{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,6]],"date-time":"2026-11-06T05:54:26Z","timestamp":1793944466943,"version":"4.8.0"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T00:00:00Z","timestamp":1632268800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T00:00:00Z","timestamp":1632268800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100018936","name":"Universit\u00e4tsklinikum Heidelberg","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100018936","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Objectives<\/jats:title>\n                <jats:p>Pulmonary perfusion abnormalities are prevalent in patients with chronic obstructive pulmonary disease (COPD), are potentially reversible, and may be associated with emphysema development. Therefore, we aimed to evaluate the clinical meaningfulness of perfusion defects in percent (QDP) using DCE-MRI.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>We investigated a subset of baseline DCE-MRIs, paired inspiratory\/expiratory CTs, and pulmonary function testing (PFT) of 83 subjects (age\u00a0=\u00a065.7\u00a0\u00b1\u00a09.0\u00a0years, patients-at-risk, and all GOLD groups) from one center of the \u201cCOSYCONET\u201d COPD cohort. QDP was computed from DCE-MRI using an in-house developed quantification pipeline, including four different approaches: Otsu\u2019s method, k-means clustering, texture analysis, and 80<jats:sup>th<\/jats:sup> percentile threshold. QDP was compared with visual MRI perfusion scoring, CT parametric response mapping (PRM) indices of emphysema (PRM<jats:sub>Emph<\/jats:sub>) and functional small airway disease (PRM<jats:sub>fSAD<\/jats:sub>), and FEV1\/FVC from PFT.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>All QDP approaches showed high correlations with the MRI perfusion score (<jats:italic>r<\/jats:italic>\u00a0=\u00a00.67\u00a0to\u00a00.72, <jats:italic>p<\/jats:italic>\u00a0&lt;\u00a00.001), with the highest association based on Otsu\u2019s method (<jats:italic>r<\/jats:italic>\u00a0=\u00a00.72, <jats:italic>p<\/jats:italic>\u00a0&lt;\u00a00.001). QDP correlated significantly with all PRM indices (<jats:italic>p\u00a0<\/jats:italic>&lt;\u00a00.001), with the strongest correlations with PRM<jats:sub>Emph<\/jats:sub>\u00a0(<jats:italic>r\u00a0<\/jats:italic>=\u00a00.70\u00a0to\u00a00.75, <jats:italic>p<\/jats:italic>\u00a0&lt;\u00a00.001). QDP was distinctly higher than PRM<jats:sub>Emph<\/jats:sub>\u00a0(mean\u00a0difference\u00a0=\u00a035.85\u00a0to\u00a040.40) and PRM<jats:sub>fSAD<\/jats:sub> (mean\u00a0difference\u00a0=\u00a015.12\u00a0to\u00a019.68), but in close agreement when combining both PRM indices (mean\u00a0difference\u00a0=\u00a01.47\u00a0to\u00a06.03) for all QDP approaches. QDP correlated moderately with FEV1\/FVC (<jats:italic>r<\/jats:italic>\u00a0=\u00a0\u2212\u00a00.54\u00a0to\u00a0\u2212\u00a00.41,\u00a0<jats:italic>p<\/jats:italic>\u00a0&lt;\u00a00.001).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>QDP is associated with established markers of disease severity and the extent corresponds to the CT-derived combined extent of PRM<jats:sub>Emph<\/jats:sub>\u00a0and PRM<jats:sub>fSAD<\/jats:sub>. We propose to use QDP based on Otsu\u2019s method for future clinical studies in COPD.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Key Points<\/jats:title>\n                <jats:p><jats:italic>\u2022 QDP quantified from DCE-MRI is associated with visual MRI perfusion score, CT PRM indices, and PFT.<\/jats:italic><\/jats:p>\n                <jats:p><jats:italic>\u2022 The extent of QDP from DCE-MRI corresponds to the combined extent of PRM<\/jats:italic><jats:sub><jats:italic>Emph<\/jats:italic><\/jats:sub><jats:italic>\u00a0and PRM<\/jats:italic><jats:sub><jats:italic>fSAD<\/jats:italic><\/jats:sub><jats:italic> from CT.