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Makimoto K, Hogg JC, Bourbeau J, Tan WC, Kirby M. Enhancing COPD classification using combined quantitative computed tomography and texture-based radiomics: a CanCOLD cohort study. ERJ Open Res 2024; 10:00968-2023. [PMID: 39040582 PMCID: PMC11261383 DOI: 10.1183/23120541.00968-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 03/13/2024] [Indexed: 07/24/2024] Open
Abstract
Background Recent advances in texture-based computed tomography (CT) radiomics have demonstrated its potential for classifying COPD. Methods Participants from the Canadian Cohort Obstructive Lung Disease (CanCOLD) study were evaluated. A total of 108 features were included: eight quantitative CT (qCT), 95 texture-based radiomic and five demographic features. Machine-learning models included demographics along with texture-based radiomics and/or qCT. Combinations of five feature selection and five classification methods were evaluated; a training dataset was used for feature selection and to train the models, and a testing dataset was used for model evaluation. Models for classifying COPD status and severity were evaluated using the area under the receiver operating characteristic curve (AUC) with DeLong's test for comparison. SHapely Additive exPlanations (SHAP) analysis was used to investigate the features selected. Results A total of 1204 participants were evaluated (n=602 no COPD; n=602 COPD). There were no differences between the groups for sex (p=0.77) or body mass index (p=0.21). For classifying COPD status, the combination of demographics, texture-based radiomics and qCT performed better (AUC=0.87) than the combination of demographics and texture-based radiomics (AUC=0.81, p<0.05) or qCT alone (AUC=0.84, p<0.05). Similarly, for classifying COPD severity, the combination of demographics, texture-based radiomics and qCT performed better (AUC=0.81) than demographics and texture-based radiomics (AUC=0.72, p<0.05) or qCT alone (AUC=0.79, p<0.05). Texture-based radiomics and qCT features were among the top five features selected (15th percentile of the CT density histogram, CT total airway count, pack-years, CT grey-level distance zone matrix zone distance entropy, CT low-attenuation clusters) for classifying COPD status. Conclusion Texture-based radiomics and conventional qCT features in combination improve machine‑learning models for classification of COPD status and severity.
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Affiliation(s)
| | - James C. Hogg
- Center for Heart, Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Jean Bourbeau
- Montreal Chest Institute of the Royal Victoria Hospital, McGill University Health Centre, Montreal, QC, Canada
- Respiratory Epidemiology and Clinical Research Unit, Research Institute of McGill University Health Centre, Montreal, QC, Canada
| | - Wan C. Tan
- Center for Heart, Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Miranda Kirby
- Toronto Metropolitan University, Toronto, ON, Canada
- Center for Heart, Lung Innovation, University of British Columbia, Vancouver, BC, Canada
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Dudurych I, Pelgrim GJ, Sidorenkov G, Garcia-Uceda A, Petersen J, Slebos DJ, de Bock GH, van den Berge M, de Bruijne M, Vliegenthart R. Low-Dose CT-derived Bronchial Parameters in Individuals with Healthy Lungs. Radiology 2024; 311:e232677. [PMID: 38916504 DOI: 10.1148/radiol.232677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Background CT-derived bronchial parameters have been linked to chronic obstructive pulmonary disease and asthma severity, but little is known about these parameters in healthy individuals. Purpose To investigate the distribution of bronchial parameters at low-dose CT in individuals with healthy lungs from a Dutch general population. Materials and Methods In this prospective study, low-dose chest CT performed between May 2017 and October 2022 were obtained from participants who had completed the second-round assessment of the prospective, longitudinal Imaging in Lifelines study. Participants were aged at least 45 years, and those with abnormal spirometry, self-reported respiratory disease, or signs of lung disease at CT were excluded. Airway lumens and walls were segmented automatically. The square root of the bronchial wall area of a hypothetical airway with an internal perimeter of 10 mm (Pi10), luminal area (LA), wall thickness (WT), and wall area percentage were calculated. Associations between sex, age, height, weight, smoking status, and bronchial parameters were assessed using univariable and multivariable analyses. Results The study sample was composed of 8869 participants with healthy lungs (mean age, 60.9 years ± 10.4 [SD]; 4841 [54.6%] female participants), including 3672 (41.4%) never-smokers and 1197 (13.5%) individuals who currently smoke. Bronchial parameters for male participants were higher than those for female participants (Pi10, slope [β] range = 3.49-3.66 mm; LA, β range = 25.40-29.76 mm2; WT, β range = 0.98-1.03 mm; all P < .001). Increasing age correlated with higher Pi10, LA, and WT (r2 range = 0.06-0.09, 0.02-0.01, and 0.02-0.07, respectively; all P < .001). Never-smoking individuals had the lowest Pi10 followed by formerly smoking and currently smoking individuals (3.62 mm ± 0.13, 3.68 mm ± 0.14, and 3.70 mm ± 0.14, respectively; all P < .001). In multivariable regression models, age, sex, height, weight, and smoking history explained up to 46% of the variation in bronchial parameters. Conclusion In healthy individuals, bronchial parameters differed by sex, height, weight, and smoking history; male sex and increasing age were associated with wider lumens and thicker walls. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Emrich and Varga-Szemes in this issue.
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Affiliation(s)
- Ivan Dudurych
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
| | - Gert-Jan Pelgrim
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
| | - Grigory Sidorenkov
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
| | - Antonio Garcia-Uceda
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
| | - Jens Petersen
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
| | - Dirk-Jan Slebos
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
| | - Geertruida H de Bock
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
| | - Maarten van den Berge
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
| | - Marleen de Bruijne
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
| | - Rozemarijn Vliegenthart
- From the Departments of Radiology (I.D., G.J.P., G.S., R.V.), Epidemiology (G.S., G.H.d.B.), and Pulmonology (D.J.S., M.v.d.B.), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 GZ Groningen, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (A.G.U., M.d.B.); Department of Computer Science, Copenhagen University, Copenhagen, Denmark (J.P., M.d.B.); and Department of Oncology, Rigshospitalet, Copenhagen, Denmark (J.P.)
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Vameghestahbanati M, Kingdom L, Hoffman EA, Kirby M, Allen NB, Angelini E, Bertoni A, Hamid Q, Hogg JC, Jacobs DR, Laine A, Maltais F, Michos ED, Sack C, Sin D, Watson KE, Wysoczanksi A, Couper D, Cooper C, Han M, Woodruff P, Tan WC, Bourbeau J, Barr RG, Smith BM. Airway tree caliber heterogeneity and airflow obstruction among older adults. J Appl Physiol (1985) 2024; 136:1144-1156. [PMID: 38420676 DOI: 10.1152/japplphysiol.00694.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/07/2024] [Accepted: 02/22/2024] [Indexed: 03/02/2024] Open
Abstract
Smaller mean airway tree caliber is associated with airflow obstruction and chronic obstructive pulmonary disease (COPD). We investigated whether airway tree caliber heterogeneity was associated with airflow obstruction and COPD. Two community-based cohorts (MESA Lung, CanCOLD) and a longitudinal case-control study of COPD (SPIROMICS) performed spirometry and computed tomography measurements of airway lumen diameters at standard anatomical locations (trachea-to-subsegments) and total lung volume. Percent-predicted airway lumen diameters were calculated using sex-specific reference equations accounting for age, height, and lung volume. The association of airway tree caliber heterogeneity, quantified as the standard deviation (SD) of percent-predicted airway lumen diameters, with baseline forced expired volume in 1-second (FEV1), FEV1/forced vital capacity (FEV1/FVC) and COPD, as well as longitudinal spirometry, were assessed using regression models adjusted for age, sex, height, race-ethnicity, and mean airway tree caliber. Among 2,505 MESA Lung participants (means ± SD age: 69 ± 9 yr; 53% female, mean airway tree caliber: 99 ± 10% predicted, airway tree caliber heterogeneity: 14 ± 5%; median follow-up: 6.1 yr), participants in the highest quartile of airway tree caliber heterogeneity exhibited lower FEV1 (adjusted mean difference: -125 mL, 95%CI: -171,-79), lower FEV1/FVC (adjusted mean difference: -0.01, 95%CI: -0.02,-0.01), and higher odds of COPD (adjusted odds ratio: 1.42, 95%CI: 1.01-2.02) when compared with the lowest quartile, whereas longitudinal changes in FEV1 and FEV1/FVC did not differ significantly. Observations in CanCOLD and SPIROMICS were consistent. Among older adults, airway tree caliber heterogeneity was associated with airflow obstruction and COPD at baseline but was not associated with longitudinal changes in spirometry.NEW & NOTEWORTHY In this study, by leveraging two community-based samples and a case-control study of heavy smokers, we show that among older adults, airway tree caliber heterogeneity quantified by CT is associated with airflow obstruction and COPD independent of age, sex, height, race-ethnicity, and dysanapsis. These observations suggest that airway tree caliber heterogeneity is a structural trait associated with low baseline lung function and normal decline trajectory that is relevant to COPD.
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Affiliation(s)
| | - Leina Kingdom
- Department of Medicine, McGill University, Montreal, Quebec, Canada
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, Iowa, United States
| | - Miranda Kirby
- Department of Physics, Ryerson University, Toronto, Ontario, Canada
| | - Norrina B Allen
- Center for Translational Metabolism and Health, Institute for Public Health and Medicine, Northwestern University, Chicago, Illinois, United States
| | - Elsa Angelini
- Faculty of Medicine, Imperial College London, London, United Kingdom
- Department of Medicine, Columbia University, New York, New York, United States
| | - Alain Bertoni
- Department of Public Health Sciences, Wake Forest University, Winston-Salem, North Carolina, United States
| | - Qutayba Hamid
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Faculty of Medicine, University of Sharjah, Sharjah, United Arab Emirates
| | - James C Hogg
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - David R Jacobs
- School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - Andrew Laine
- Department of Medicine, Columbia University, New York, New York, United States
| | - Francois Maltais
- Faculty of Medicine , University of Laval, Laval, Quebec, Canada
| | - Erin D Michos
- Faculty of Medicine, Johns Hopkins University, Baltimore, Maryland, United States
| | - Coralynn Sack
- Department of Medicine, University of Washington, Seattle, Washington, United States
| | - Don Sin
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - Karol E Watson
- Department of Medicine, University of California, Los Angeles, California, United States
| | - Artur Wysoczanksi
- Department of Medicine, Columbia University, New York, New York, United States
| | - David Couper
- Department of Biostatistics, University of North Carolina, North Carolina, United States
| | - Christopher Cooper
- Department of Medicine, University of California, Los Angeles, California, United States
| | - Meilan Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, Michigan, United States
| | - Prescott Woodruff
- Division of Pulmonary and Critical Care Medicine, University of California, San Francisco, California, United States
| | - Wan C Tan
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jean Bourbeau
- Department of Medicine, McGill University, Montreal, Quebec, Canada
| | - R Graham Barr
- Department of Medicine, Columbia University, New York, New York, United States
| | - Benjamin M Smith
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Medicine, Columbia University, New York, New York, United States
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Genkin D, Zanette B, Grzela P, Benkert T, Subbarao P, Moraes TJ, Katz S, Ratjen F, Santyr G, Kirby M. Semiautomated Segmentation and Analysis of Airway Lumen in Pediatric Patients Using Ultra Short Echo Time MRI. Acad Radiol 2024; 31:648-659. [PMID: 37550154 DOI: 10.1016/j.acra.2023.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/06/2023] [Accepted: 07/10/2023] [Indexed: 08/09/2023]
Abstract
RATIONALE AND OBJECTIVES Ultra short echo time (UTE) magnetic resonance imaging (MRI) pulse sequences have shown promise for airway assessment, but the feasibility and repeatability in the pediatric lung are unknown. The purpose of this work was to develop a semiautomated UTE MRI airway segmentation pipeline from the trachea-to-tertiary airways in pediatric participants and assess repeatability and lumen diameter correlations to lung function. MATERIALS AND METHODS A total of 29 participants (n = 7 healthy, n = 11 cystic fibrosis, n = 6 asthma, and n = 5 ex-preterm), aged 7-18 years, were imaged using a 3D stack-of-spirals UTE examination at 3 T. Two independent observers performed airway segmentations using a pipeline developed in-house; observer 1 repeated segmentations 1 month later. Segmentations were extracted using region-growing with leak detection, then manually edited if required. The airway trees were skeletonized, pruned, and labeled. Airway lumen diameter measurements were extracted using ray casting. Intra- and interobserver variability was assessed using the Sørensen-Dice coefficient (DSC) and intra-class correlation coefficient (ICC). Correlations between lumen diameter and pulmonary function were assessed using Spearman's correlation coefficient. RESULTS For airway segmentations and lumen diameter, intra- and interobserver DSCs were 0.88 and 0.80, while ICCs were 0.95 and 0.89, respectively. The variability increased from the trachea-to-tertiary airways for intra- (DSC: 0.91-0.64; ICC: 0.91-0.49) and interobserver (DSC: 0.84-0.51; ICC: 0.89-0.21) measurements. Lumen diameter was significantly correlated with forced expiratory volume in 1 second and forced vital capacity (P < .05). CONCLUSION UTE MRI airway segmentation from the trachea-to-tertiary airways in pediatric participants across a range of diseases is feasible. The UTE MRI-derived lumen measurements were repeatable and correlated with lung function.
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Affiliation(s)
- Daniel Genkin
- Department of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada (D.G.)
| | - Brandon Zanette
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.)
| | - Patrick Grzela
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.)
| | - Thomas Benkert
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (T.B.)
| | - Padmaja Subbarao
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.); Department of Pediatrics, University of Toronto, Toronto, ON, Canada (P.S., T.J.M., F.R.)
| | - Theo J Moraes
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.); Department of Pediatrics, University of Toronto, Toronto, ON, Canada (P.S., T.J.M., F.R.)
| | - Sherri Katz
- Department of Pediatrics, University of Ottawa, Ottawa, ON, Canada (S.K.); Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada (S.K.)
| | - Felix Ratjen
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.); Department of Pediatrics, University of Toronto, Toronto, ON, Canada (P.S., T.J.M., F.R.)
| | - Giles Santyr
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada (B.Z., P.G., P.S., T.J.M., F.R., G.S.); Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada (G.S.)
| | - Miranda Kirby
- Department of Physics, Toronto Metropolitan University, Kerr Hall South Bldg., Room KHS-344, 350 Victoria St., Toronto, ON M5B 2K3, Canada (M.K.).
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Ortiz-Puerta D, Diaz O, Retamal J, Hurtado DE. Morphometric analysis of airways in pre-COPD and mild COPD lungs using continuous surface representations of the bronchial lumen. Front Bioeng Biotechnol 2023; 11:1271760. [PMID: 38192638 PMCID: PMC10773673 DOI: 10.3389/fbioe.2023.1271760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 12/07/2023] [Indexed: 01/10/2024] Open
Abstract
Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a prevalent respiratory disease that presents a high rate of underdiagnosis during onset and early stages. Studies have shown that in mild COPD patients, remodeling of the small airways occurs concurrently with morphological changes in the proximal airways. Despite this evidence, the geometrical study of the airway tree from computed tomography (CT) lung images remains underexplored due to poor representations and limited tools to characterize the airway structure. Methods: We perform a comprehensive morphometric study of the proximal airways based on geometrical measures associated with the different airway generations. To this end, we leverage the geometric flexibility of the Snakes IsoGeometric Analysis method to accurately represent and characterize the airway luminal surface and volume informed by CT images of the respiratory tree. Based on this framework, we study the airway geometry of smoking pre-COPD and mild COPD individuals. Results: Our results show a significant difference between groups in airway volume, length, luminal eccentricity, minimum radius, and surface-area-to-volume ratio in the most distal airways. Discussion: Our findings suggest a higher degree of airway narrowing and collapse in COPD patients when compared to pre-COPD patients. We envision that our work has the potential to deliver a comprehensive tool for assessing morphological changes in airway geometry that take place in the early stages of COPD.
