To correlate ex vivo parametric response mapping (PRM) analysis to in vivo lung tissue measurements of patients with severe COPD treated by lung transplantation and control subjects.Methods: Resected lungs were inflated, frozen, and systematically sampled, generating 33 COPD (n = 11 subjects) and 22 control tissue samples (n = 3 subjects) for micro-computed tomography analysis of terminal bronchioles (TBs; last generation of conducting airways) and emphysema.Measurements and Main Results: PRM analysis was conducted to differentiate functional small airways disease (PRMfSAD) from emphysema (PRMEmph). In COPD lungs, TB numbers were reduced (P = 0.01); surviving TBs had increased wall area percentage (P < 0.001), decreased circularity (P < 0.001), reduced cross-sectional luminal area (P < 0.001), and greater airway obstruction (P = 0.008). COPD lungs had increased airspace size (P < 0.001) and decreased alveolar surface area (P < 0.001). Regression analyses demonstrated unique correlations between PRMfSAD and TBs, with decreased circularity (P < 0.001), decreased luminal area (P < 0.001), and complete obstruction (P = 0.008). PRMEmph correlated with increased airspace size (P < 0.001), decreased alveolar surface area (P = 0.003), and fewer alveolar attachments per TB (P = 0.01).Conclusions: PRMfSAD identifies areas of lung tissue with TB loss, luminal narrowing, and obstruction. This is the first confirmation that an imaging biomarker can identify terminal bronchial pathology in established COPD and provides a noninvasive imaging methodology to identify small airway damage in COPD.Rationale: Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography densitometry has been demonstrated to identify emphysema, but no such studies have been performed linking an imaging metric to small airway abnormality.Objectives: To correlate ex vivo parametric response mapping (PRM) analysis to in vivo lung tissue measurements of patients with severe COPD treated by lung transplantation and control subjects.Methods: Resected lungs were inflated, frozen, and systematically sampled, generating 33 COPD (n = 11 subjects) and 22 control tissue samples (n = 3 subjects) for micro-computed tomography analysis of terminal bronchioles (TBs; last generation of conducting airways) and emphysema.Measurements and Main Results: PRM analysis was conducted to differentiate functional small airways disease (PRMfSAD) from emphysema (PRMEmph). In COPD lungs, TB numbers were reduced (P = 0.01); surviving TBs had increased wall area percentage (P < 0.001), decreased circularity (P < 0.001), reduced cross-sectional luminal area (P < 0.001), and greater airway obstruction (P = 0.008). COPD lungs had increased airspace size (P < 0.001) and decreased alveolar surface area (P < 0.001). Regression analyses demonstrated unique correlations between PRMfSAD and TBs, with decreased circularity (P < 0.001), decreased luminal area (P < 0.001), and complete obstruction (P = 0.008). PRMEmph correlated with increased airspace size (P < 0.001), decreased alveolar surface area (P = 0.003), and fewer alveolar attachments per TB (P = 0.01).Conclusions: PRMfSAD identifies areas of lung tissue with TB loss, luminal narrowing, and obstruction. This is the first confirmation that an imaging biomarker can identify terminal bronchial pathology in established COPD and provides a noninvasive imaging methodology to identify small airway damage in COPD. Rationale: Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography densitometry has been demonstrated to identify emphysema, but no such studies have been performed linking an imaging metric to small airway abnormality. Objectives: To correlate ex vivo parametric response mapping (PRM) analysis to in vivo lung tissue measurements of patients with severe COPD treated by lung transplantation and control subjects. Methods: Resected lungs were inflated, frozen, and systematically sampled, generating 33 COPD (n = 11 subjects) and 22 