<\/jats:italic><\/jats:p>\n                <jats:p><jats:italic>\u2022 Assessing pulmonary perfusion abnormalities using DCE-MRI with QDP improved the correlations with CT PRM indices and PFT compared to the quantification of pulmonary blood flow and volume.<\/jats:italic><\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00330-021-08229-6","type":"journal-article","created":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T19:24:50Z","timestamp":1632338690000},"page":"1879-1890","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Quantification of pulmonary perfusion abnormalities using DCE-MRI in COPD: comparison with quantitative CT and pulmonary function"],"prefix":"10.1007","volume":"32","author":[{"given":"Marilisa","family":"Schiwek","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon M. F.","family":"Triphan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J\u00fcrgen","family":"Biederer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oliver","family":"Weinheimer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Monika","family":"Eichinger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claus F.","family":"Vogelmeier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rudolf A.","family":"J\u00f6rres","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hans-Ulrich","family":"Kauczor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claus P.","family":"Heu\u00dfel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philip","family":"Konietzke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oyunbileg","family":"von Stackelberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frank","family":"Risse","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bertram J.","family":"Jobst","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6962-037X","authenticated-orcid":false,"given":"Mark O.","family":"Wielp\u00fctz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"on behalf of the COSYCONET study group","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,9,22]]},"reference":[{"key":"8229_CR1","doi-asserted-by":"publisher","first-page":"570","DOI":"10.1164\/rccm.201411-2120oc","volume":"192","author":"K Hueper","year":"2015","unstructured":"Hueper K, Vogel-Claussen J, Parikh MA et al (2015) Pulmonary microvascular blood flow in mild chronic obstructive pulmonary disease and emphysema. The MESA COPD Study. Am J Respir Crit Care Med 192:570\u2013580. https:\/\/doi.org\/10.1164\/rccm.201411-2120oc","journal-title":"Am J Respir Crit Care Med"},{"key":"8229_CR2","doi-asserted-by":"publisher","first-page":"1321","DOI":"10.1016\/j.ejrad.2011.02.045","volume":"81","author":"M Eichinger","year":"2012","unstructured":"Eichinger M, Optazaite DE, Kopp-Schneider A et al (2012) Morphologic and functional scoring of cystic fibrosis lung disease using MRI. Eur J Radiol 81:1321\u20131329. https:\/\/doi.org\/10.1016\/j.ejrad.2011.02.045","journal-title":"Eur J Radiol"},{"key":"8229_CR3","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1164\/rccm.201812-2356le","volume":"200","author":"MO Wielp\u00fctz","year":"2019","unstructured":"Wielp\u00fctz MO, Eichinger M, Wege S et al (2019) Midterm reproducibility of chest magnetic resonance imaging in adults with clinically stable cystic fibrosis and chronic obstructive pulmonary disease. Am J Resp Crit Care 200:103\u2013107. https:\/\/doi.org\/10.1164\/rccm.201812-2356le","journal-title":"Am J Resp Crit Care"},{"key":"8229_CR4","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1002\/jmri.20137","volume":"20","author":"Y Ohno","year":"2004","unstructured":"Ohno Y, Hatabu H, Murase K et al (2004) Quantitative assessment of regional pulmonary perfusion in the entire lung using three-dimensional ultrafast dynamic contrast-enhanced magnetic resonance imaging: preliminary experience in 40 subjects. J Magn Reson