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Affiliation(s)
- David Ortiz-Puerta
- Department of Structural and Geotechnical Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Orlando Diaz
- Department of Intensive Care Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Jaime Retamal
- Department of Intensive Care Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Daniel E. Hurtado
- Department of Structural and Geotechnical Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile
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Kirby M, Smith BM. Quantitative CT Scan Imaging of the Airways for Diagnosis and Management of Lung Disease. Chest 2023; 164:1150-1158. [PMID: 36871841 PMCID: PMC10792293 DOI: 10.1016/j.chest.2023.02.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 02/23/2023] [Accepted: 02/23/2023] [Indexed: 03/06/2023] Open
Abstract
CT scan imaging provides high-resolution images of the lungs in patients with chronic respiratory diseases. Extensive research over the last several decades has focused on developing novel quantitative CT scan airway measurements that reflect abnormal airway structure. Despite many observational studies demonstrating that associations between CT scan airway measurements and clinically important outcomes such as morbidity, mortality, and lung function decline, few quantitative CT scan measurements are applied in clinical practice. This article provides an overview of the relevant methodologic considerations for implementing quantitative CT scan airway analyses and provides a review of the scientific literature involving quantitative CT scan airway measurements used in clinical or randomized trials and observational studies of humans. We also discuss emerging evidence for the clinical usefulness of quantitative CT scan imaging of the airways and discuss what is required to bridge the gap between research and clinical application. CT scan airway measurements continue to improve our understanding of disease pathophysiologic features, diagnosis, and outcomes. However, a literature review revealed a need for studies evaluating clinical benefit when quantitative CT scan imaging is applied in the clinical setting. Technical standards for quantitative CT scan imaging of the airways and high-quality evidence of clinical benefit from management guided by quantitative CT scan imaging of the airways are required.
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Affiliation(s)
- Miranda Kirby
- Department of Physics, Toronto Metropolitan University, Toronto, ON, Canada; iBEST, St. Michael's Hospital, Toronto, ON, Canada.
| | - Benjamin M Smith
- Department of Medicine, McGill University, Montreal, QC, Canada; Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY
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Saha PK, Nadeem SA, Comellas AP. A Survey on Artificial Intelligence in Pulmonary Imaging. WILEY INTERDISCIPLINARY REVIEWS. DATA MINING AND KNOWLEDGE DISCOVERY 2023; 13:e1510. [PMID: 38249785 PMCID: PMC10796150 DOI: 10.1002/widm.1510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 06/21/2023] [Indexed: 01/23/2024]
Abstract
Over the last decade, deep learning (DL) has contributed a paradigm shift in computer vision and image recognition creating widespread opportunities of using artificial intelligence in research as well as industrial applications. DL has been extensively studied in medical imaging applications, including those related to pulmonary diseases. Chronic obstructive pulmonary disease, asthma, lung cancer, pneumonia, and, more recently, COVID-19 are common lung diseases affecting nearly 7.4% of world population. Pulmonary imaging has been widely investigated toward improving our understanding of disease etiologies and early diagnosis and assessment of disease progression and clinical outcomes. DL has been broadly applied to solve various pulmonary image processing challenges including classification, recognition, registration, and segmentation. This paper presents a survey of pulmonary diseases, roles of imaging in translational and clinical pulmonary research, and applications of different DL architectures and methods in pulmonary imaging with emphasis on DL-based segmentation of major pulmonary anatomies such as lung volumes, lung lobes, pulmonary vessels, and airways as well as thoracic musculoskeletal anatomies related to pulmonary diseases.
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Affiliation(s)
- Punam K Saha
- Departments of Radiology and Electrical and Computer Engineering, University of Iowa, Iowa City, IA, 52242
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Dai Q, Zhu X, Zhang J, Dong Z, Pompeo E, Zheng J, Shi J. The utility of quantitative computed tomography in cohort studies of chronic obstructive pulmonary disease: a narrative review. J Thorac Dis 2023; 15:5784-5800. [PMID: 37969311 PMCID: PMC10636446 DOI: 10.21037/jtd-23-1421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 09/27/2023] [Indexed: 11/17/2023]
Abstract
Background and Objective Chronic obstructive pulmonary disease (COPD) is a significant contributor to global morbidity and mortality. Quantitative computed tomography (QCT), a non-invasive imaging modality, offers the potential to assess lung structure and function in COPD patients. Amidst the coronavirus disease 2019 (COVID-19) pandemic, chest computed tomography (CT) scans have emerged as a viable alternative for assessing pulmonary function (e.g., spirometry), minimizing the risk of aerosolized virus transmission. However, the clinical application of QCT measurements is not yet widespread enough, necessitating broader validation to determine its usefulness in COPD management. Methods We conducted a search in the PubMed database in English from January 1, 2013 to April 20, 2023, using keywords and controlled vocabulary related to QCT, COPD, and cohort studies. Key Content and Findings Existing studies have demonstrated the potential of QCT in providing valuable information on lung volume, airway geometry, airway wall thickness, emphysema, and lung tissue density in COPD patients. Moreover, QCT values have shown robust correlations with pulmonary function tests, and can predict exacerbation risk and mortality in patients with COPD. QCT can even discern COPD subtypes based on phenotypic characteristics such as emphysema predominance, supporting targeted management and interventions. Conclusions QCT has shown promise in cohort studies related to COPD, since it can provide critical insights into the pathogenesis and progression of the disease. Further research is necessary to determine the clinical significance of QCT measurements for COPD management.
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Affiliation(s)
- Qi Dai
- School of Medicine, Tongji University, Shanghai, China
- Department of Radiology, Ningbo No.2 Hospitall, Ningbo, China
| | - Xiaoxiao Zhu
- Department of Respiratory and Critical Care Medicine, Ningbo No.2 Hospital, Ningbo, China
| | - Jingfeng Zhang
- Department of Radiology, Ningbo No.2 Hospitall, Ningbo, China
| | - Zhaoxing Dong
- Department of Respiratory and Critical Care Medicine, Ningbo No.2 Hospital, Ningbo, China
| | - Eugenio Pompeo
- Department of Thoracic Surgery, Policlinico Tor Vergata University, Rome, Italy
| | - Jianjun Zheng
- Department of Radiology, Ningbo No.2 Hospitall, Ningbo, China
| | - Jingyun Shi
- School of Medicine, Tongji University, Shanghai, China
- Department of Radiology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
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9
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Nordenmark LH, Hellqvist Å, Emson C, Diver S, Porsbjerg C, Griffiths JM, Newell JD, Peterson S, Pawlikowska B, Parnes JR, Megally A, Colice G, Brightling CE. Tezepelumab and Mucus Plugs in Patients with Moderate-to-Severe Asthma. NEJM EVIDENCE 2023; 2:EVIDoa2300135. [PMID: 38320181 DOI: 10.1056/evidoa2300135] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
BACKGROUND: Mucus plugs in asthmatic airways are associated with airway obstruction and the activity of inflammatory cytokines, specifically interleukin (IL)-5 and IL-13, and they may provide an opportunity for targeted therapy. This analysis of the CASCADE (Study to Evaluate Tezepelumab on Airway Inflammation in Adults With Uncontrolled Asthma) placebo-controlled trial used computed tomography (CT) imaging to assess mucus plugs in patients with moderate-to-severe, uncontrolled asthma who received tezepelumab or placebo. METHODS: CASCADE was an exploratory, double-blind, placebo-controlled trial examining the anti-inflammatory effect of tezepelumab. Patients (aged 18 to 75 years old) were randomly assigned 1:1 to 210 mg tezepelumab or placebo every 4 weeks subcutaneously for at least 28 weeks. An expert radiologist, blinded to treatment groups and time points, objectively scored 18 lung segments for the presence of mucus plugs in CT scans obtained before and after treatment; greater numbers of mucus plugs resulted in higher mucus plug scores. RESULTS: Absolute change from baseline (mean [±standard deviation]) in mucus plug score was −1.7±2.6 in patients receiving tezepelumab (n=37) and 0.0±1.4 in patients receiving placebo (n=45). At baseline, mucus plug scores correlated positively with levels of inflammatory biomarkers (blood eosinophils, eosinophil-derived neurotoxin, fractional exhaled nitric oxide, IL-5, and IL-13) and negatively with lung function measures (prebronchodilator forced expiratory volume in 1 second and forced mid-expiratory flow). In tezepelumab recipients, reductions in mucus plug scores were correlated with improvements in lung function and reductions in blood eosinophil count and levels of eosinophil-derived neurotoxin, a biomarker of eosinophilic degranulation. CONCLUSIONS: Tezepelumab was associated with a reduction in occlusive mucus plugs versus placebo in a randomized controlled trial in patients with moderate-to-severe, uncontrolled asthma. (Funded by AstraZeneca and Amgen Inc.; ClinicalTrials.gov number, NCT03688074.)
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Affiliation(s)
- Lars H Nordenmark
- Late-Stage Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Oslo
| | - Åsa Hellqvist
- Biometrics, Late-Stage Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Claire Emson
- Translational Science and Experimental Medicine, Research and Early Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD
| | - Sarah Diver
- National Institute for Health and Care Research, Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom
| | - Celeste Porsbjerg
- Department of Respiratory Medicine, Bispebjerg University Hospital, University of Copenhagen, Copenhagen
| | - Janet M Griffiths
- Translational Science and Experimental Medicine, Research and Early Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD
| | - John D Newell
- Department of Radiology and Biomedical Engineering, University of Iowa, Iowa City
- VIDA Diagnostics, Coralville, IA
| | | | - Beata Pawlikowska
- Late-Stage Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Warsaw, Poland
| | | | - Ayman Megally
- Late-Stage Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD
| | - Gene Colice
- Late-Stage Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD
| | - Christopher E Brightling
- National Institute for Health and Care Research, Leicester Biomedical Research Centre, University of Leicester, Leicester, United Kingdom
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10
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Motahari A, Barr RG, Han MK, Anderson WH, Barjaktarevic I, Bleecker ER, Comellas AP, Cooper CB, Couper DJ, Hansel NN, Kanner RE, Kazerooni EA, Lynch DA, Martinez FJ, Newell JD, Schroeder JD, Smith BM, Woodruff PG, Hoffman EA. Repeatability of Pulmonary Quantitative Computed Tomography Measurements in Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 2023; 208:657-665. [PMID: 37490608 PMCID: PMC10515564 DOI: 10.1164/rccm.202209-1698pp] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 07/24/2023] [Indexed: 07/27/2023] Open
Affiliation(s)
| | - R. Graham Barr
- Department of Medicine and
- Department of Epidemiology, Columbia University College of Medicine, New York, New York
| | | | - Wayne H. Anderson
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Igor Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, University of California Los Angeles Medical Center, Los Angeles, California
| | | | - Alejandro P. Comellas
- Department of Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Christopher B. Cooper
- Department of Medicine and
- Department of Physiology, University of California Los Angeles, Los Angeles, California
| | - David J. Couper
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Nadia N. Hansel
- Department of Medicine, The Johns Hopkins University, Baltimore, Maryland
| | | | - Ella A. Kazerooni
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - David A. Lynch
- Department of Radiology, National Jewish Health, Denver, Colorado
| | | | - John D. Newell
- Department of Radiology and
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
| | | | - Benjamin M. Smith
- Department of Medicine and
- Department of Epidemiology, Columbia University College of Medicine, New York, New York
- Department of Medicine, McGill University, Montreal, Quebec, Canada; and
| | - Prescott G. Woodruff
- Department of Medicine, University of California San Francisco, San Francisco, California
| | - Eric A. Hoffman
- Department of Radiology and
- Department of Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
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11
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Konietzke P, Brunner C, Konietzke M, Wagner WL, Weinheimer O, Heußel CP, Herth FJF, Trudzinski F, Kauczor HU, Wielpütz MO. GOLD stage-specific phenotyping of emphysema and airway disease using quantitative computed tomography. Front Med (Lausanne) 2023; 10:1184784. [PMID: 37534319 PMCID: PMC10393128 DOI: 10.3389/fmed.2023.1184784] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 06/22/2023] [Indexed: 08/04/2023] Open
Abstract
Background In chronic obstructive pulmonary disease (COPD) abnormal lung function is related to emphysema and airway obstruction, but their relative contribution in each GOLD-stage is not fully understood. In this study, we used quantitative computed tomography (QCT) parameters for phenotyping of emphysema and airway abnormalities, and to investigate the relative contribution of QCT emphysema and airway parameters to airflow limitation specifically in each GOLD stage. Methods Non-contrast computed tomography (CT) of 492 patients with COPD former GOLD 0 COPD and COPD stages GOLD 1-4 were evaluated using fully automated software for quantitative CT. Total lung volume (TLV), emphysema index (EI), mean lung density (MLD), and airway wall thickness (WT), total diameter (TD), lumen area (LA), and wall percentage (WP) were calculated for the entire lung, as well as for all lung lobes separately. Results from the 3rd-8th airway generation were aggregated (WT3-8, TD3-8, LA3-8, WP3-8). All subjects underwent whole-body plethysmography (FEV1%pred, VC, RV, TLC). Results EI was higher with increasing GOLD stages with 1.0 ± 1.8% in GOLD 0, 4.5 ± 9.9% in GOLD 1, 19.4 ± 15.8% in GOLD 2, 32.7 ± 13.4% in GOLD 3 and 41.4 ± 10.0% in GOLD 4 subjects (p < 0.001). WP3-8 showed no essential differences between GOLD 0 and GOLD 1, tended to be higher in GOLD 2 with 52.4 ± 7.2%, and was lower in GOLD 4 with 50.6 ± 5.9% (p = 0.010 - p = 0.960). In the upper lobes WP3-8 showed no significant differences between the GOLD stages (p = 0.824), while in the lower lobes the lowest WP3-8 was found in GOLD 0/1 with 49.9 ± 6.5%, while higher values were detected in GOLD 2 with 51.9 ± 6.4% and in GOLD 3/4 with 51.0 ± 6.0% (p < 0.05). In a multilinear regression analysis, the dependent variable FEV1%pred can be predicted by a combination of both the independent variables EI (p < 0.001) and WP3-8 (p < 0.001). Conclusion QCT parameters showed a significant increase of emphysema from GOLD 0-4 COPD. Airway changes showed a different spatial pattern with higher values of relative wall thickness in the lower lobes until GOLD 2 and subsequent lower values in GOLD3/4, whereas there were no significant differences in the upper lobes. Both, EI and WP5-8 are independently correlated with lung function decline.