control tissue samples (n = 3 subjects) for micro–computed tomography analysis of terminal bronchioles (TBs; last generation of conducting airways) and emphysema. Measurements and Main Results: PRM analysis was conducted to differentiate functional small airways disease (PRMfSAD) from emphysema (PRMEmph). In COPD lungs, TB numbers were reduced (P = 0.01); surviving TBs had increased wall area percentage (P < 0.001), decreased circularity (P < 0.001), reduced cross-sectional luminal area (P < 0.001), and greater airway obstruction (P = 0.008). COPD lungs had increased airspace size (P < 0.001) and decreased alveolar surface area (P < 0.001). Regression analyses demonstrated unique correlations between PRMfSAD and TBs, with decreased circularity (P < 0.001), decreased luminal area (P < 0.001), and complete obstruction (P = 0.008). PRMEmph correlated with increased airspace size (P < 0.001), decreased alveolar surface area (P = 0.003), and fewer alveolar attachments per TB (P = 0.01). Conclusions: PRMfSAD identifies areas of lung tissue with TB loss, luminal narrowing, and obstruction. This is the first confirmation that an imaging biomarker can identify terminal bronchial pathology in established COPD and provides a noninvasive imaging methodology to identify small airway damage in COPD. Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography densitometry has been demonstrated to identify emphysema, but no such studies have been performed linking an imaging metric to small airway abnormality. To correlate parametric response mapping (PRM) analysis to lung tissue measurements of patients with severe COPD treated by lung transplantation and control subjects. Resected lungs were inflated, frozen, and systematically sampled, generating 33 COPD ( = 11 subjects) and 22 control tissue samples ( = 3 subjects) for micro-computed tomography analysis of terminal bronchioles (TBs; last generation of conducting airways) and emphysema. PRM analysis was conducted to differentiate functional small airways disease (PRM ) from emphysema (PRM ). In COPD lungs, TB numbers were reduced ( = 0.01); surviving TBs had increased wall area percentage ( < 0.001), decreased circularity ( < 0.001), reduced cross-sectional luminal area ( < 0.001), and greater airway obstruction ( = 0.008). COPD lungs had increased airspace size ( < 0.001) and decreased alveolar surface area ( < 0.001). Regression analyses demonstrated unique correlations between PRM and TBs, with decreased circularity ( < 0.001), decreased luminal area ( < 0.001), and complete obstruction ( = 0.008). PRM correlated with increased airspace size ( < 0.001), decreased alveolar surface area ( = 0.003), and fewer alveolar attachments per TB ( = 0.01). PRM identifies areas of lung tissue with TB loss, luminal narrowing, and obstruction. This is the first confirmation that an imaging biomarker can identify terminal bronchial pathology in established COPD and provides a noninvasive imaging methodology to identify small airway damage in COPD. |
Author | Criner, Gerard J. Curtis, Jeffrey L. Hackett, Tillie L. Martinez, Fernando J. Labaki, Wassim W. Meldrum, Catherine A. Ross, Brian D. Marchetti, Nathaniel Hogg, James C. Galbán, Craig J. Reddy, Rishindra M. Meng, Xia Dass, Chandra Hatt, Charles Vasilescu, Dragoş M. Tanabe, Naoya Lagstein, Amir Murray, Susan Han, MeiLan K. Kazerooni, Ella A. |
Author_xml | – sequence: 1 givenname: Dragoş M. orcidid: 0000-0003-3936-4365 surname: Vasilescu fullname: Vasilescu, Dragoş M. organization: University of British Columbia, Vancouver, British Columbia, Canada – sequence: 2 givenname: Fernando J. surname: Martinez fullname: Martinez, Fernando J. organization: Weill Cornell Medical College, New York, New York – sequence: 3 givenname: Nathaniel surname: Marchetti fullname: Marchetti, Nathaniel organization: Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania – sequence: 4 givenname: Craig J. surname: Galbán fullname: Galbán, Craig J. organization: University of Michigan, Ann Arbor, Michigan – sequence: 5 givenname: Charles surname: Hatt fullname: Hatt, Charles organization: University of Michigan, Ann Arbor, Michigan, Imbio, Minneapolis, Minnesota – sequence: 6 givenname: Catherine A. surname: Meldrum fullname: Meldrum, Catherine A. organization: University of Michigan, Ann Arbor, Michigan – sequence: 7 givenname: Chandra surname: Dass fullname: Dass, Chandra organization: Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania – sequence: 8 givenname: Naoya surname: Tanabe fullname: Tanabe, Naoya organization: Kyoto University, Kyoto, Japan; and – sequence: 9 givenname: Rishindra M. surname: Reddy fullname: Reddy, Rishindra M. organization: University of Michigan, Ann Arbor, Michigan – sequence: 10 givenname: Amir surname: Lagstein fullname: Lagstein, Amir organization: University of Michigan, Ann Arbor, Michigan – sequence: 11 givenname: Brian D. surname: Ross fullname: Ross, Brian D. organization: University of Michigan, Ann Arbor, Michigan – sequence: 12 givenname: Wassim W. surname: Labaki fullname: Labaki, Wassim W. organization: University of Michigan, Ann Arbor, Michigan – sequence: 13 givenname: Susan surname: Murray fullname: Murray, Susan organization: University of Michigan, Ann Arbor, Michigan – sequence: 14 givenname: Xia surname: Meng fullname: Meng, Xia – sequence: 15 givenname: Jeffrey L. surname: Curtis fullname: Curtis, Jeffrey L. organization: University of Michigan, Ann Arbor, Michigan, VA Ann Arbor Healthcare System, Ann Arbor, Michigan – sequence: 16 givenname: Tillie L. surname: Hackett fullname: Hackett, Tillie L. organization: University of British Columbia, Vancouver, British Columbia, Canada – sequence: 17 givenname: Ella A. surname: Kazerooni fullname: Kazerooni, Ella A. organization: University of Michigan, Ann Arbor, Michigan – sequence: 18 givenname: Gerard J. surname: Criner fullname: Criner, Gerard J. organization: Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania – sequence: 19 givenname: James C. surname: Hogg fullname: Hogg, James C. organization: University of British Columbia, Vancouver, British Columbia, Canada – sequence: 20 givenname: MeiLan K. surname: Han fullname: Han, MeiLan K. organization: University of Michigan, Ann Arbor, Michigan |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30794432$$D View this record in MEDLINE/PubMed |
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Copyright | Copyright American Thoracic Society Sep 1, 2019 Copyright © 2019 by the American Thoracic Society 2019 |
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References | bib12 bib10 Vasilescu DM (bib15) 2018; 197 bib32 bib11 bib30 bib31 bib29 bib27 bib28 Vasilescu DM (bib14) 2017; 50 bib25 bib26 bib23 bib24 bib21 bib22 bib20 bib9 bib7 bib8 bib5 bib18 bib6 bib19 bib3 Vasilescu DM (bib13) 2017; 195 bib16 bib4 bib17 bib1 bib2 30836008 - Am J Respir Crit Care Med. 2019 Sep 1;200(5):524-525. doi: 10.1164/rccm.201902-0395ED 31804849 - Am J Respir Crit Care Med. 2020 Apr 1;201(7):878-879. doi: 10.1164/rccm.201910-1981LE 31804850 - Am J Respir Crit Care Med. 2020 Apr 1;201(7):879-880. doi: 10.1164/rccm.201911-2154LE |
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Snippet | Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography densitometry has been... Rationale: Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography... |
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SubjectTerms | Adult Aged Aged, 80 and over Airway Obstruction - diagnostic imaging Biomarkers Chronic obstructive pulmonary disease Collaboration Cross-Sectional Studies Emphysema Female Histology Humans Male Medical imaging Middle Aged Original Pulmonary Disease, Chronic Obstructive - physiopathology Transplants & implants X-Ray Microtomography - methods |
Title | Noninvasive Imaging Biomarker Identifies Small Airway Damage in Severe Chronic Obstructive Pulmonary Disease |
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