Imaging 20:353\u2013365. https:\/\/doi.org\/10.1002\/jmri.20137","journal-title":"J Magn Reson Imaging"},{"key":"8229_CR5","doi-asserted-by":"publisher","first-page":"1033","DOI":"10.1002\/(sici)1522-2594(199912)42:6<1033::aid-mrm7>3.0.co;2-7","volume":"42","author":"H Hatabu","year":"1999","unstructured":"Hatabu H, Tadamura E, Levin DL et al (1999) Quantitative assessment of pulmonary perfusion with dynamic contrast-enhanced MRI. Magnet Reson Med 42:1033\u20131038. https:\/\/doi.org\/10.1002\/(sici)1522-2594(199912)42:6%3c1033::aid-mrm7%3e3.0.co;2-7","journal-title":"Magnet Reson Med"},{"key":"8229_CR6","doi-asserted-by":"publisher","first-page":"2102","DOI":"10.1007\/s00330-008-0974-1","volume":"18","author":"M Puderbach","year":"2008","unstructured":"Puderbach M, Risse F, Biederer J et al (2008) In vivo Gd-DTPA concentration for MR lung perfusion measurements: assessment with computed tomography in a porcine model. Eur Radiol 18:2102\u20132107. https:\/\/doi.org\/10.1007\/s00330-008-0974-1","journal-title":"Eur Radiol"},{"key":"8229_CR7","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1002\/mrm.22025","volume":"62","author":"D Neeb","year":"2009","unstructured":"Neeb D, Kunz RP, Ley S et al (2009) Quantification of pulmonary blood flow (PBF): Validation of perfusion MRI and nonlinear contrast agent (CA) dose correction with H 215O positron emission tomography (PET). Magnet Reson Med 62:476\u2013487. https:\/\/doi.org\/10.1002\/mrm.22025","journal-title":"Magnet Reson Med"},{"key":"8229_CR8","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1097\/rti.0b013e3181e48c36","volume":"26","author":"J Ley-Zaporozhan","year":"2011","unstructured":"Ley-Zaporozhan J, Molinari F, Risse F et al (2011) Repeatability and reproducibility of quantitative whole-lung perfusion magnetic resonance imaging. J Thorac Imaging 26:230\u2013239. https:\/\/doi.org\/10.1097\/rti.0b013e3181e48c36","journal-title":"J Thorac Imaging"},{"key":"8229_CR9","doi-asserted-by":"publisher","unstructured":"Ter-Karapetyan A, Triphan SMF, Jobst BJ et al (2018) Towards quantitative perfusion MRI of the lung in COPD: the problem of short-term repeatability. PLoS One\u00a013:e0208587. https:\/\/doi.org\/10.1371\/journal.pone.0208587","DOI":"10.1371\/journal.pone.0208587"},{"key":"8229_CR10","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1002\/jmri.20290","volume":"21","author":"N Woodhouse","year":"2005","unstructured":"Woodhouse N, Wild JM, Paley MNJ et al (2005) Combined helium-3\/proton magnetic resonance imaging measurement of ventilated lung volumes in smokers compared to never-smokers. J Magn Reson Imaging 21:365\u2013369. https:\/\/doi.org\/10.1002\/jmri.20290","journal-title":"J Magn Reson Imaging"},{"key":"8229_CR11","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1016\/j.acra.2007.10.019","volume":"15","author":"SB Fain","year":"2008","unstructured":"Fain SB, Gonzalez-Fernandez G, Peterson ET et al (2008) Evaluation of structure-function relationships in asthma using multidetector CT and hyperpolarized He-3 MRI. Acad Radiol 15:753\u2013762. https:\/\/doi.org\/10.1016\/j.acra.2007.10.019","journal-title":"Acad Radiol"},{"key":"8229_CR12","doi-asserted-by":"publisher","first-page":"1122","DOI":"10.1002\/jmri.26342","volume":"49","author":"TF Kaireit","year":"2019","unstructured":"Kaireit TF, Voskrebenzev A, Gutberlet M et al (2019) Comparison of quantitative regional perfusion-weighted phase resolved functional lung (PREFUL) MRI with dynamic gadolinium-enhanced regional pulmonary perfusion MRI in COPD patients. J Magn Reson Imaging 49:1122\u20131132. https:\/\/doi.org\/10.1002\/jmri.26342","journal-title":"J Magn Reson Imaging"},{"key":"8229_CR13","doi-asserted-by":"publisher","first-page":"1901987","DOI":"10.1183\/13993003.01987-2019","volume":"55","author":"RL Eddy","year":"2020","unstructured":"Eddy