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Affiliation(s)
- Philip Konietzke
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Christian Brunner
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Marilisa Konietzke
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
| | - Willi Linus Wagner
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Claus Peter Heußel
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Felix J. F. Herth
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Pulmonology, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Franziska Trudzinski
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Pulmonology, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
| | - Mark Oliver Wielpütz
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany
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12
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Abozid H, Kirby M, Nasir N, Hartl S, Breyer-Kohansal R, Breyer MK, Burghuber OC, Bourbeau J, Wouters EFM, Tan W. CT airway remodelling and chronic cough. BMJ Open Respir Res 2023; 10:10/1/e001462. [PMID: 37173074 DOI: 10.1136/bmjresp-2022-001462] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 04/21/2023] [Indexed: 05/15/2023] Open
Abstract
RATIONALE Structural airway changes related to chronic cough (CC) are described in the literature, but so far reported data are rare and non-conclusive. Furthermore, they derive mainly from cohorts with small sample sizes. Advanced CT imaging not only allows airway abnormalities to be quantified, but also to count the number of visible airways. The current study evaluates these airway abnormalities in CC and assesses the contribution of CC in addition to CT findings on the progression of airflow limitation, defined as a decline in forced expiratory volume in 1 s (FEV1) over time. METHODS A total of 1183 males and females aged ≥40 years with thoracic CT scans and valid spirometry from Canadian Obstructive Lung Disease, a Canadian multicentre, population-based study has been included in this analysis. Participants were stratified into 286 never-smokers, 297 ever-smokers with normal lung function and 600 with chronic obstructive pulmonary disease (COPD) of different severity grades. Imaging parameters analyses included total airway count (TAC), airway wall thickness, emphysema as well as parameters for functional small airway disease quantification. RESULTS Irrespective of COPD presence, CC was not related to specific airway and lung structure features. Independent of TAC and emphysema score, CC was highly associated with FEV1 decline over time in the entire study population, particularly in ever-smokers (p<0.0001). CONCLUSION The absence of specific structural CT features independently from COPD presence indicate that other underlying mechanisms are contributing to the symptomatology of CC. On top of derived CT parameters, CC seems to be independently associated with FEV1 decline. TRIAL REGISTRATION NUMBER NCT00920348.
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Affiliation(s)
- Hazim Abozid
- Department of Respiratory and Pulmonary Diseases, Clinic Penzing, Vienna, Austria
- Ludwig Boltzmann Institute for Lung Health, Vienna, Austria
| | - Miranda Kirby
- Department of Physics, Toronto Metropolitan University, Toronto, Ontario, Canada
- Institute for Biomedical Engineering, Science and Technology (iBEST), Unity Health Toronto, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Neha Nasir
- Department of Physics, Toronto Metropolitan University, Toronto, Ontario, Canada
| | - Sylvia Hartl
- Ludwig Boltzmann Institute for Lung Health, Vienna, Austria
- Department of Respiratory and Pulmonary Diseases, Clinic Penzing, Vienna Healthcare Group, Vienna, Austria
| | - Robab Breyer-Kohansal
- Ludwig Boltzmann Institute for Lung Health, Vienna, Austria
- Department of Respiratory and Pulmonary Diseases, Clinic Penzing, Vienna Healthcare Group, Vienna, Austria
| | - Marie-Kathrin Breyer
- Ludwig Boltzmann Institute for Lung Health, Vienna, Austria
- Department of Respiratory and Pulmonary Diseases, Clinic Penzing, Vienna Healthcare Group, Vienna, Austria
| | - Otto C Burghuber
- Ludwig Boltzmann Institute for Lung Health, Vienna, Austria
- Faculty for Medicine, Sigmund Freud University, Vienna, Austria
| | - Jean Bourbeau
- Respiratory Epidemiology and Clinical Research Unit, Research Institute, McGill University, Montreal, Québec, Canada
| | - Emiel F M Wouters
- Ludwig Boltzmann Institute for Lung Health, Vienna, Austria
- Maastricht University Medical Center, Maastricht, The Netherlands
| | - Wan Tan
- Centre for Heart Lung Innovation, University of British Columbia, St Pauls's Hospital, Vancouver, British Columbia, Canada
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13
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Fortis S, Quibrera PM, Comellas AP, Bhatt SP, Tashkin DP, Hoffman EA, Criner GJ, Han MK, Barr RG, Arjomandi M, Dransfield MB, Peters SP, Dolezal BA, Kim V, Putcha N, Rennard SI, Paine R, Kanner RE, Curtis JL, Bowler RP, Martinez FJ, Hansel NN, Krishnan JA, Woodruff PG, Barjaktarevic IZ, Couper D, Anderson WH, Cooper CB. Bronchodilator Responsiveness in Tobacco-Exposed People With or Without COPD. Chest 2023; 163:502-514. [PMID: 36395858 PMCID: PMC9993341 DOI: 10.1016/j.chest.2022.11.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 11/04/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Bronchodilator responsiveness (BDR) in obstructive lung disease varies over time and may be associated with distinct clinical features. RESEARCH QUESTION Is consistent BDR over time (always present) differentially associated with obstructive lung disease features relative to inconsistent (sometimes present) or never (never present) BDR in tobacco-exposed people with or without COPD? STUDY DESIGN AND METHODS We retrospectively analyzed data from 2,269 tobacco-exposed participants in the Subpopulations and Intermediate Outcome Measures in COPD Study with or without COPD. We used various BDR definitions: change of ≥ 200 mL and ≥ 12% in FEV1 (FEV1-BDR), change in FVC (FVC-BDR), and change in in FEV1, FVC or both (ATS-BDR). Using generalized linear models adjusted for demographics, smoking history, FEV1 % predicted after bronchodilator administration, and number of visits that the participant completed, we assessed the association of BDR group: (1) consistent BDR, (2) inconsistent BDR, and (3) never BDR with asthma, CT scan features, blood eosinophil levels, and FEV1 decline in participants without COPD (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage 0) and the entire cohort (participants with or without COPD). RESULTS Both consistent and inconsistent ATS-BDR were associated with asthma history and greater small airways disease (%parametric response mapping functional small airways disease) relative to never ATS-BDR in participants with GOLD stage 0 disease and the entire cohort. We observed similar findings using FEV1-BDR and FVC-BDR definitions. Eosinophils did not vary consistently among BDR groups. Consistent BDR was associated with FEV1 decline over time relative to never BDR in the entire cohort. In participants with GOLD stage 0 disease, both the inconsistent ATS-BDR group (OR, 3.20; 95% CI, 2.21-4.66; P < .001) and consistent ATS-BDR group (OR, 9.48; 95% CI, 3.77-29.12; P < .001) were associated with progression to COPD relative to the never ATS-BDR group. INTERPRETATION Demonstration of BDR, even once, describes an obstructive lung disease phenotype with a history of asthma and greater small airways disease. Consistent demonstration of BDR indicated a high risk of lung function decline over time in the entire cohort and was associated with higher risk of progression to COPD in patients with GOLD stage 0 disease.
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Affiliation(s)
- Spyridon Fortis
- Center for Access & Delivery Research & Evaluation, Iowa City VA Health Care System, Iowa City, IA; Division of Pulmonary, Critical Care and Occupational Medicine, Department of Internal Medicine, University of Iowa Roy J. and Lucille A. Carver College of Medicine, Iowa City, IA.
| | - Pedro M Quibrera
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Alejandro P Comellas
- Division of Pulmonary, Critical Care and Occupational Medicine, Department of Internal Medicine, University of Iowa Roy J. and Lucille A. Carver College of Medicine, Iowa City, IA
| | - Surya P Bhatt
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham VA Medical Center, Birmingham, AL
| | - Donald P Tashkin
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA
| | - Eric A Hoffman
- Departments of Radiology, Biomedical Engineering and Medicine, University of Iowa, Iowa City, IA
| | - Gerard J Criner
- Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine at Temple University, Philadelphia, PA
| | - MeiLan K Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI
| | - R Graham Barr
- Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY
| | - Mehrdad Arjomandi
- Department of Medicine, University of California, San Francisco, CA; San Francisco Veterans Affairs Healthcare System, San Francisco, CA
| | - Mark B Dransfield
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham VA Medical Center, Birmingham, AL; Division of Pulmonary and Critical Care Medicine, Birmingham VA Medical Center, Birmingham, AL
| | - Stephen P Peters
- Section on Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Brett A Dolezal
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA
| | - Victor Kim
- Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine at Temple University, Philadelphia, PA
| | - Nirupama Putcha
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD
| | - Stephen I Rennard
- Division of Pulmonary and Critical Care Medicine, University of Nebraska Medical Center, Omaha, NE
| | - Robert Paine
- Division of Respiratory, Critical Care and Occupational Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, UT
| | - Richard E Kanner
- Division of Respiratory, Critical Care and Occupational Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, UT
| | - Jeffrey L Curtis
- Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI; Medicine Service, VA Ann Arbor Healthcare System, Ann Arbor, MI
| | - Russell P Bowler
- Department of Medicine, National Jewish Medical and Research Center, Denver, CO
| | - Fernando J Martinez
- Departments of Medicine and Genetic Medicine, Weill Cornell Medicine, New York, NY
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD
| | - Jerry A Krishnan
- Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Illinois at Chicago, Chicago, IL
| | | | - Igor Z Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA
| | - David Couper
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Wayne H Anderson
- Division of Pulmonary and Critical Care Medicine, Marsico Lung Institute, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Christopher B Cooper
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA
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14
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McIntosh MJ, Kooner HK, Eddy RL, Wilson A, Serajeddini H, Bhalla A, Licskai C, Mackenzie CA, Yamashita C, Parraga G. CT Mucus Score and 129Xe MRI Ventilation Defects After 2.5 Years' Anti-IL-5Rα in Eosinophilic Asthma. Chest 2023:S0012-3692(23)00189-7. [PMID: 36781102 DOI: 10.1016/j.chest.2023.02.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 02/06/2023] [Accepted: 02/08/2023] [Indexed: 02/13/2023] Open
Abstract
BACKGROUND We previously showed in patients with poorly controlled eosinophilic asthma that a single dose of benralizumab resulted in significantly improved asthma-control-questionnaire (ACQ-6) score and 129Xe MRI ventilation defect percent (VDP), 28 days post-injection, and 129Xe MRI VDP and CT airway mucus occlusions were shown to independently predict this early ACQ-6 response to benralizumab. RESEARCH QUESTION Do early VDP responses at 28 days persist, and do FEV1, fractional exhaled nitric oxide (Feno), and mucus plug score improve during a 2.5 year treatment period? STUDY DESIGN AND METHODS Participants with poorly controlled eosinophilic asthma completed spirometry, ACQ-6, and MRI, 28 days, 1, and 2.5 years after benralizumab; chest CT was acquired at enrollment and 2.5 years later. RESULTS Of 29 participants evaluated at 28 days post-benralizumab, 16 participants returned for follow-up while on therapy at 1 year, and 13 participants were evaluable while on therapy at 2.5 years, post-benralizumab initiation. As compared with 28 days post-benralizumab, ACQ-6 score (2.0 ± 1.4) significantly improved after 1 year (0.5 ± 0.6, P = .02; 95% CI, 0.1-1.1) and 2.5 years (0.5 ± 0.5, P = .03; 95% CI, 0.1-1.1). The mean VDP change at 2.5 years (-4% ± 3%) was greater than the minimal clinically important difference, but not significantly different from VDP measured 28 days post-benralizumab. Mucus score (3 ± 4) was significantly improved at 2.5 years (1 ± 1, P = .03; 95% CI, 0.3-5.5). In six of eight participants with previous occlusions, mucus plugs vanished or substantially diminished 2.5 years later. VDP (P < .001) and mucus score (P < .001) measured at baseline, but not Feno or FEV1, independently predicted ACQ score after 2.5 years. INTERPRETATION In poorly controlled eosinophilic asthma, early MRI VDP responses at 28 days post-benralizumab persisted 2.5 years later, alongside significantly improved mucus score and asthma control.
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Affiliation(s)
- Marrissa J McIntosh
- Robarts Research Institute; Department of Medical Biophysics, Western University, London, ON, Canada
| | - Harkiran K Kooner
- Robarts Research Institute; Department of Medical Biophysics, Western University, London, ON, Canada
| | - Rachel L Eddy
- University of British Columbia Centre for Heart Lung Innovation, St. Paul's Hospital Vancouver, Vancouver, BC, Canada
| | | | | | | | | | - Constance A Mackenzie
- Division of Respirology; Division of Clinical Pharmacology and Toxicology, Department of Medicine, Western University, London, ON, Canada
| | | | - Grace Parraga
- Robarts Research Institute; Department of Medical Biophysics, Western University, London, ON, Canada; Division of Respirology.
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15
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Hsia CCW, Bates JHT, Driehuys B, Fain SB, Goldin JG, Hoffman EA, Hogg JC, Levin DL, Lynch DA, Ochs M, Parraga G, Prisk GK, Smith BM, Tawhai M, Vidal Melo MF, Woods JC, Hopkins SR. Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report. Ann Am Thorac Soc 2023; 20:161-195. [PMID: 36723475 PMCID: PMC9989862 DOI: 10.1513/annalsats.202211-915st] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.
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16
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Kahnert K, Jörres RA, Kauczor HU, Alter P, Trudzinski FC, Herth F, Jobst B, Weinheimer O, Nauck S, Mertsch P, Kauffmann-Guerrero D, Behr J, Bals R, Watz H, Rabe KF, Welte T, Vogelmeier CF, Biederer J. Standardized airway wall thickness Pi10 from routine CT scans of COPD patients as imaging biomarker for disease severity, lung function decline, and mortality. Ther Adv Respir Dis 2023; 17:17534666221148663. [PMID: 36718763 PMCID: PMC9896094 DOI: 10.1177/17534666221148663] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Chest computed tomography (CT) is increasingly used for phenotyping and monitoring of patients with COPD. The aim of this work was to evaluate the association of Pi10 as a measure of standardized airway wall thickness on CT with exacerbations, mortality, and response to triple therapy. METHODS Patients of GOLD grades 1-4 of the COSYCONET cohort with prospective CT scans were included. Pi10 was automatically computed and analyzed for its relationship to COPD severity, comorbidities, lung function, respiratory therapy, and mortality over a 6-year period, using univariate and multivariate comparisons. RESULTS We included n = 433 patients (61%male). Pi10 was dependent on both GOLD grades 1-4 (p = 0.009) and GOLD groups A-D (p = 0.008); it was particularly elevated in group D, and ROC analysis yielded a cut-off of 0.26 cm. Higher Pi10 was associated to lower FEV1 % predicted and higher RV/TLC, moreover the annual changes of lung function parameters (p < 0.05), as well as to an airway-dominated phenotype and a history of myocardial infarction (p = 0.001). These associations were confirmed in multivariate analyses. Pi10 was lower in patients receiving triple therapy, in particular in patients of GOLD groups C and D. Pi10 was also a significant predictor for mortality (p = 0.006), even after including multiple other predictors. CONCLUSION In summary, Pi10 was found to be predictive for the course of the disease in COPD, in particular mortality. The fact that Pi10 was lower in patients with severe COPD receiving triple therapy might hint toward additional effects of this functional therapy on airway remodeling. REGISTRATION ClinicalTrials.gov, Identifier: NCT01245933.
