Firdaus A A Mohamed Hoesein1, Michael Schmidt2, Onno M Mets3, Hester A Gietema4, Jan-Willem J Lammers5, Pieter Zanen6, Harry J de Koning7, Carlijn van der Aalst8, Matthijs Oudkerk9, Rozemarijn Vliegenthart10, Ivana Isgum11, Mathias Prokop12, Bram van Ginneken13, Eva M van Rikxoort14, Pim A de Jong15. 1. Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: fmohamedhoesein@gmail.com. 2. Fraunhofer MEVIS, Institute for Medical Image Computing, Bremen, Germany. Electronic address: Michael.Schmidt@mevis.fraunhofer.de. 3. Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: metsonno@gmail.com. 4. Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: h.gietema@umcutrecht.nl. 5. Department of Respiratory Medicine, Division of Heart & Lungs, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: j.w.j.lammers@umcutrecht.nl. 6. Department of Respiratory Medicine, Division of Heart & Lungs, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: p.zanen@umcutrecht.nl. 7. Department of Public Health, Erasmus MC, Rotterdam, The Netherlands. Electronic address: h.dekoning@erasmusmc.nl. 8. Department of Public Health, Erasmus MC, Rotterdam, The Netherlands. Electronic address: c.vanderaalst@erasmusmc.nl. 9. Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. Electronic address: m.oudkerk@umcg.nl. 10. Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. Electronic address: r.vliegenthart@rad.umcg.nl. 11. Image Sciences Institute, University Medical Center Utrecht, The Netherlands. Electronic address: ivana.isgum@gmail.com. 12. Department of Radiology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands. Electronic address: M.Prokop@rad.umcn.nl. 13. Department of Radiology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands. Electronic address: b.vanginneken@rad.umcn.nl. 14. Department of Radiology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands. Electronic address: E.vanRikxoort@rad.umcn.nl. 15. Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: pimdejong@gmail.com.
Abstract
BACKGROUND: Finding phenotypes within COPD patients may prove imperative for optimizing treatment and prognosis. We hypothesized that it would be possible to discriminate emphysematous, large airway wall thickening and small airways disease dominant phenotypes. METHODS: Inspiratory and expiratory CTs were performed in 1140 male smokers without or with mild COPD to quantify emphysema, airway wall thickness and air trapping. Spirometry, residual volume to total lung capacity (RV/TLC) and diffusion capacity (Kco) were measured. Dominant phenotype (emphysema, airway wall thickening or air trapping dominant) was defined as one of the respective CT measure in the upper quartile, with the other measures not in the upper quartile. RESULTS: 573 subjects had any of the three CT measures in the upper quartile. Of these, 367 (64%) were in a single dominant group and 206 (36%) were in a mixed group. Airway wall thickening dominance was associated with younger age (p < 0.001), higher body mass index (p < 0.001), more wheezing (p < 0.05) and lower FEV1 %predicted (p < 0.001). Emphysema dominant subjects had lower FEV1/FVC (p < 0.05) and Kco %predicted (p < 0.05). There was no significant difference in respiratory related hospitalizations (p = 0.09). CONCLUSION: CT measures can discriminate three different CT dominant groups of disease in male smokers without or with mild COPD. TRIAL REGISTRATION NUMBER: ISRCTN63545820, registered at www.trialregister.nl.
BACKGROUND: Finding phenotypes within COPDpatients may prove imperative for optimizing treatment and prognosis. We hypothesized that it would be possible to discriminate emphysematous, large airway wall thickening and small airways disease dominant phenotypes. METHODS: Inspiratory and expiratory CTs were performed in 1140 male smokers without or with mild COPD to quantify emphysema, airway wall thickness and air trapping. Spirometry, residual volume to total lung capacity (RV/TLC) and diffusion capacity (Kco) were measured. Dominant phenotype (emphysema, airway wall thickening or air trapping dominant) was defined as one of the respective CT measure in the upper quartile, with the other measures not in the upper quartile. RESULTS: 573 subjects had any of the three CT measures in the upper quartile. Of these, 367 (64%) were in a single dominant group and 206 (36%) were in a mixed group. Airway wall thickening dominance was associated with younger age (p < 0.001), higher body mass index (p < 0.001), more wheezing (p < 0.05) and lower FEV1 %predicted (p < 0.001). Emphysema dominant subjects had lower FEV1/FVC (p < 0.05) and Kco %predicted (p < 0.05). There was no significant difference in respiratory related hospitalizations (p = 0.09). CONCLUSION: CT measures can discriminate three different CT dominant groups of disease in male smokers without or with mild COPD. TRIAL REGISTRATION NUMBER: ISRCTN63545820, registered at www.trialregister.nl.
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