RL, Parraga G (2020) Pulmonary xenon-129 MRI: new opportunities to unravel enigmas in respiratory medicine. Eur Respir J 55:1901987. https:\/\/doi.org\/10.1183\/13993003.01987-2019","journal-title":"Eur Respir J"},{"key":"8229_CR14","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1148\/radiol.2018171993","volume":"287","author":"DPI Capaldi","year":"2018","unstructured":"Capaldi DPI, Eddy RL, Svenningsen S et al (2018) Free-breathing pulmonary MR imaging to quantify regional ventilation. Radiology 287:693\u2013704. https:\/\/doi.org\/10.1148\/radiol.2018171993","journal-title":"Radiology"},{"key":"8229_CR15","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.ejrad.2009.10.028","volume":"79","author":"L Mathew","year":"2011","unstructured":"Mathew L, Kirby M, Etemad-Rezai R et al (2011) Hyperpolarized 3He magnetic resonance imaging: preliminary evaluation of phenotyping potential in chronic obstructive pulmonary disease. Eur J Radiol 79:140\u2013146. https:\/\/doi.org\/10.1016\/j.ejrad.2009.10.028","journal-title":"Eur J Radiol"},{"key":"8229_CR16","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1016\/j.jcf.2019.03.005","volume":"18","author":"MJ Couch","year":"2019","unstructured":"Couch MJ, Thomen R, Kanhere N et al (2019) A two-center analysis of hyperpolarized 129Xe lung MRI in stable pediatric cystic fibrosis: potential as a biomarker for multi-site trials. J Cyst Fibros 18:728\u2013733. https:\/\/doi.org\/10.1016\/j.jcf.2019.03.005","journal-title":"J Cyst Fibros"},{"key":"8229_CR17","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1055\/s-0030-1249185","volume":"135","author":"R J\u00f6rres","year":"2010","unstructured":"J\u00f6rres R, Welte T, Bals R et al (2010) Einfluss systemischer Manifestationen und Komorbidit\u00e4ten auf den klinischen Zustand und den Verlauf bei COPD. Dtsch Med Wochenschr 135:446\u2013449. https:\/\/doi.org\/10.1055\/s-0030-1249185","journal-title":"Dtsch Med Wochenschr"},{"key":"8229_CR18","doi-asserted-by":"publisher","first-page":"1900164","DOI":"10.1183\/13993003.00164-2019","volume":"53","author":"D Singh","year":"2019","unstructured":"Singh D, Agusti A, Anzueto A et al (2019) Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease: the GOLD science committee report 2019. Eur Respir J 53:1900164. https:\/\/doi.org\/10.1183\/13993003.00164-2019","journal-title":"Eur Respir J"},{"key":"8229_CR19","doi-asserted-by":"publisher","unstructured":"Jobst BJ, Triphan SMF, Sedlaczek O et al (2015) Functional lung MRI in chronic obstructive pulmonary disease: comparison of T1 mapping, oxygen-enhanced T1 mapping and dynamic contrast enhanced perfusion. PLoS One 10:e0121520. https:\/\/doi.org\/10.1371\/journal.pone.0121520","DOI":"10.1371\/journal.pone.0121520"},{"key":"8229_CR20","doi-asserted-by":"publisher","first-page":"956","DOI":"10.1164\/rccm.201309-1659oc","volume":"189","author":"MO Wielp\u00fctz","year":"2014","unstructured":"Wielp\u00fctz MO, Puderbach M, Kopp-Schneider A et al (2014) Magnetic resonance imaging detects changes in structure and perfusion, and response to therapy in early cystic fibrosis lung disease. Am J Respir Crit Care Med 189:956\u2013965. https:\/\/doi.org\/10.1164\/rccm.201309-1659oc","journal-title":"Am J Respir Crit Care Med"},{"key":"8229_CR21","doi-asserted-by":"publisher","unstructured":"Triphan SMF, Biederer J, Burmester K et al (2018) Design and application of an MR reference phantom for multicentre lung imaging trials. PLoS One 13:e0199148. https:\/\/doi.org\/10.1371\/journal.pone.0199148","DOI":"10.1371\/journal.pone.0199148"},{"key":"8229_CR22","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1002\/mrm.1910360304","volume":"36","author":"FR Korosec","year":"1996","unstructured":"Korosec FR, Frayne R, Grist TM, Mistretta CA (1996) Time-resolved contrast-enhanced 