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Affiliation(s)
- Kathrin Kahnert
- Department of Medicine V, Comprehensive Pneumology Center, Member of the German Center for Lung Research (DZL), University Hospital, LMU Munich, Ziemssenstr. 5, Munich 80336, Germany
| | - Rudolf A Jörres
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Ludwig-Maximilians-Universität München, Munich, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany
| | - Peter Alter
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Franziska C Trudzinski
- Thoraxklinik-Heidelberg gGmbH, Translational Lung Research Centre.,Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Felix Herth
- Thoraxklinik-Heidelberg gGmbH, Translational Lung Research Centre.,Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Bertram Jobst
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany
| | - Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany
| | - Sebastian Nauck
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany
| | - Pontus Mertsch
- Department of Medicine V, Comprehensive Pneumology Center, Member of the German Center for Lung Research (DZL), University Hospital, LMU Munich, Munich, Germany
| | - Diego Kauffmann-Guerrero
- Department of Medicine V, Comprehensive Pneumology Center, Member of the German Center for Lung Research (DZL), University Hospital, LMU Munich, Munich, Germany
| | - Jürgen Behr
- Department of Medicine V, Comprehensive Pneumology Center, Member of the German Center for Lung Research (DZL), University Hospital, LMU Munich, Munich, Germany
| | - Robert Bals
- Department of Internal Medicine V - Pulmonology, Allergology, Respiratory Intensive Care Medicine, Saarland University Hospital, Homburg, Germany.,Helmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research (HZI), Saarland University Campus, Saarbrücken, Germany
| | - Henrik Watz
- Pulmonary Research Institute at LungenClinic Grosshansdorf, Airway Research Center North (ARCN), Member of the German Center for Lung Research (DZL), Grosshansdorf, Germany
| | - Klaus F Rabe
- Lung Clinic Grosshansdorf, Airway Research Center (ARCN), Grosshansdorf, German.,Faculty of Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Tobias Welte
- Department of Pneumology, Hannover Medical School, Hannover, Germany
| | - Claus F Vogelmeier
- Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Philipps-University Marburg, Member of the German Center for Lung Research (DZL), Marburg, Germany
| | - Jürgen Biederer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.,Translational Lung Research Centre Heidelberg (TLRC), Member of the German Center for Lung Research, Heidelberg, Germany.,Faculty of Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany.,University of Latvia, Faculty of Medicine, Raina bulvaris 19, Riga, LV-1586 Latvia
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17
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Taskiran NP, Hiura GT, Zhang X, Barr RG, Dashnaw SM, Hoffman EA, Malinsky D, Oelsner EC, Prince MR, Smith BM, Sun Y, Sun Y, Wild JM, Shen W, Hughes EW. Mapping Alveolar Oxygen Partial Pressure in COPD Using Hyperpolarized Helium-3: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study. Tomography 2022; 8:2268-2284. [PMID: 36136886 PMCID: PMC9498778 DOI: 10.3390/tomography8050190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 09/05/2022] [Accepted: 09/05/2022] [Indexed: 11/24/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) and emphysema are characterized by functional and structural damage which increases the spaces for gaseous diffusion and impairs oxygen exchange. Here we explore the potential for hyperpolarized (HP) 3He MRI to characterize lung structure and function in a large-scale population-based study. Participants (n = 54) from the Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study, a nested case-control study of COPD among participants with 10+ packyears underwent HP 3He MRI measuring pAO2, apparent diffusion coefficient (ADC), and ventilation. HP MRI measures were compared to full-lung CT and pulmonary function testing. High ADC values (>0.4 cm2/s) correlated with emphysema and heterogeneity in pAO2 measurements. Strong correlations were found between the heterogeneity of global pAO2 as summarized by its standard deviation (SD) (p < 0.0002) and non-physiologic pAO2 values (p < 0.0001) with percent emphysema on CT. A regional study revealed a strong association between pAO2 SD and visual emphysema severity (p < 0.003) and an association with the paraseptal emphysema subtype (p < 0.04) after adjustment for demographics and smoking status. HP noble gas pAO2 heterogeneity and the fraction of non-physiological pAO2 results increase in mild to moderate COPD. Measurements of pAO2 are sensitive to regional emphysematous damage detected by CT and may be used to probe pulmonary emphysema subtypes. HP noble gas lung MRI provides non-invasive information about COPD severity and lung function without ionizing radiation.
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Affiliation(s)
- Naz P. Taskiran
- Department of Chemical Engineering, Columbia University, New York, NY 10027, USA
- Correspondence: (N.P.T.); (E.W.H.); Tel.: +1-347-3693052 (N.P.T.); +1-626-4838731 (E.W.H.)
| | - Grant T. Hiura
- Division of General Medicine, Columbia University Irving Medial Center, New York, NY 10032, USA
| | - Xuzhe Zhang
- Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
| | - R. Graham Barr
- Division of General Medicine, Columbia University Irving Medial Center, New York, NY 10032, USA
| | - Stephen M. Dashnaw
- Neurological Institute, Radiology, Columbia University, New York, NY 10032, USA
| | - Eric A. Hoffman
- Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA
| | - Daniel Malinsky
- Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Elizabeth C. Oelsner
- Division of General Medicine, Columbia University Irving Medial Center, New York, NY 10032, USA
| | - Martin R. Prince
- Division of General Medicine, Columbia University Irving Medial Center, New York, NY 10032, USA
- Department of Radiology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Benjamin M. Smith
- Division of General Medicine, Columbia University Irving Medial Center, New York, NY 10032, USA
- Department of Medicine, McGill University, Montreal, QC H3G 2M1, Canada
| | - Yanping Sun
- Division of General Medicine, Columbia University Irving Medial Center, New York, NY 10032, USA
| | - Yifei Sun
- Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Jim M. Wild
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield S10 2TN, UK
| | - Wei Shen
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Columbia University Irving Medical Center, New York, NY 10032, USA
- Institute of Human Nutrition, College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, NY 10032, USA
- Columbia Magnetic Resonance Research Center (CMRRC), Columbia University, New York, NY 10027, USA
| | - Emlyn W. Hughes
- Department of Physics, Columbia University, New York, NY 10027, USA
- Correspondence: (N.P.T.); (E.W.H.); Tel.: +1-347-3693052 (N.P.T.); +1-626-4838731 (E.W.H.)
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18
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Kim T, Lim MN, Kim WJ, Ho TT, Lee CH, Chae KJ, Bak SH, Jin GY, Park EK, Choi S. Structural and functional alterations of subjects with cement dust exposure: A longitudinal quantitative computed tomography-based study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 837:155812. [PMID: 35550893 DOI: 10.1016/j.scitotenv.2022.155812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 04/13/2022] [Accepted: 05/05/2022] [Indexed: 06/15/2023]
Abstract
Cement dust exposure (CDE) can be a risk factor for pulmonary disease, causing changes in segmental airways and parenchymal lungs. This study investigates longitudinal alterations in quantitative computed tomography (CT)-based metrics due to CDE. We obtained CT-based airway structural and lung functional metrics from CDE subjects with baseline CT and follow-up CT scans performed three years later. From the CT, we extracted wall thickness (WT) and bifurcation angle (θ) at total lung capacity (TLC) and functional residual capacity (FRC), respectively. We also computed air volume (Vair), tissue volume (Vtissue), global lung shape, percentage of emphysema (Emph%), and more. Clinical measures were used to associate with CT-based metrics. Three years after their baseline, the pulmonary function tests of CDE subjects were similar or improved, but there were significant alterations in the CT-based structural and functional metrics. The follow-up CT scans showed changes in θ at most of the central airways; increased WT at the subgroup bronchi; smaller Vair at TLC at all except the right upper and lower lobes; smaller Vtissue at all lobes in TLC and FRC except for the upper lobes in FRC; smaller global lung shape; and greater Emph% at the right upper and lower lobes. CT-based structural and functional variables are more sensitive to the early identification of CDE subjects, while most clinical lung function changes were not noticeable. We speculate that the significant long-term changes in CT are uniquely observed in CDE subjects, different from smoking-induced structural changes.
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Affiliation(s)
- Taewoo Kim
- School of Mechanical Engineering, Kyungpook National University, Daegu, Republic of Korea
| | - Myoung-Nam Lim
- Biomedical Research Institute, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea
| | - Woo Jin Kim
- Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea
| | - Thao Thi Ho
- School of Mechanical Engineering, Kyungpook National University, Daegu, Republic of Korea
| | - Chang Hyun Lee
- Department of Radiology, College of Medicine, Seoul National University, Seoul, Republic of Korea; Department of Radiology, College of Medicine, The University of Iowa, Iowa City, IA, USA
| | - Kum Ju Chae
- Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - So Hyeon Bak
- Department of Radiology, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea
| | - Gong Yong Jin
- Department of Radiology, College of Medicine, The University of Iowa, Iowa City, IA, USA
| | - Eun-Kee Park
- Department of Medical Humanities and Social Medicine, College of Medicine, Kosin University, Busan, Republic of Korea
| | - Sanghun Choi
- School of Mechanical Engineering, Kyungpook National University, Daegu, Republic of Korea.
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19
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McIntosh MJ, Kooner HK, Eddy RL, Jeimy S, Licskai C, Mackenzie CA, Svenningsen S, Nair P, Yamashita C, Parraga G. Asthma Control, Airway Mucus, and 129Xe MRI Ventilation After a Single Benralizumab Dose. Chest 2022; 162:520-533. [DOI: 10.1016/j.chest.2022.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 02/17/2022] [Accepted: 03/02/2022] [Indexed: 10/18/2022] Open
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20
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Oelsner EC, Krishnaswamy A, Balte PP, Allen NB, Ali T, Anugu P, Andrews H, Arora K, Asaro A, Barr RG, Bertoni AG, Bon J, Boyle R, Chang AA, Chen G, Coady S, Cole SA, Coresh J, Cornell E, Correa A, Couper D, Cushman M, Demmer RT, Elkind MSV, Folsom AR, Fretts AM, Gabriel KP, Gallo L, Gutierrez J, Han MLK, Henderson JM, Howard VJ, Isasi CR, Jacobs Jr DR, Judd SE, Mukaz DK, Kanaya AM, Kandula NR, Kaplan R, Kinney GL, Kucharska-Newton A, Lee JS, Lewis CE, Levine DA, Levitan EB, Levy B, Make B, Malloy K, Manly JJ, Mendoza-Puccini C, Meyer KA, Min YI, Moll M, Moore WC, Mauger D, Ortega VE, Palta P, Parker MM, Phipatanakul W, Post WS, Postow L, Psaty BM, Regan EA, Ring K, Roger VL, Rotter JI, Rundek T, Sacco RL, Schembri M, Schwartz DA, Seshadri S, Shikany JM, Sims M, Hinckley Stukovsky KD, Talavera GA, Tracy RP, Umans JG, Vasan RS, Watson K, Wenzel SE, Winters K, Woodruff PG, Xanthakis V, Zhang Y, Zhang Y, C4R Investigators FT. Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design. Am J Epidemiol 2022; 191:1153-1173. [PMID: 35279711 PMCID: PMC8992336 DOI: 10.1093/aje/kwac032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 01/26/2022] [Accepted: 02/09/2022] [Indexed: 01/26/2023] Open
Abstract
The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and reflects the racial, ethnic, socioeconomic, and geographic diversity of the United States. C4R ascertains SARS-CoV-2 infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey conducted via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations and high-quality event surveillance. Extensive prepandemic data minimize referral, survival, and recall bias. Data are harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these data will be pooled and shared widely to expedite collaboration and scientific findings. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including postacute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term health trajectories.
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Affiliation(s)
- Elizabeth C Oelsner
- Correspondence to Dr. Elizabeth C Oelsner, MD MPH, Herbert Irving Associate Professor of Medicine, Division of General Medicine, Columbia University Irving Medical Center, 622 West 168 Street, PH9-105K New York, NY 10032 Tel: 917-880-7099
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21
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Moslemi A, Makimoto K, Tan WC, Bourbeau J, Hogg JC, Coxson HO, Kirby M. Quantitative CT Lung Imaging and Machine Learning Improves Prediction of Emergency Room Visits and Hospitalizations in COPD. Acad Radiol 2022; 30:707-716. [PMID: 35690537 DOI: 10.1016/j.acra.2022.05.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/03/2022] [Accepted: 05/15/2022] [Indexed: 12/12/2022]
Abstract
RATIONALE Predicting increased risk of future healthcare utilization in chronic obstructive pulmonary disease (COPD) patients is an important goal for improving patient management. OBJECTIVE Our objective was to determine the importance of computed tomography (CT) lung imaging measurements relative to other demographic and clinical measurements for predicting future health services use with machine learning in COPD. MATERIALS AND METHODS In this retrospective study, lung function measurements and chest CT images were acquired from Canadian Cohort of Obstructive Lung Disease study participants from 2010 to 2017 (https://clinicaltrials.gov, NCT00920348). Up to two follow-up visits (1.5- and 3-year follow-up) were performed and participants were asked for details related to healthcare utilization. Healthcare utilization was defined as any COPD hospitalization or emergency room visit due to respiratory problems in the 12 months prior to the follow-up visits. CT analysis was performed (VIDA Diagnostics Inc.); a total of 108 CT quantitative emphysema, airway and vascular measurements were investigated. A hybrid feature selection method with support vector machine classifier was used to predict healthcare utilization. Performance was determined using accuracy, F1-measure and area under the receiver operating characteristic curve (AUC) and Matthews's correlation coefficient (MC). RESULTS Of the 527 COPD participants evaluated, 179 (35%) used healthcare services at follow-up. There were no significant differences between the participants with or without healthcare utilization at follow-up for age (p = 0.50), sex (p = 0.44), BMI (p = 0.05) or pack-years (p = 0.76). The accuracy for predicting subsequent healthcare utilization was 80% ± 3% (F1-measure = 74%, AUC = 0.80, MC = 0.6) when all measurements were considered, 76% ± 6% (F1-measure = 72%, AUC = 0.77, MC = 0.55) for CT measurements alone and 65% ± 5% (F1-measure = 60%, AUC = 0.67, MC = 0.34) for demographic and lung function measurements alone. CONCLUSION The combination of CT lung imaging and conventional measurements leads to greater prediction accuracy of subsequent health services use than conventional measurements alone, and may provide needed prognostic information for patients suffering from COPD.
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Affiliation(s)
- Amir Moslemi
- Department of Physics, Toronto Metropolitan University, Toronto, ON, Canada
| | - Kalysta Makimoto
- Department of Physics, Toronto Metropolitan University, Toronto, ON, Canada
| | - Wan C Tan
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Jean Bourbeau
- Montreal Chest Institute of the Royal Victoria Hospital, McGill University Health Centre, Montreal, QC, Canada; Respiratory Epidemiology and Clinical Research Unit, Research Institute of McGill University Health Centre, Montreal, QC, Canada
| | - James C Hogg
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Harvey O Coxson
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | - Miranda Kirby
- Department of Physics, Toronto Metropolitan University, Toronto, ON, Canada; Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada.
