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Asthma
Differentiation of quantitative CT imaging phenotypes in asthma versus COPD
  1. Sanghun Choi1,
  2. Babak Haghighi2,3,
  3. Jiwoong Choi2,3,
  4. Eric A Hoffman4,5,
  5. Alejandro P Comellas5,
  6. John D Newell4,5,
  7. Sally E Wenzel6,
  8. Mario Castro7,
  9. Sean B Fain8,9,
  10. Nizar N Jarjour8,
  11. Mark L Schiebler8,
  12. R Graham Barr10,
  13. MeiLan K Han11,
  14. Eugene R Bleecker12,
  15. Christopher B Cooper13,
  16. David Couper14,
  17. Nadia Hansel15,
  18. Richard E Kanner16,
  19. Ella A Kazerooni17,
  20. Eric A C Kleerup18,
  21. Fernando J Martinez19,
  22. Wanda K O’Neal20,
  23. Prescott G Woodruff21 and
  24. Ching-Long Lin2,3
  25. for the National Heart, Lung and Blood Institute’s SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Severe Asthma Research Program (SARP)
  1. 1 Department of Mechanical Engineering, Kyungpook National University, Daegu, South Korea
  2. 2 Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, Iowa, USA
  3. 3 IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, Iowa, USA
  4. 4 Department of Radiology, University of Iowa, Iowa City, Iowa, USA
  5. 5 Department of Internal Medicine, University of Iowa, Iowa City, Iowa, USA
  6. 6 Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
  7. 7 Departments of Internal Medicine and Pediatrics, Washington University School of Medicine, St. Louis, Missouri, USA
  8. 8 Departments of Radiology and Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, USA
  9. 9 Department of Medical Physics and Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA
  10. 10 Mailman School of Public Health, Columbia University, New York, USA
  11. 11 Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
  12. 12 Center for Genomics and Personalized Medicine, Wake Forest University, Winston-Salem, North Carolina, USA
  13. 13 Department of Physiology, University of California, Los Angeles, California, USA
  14. 14 Department of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
  15. 15 School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
  16. 16 School of Medicine, University of Utah, Salt Lake City, Utah, USA
  17. 17 Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
  18. 18 Department of Medicine, University of California, Los Angeles, Los Angeles, California, USA
  19. 19 Department of Medicine, Weill Cornell School of Medicine, Cornell University, New York, USA
  20. 20 Marsico Lung Institute, University of North Carolina, Chapel Hill, North Carolina, USA
  21. 21 School of Medicine, University of California at San Francisco, San Francisco, California, USA
  1. Correspondence to Dr Ching-Long Lin; ching-long-lin{at}uiowa.edu

Abstract

Introduction Quantitative CT (QCT) imaging-based metrics have quantified disease alterations in asthma and chronic obstructive pulmonary disease (COPD), respectively. We seek to characterise the similarity and disparity between these groups using QCT-derived airway and parenchymal metrics.

Methods Asthma and COPD subjects (former-smoker status) were selected with a criterion of post-bronchodilator FEV1 <80%. Healthy non-smokers were included as a control group. Inspiratory and expiratory QCT images of 75 asthmatic, 215 COPD and 94 healthy subjects were evaluated. We compared three segmental variables: airway circularity, normalised wall thickness and normalised hydraulic diameter, indicating heterogeneous airway shape, wall thickening and luminal narrowing, respectively. Using an image registration, we also computed six lobar variables including per cent functional small-airway disease, per cent emphysema, tissue fraction at inspiration, fractional-air-volume change, Jacobian and functional metric characterising anisotropic deformation.

Results Compared with healthy subjects, both asthma and COPD subjects demonstrated a decreased airway circularity especially in large and upper lobar airways, and a decreased normalised hydraulic diameter in segmental airways. Besides, COPD subjects had more severe emphysema and small-airway disease, as well as smaller regional tissue fraction and lung deformation, compared with asthmatic subjects. The difference of emphysema, small-airway disease and tissue fraction between asthma and COPD was more prominent in upper and middle lobes.

Conclusions Patients with asthma and COPD, with a persistent FEV1 <80%, demonstrated similar alterations in airway geometry compared with controls, but different degrees of alterations in parenchymal regions. Density-based metrics measured at upper and middle lobes were found to be discriminant variables between patients with asthma and COPD.

  • emphysema
  • functional small airway disease
  • image registration
  • quantitative computed tomography
  • airway luminal narrowing

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

https://doi.org/10.1136/bmjresp-2017-000252

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    Footnotes

    • Contributors Conception and design: SC. Acquisition of data: SC, BH, EAH, SEW, MC, SBF, SBF, NNJ, MLS, RGB., MKH, ERB, CBC, DC, NH, REK, EAK, EACK, FJM, WKO, PGW and C-LL. Analysis and interpretation of data and final approval of the version to be published: all authors. Drafting the article or revising it critically for important intellectual content: SC, JC, EAH, APC, MLS, REK, WKO and C-LL.

    • Funding This study was supported by the NIH grants: U01 HL114494, HL209152; R01HL094315, HL112986, HL69174, HL064368, HL091762, HL069116; S10RR022421; U10 HL109257, HL109168; UL1 RR024153 (CTSI), UL1 TR000448, UL1 TR000427 (CTSA), and by BasicScience Research Program through the National Research Foundation ofKorea (NRF) funded by the Ministry of Education(NRF-2017R1D1A1B03034157). SPIROMICS was supported bycontracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C,HHSN268200900015C, HHSN268200900016C, HHSN268200900017C,HHSN268200900018C, HHSN268200900019C, HHSN268200900020C), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc; Chiesi Farmaceutici S.p.A; Forest Research Institute, Inc; GlaxoSmithKline; Grifols Therapeutics, Inc; Ikaria, Inc; Nycomed GmbH; Takeda Pharmaceutical Company; Novartis Pharmaceuticals Corporation; ProterixBio; Regeneron Pharmaceuticals, Inc; Sanofi; and Sunovion.

    • Competing interests EAH is a shareholder in VIDA diagnostics, a company that is commercialising lung image analysis software derived by the University of Iowa lung imaging group. He is also a member of the Siemens CT advisory board. SBF receives grant funding from GE Healthcare.

    • Patient consent Obtained.

    • Ethics approval The imaging protocols for acquiring CT images were approved by the institutional review boards of the respective institutions.

    • Provenance and peer review Not commissioned; internally peer reviewed.

    • Data sharing statement No additional data are available.