3D MR angiography. Magnet Reson Med 36:345\u2013351. https:\/\/doi.org\/10.1002\/mrm.1910360304","journal-title":"Magnet Reson Med"},{"key":"8229_CR23","doi-asserted-by":"publisher","first-page":"2147","DOI":"10.1007\/s00330-006-0257-7","volume":"16","author":"M Eichinger","year":"2006","unstructured":"Eichinger M, Puderbach M, Fink C et al (2006) Contrast-enhanced 3D MRI of lung perfusion in children with cystic fibrosis\u2014initial results. Eur Radiol 16:2147\u20132152. https:\/\/doi.org\/10.1007\/s00330-006-0257-7","journal-title":"Eur Radiol"},{"key":"8229_CR24","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1016\/j.jcf.2013.09.003","volume":"13","author":"C Sileo","year":"2014","unstructured":"Sileo C, Corvol H, Boelle P-Y et al (2014) HRCT and MRI of the lung in children with cystic fibrosis: comparison of different scoring systems. J Cyst Fibros 13:198\u2013204. https:\/\/doi.org\/10.1016\/j.jcf.2013.09.003","journal-title":"J Cyst Fibros"},{"key":"8229_CR25","unstructured":"Kohlmann P, Laue H, Krass S, Peitgen H-O (2011) Fully-automatic determination of the arterial input function for dynamic contrast-enhanced pulmonary MR imaging. Proceedings of Medical Image Understanding and Analysis 281\u2013285. http:\/\/www.bmva.org\/miua\/2011\/miua-11-43.pdf. Accessed 1 Sep 2020"},{"key":"8229_CR26","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1088\/0031-9155\/52\/2\/009","volume":"52","author":"S Sourbron","year":"2006","unstructured":"Sourbron S, Dujardin M, Makkat S, Luypaert R (2006) Pixel-by-pixel deconvolution of bolus-tracking data: optimization and implementation. Phys Med Biol 52:429\u2013447. https:\/\/doi.org\/10.1088\/0031-9155\/52\/2\/009","journal-title":"Phys Med Biol"},{"key":"8229_CR27","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1161\/01.res.10.3.393","volume":"10","author":"KL Zierler","year":"1962","unstructured":"Zierler KL (1962) Theoretical basis of indicator-dilution methods for measuring flow and volume. Circ Res 10:393\u2013407. https:\/\/doi.org\/10.1161\/01.res.10.3.393","journal-title":"Circ Res"},{"key":"8229_CR28","doi-asserted-by":"publisher","unstructured":"Meier P, Zierler KL (1954) On the theory of the indicator-dilution method for measurement of blood flow and volume. J Appl Physiol 6:731\u2013744. https:\/\/doi.org\/10.1152\/jappl.1954.6.12.731","DOI":"10.1152\/jappl.1954.6.12.731"},{"key":"8229_CR29","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1007\/s11548-014-1090-0","volume":"10","author":"P Kohlmann","year":"2015","unstructured":"Kohlmann P, Strehlow J, Jobst B et al (2015) Automatic lung segmentation method for MRI-based lung perfusion studies of patients with chronic obstructive pulmonary disease. Int J Comput Assist Radiol Surg 10:403\u2013417. https:\/\/doi.org\/10.1007\/s11548-014-1090-0","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"8229_CR30","doi-asserted-by":"publisher","first-page":"2371","DOI":"10.1016\/j.ejrad.2013.08.018","volume":"82","author":"G Bauman","year":"2013","unstructured":"Bauman G, Puderbach M, Heimann T et al (2013) Validation of Fourier decomposition MRI with dynamic contrast-enhanced MRI using visual and automated scoring of pulmonary perfusion in young cystic fibrosis patients. Eur J Radiol 82:2371\u20132377. https:\/\/doi.org\/10.1016\/j.ejrad.2013.08.018","journal-title":"Eur J Radiol"},{"key":"8229_CR31","doi-asserted-by":"publisher","first-page":"2502","DOI":"10.1007\/s00330-019-06577-y","volume":"30","author":"P Konietzke","year":"2020","unstructured":"Konietzke P, Wielp\u00fctz MO, Wagner WL et al (2020) Quantitative CT detects progression in COPD patients with severe emphysema in a 3-month interval. Eur Radiol 30:2502\u20132512. https:\/\/doi.org\/10.1007\/s00330-019-06577-y","journal-title":"Eur