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22
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Phillips DB, Elbehairy AF, James MD, Vincent SG, Milne KM, de-Torres JP, Neder JA, Kirby M, Jensen D, Stickland MK, Guenette JA, Smith BM, Aaron SD, Tan WC, Bourbeau J, O'Donnell DE. Impaired Ventilatory Efficiency, Dyspnea and Exercise Intolerance in Chronic Obstructive Pulmonary Disease: Results from the CanCOLD Study. Am J Respir Crit Care Med 2022; 205:1391-1402. [PMID: 35333135 DOI: 10.1164/rccm.202109-2171oc] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
RATIONALE Impaired exercise ventilatory efficiency (high ventilatory requirements for CO2 [V̇E/V̇CO2]) provides an indication of pulmonary gas exchange abnormalities in chronic obstructive pulmonary disease (COPD). OBJECTIVES To determine: 1) the association between high V̇E/V̇CO2 and clinical outcomes (dyspnea and exercise capacity) and its relationship to lung function and structural radiographic abnormalities; and 2) its prevalence in a large population-based cohort. METHODS Participants were recruited randomly from the population and underwent clinical evaluation, pulmonary function, cardiopulmonary exercise testing and chest computed tomography (CT). Impaired exercise ventilatory efficiency was defined by a nadir V̇E/V̇CO2 above the upper limit of normal (V̇E/V̇CO2>ULN), using population-based normative values. MEASUREMENTS AND MAIN RESULTS Participants included 445 never-smokers, 381 ever-smokers without airflow obstruction, 224 with GOLD 1 COPD, and 200 with GOLD 2-4 COPD. Participants with V̇E/V̇CO2>ULN were more likely to have activity-related dyspnea (Medical Research Council dyspnea scale≥2, odds ratio=1.77[1.31-2.39]) and abnormally low peak oxygen uptake (V̇O2peak<LLN, odds ratio=4.58[3.06-6.86]). The carbon monoxide transfer coefficient (KCO) had a stronger correlation with nadir V̇E/V̇CO2 (r=-0.38, p<0.001) than other relevant lung function and CT metrics. The prevalence of V̇E/V̇CO2>ULN was 24% in COPD (similar in GOLD 1 and 2-4), which was greater than in never-smokers (13%) and ever-smokers (12%). CONCLUSIONS V̇E/V̇CO2>ULN was associated with greater dyspnea and low VO2peak and was present in 24% of all participants with COPD, regardless of GOLD stage. The results show the importance of recognizing impaired exercise ventilatory efficiency as a potential contributor to dyspnea and exercise limitation, even in mild COPD.
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Affiliation(s)
| | - Amany F Elbehairy
- Queen's University and Kingston General Hospital, Medicine, Kingston, Ontario, Canada.,Alexandria University, Department of Chest Diseases, Faculty of Medicine, Alexandria, Egypt
| | - Matthew D James
- Queen's University, 4257, Medicine, Kingston, Ontario, Canada
| | | | - Kathryn M Milne
- The University of British Columbia, 8166, Medicine, Vancouver, British Columbia, Canada
| | | | - J Alberto Neder
- Queen's University, 4257, Medicine, Kingston, Ontario, Canada
| | - Miranda Kirby
- Ryerson University, Physics, Toronto, Ontario, Canada
| | - Dennis Jensen
- McGill University, Kinesiology & Physical Education, Montreal, Quebec, Canada
| | | | | | - Benjamin M Smith
- McGill University, Respiratory Medicine, Montreal, Quebec, Canada
| | - Shawn D Aaron
- Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Wan C Tan
- Providence Heart & Lung Institute, University of British Columbia, St Paul's Hospital, UBC James Hogg Research Centre, Vancouver, British Columbia, Canada
| | - Jean Bourbeau
- Montreal Chest Institute, CORE, Montreal, Quebec, Canada.,McGill University Health Centre, 54473, Montreal, Quebec, Canada
| | - Denis E O'Donnell
- Queen's University, Division of Respiratory and Critical Care Medicine, Department of Medicine, Kingston, Ontario, Canada;
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23
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Moslemi A, Kontogianni K, Brock J, Wood S, Herth F, Kirby M. Differentiating COPD and Asthma using Quantitative CT Imaging and Machine Learning. Eur Respir J 2022; 60:13993003.03078-2021. [PMID: 35210316 DOI: 10.1183/13993003.03078-2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 02/04/2022] [Indexed: 11/05/2022]
Abstract
There are similarities and differences between chronic obstructive pulmonary disease (COPD) and asthma patients in terms of computed tomography (CT) disease-related features. Our objective was to determine the optimal subset of CT imaging features for differentiating COPD and asthma using machine learning.COPD and asthma patients were recruited from Heidelberg University Hospital. CT was acquired and 93 features were extracted (VIDA Diagnostics): percentage of low-attenuating-areas below -950HU (LAA950), LAA950 hole count, estimated airway-wall-thickness for a 10 mm internal perimeter airway (Pi10), total-airway-count (TAC), as well as inner/outer perimeter/areas and wall thickness for each of five segmental airways, and the average of those five airways. Hybrid feature selection was used to select the optimum number of features, and support vector machine was used to classify COPD and asthma.Ninety-five participants were included (n=48 COPD; n=47 asthma); there were no differences between COPD and asthma for age (p=0.25) or FEV1 (p=0.31). In a model including all CT features, the accuracy and F1-score was 80% and 81%, respectively. The top features were: LAA950, LAA950 hole count, average outer and inner airway perimeter, outer and inner airway area RB1, and TAC. In the model with only airway features, the accuracy and F1-score were 66% and 68%, respectively. The top features were: inner area RB1, wall thickness RB1, outer area LB1, TAC LB10, average outer/inner perimeter, Pi10, and TAC.In conclusions, COPD and asthma can be differentiated using machine learning with moderate-high accuracy by a subset of only 7 CT features.
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Affiliation(s)
- Amir Moslemi
- Department of Physics, Ryerson University, Toronto, ON, Canada.,Co-first authors
| | - Konstantina Kontogianni
- Department of Pneumology and Critical Care Medicine, Thoraxklinik and Translational Lung Research Center (TLRCH), University of Heidelberg, Germany.,Co-first authors
| | - Judith Brock
- Department of Pneumology and Critical Care Medicine, Thoraxklinik and Translational Lung Research Center (TLRCH), University of Heidelberg, Germany
| | | | - Felix Herth
- Department of Pneumology and Critical Care Medicine, Thoraxklinik and Translational Lung Research Center (TLRCH), University of Heidelberg, Germany .,Co-senior authors
| | - Miranda Kirby
- Department of Physics, Ryerson University, Toronto, ON, Canada.,Co-senior authors
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Dudurych I, Muiser S, McVeigh N, Kerstjens HAM, van den Berge M, de Bruijne M, Vliegenthart R. Bronchial wall parameters on CT in healthy never-smoking, smoking, COPD, and asthma populations: a systematic review and meta-analysis. Eur Radiol 2022; 32:5308-5318. [PMID: 35192013 PMCID: PMC9279249 DOI: 10.1007/s00330-022-08600-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 12/14/2021] [Accepted: 01/29/2022] [Indexed: 11/25/2022]
Abstract
Objective Research on computed tomography (CT) bronchial parameter measurements shows that there are conflicting results on the values for bronchial parameters in the never-smoking, smoking, asthma, and chronic obstructive pulmonary disease (COPD) populations. This review assesses the current CT methods for obtaining bronchial wall parameters and their comparison between populations. Methods A systematic review of MEDLINE and Embase was conducted following PRISMA guidelines (last search date 25th October 2021). Methodology data was collected and summarised. Values of percentage wall area (WA%), wall thickness (WT), summary airway measure (Pi10), and luminal area (Ai) were pooled and compared between populations. Results A total of 169 articles were included for methodologic review; 66 of these were included for meta-analysis. Most measurements were obtained from multiplanar reconstructions of segmented airways (93 of 169 articles), using various tools and algorithms; third generation airways in the upper and lower lobes were most frequently studied. COPD (12,746) and smoking (15,092) populations were largest across studies and mostly consisted of men (median 64.4%, IQR 61.5 – 66.1%). There were significant differences between populations; the largest WA% was found in COPD (mean SD 62.93 ± 7.41%, n = 6,045), and the asthma population had the largest Pi10 (4.03 ± 0.27 mm, n = 442). Ai normalised to body surface area (Ai/BSA) (12.46 ± 4 mm2, n = 134) was largest in the never-smoking population. Conclusions Studies on CT-derived bronchial parameter measurements are heterogenous in methodology and population, resulting in challenges to compare outcomes between studies. Significant differences between populations exist for several parameters, most notably in the wall area percentage; however, there is a large overlap in their ranges. Key Points • Diverse methodology in measuring airways contributes to overlap in ranges of bronchial parameters among the never-smoking, smoking, COPD, and asthma populations. • The combined number of never-smoking participants in studies is low, limiting insight into this population and the impact of participant characteristics on bronchial parameters. • Wall area percent of the right upper lobe apical segment is the most studied (87 articles) and differentiates all except smoking vs asthma populations. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-022-08600-1.
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Affiliation(s)
- Ivan Dudurych
- Department of Radiology, EB49, University Medical Centre Groningen, University of Groningen, Hanzeplein 1, 9700RB, Groningen, The Netherlands
| | - Susan Muiser
- Department of Pulmonology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Niall McVeigh
- Department of Cardiothoracic Surgery, St. Vincent's University Hospital, Dublin, Ireland
| | - Huib A M Kerstjens
- Department of Pulmonology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Maarten van den Berge
- Department of Pulmonology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Marleen de Bruijne
- Department of Radiology and Nuclear Medicine, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam, The Netherlands
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Rozemarijn Vliegenthart
- Department of Radiology, EB49, University Medical Centre Groningen, University of Groningen, Hanzeplein 1, 9700RB, Groningen, The Netherlands.
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Kim T, Kim WJ, Lee CH, Chae KJ, Bak SH, Kwon SO, Jin GY, Park EK, Choi S. Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique. Comput Biol Med 2021; 141:105162. [PMID: 34973583 DOI: 10.1016/j.compbiomed.2021.105162] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 12/06/2021] [Accepted: 12/19/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND OBJECTIVE Cement dust exposure is likely to affect the structural and functional alterations in segmental airways and parenchymal lungs. This study develops an artificial neural network (ANN) model for identifying cement dust-exposed (CDE) subjects using quantitative computed tomography-based airway structural and functional features. METHODS We obtained the airway features in five central and five sub-grouped segmental regions and the lung features in five lobar regions and one total lung region from 311 CDE and 298 non-CDE (NCDE) subjects. The five-fold cross-validation method was adopted to train the following classification models:ANN, support vector machine (SVM), logistic regression (LR), and decision tree (DT). For all the classification models, linear discriminant analysis (LDA) and genetic algorithm (GA) were applied for dimensional reduction and hyperparameterization, respectively. The ANN model without LDA was also optimized by the GA method to observe the effect of the dimensional reduction. RESULTS The genetically optimized ANN model without the LDA method was the best in terms of the classification accuracy. The accuracy, sensitivity, and specificity of the GA-ANN model with four layers were greater than those of the other classification models (i.e., ANN, SVM, LR, and DT using LDA and GA methods) in the five-fold cross-validation. The average values of accuracy, sensitivity, and specificity for the five-fold cross-validation were 97.0%, 98.7%, and 98.6%, respectively. CONCLUSIONS We demonstrated herein that a quantitative computed tomography-based ANN model could more effectively detect CDE subjects when compared to their counterpart models. By employing the model, the CDE subjects may be identified early for therapeutic intervention.
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Affiliation(s)
- Taewoo Kim
- School of Mechanical Engineering, Kyungpook National University, Daegu, Republic of Korea
| | - Woo Jin Kim
- Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea
| | - Chang Hyun Lee
- Department of Radiology, College of Medicine, Seoul National University, Seoul, Republic of Korea; Department of Radiology, College of Medicine, The University of Iowa, Iowa City, IA, USA
| | - Kum Ju Chae
- Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - So Hyeon Bak
- Department of Radiology, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea
| | - Sung Ok Kwon
- Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea
| | - Gong Yong Jin
- Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - Eun-Kee Park
- Department of Medical Humanities and Social Medicine, College of Medicine, Kosin University, Busan, Republic of Korea
| | - Sanghun Choi
- School of Mechanical Engineering, Kyungpook National University, Daegu, Republic of Korea.
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26
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Au RC, Tan WC, Bourbeau J, Hogg JC, Kirby M. Impact of image pre-processing methods on computed tomography radiomics features in chronic obstructive pulmonary disease. Phys Med Biol 2021; 66. [PMID: 34847536 DOI: 10.1088/1361-6560/ac3eac] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 11/30/2021] [Indexed: 01/06/2023]
Abstract
Computed tomography (CT) imaging texture-based radiomics analysis can be used to assess chronic obstructive pulmonary disease (COPD). However, different image pre-processing methods are commonly used, and how these different methods impact radiomics features and lung disease assessment, is unknown. The purpose of this study was to develop an image pre-processing pipeline to investigate how various pre-processing combinations impact radiomics features and their use for COPD assessment. Spirometry and CT images were obtained from the multi-centered Canadian Cohort of Obstructive Lung Disease study. Participants were divided based on assessment site and were further dichotomized as No COPD or COPD within their participant groups. An image pre-processing pipeline was developed, calculating 32 grey level co-occurrence matrix radiomics features. The pipeline included lung segmentation, airway segmentation or no segmentation, image resampling or no resampling, and either no pre-processing, binning, edgmentation, or thresholding pre-processing techniques. A three-way analysis of variance was used for method comparison. A nested 10-fold cross validation using logistic regression and multiple linear regression models were constructed to classify COPD and assess correlation with lung function, respectively. Logistic regression performance was evaluated using the area under the receiver operating characteristic curve (AUC). A total of 1210 participants (Sites 1-8: No COPD:n = 447, COPD:n = 413; and Site 9: No COPD:n = 155, COPD:n = 195) were evaluated. Between the two participant groups, at least 16/32 features were different between airway segmentation/no segmentation (P ≤ 0.04), at least 29/32 features were different between no resampling/resampling (P ≤ 0.04), and 32/32 features were different between the pre-processing techniques (P < 0.0001). Features generated using the resampling/edgmentation and resampling/thresholding pre-processing combinations, regardless of airway segmentation, performed the best in COPD classification (AUC ≥ 0.718), and explained the most variance with lung function (R2 ≥ 0.353). Therefore, the image pre-processing methods completed prior to CT radiomics feature extraction significantly impacted extracted features and their ability to assess COPD.
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Affiliation(s)
- Ryan C Au
- Department of Physics, Ryerson University, Toronto, ON, M5B 2K3, Canada
| | - Wan C Tan
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Jean Bourbeau
- McGill University Health Centre, McGill University, Montreal, QC, H3A 0G4, Canada
| | - James C Hogg
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
| | - Miranda Kirby
- Department of Physics, Ryerson University, Toronto, ON, M5B 2K3, Canada.,Institute for Biomedical Engineering, Science and Technology, St. Michael's Hospital, Toronto, ON, M5B 1T8, Canada
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27
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Tanabe N, Hirai T. Recent advances in airway imaging using micro-computed tomography and computed tomography for chronic obstructive pulmonary disease. Korean J Intern Med 2021; 36:1294-1304. [PMID: 34607419 PMCID: PMC8588974 DOI: 10.3904/kjim.2021.124] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 05/14/2021] [Indexed: 12/13/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a complex lung disease characterized by a combination of airway disease and emphysema. Emphysema is classified as centrilobular emphysema (CLE), paraseptal emphysema (PSE), or panlobular emphysema (PLE), and airway disease extends from the respiratory, terminal, and preterminal bronchioles to the central segmental airways. Although clinical computed tomography (CT) cannot be used to visualize the small airways, micro-CT has shown that terminal bronchiole disease is more severe in CLE than in PSE and PLE, and micro-CT findings suggest that the loss and luminal narrowing of terminal bronchioles is an early pathological change in CLE. Furthermore, the introduction of ultra-high-resolution CT has enabled direct evaluation of the proximal small (1 to 2-mm diameter) airways, and new CT analytical methods have enabled estimation of small airway disease and prediction of future COPD onset and lung function decline in smokers with and without COPD. This review discusses the literature on micro-CT and the technical advancements in clinical CT analysis for COPD. Hopefully, novel micro-CT findings will improve our understanding of the distinct pathogeneses of the emphysema subtypes to enable exploration of new therapeutic targets, and sophisticated CT imaging methods will be integrated into clinical practice to achieve more personalized management.
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Affiliation(s)
- Naoya Tanabe
- Department of Respiratory Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Toyohiro Hirai
- Department of Respiratory Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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Kirby M, Smith BM, Tanabe N, Hogg JC, Coxson HO, Sin DD, Bourbeau J, Tan WC. Computed tomography total airway count predicts progression to COPD in at-risk smokers. ERJ Open Res 2021; 7:00307-2021. [PMID: 34708120 PMCID: PMC8542990 DOI: 10.1183/23120541.00307-2021] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/07/2021] [Indexed: 11/13/2022] Open
Abstract
There is limited understanding of how to identify people at high risk of developing COPD. Our objective was to investigate the association between computed tomography (CT) total airway count (TAC) and incident COPD over 3 years among ever-smokers from the population-based Canadian Cohort Obstructive Lung Disease (CanCOLD) study. CT and spirometry were acquired in ever-smokers at baseline; spirometry was repeated at 3-year follow-up. CT TAC was generated by summing all airway segments in the segmented airway tree (VIDA Diagnostics, Inc.). CT airway wall area, wall thickness for a theoretical airway with 10 mm perimeter (Pi10), and low attenuation areas below −856 HU (LAA856) were also measured. Logistic and mixed effects regression models were constructed to determine the association for CT measurements with development of COPD and forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) decline, respectively. Among 316 at-risk participants evaluated at baseline (65±9 years, 40% female, 18±19 pack-years), incident COPD was detected in 56 participants (18%) over a median 3.1±0.6 years of follow-up. Among CT measurements, only TAC was associated with incident COPD (p=0.03), where a 1-sd decrement in TAC increased the odds ratio for incident COPD by a factor of two. In a multivariable linear regression model, reduced TAC was significantly associated with greater longitudinal FEV1/FVC decline (p=0.03), but no other measurements were significant. CT TAC predicts incident COPD in at-risk smokers, indicating that smokers exhibit early structural changes associated with COPD prior to abnormal spirometry. Computed tomography (CT) total airway count (TAC) predicts incident COPD in at-risk smokers, indicating that smokers exhibit early airway remodelling prior to abnormal spirometry and that CT TAC is a potential tool to help identify smokers at increased risk of COPDhttps://bit.ly/2UTw3I4
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Affiliation(s)
- Miranda Kirby
- Dept of Physics, Ryerson University, Toronto, ON, Canada.,UBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada
| | - Benjamin M Smith
- Dept of Medicine, McGill University, Montreal, QC, Canada.,Dept of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada.,Dept of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Naoya Tanabe
- UBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada
| | - James C Hogg
- UBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada
| | - Harvey O Coxson
- UBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada
| | - Don D Sin
- UBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada
| | - Jean Bourbeau
- Montreal Chest Institute of the Royal Victoria Hospital, McGill University Health Centre, Montreal, QC, Canada.,Respiratory Epidemiology and Clinical Research Unit, Research Institute of McGill University Health Centre, Montreal, QC, Canada
| | - Wan C Tan
- UBC Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, BC, Canada
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Fujikura K, Albini A, Barr RG, Parikh M, Kern J, Hoffman E, Hiura GT, Bluemke DA, Carr J, Lima JAC, Michos ED, Gomes AS, Prince MR. Aortic enlargement in chronic obstructive pulmonary disease (COPD) and emphysema: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD study. Int J Cardiol 2021; 331:214-220. [PMID: 33587941 PMCID: PMC8026709 DOI: 10.1016/j.ijcard.2021.02.017] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 12/25/2020] [Accepted: 02/05/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND The prevalence of abdominal aortic aneurysm is high in chronic obstructive pulmonary disease (COPD) population. Emphysema involves proteolytic destruction of elastic fibers. Therefore, emphysema may also contribute to thoracic aorta dilatation. This study assessed aorta dilation in smokers stratified by presence of COPD, emphysema and airway thickening. METHODS Aorta diameters were measured on 3D magnetic resonance angiography in smokers recruited from the Multi-Ethnic Study of Atherosclerosis (MESA), the Emphysema and Cancer Action Project (EMCAP), and the local community. COPD was defined by standard spirometric criteria; emphysema was measured quantitatively on computed tomography and bronchitis was determined from medical history. RESULTS Participants (n = 315, age 58-79) included 150 with COPD and 165 without COPD, of whom 56% and 19%, respectively, had emphysema. Subjects in the most severe quartile of emphysematous change showed the largest diameter at all four aorta locations compared to those in the least severe quartiles (all p < 0.001). Comparing subjects with and without COPD, aorta diameters were larger in participants with severe COPD in ascending and arch (both p < 0.001), and abdominal aorta (p = 0.001). Chronic bronchitis and bronchial wall thickness did not correlate with aorta diameter. In subjects with emphysema, subjects with coexistence of COPD showed larger aorta than those without COPD in ascending (p = 0.003), arch (p = 0.002), and abdominal aorta (p = 0.04). CONCLUSIONS This study showed larger aorta diameter in subjects with COPD and severe emphysema compared to COPD related to chronic bronchitis or bronchial wall thickening.
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Affiliation(s)
- Kana Fujikura
- Advanced Cardiovascular Imaging Laboratory, National Heart, Lung and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, ML, USA
| | | | - R Graham Barr
- Department of Medicine, Columbia University, New York, USA
| | - Megha Parikh
- Department of Medicine, Columbia University, New York, USA
| | - Julia Kern
- Department of Medicine, Columbia University, New York, USA
| | - Eric Hoffman
- Department of Radiology, Medicine and Biomedical Engineering, University of Iowa, Iowa City, USA
| | - Grant T Hiura
- Department of Medicine, Columbia University, New York, USA
| | - David A Bluemke
- Department of Radiology, University of Wisconsin, Madison, USA
| | - James Carr
- Department of Radiology, Northwestern University, Chicago, USA
| | - João A C Lima
- Division of Cardiology, Johns Hopkins University, Baltimore, USA
| | - Erin D Michos
- Division of Cardiology, Johns Hopkins University, Baltimore, USA
| | - Antoinette S Gomes
- Department of Radiology, University of California-Los Angeles, School of Medicine, Los Angeles, USA
| | - Martin R Prince
- Department of Radiology, Weill Cornell Medicine, NY, New York, USA.
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Tanaka Y, Ohno Y, Hanamatsu S, Obama Y, Ueda T, Ikeda H, Iwase A, Fukuba T, Hattori H, Murayama K, Yoshikawa T, Takenaka D, Koyama H, Toyama H. State-of-the-art MR Imaging for Thoracic Diseases. Magn Reson Med Sci 2021; 21:212-234. [PMID: 33952785 PMCID: PMC9199970 DOI: 10.2463/mrms.rev.2020-0184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Since thoracic MR imaging was first used in a clinical setting, it has been suggested that MR imaging has limited clinical utility for thoracic diseases, especially lung diseases, in comparison with x-ray CT and positron emission tomography (PET)/CT. However, in many countries and states and for specific indications, MR imaging has recently become practicable. In addition, recently developed pulmonary MR imaging with ultra-short TE (UTE) and zero TE (ZTE) has enhanced the utility of MR imaging for thoracic diseases in routine clinical practice. Furthermore, MR imaging has been introduced as being capable of assessing pulmonary function. It should be borne in mind, however, that these applications have so far been academically and clinically used only for healthy volunteers, but not for patients with various pulmonary diseases in Japan or other countries. In 2020, the Fleischner Society published a new report, which provides consensus expert opinions regarding appropriate clinical indications of pulmonary MR imaging for not only oncologic but also pulmonary diseases. This review article presents a brief history of MR imaging for thoracic diseases regarding its technical aspects and major clinical indications in Japan 1) in terms of what is currently available, 2) promising but requiring further validation or evaluation, and 3) developments warranting research investigations in preclinical or patient studies. State-of-the-art MR imaging can non-invasively visualize lung structural and functional abnormalities without ionizing radiation and thus provide an alternative to CT. MR imaging is considered as a tool for providing unique information. Moreover, prospective, randomized, and multi-center trials should be conducted to directly compare MR imaging with conventional methods to determine whether the former has equal or superior clinical relevance. The results of these trials together with continued improvements are expected to update or modify recommendations for the use of MRI in near future.
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Affiliation(s)
- Yumi Tanaka
- Department of Radiology, Fujita Health University School of Medicine
| | - Yoshiharu Ohno
- Department of Radiology, Fujita Health University School of Medicine.,Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
| | - Satomu Hanamatsu
- Department of Radiology, Fujita Health University School of Medicine
| | - Yuki Obama
- Department of Radiology, Fujita Health University School of Medicine
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University School of Medicine
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University School of Medicine
| | - Akiyoshi Iwase
- Department of Radiology, Fujita Health University Hospital
| | - Takashi Fukuba
- Department of Radiology, Fujita Health University Hospital
| | - Hidekazu Hattori
- Department of Radiology, Fujita Health University School of Medicine
| | - Kazuhiro Murayama
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
| | | | | | | | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine
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31
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Benlala I, Laurent F, Dournes G. Structural and functional changes in COPD: What we have learned from imaging. Respirology 2021; 26:731-741. [PMID: 33829593 DOI: 10.1111/resp.14047] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is the third leading cause of mortality worldwide. It is a heterogeneous disease involving different components of the lung to varying extents. Developments in medical imaging and image analysis techniques provide new insights in the assessment of the structural and functional changes of the disease. This article reviews the leading imaging techniques: CT and MRI of the lung in research settings and clinical routine. Both visual and quantitative methods are reviewed, emphasizing their relevance to patient phenotyping and outcome prediction.
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Affiliation(s)
- Ilyes Benlala
- Centre de recherche Cardio-Thoracique de Bordeaux, University of Bordeaux, INSERM, Bordeaux, France
| | - François Laurent
- Centre de recherche Cardio-Thoracique de Bordeaux, University of Bordeaux, INSERM, Bordeaux, France
| | - Gael Dournes
- Centre de recherche Cardio-Thoracique de Bordeaux, University of Bordeaux, INSERM, Bordeaux, France
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Oelsner EC, Allen NB, Ali T, Anugu P, Andrews H, Asaro A, Balte PP, Barr RG, Bertoni AG, Bon J, Boyle R, Chang AA, Chen G, Cole SA, Coresh J, Cornell E, Correa A, Couper D, Cushman M, Demmer RT, Elkind MSV, Folsom AR, Fretts AM, Gabriel KP, Gallo L, Gutierrez J, Han MK, Henderson JM, Howard VJ, Isasi CR, Jacobs DR, Judd SE, Mukaz DK, Kanaya AM, Kandula NR, Kaplan R, Krishnaswamy A, Kinney GL, Kucharska-Newton A, Lee JS, Lewis CE, Levine DA, Levitan EB, Levy B, Make B, Malloy K, Manly JJ, Meyer KA, Min YI, Moll M, Moore WC, Mauger D, Ortega VE, Palta P, Parker MM, Phipatanakul W, Post W, Psaty BM, Regan EA, Ring K, Roger VL, Rotter JI, Rundek T, Sacco RL, Schembri M, Schwartz DA, Seshadri S, Shikany JM, Sims M, Hinckley Stukovsky KD, Talavera GA, Tracy RP, Umans JG, Vasan RS, Watson K, Wenzel SE, Winters K, Woodruff PG, Xanthakis V, Zhang Y, Zhang Y. Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.03.19.21253986. [PMID: 33758891 PMCID: PMC7987050 DOI: 10.1101/2021.03.19.21253986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults at risk for coronavirus disease 2019 (COVID-19) comprising 14 established United States (US) prospective cohort studies. For decades, C4R cohorts have collected extensive data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R will link this pre-COVID phenotyping to information on SARS-CoV-2 infection and acute and post-acute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and broadly reflects the racial, ethnic, socioeconomic, and geographic diversity of the US. C4R is ascertaining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations, and high-quality events surveillance. Extensive pre-pandemic data minimize referral, survival, and recall bias. Data are being harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these will be pooled and shared widely to expedite collaboration and scientific findings. This unique resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including post-acute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term trajectories of health and aging.
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Chae KJ, Jin GY, Choi J, Lee CH, Choi S, Choi H, Park J, Lin CL, Hoffman EA. Generation-based study of airway remodeling in smokers with normal-looking CT with normalization to control inter-subject variability. Eur J Radiol 2021; 138:109657. [PMID: 33773402 DOI: 10.1016/j.ejrad.2021.109657] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 02/01/2021] [Accepted: 03/09/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE With the help of quantitative computed tomography (QCT), it is possible to identify smoking-associated airway remodeling. However, there is currently little information on whether QCT-based airway metrics are sensitive to early airway wall remodeling in subclinical phases of smoking-associated airway disease. This study aimed to evaluate a predictive model that normalized airway parameters and investigate structural airway alterations in smokers with normal-looking CT using the normalization scheme. METHODS In this retrospective analysis, 222 non-smokers (male 97, female 125) and 69 smokers (male 66, female 3) from January 2014 to December 2016 were included, and airway parameters were quantitatively analyzed. To control inter-subject variability, multiple linear regressions of tracheal wall thickness (WT), diameter (D), and luminal area (LA) were performed, adjusted for age, sex, and height. Using this normalization scheme, airway parameters with matched generation were compared between smokers and non-smokers. RESULTS Using the normalization scheme, it was possible to assess generation-based structural alterations of the airways in subclinical smokers. Smokers showed diffuse luminal narrowing of airways for most generations (P < 0.05, except 3rd generation), no change in wall thickness of the proximal bronchi (1st-3rd generation), and a thinning of distal airways (P <0.05, ≥4th generation). CONCLUSION QCT assessment for subclinical smokers can help identify minimal structural changes in airways induced by smoking.