Radiol"},{"key":"8229_CR32","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1007\/s00330-017-5030-6","volume":"28","author":"BJ Jobst","year":"2018","unstructured":"Jobst BJ, Weinheimer O, Trauth M et al (2018) Effect of smoking cessation on quantitative computed tomography in smokers at risk in a lung cancer screening population. Eur Radiol 28:807\u2013815. https:\/\/doi.org\/10.1007\/s00330-017-5030-6","journal-title":"Eur Radiol"},{"key":"8229_CR33","doi-asserted-by":"publisher","first-page":"1711","DOI":"10.1038\/nm.2971","volume":"18","author":"CJ Galb\u00e1n","year":"2012","unstructured":"Galb\u00e1n CJ, Han MK, Boes JL et al (2012) Computed tomography\u2013based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression. Nat Med 18:1711\u20131715. https:\/\/doi.org\/10.1038\/nm.2971","journal-title":"Nat Med"},{"key":"8229_CR34","doi-asserted-by":"publisher","first-page":"e70","DOI":"10.1164\/rccm.201908-1590st","volume":"200","author":"BL Graham","year":"2019","unstructured":"Graham BL, Steenbruggen I, Miller MR et al (2019) Standardization of spirometry 2019 update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Resp Crit Care 200:e70\u2013e88. https:\/\/doi.org\/10.1164\/rccm.201908-1590st","journal-title":"Am J Resp Crit Care"},{"key":"8229_CR35","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1097\/rli.0b013e3181bc2d0c","volume":"45","author":"M Ingrisch","year":"2010","unstructured":"Ingrisch M, Dietrich O, Attenberger UI et al (2010) Quantitative pulmonary perfusion magnetic resonance imaging. Invest Radiol 45:7\u201314. https:\/\/doi.org\/10.1097\/rli.0b013e3181bc2d0c","journal-title":"Invest Radiol"},{"key":"8229_CR36","doi-asserted-by":"publisher","unstructured":"Heimann T, Eichinger M, Bauman G et al (2012) Automated scoring of regional lung perfusion in children from contrast enhanced 3D MRI. Proc SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83150U. https:\/\/doi.org\/10.1117\/12.911946","DOI":"10.1117\/12.911946"},{"key":"8229_CR37","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.jcf.2016.12.004","volume":"16","author":"TA Altes","year":"2017","unstructured":"Altes TA, Johnson M, Fidler M et al (2017) Use of hyperpolarized helium-3 MRI to assess response to ivacaftor treatment in patients with cystic fibrosis. J Cyst Fibros 16:267\u2013274. https:\/\/doi.org\/10.1016\/j.jcf.2016.12.004","journal-title":"J Cyst Fibros"},{"key":"8229_CR38","doi-asserted-by":"publisher","first-page":"1802188","DOI":"10.1183\/13993003.02188-2018","volume":"53","author":"JH Rayment","year":"2019","unstructured":"Rayment JH, Couch MJ, McDonald N et al (2019) Hyperpolarised 129Xe magnetic resonance imaging to monitor treatment response in children with cystic fibrosis. Eur Respir J 53:1802188. https:\/\/doi.org\/10.1183\/13993003.02188-2018","journal-title":"Eur Respir J"},{"key":"8229_CR39","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1164\/ajrccm\/141.4_pt_1.895","volume":"141","author":"JA Barbera","year":"1990","unstructured":"Barbera JA, Ramirez J, Roca J et al (1990) Lung structure and gas exchange in mild chronic obstructive pulmonary disease. Am Rev Respir Dis 141:895\u2013901. https:\/\/doi.org\/10.1164\/ajrccm\/141.4_pt_1.895","journal-title":"Am Rev Respir Dis"},{"key":"8229_CR40","doi-asserted-by":"publisher","first-page":"7485","DOI":"10.1073\/pnas.0913880107","volume":"107","author":"SK Alford","year":"2010","unstructured":"Alford SK, van Beek EJ, McLennan G, Hoffman EA (2010) Heterogeneity of pulmonary perfusion as a mechanistic image-based phenotype in emphysema susceptible smokers. Proc Natl Acad Sci USA 107:7485\u20137490. https:\/\/doi.org\/10.1073\/pnas.0913880107","journal-title":"Proc Natl Acad Sci USA"},{"key":"8229_CR41","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1016\/j.acra.2019.02.003","volume":"26","author":"WW Labaki","year":"2019","unstructured":"Labaki