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Affiliation(s)
- Kum Ju Chae
- Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea
| | - Gong Yong Jin
- Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea.
| | - Jiwoong Choi
- Department of Internal Medicine, School of Medicine, University of Kansas, Kansas City, KS, USA; Department of Bioengineering, University of Kansas, Lawrence, KS, USA
| | - Chang Hyun Lee
- Department of Radiology, Seoul National University Hospital, Seoul, South Korea; Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul, South Korea
| | - Sanghun Choi
- School of Mechanical Engineering, Kyungpook National University, Daegu, South Korea
| | - Hyemi Choi
- Department of Statistics and Institute of Applied Statistics, Jeonbuk National University, Jeonju, Jeonbuk, South Korea
| | - Jeongjae Park
- Department of Statistics, Regional Cardiocerebrovascular Center, Wonkwang University School of Medicine, Iksan, Jeonbuk, South Korea
| | - Ching-Long Lin
- Department of Radiology & Department of Biomedical Engineering, The University of Iowa, Iowa City, IA, USA
| | - Eric A Hoffman
- Department of Radiology & Department of Biomedical Engineering, The University of Iowa, Iowa City, IA, USA
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Nadeem SA, Hoffman EA, Sieren JC, Comellas AP, Bhatt SP, Barjaktarevic IZ, Abtin F, Saha PK. A CT-Based Automated Algorithm for Airway Segmentation Using Freeze-and-Grow Propagation and Deep Learning. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:405-418. [PMID: 33021934 PMCID: PMC7772272 DOI: 10.1109/tmi.2020.3029013] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Chronic obstructive pulmonary disease (COPD) is a common lung disease, and quantitative CT-based bronchial phenotypes are of increasing interest as a means of exploring COPD sub-phenotypes, establishing disease progression, and evaluating intervention outcomes. Reliable, fully automated, and accurate segmentation of pulmonary airway trees is critical to such exploration. We present a novel approach of multi-parametric freeze-and-grow (FG) propagation which starts with a conservative segmentation parameter and captures finer details through iterative parameter relaxation. First, a CT intensity-based FG algorithm is developed and applied for airway tree segmentation. A more efficient version is produced using deep learning methods generating airway lumen likelihood maps from CT images, which are input to the FG algorithm. Both CT intensity- and deep learning-based algorithms are fully automated, and their performance, in terms of repeat scan reproducibility, accuracy, and leakages, is evaluated and compared with results from several state-of-the-art methods including an industry-standard one, where segmentation results were manually reviewed and corrected. Both new algorithms show a reproducibility of 95% or higher for total lung capacity (TLC) repeat CT scans. Experiments on TLC CT scans from different imaging sites at standard and low radiation dosages show that both new algorithms outperform the other methods in terms of leakages and branch-level accuracy. Considering the performance and execution times, the deep learning-based FG algorithm is a fully automated option for large multi-site studies.
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Influence of Asthma Onset on Airway Dimensions on Ultra-high-resolution Computed Tomography in Chronic Obstructive Pulmonary Disease. J Thorac Imaging 2020; 36:224-230. [PMID: 33156159 DOI: 10.1097/rti.0000000000000568] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE Asthma onset before the age of 40 years is associated with distinct clinical manifestations in chronic obstructive pulmonary disease (COPD) patients, but its morphologic features remain unestablished. This study aimed to explore airway morphology in COPD patients with asthma onset before 40 years of age using ultra-high-resolution computed tomography (U-HRCT), which allows a more accurate quantitation of the lumen and the wall in smaller airways than using conventional CT. MATERIALS AND METHODS Clinical data of 500 consecutive patients undergoing full inspiratory U-HRCT (1024×1024 matrix and 0.25 mm slice thickness) were retrospectively analyzed. COPD patients without asthma, COPD patients with asthma onset at age below or 40 years and above, and non-COPD smoker controls (N=137, 29, 34, and 22, respectively) were enrolled. The length, lumen area (LA), wall thickness and area (WA), and wall area percent (WA%) of the segmental (third-generation) to sub-subsegmental (fifth-generation) bronchus and the low attenuation volume percent (LAV%) were measured. RESULTS LA and WA were smaller in the fourth and fifth generation in COPD patients than in non-COPD controls, regardless of the age of asthma onset. LA was smaller and WA% was larger in the fourth-generation and fifth-generation airways in COPD with asthma onset before 40 years than COPD without asthma, whereas WA did not differ between them. In multivariate analyses, asthma onset before 40 years was associated with smaller LA in COPD patients independent of demographics, use of inhaled corticosteroids and long-acting bronchodilators, airflow limitation, and LAV%. CONCLUSIONS Asthma onset before 40 years of age could be associated with greater lumen narrowing of the airways in COPD.
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Dolliver WR, Diaz AA. Advances in Chronic Obstructive Pulmonary Disease Imaging. ACTA ACUST UNITED AC 2020; 6:128-143. [PMID: 33758787 DOI: 10.23866/brnrev:2019-0023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Chest computed tomography (CT) imaging is a useful tool that provides in vivo information regarding lung structure. Imaging has contributed to a better understanding of COPD, allowing for the detection of early structural changes and the quantification of extra-pulmonary structures. Novel CT imaging techniques have provided insight into the progression of the main COPD subtypes, such as emphysema and small airway disease. This article serves as a review of new information relevant to COPD imaging. CT abnormalities, such as emphysema and loss of airways, are present even in smokers who do not meet the criteria for COPD and in those with mild-to-moderate disease. Subjects with mild-to-moderate COPD, with the highest loss of airways, also experience the highest decline in lung function. Extra-pulmonary manifestations of COPD, such as right ventricle enlargement and low muscle mass measured on CT, are associated with increased risk for all-cause mortality. CT longitudinal data has also given insight into the progression of COPD. Mechanically affected areas of lung parenchyma adjacent to emphysematous areas are associated with a greater decline in FEV1. Subjects with the greatest percentage of small airway disease, as measured on matched inspiratory-expiratory CT scan, also present with the greatest decline in lung function.
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Affiliation(s)
- Wojciech R Dolliver
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Alejandro A Diaz
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
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Xu C, Qi S, Feng J, Xia S, Kang Y, Yao Y, Qian W. DCT-MIL: Deep CNN transferred multiple instance learning for COPD identification using CT images. Phys Med Biol 2020; 65:145011. [PMID: 32235077 DOI: 10.1088/1361-6560/ab857d] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
While many pre-defined computed tomographic (CT) measures have been utilized to characterize chronic obstructive pulmonary disease (COPD), it is still challenging to represent pathological alternations of multiple dimensions and highly spatial heterogeneity. Deep CNN transferred multiple instance learning (DCT-MIL) is proposed to identify COPD via CT images. After the lung is divided into eight sections along the axial direction, one random axial CT image is taken out from each section as one instance. With one instance as the input, the activations of neural layers of AlexNet trained by natural images are extracted as features. After dimension reduction through principle component analysis, features of all instances are input into three MIL methods: Citation k-Nearest-Neighbor (Citation-KNN), multiple instance support vector machine, and expectation-maximization diverse density. Moreover, the performance dependence of the resulted models on the depth of the neural layer where activations are extracted and the number of features is investigated. The proposed DCT-MIL achieves an exceptional performance with an accuracy of 99.29% and area under curve of 0.9826 while using 100 principle components of features extracted from the fourth convolutional layer and Citation-KNN. It outperforms not only DCT-MIL models using other settings and the pre-trained AlexNet with fine-tuning by montages of eight lung CT images, but also other state-of-art methods. Deep CNN transferred multiple instance learning is suited for identification of COPD using CT images. It can help finding subgroups with high risk of COPD from large populations through CT scans ordered doing lung cancer screening.
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Affiliation(s)
- Caiwen Xu
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, People's Republic of China
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Eddy RL, Svenningsen S, Kirby M, Knipping D, McCormack DG, Licskai C, Nair P, Parraga G. Is Computed Tomography Airway Count Related to Asthma Severity and Airway Structure and Function? Am J Respir Crit Care Med 2020; 201:923-933. [PMID: 31895987 DOI: 10.1164/rccm.201908-1552oc] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Rationale: In patients with asthma, X-ray computed tomography (CT) has provided evidence of thickened airway walls and airway occlusions, but the total number of CT-visible airways and its relationship with disease severity is unknown.Objectives: To measure CT total airway count (TAC) in asthma and evaluate relationships with asthma severity, airway morphology, pulmonary function, and magnetic resonance imaging (MRI) ventilation.Methods: Participants underwent post-bronchodilator inspiratory CT, and prebronchodilator and post-bronchodilator spirometry and hyperpolarized 3He MRI. CT TAC was quantified as the sum of airways in the segmented airway tree, and airway wall area percent (WA%) and lumen area were measured. MRI ventilation abnormalities were quantified as the ventilation defect percent.Measurements and Main Results: We evaluated 70 participants, including 15 Global Initiative for Asthma (GINA) steps 1 to 3, 19 GINA 4, and 36 GINA 5 participants with asthma. As compared with GINA 1 to 3, TAC was significantly diminished in GINA 4 (P = 0.03) and GINA 5 (P = 0.045). Terminal airway intraluminal occlusion was present in 5 (2 GINA 4 and 3 GINA 5) of 70 participants. Sub-subsegmental airways were CT-invisible or missing in 69 out of 70 participants; the most common number of missing sub-subsegments was 10. Participants with ≥10 missing subsegments had worse WA% (P < 0.0001), lumen area (P < 0.0001), and ventilation defect percent (P = 0.03) than those with <10 missing subsegments. In a multivariable model, TAC (standardized regression coefficient = 0.50; P = 0.001) independently predicted FEV1 (R2 = 0.27; P = 0.003) and, in a separate model, TAC (standardized regression coefficient = -0.53; P < 0.0001) independently predicted airway WA% (R2 = 0.32; P = 0.0001).Conclusions: TAC was significantly diminished in participants with greater asthma severity and was related to airway wall thickness and ventilation defects. Fewer airways in severe than in mild asthma challenges our understanding of airway disease in asthma.Clinical trial registered with www.clinicaltrials.gov (NCT02351141).
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Affiliation(s)
- Rachel L Eddy
- Robarts Research Institute.,Department of Medical Biophysics, and
| | - Sarah Svenningsen
- Department of Medicine, McMaster University and Firestone Institute for Respiratory Health, St. Joseph's Healthcare, Hamilton, Ontario, Canada; and
| | - Miranda Kirby
- Department of Physics, Ryerson University, Toronto, Ontario, Canada
| | | | - David G McCormack
- Division of Respirology, Department of Medicine, Western University, London, Ontario, Canada
| | - Christopher Licskai
- Division of Respirology, Department of Medicine, Western University, London, Ontario, Canada
| | - Parameswaran Nair
- Department of Medicine, McMaster University and Firestone Institute for Respiratory Health, St. Joseph's Healthcare, Hamilton, Ontario, Canada; and
| | - Grace Parraga
- Robarts Research Institute.,Department of Medical Biophysics, and.,Division of Respirology, Department of Medicine, Western University, London, Ontario, Canada
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Smith BM, Kirby M, Hoffman EA, Kronmal RA, Aaron SD, Allen NB, Bertoni A, Coxson HO, Cooper C, Couper DJ, Criner G, Dransfield MT, Han MK, Hansel NN, Jacobs DR, Kaufman JD, Lin CL, Manichaikul A, Martinez FJ, Michos ED, Oelsner EC, Paine R, Watson KE, Benedetti A, Tan WC, Bourbeau J, Woodruff PG, Barr RG. Association of Dysanapsis With Chronic Obstructive Pulmonary Disease Among Older Adults. JAMA 2020; 323:2268-2280. [PMID: 32515814 PMCID: PMC7284296 DOI: 10.1001/jama.2020.6918] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Accepted: 04/15/2020] [Indexed: 12/23/2022]
Abstract
Importance Smoking is a major risk factor for chronic obstructive pulmonary disease (COPD), yet much of COPD risk remains unexplained. Objective To determine whether dysanapsis, a mismatch of airway tree caliber to lung size, assessed by computed tomography (CT), is associated with incident COPD among older adults and lung function decline in COPD. Design, Setting, and Participants A retrospective cohort study of 2 community-based samples: the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study, which involved 2531 participants (6 US sites, 2010-2018) and the Canadian Cohort of Obstructive Lung Disease (CanCOLD), which involved 1272 participants (9 Canadian sites, 2010-2018), and a case-control study of COPD: the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), which involved 2726 participants (12 US sites, 2011-2016). Exposures Dysanapsis was quantified on CT as the geometric mean of airway lumen diameters measured at 19 standard anatomic locations divided by the cube root of lung volume (airway to lung ratio). Main Outcomes and Measures Primary outcome was COPD defined by postbronchodilator ratio of forced expired volume in the first second to vital capacity (FEV1:FVC) less than 0.70 with respiratory symptoms. Secondary outcome was longitudinal lung function. All analyses were adjusted for demographics and standard COPD risk factors (primary and secondhand tobacco smoke exposures, occupational and environmental pollutants, and asthma). Results In the MESA Lung sample (mean [SD] age, 69 years [9 years]; 1334 women [52.7%]), 237 of 2531 participants (9.4%) had prevalent COPD, the mean (SD) airway to lung ratio was 0.033 (0.004), and the mean (SD) FEV1 decline was -33 mL/y (31 mL/y). Of 2294 MESA Lung participants without prevalent COPD, 98 (4.3%) had incident COPD at a median of 6.2 years. Compared with participants in the highest quartile of airway to lung ratio, those in the lowest had a significantly higher COPD incidence (9.8 vs 1.2 cases per 1000 person-years; rate ratio [RR], 8.12; 95% CI, 3.81 to 17.27; rate difference, 8.6 cases per 1000 person-years; 95% CI, 7.1 to 9.2; P < .001) but no significant difference in FEV1 decline (-31 vs -33 mL/y; difference, 2 mL/y; 95% CI, -2 to 5; P = .30). Among CanCOLD participants (mean [SD] age, 67 years [10 years]; 564 women [44.3%]), 113 of 752 (15.0%) had incident COPD at a median of 3.1 years and the mean (SD) FEV1 decline was -36 mL/y (75 mL/y). The COPD incidence in the lowest airway to lung quartile was significantly higher than in the highest quartile (80.6 vs 24.2 cases per 1000 person-years; RR, 3.33; 95% CI, 1.89 to 5.85; rate difference, 56.4 cases per 1000 person-years; 95% CI, 38.0 to 66.8; P<.001), but the FEV1 decline did not differ significantly (-34 vs -36 mL/y; difference, 1 mL/y; 95% CI, -15 to 16; P=.97). Among 1206 SPIROMICS participants (mean [SD] age, 65 years [8 years]; 542 women [44.9%]) with COPD who were followed up for a median 2.1 years, those in the lowest airway to lung ratio quartile had a mean FEV1 decline of -37 mL/y (15 mL/y), which did not differ significantly from the decline in MESA Lung participants (P = .98), whereas those in highest quartile had significantly faster decline than participants in MESA Lung (-55 mL/y [16 mL/y ]; difference, -17 mL/y; 95% CI, -32 to -3; P = .004). Conclusions and Relevance Among older adults, dysanapsis was significantly associated with COPD, with lower airway tree caliber relative to lung size associated with greater COPD risk. Dysanapsis appears to be a risk factor associated with COPD.