WW, Gu T, Murray S et al (2019) Voxel-wise longitudinal parametric response mapping analysis of chest computed tomography in smokers. Acad Radiol 26:306\u2013312. https:\/\/doi.org\/10.1016\/j.acra.2019.02.003","journal-title":"Acad Radiol"},{"key":"8229_CR42","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1016\/j.acra.2014.08.015","volume":"22","author":"JL Boes","year":"2015","unstructured":"Boes JL, Hoff BA, Bule M et al (2015) Parametric response mapping monitors temporal changes on lung CT scans in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS). Acad Radiol 22:186\u2013194. https:\/\/doi.org\/10.1016\/j.acra.2014.08.015","journal-title":"Acad Radiol"},{"key":"8229_CR43","doi-asserted-by":"publisher","first-page":"1086","DOI":"10.1164\/rccm.201805-0995oc","volume":"199","author":"J Vogel-Claussen","year":"2019","unstructured":"Vogel-Claussen J, Sch\u00f6nfeld C-O, Kaireit TF et al (2019) Effect of indacaterol\/glycopyrronium on pulmonary perfusion and ventilation in hyperinflated patients with chronic obstructive pulmonary disease (CLAIM). A double-blind, randomized, crossover trial. Am J Resp Crit Care 199:1086\u20131096. https:\/\/doi.org\/10.1164\/rccm.201805-0995oc","journal-title":"Am J Resp Crit Care"},{"key":"8229_CR44","doi-asserted-by":"publisher","first-page":"510","DOI":"10.3109\/15412555.2014.948990","volume":"11","author":"Y Xia","year":"2014","unstructured":"Xia Y, Guan Y, Fan L et al (2014) Dynamic contrast enhanced magnetic resonance perfusion imaging in high-risk smokers and smoking-related COPD: correlations with pulmonary function tests and quantitative computed tomography. COPD 11:510\u2013520. https:\/\/doi.org\/10.3109\/15412555.2014.948990","journal-title":"COPD"}],"container-title":["European Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-021-08229-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00330-021-08229-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-021-08229-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T15:05:35Z","timestamp":1645542335000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00330-021-08229-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,22]]},"references-count":44,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["8229"],"URL":"https:\/\/doi.org\/10.1007\/s00330-021-08229-6","relation":{},"ISSN":["0938-7994","1432-1084"],"issn-type":[{"value":"0938-7994","type":"print"},{"value":"1432-1084","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,22]]},"assertion":[{"value":"7 May 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 July 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 February 2022","order":5,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Update","order":6,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"In this article the following funding information was added: Open Access funding enabled and organized by Projekt DEAL.","order":7,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The scientific guarantor of this publication is Prof. Dr. med. Mark O. Wielp\u00fctz, EDIR, MHBA.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Guarantor"}},{"value":"The authors of this manuscript declare relationships with the following companies: Marilisa Schiwek and Frank Risse are\u00a0employees of Boehringer Ingelheim.The (remaining) authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Carina Ittrich kindly provided statistical advice for this manuscript.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was obtained from all subjects in this study.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Institutional Review Board approval was obtained.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"\u2022 retrospective\u2022 cross-sectional study\u2022 performed at one institution","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}