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Affiliation(s)
- Benjamin M. Smith
- Department of Medicine, Columbia University Medical Center, New York, New York
- Department of Medicine, McGill University, Montreal, Quebec, Canada
| | - Miranda Kirby
- Department of Physics, Ryerson University, Toronto, Ontario, Canada
| | - Eric A. Hoffman
- Department of Radiology, University of Iowa, Iowa City
- Department of Biomedical Engineering, University of Iowa, Iowa City
- Department of Internal Medicine, University of Iowa, Iowa City
| | | | - Shawn D. Aaron
- Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Norrina B. Allen
- Department of Medicine, Northwestern University, Chicago, Illinois
| | - Alain Bertoni
- Department of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Harvey O. Coxson
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - Chris Cooper
- Department of Medicine, University of California, Los Angeles
| | - David J. Couper
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill
| | - Gerard Criner
- Department of Medicine, Temple University, Philadelphia, Pennsylvania
| | | | - MeiLan K. Han
- Department of Medicine, University of Michigan, Ann Arbor
| | - Nadia N. Hansel
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - David R. Jacobs
- Division of Epidemiology and Community Health School of Public Health, University of Minnesota, Minneapolis
| | - Joel D. Kaufman
- Department of Epidemiology, University of Washington, Seattle
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle
| | - Ching-Long Lin
- Department of Mechanical Engineering, University of Iowa, Iowa City
| | - Ani Manichaikul
- Department of Public Health Sciences, University of Virginia, Charlottesville
| | | | - Erin D. Michos
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | | | - Robert Paine
- Department of Medicine, University of Utah, Salt Lake City
| | - Karol E. Watson
- Department of Medicine, University of California, Los Angeles
| | - Andrea Benedetti
- Department of Medicine, McGill University, Montreal, Quebec, Canada
| | - Wan C. Tan
- Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Jean Bourbeau
- Department of Medicine, McGill University, Montreal, Quebec, Canada
| | | | - R. Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, New York
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Kim T, Cho HB, Kim WJ, Lee CH, Chae KJ, Choi SH, Lee KE, Bak SH, Kwon SO, Jin GY, Choi J, Park EK, Lin CL, Hoffman EA, Choi S. Quantitative CT-based structural alterations of segmental airways in cement dust-exposed subjects. Respir Res 2020; 21:133. [PMID: 32471435 PMCID: PMC7260806 DOI: 10.1186/s12931-020-01399-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 05/19/2020] [Indexed: 11/24/2022] Open
Abstract
Background Dust exposure has been reported as a risk factor of pulmonary disease, leading to alterations of segmental airways and parenchymal lungs. This study aims to investigate alterations of quantitative computed tomography (QCT)-based airway structural and functional metrics due to cement-dust exposure. Methods To reduce confounding factors, subjects with normal spirometry without fibrosis, asthma and pneumonia histories were only selected, and a propensity score matching was applied to match age, sex, height, smoking status, and pack-years. Thus, from a larger data set (N = 609), only 41 cement dust-exposed subjects were compared with 164 non-cement dust-exposed subjects. QCT imaging metrics of airway hydraulic diameter (Dh), wall thickness (WT), and bifurcation angle (θ) were extracted at total lung capacity (TLC) and functional residual capacity (FRC), along with their deformation ratios between TLC and FRC. Results In TLC scan, dust-exposed subjects showed a decrease of Dh (airway narrowing) especially at lower-lobes (p < 0.05), an increase of WT (wall thickening) at all segmental airways (p < 0.05), and an alteration of θ at most of the central airways (p < 0.001) compared with non-dust-exposed subjects. Furthermore, dust-exposed subjects had smaller deformation ratios of WT at the segmental airways (p < 0.05) and θ at the right main bronchi and left main bronchi (p < 0.01), indicating airway stiffness. Conclusions Dust-exposed subjects with normal spirometry demonstrated airway narrowing at lower-lobes, wall thickening at all segmental airways, a different bifurcation angle at central airways, and a loss of airway wall elasticity at lower-lobes. The airway structural alterations may indicate different airway pathophysiology due to cement dusts.
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Affiliation(s)
- Taewoo Kim
- School of Mechanical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 41566, South Korea
| | - Hyun Bin Cho
- School of Mechanical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 41566, South Korea
| | - Woo Jin Kim
- Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, South Korea
| | - Chang Hyun Lee
- Department of Radiology, College of Medicine, Seoul National University, Seoul, South Korea.,Department of Radiology, College of Medicine, The University of Iowa, Iowa City, Iowa, USA
| | - Kum Ju Chae
- Department of Radiology, Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Jeonju, South Korea
| | - So-Hyun Choi
- Department of Statistics, Kyungpook National University, Daegu, South Korea
| | - Kyeong Eun Lee
- Department of Statistics, Kyungpook National University, Daegu, South Korea
| | - So Hyeon Bak
- Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, South Korea
| | - Sung Ok Kwon
- Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, South Korea
| | - Gong Yong Jin
- Department of Radiology, Research Institute of Clinical Medicine of Chonbuk National University-Biomedical Research Institute of Chonbuk National University Hospital, Jeonju, South Korea
| | - Jiwoong Choi
- IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, Iowa, USA
| | - Eun-Kee Park
- Department of Medical Humanities and Social Medicine, College of Medicine, Kosin University, Busan, South Korea
| | - Ching-Long Lin
- IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, Iowa, USA
| | - Eric A Hoffman
- Department of Radiology, College of Medicine, The University of Iowa, Iowa City, Iowa, USA
| | - Sanghun Choi
- School of Mechanical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 41566, South Korea.
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Nadeem SA, Hoffman EA, Comellas AP, Saha PK. LOCALLY ADAPTIVE HALF-MAX METHODS FOR AIRWAY LUMEN-AREA AND WALL-THICKNESS AND THEIR REPEAT CT SCAN REPRODUCIBILITY. PROCEEDINGS. IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING 2020; 2020:10.1109/isbi45749.2020.9098558. [PMID: 34422222 PMCID: PMC8375398 DOI: 10.1109/isbi45749.2020.9098558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Quantitative computed tomography (CT)-based characterization of bronchial metrics is increasingly being used to investigate chronic obstructive pulmonary disease (COPD)-related phenotypes. Automated methods for airway measurements benefit large multi-site studies by reducing cost and subjectivity errors. Critical challenges for CT-based analysis of airway morphology are related to location of lumen and wall transitions in the presence of varying scales and intensity-contrasts from proximal to distal sites. This paper introduces locally adaptive half-max methods to locate airway lumen and wall transitions and compute cross-sectional lumen area and wall-thickness. Also, the method uses a consistency analysis of wall-thickness to avoid adjoining-structure-artifacts. Experimental results show that computed bronchial measures at individual anatomic airway tree locations are repeat CT scan reproducible with intra-class correlation coefficient (ICC) values exceeding 0.9 and 0.8 for lumen-area and wall-thickness, respectively. Observed ICC values for derived morphologic measures, e.g., lumen-area compactness (ICC>0.67) and tapering (ICC>0.47) are relatively lower.
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Affiliation(s)
- Syed Ahmed Nadeem
- Department of Electrical and Computer Engineering, College of Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Eric A Hoffman
- Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA
| | - Alejandro P Comellas
- Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA
| | - Punam K Saha
- Department of Electrical and Computer Engineering, College of Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA
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Burkes RM, Ceppe AS, Doerschuk CM, Couper D, Hoffman EA, Comellas AP, Barr RG, Krishnan JA, Cooper C, Labaki WW, Ortega VE, Wells JM, Criner GJ, Woodruff PG, Bowler RP, Pirozzi CS, Hansel NN, Wise RA, Brown TT, Drummond MB. Associations Among 25-Hydroxyvitamin D Levels, Lung Function, and Exacerbation Outcomes in COPD: An Analysis of the SPIROMICS Cohort. Chest 2020; 157:856-865. [PMID: 31958447 PMCID: PMC7118244 DOI: 10.1016/j.chest.2019.11.047] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 11/25/2019] [Accepted: 11/30/2019] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND The relationship between 25-hydroxyvitamin D (25-OH-vitamin D) and COPD outcomes remains unclear. Using the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), we determined associations among baseline 25-OH-vitamin D and cross-sectional and longitudinal lung function and COPD exacerbations. METHODS Serum 25-OH-vitamin D level was measured in stored samples from 1,609 SPIROMICS participants with COPD. 25-OH-vitamin D levels were modeled continuously and dichotomized as deficient (< 20 ng/mL) vs not deficient (≥ 20 ng/mL). Outcomes of interest included % predicted FEV1 (current and 1-year longitudinal decline) and COPD exacerbations (separately any and severe, occurring in prior year and first year of follow-up). RESULTS Vitamin D deficiency was present in 21% of the cohort and was more prevalent in the younger, active smokers, and blacks. Vitamin D deficiency was independently associated with lower % predicted FEV1 (by 4.11%) at enrollment (95% CI, -6.90% to -1.34% predicted FEV1; P = .004), 1.27% predicted greater rate of FEV1 decline after 1 year (95% CI, -2.32% to -0.22% predicted/y; P = .02), and higher odds of any COPD exacerbation in the prior year (OR, 1.32; 95% CI, 1.00-1.74; P = .049). Each 10-ng/mL decrease in 25-OH-vitamin D was associated with lower baseline lung function (-1.04% predicted; 95% CI, -1.96% to -0.12% predicted; P = .03) and increased odds of any exacerbation in the year before enrollment (OR, 1.11; 95% CI, 1.01-1.22; P = .04). CONCLUSIONS Vitamin D deficiency is associated with worse cross-sectional and longitudinal lung function and increased odds of prior COPD exacerbations. These findings identify 25-OH-vitamin D levels as a potentially useful marker of adverse COPD-related outcomes.
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Affiliation(s)
- Robert M Burkes
- Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC.
| | - Agathe S Ceppe
- Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Claire M Doerschuk
- Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC; Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - David Couper
- University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC
| | - Eric A Hoffman
- Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, IA
| | - Alejandro P Comellas
- Division of Pulmonary, Critical Care, and Occupational Medicine, University of Iowa Carver College of Medicine, Iowa City, IA
| | - R Graham Barr
- Department of Epidemiology, Columbia University, New York, NY
| | - Jerry A Krishnan
- Division of Pulmonary, Critical Care, Sleep, and Allergy Medicine, University of Illinois at Chicago, Chicago, IL
| | - Christopher Cooper
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA
| | - Wassim W Labaki
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI
| | - Victor E Ortega
- Section of Pulmonary, Critical Care, Allergy, and Immunologic Disease, Wake Forest University, Winston-Salem, NC
| | - J Michael Wells
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Gerard J Criner
- Division of Thoracic Medicine and Surgery, Temple University, Philadelphia, PA
| | - Prescott G Woodruff
- Division of Pulmonary Critical Care, Allergy, and Sleep Medicine, University of California, San Francisco, San Francisco, CA
| | - Russell P Bowler
- Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO
| | - Cheryl S Pirozzi
- Division of Pulmonary and Critical Care Medicine, University of Utah, Salt Lake City, UT
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
| | - Robert A Wise
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
| | - Todd T Brown
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins University, Baltimore, MD
| | - M Bradley Drummond
- Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC; Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC
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Okazawa M, Imaizumi K, Mieno Y, Takahashi H, Paré PD. Ratio of Maximal Inspiratory to Expiratory Flow Aids in the Separation of COPD from Asthma. COPD 2020; 17:230-239. [PMID: 32237910 DOI: 10.1080/15412555.2020.1742679] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Patients who have chronic obstructive pulmonary disease (COPD) and bronchial asthma (BA) share symptoms such as, dyspnoea, cough and wheeze. Differentiating these diseases in the ambulatory setting can be challenging especially in older adult smokers who are being treated with a variety of medications. The objective of this study was to test the value of adding a maximal inspiratory manoeuvre to basic spirometry to differentiate COPD and BA. One hundred forty-three COPD patients and 142 BA patients had measurements of maximal inspiratory and expiratory flow during routine spirometry. Parameters from these tests were used to assess diagnostic accuracy using receiver-operating characteristic (ROC) analyses followed by logistic regression. The association of two independent parameters were analyzed using linear regression analyses. Results show that forced expiratory volume in one second/forced vital capacity (FEV1/FVC%) <62.4 was the best independent predictor to diagnose COPD. The combination of FEV1/FVC% <62.4 and the ratio of peak inspiratory flow/maximal expiratory flow at 50% FVC (PIF/MEF50) >3.06 significantly predicted COPD. Post-test probability for prediction of COPD was 82.0% when patients had both parameters. When asthmatic patients with a smoking history were compared with COPD patients, FEV1/FVC% <63.4 and PIF/MEF50 >3.29 were both independent predictors of COPD. The post-test probability for COPD was 94.4% when patients had both parameters. The association between FEV1/FVC% and PIF/MEF50 was significantly different between COPD and BA. In conclusion, the addition of the maximal inspiratory effort to routine pulmonary function measurements provides a simple test to help differentiate COPD and BA.
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Affiliation(s)
- Mitsushi Okazawa
- Department of Internal Medicine, Division of Respiratory Medicine and Clinical Allergy, Fujita Health University, Toyoake, Japan.,Daiyukai General Hospital, Daiyukai Health System, Ichinomiya, Japan
| | - Kazuyoshi Imaizumi
- Department of Internal Medicine, Division of Respiratory Medicine and Clinical Allergy, Fujita Health University, Toyoake, Japan
| | - Yuki Mieno
- Department of Internal Medicine, Division of Respiratory Medicine and Clinical Allergy, Fujita Health University, Toyoake, Japan
| | - Hiroshi Takahashi
- Division of Medical Statistics, Fujita Health University, Toyoake, Japan
| | - Peter D Paré
- University of British Columbia, Center for Heat Lung Innovation, St Paul's Hospital, Vancouver, Canada
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Oelsner EC, Ortega VE, Smith BM, Nguyen JN, Manichaikul AW, Hoffman EA, Guo X, Taylor KD, Woodruff PG, Couper DJ, Hansel NN, Martinez FJ, Paine R, Han MK, Cooper C, Dransfield MT, Criner G, Krishnan JA, Bowler R, Bleecker ER, Peters S, Rich SS, Meyers DA, Rotter JI, Barr RG. A Genetic Risk Score Associated with Chronic Obstructive Pulmonary Disease Susceptibility and Lung Structure on Computed Tomography. Am J Respir Crit Care Med 2020; 200:721-731. [PMID: 30925230 DOI: 10.1164/rccm.201812-2355oc] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Rationale: Chronic obstructive pulmonary disease (COPD) has been associated with numerous genetic variants, yet the extent to which its genetic risk is mediated by variation in lung structure remains unknown.Objectives: To characterize associations between a genetic risk score (GRS) associated with COPD susceptibility and lung structure on computed tomography (CT).Methods: We analyzed data from MESA Lung (Multi-Ethnic Study of Atherosclerosis Lung Study), a U.S. general population-based cohort, and SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study). A weighted GRS was calculated from 83 SNPs that were previously associated with lung function. Lung density, spatially matched airway dimensions, and airway counts were assessed on full-lung CT. Generalized linear models were adjusted for age, age squared, sex, height, principal components of genetic ancestry, smoking status, pack-years, CT model, milliamperes, and total lung volume.Measurements and Main Results: MESA Lung and SPIROMICS contributed 2,517 and 2,339 participants, respectively. Higher GRS was associated with lower lung function and increased COPD risk, as well as lower lung density, smaller airway lumens, and fewer small airways, without effect modification by smoking. Adjustment for CT lung structure, particularly small airway measures, attenuated associations between the GRS and FEV1/FVC by 100% and 60% in MESA and SPIROMICS, respectively. Lung structure (P < 0.0001), but not the GRS (P > 0.10), improved discrimination of moderate-to-severe COPD cases relative to clinical factors alone.Conclusions: A GRS associated with COPD susceptibility was associated with CT lung structure. Lung structure may be an important mediator of heritability and determinant of personalized COPD risk.
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Affiliation(s)
- Elizabeth C Oelsner
- Department of Medicine, Columbia University College of Physicians & Surgeons, New York, New York
| | - Victor E Ortega
- Division of Pulmonary, Critical Care, Allergy, and Immunologic Medicine, Department of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Benjamin M Smith
- Department of Medicine, Columbia University College of Physicians & Surgeons, New York, New York
| | - Jennifer N Nguyen
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | - Eric A Hoffman
- Department of Radiology.,Department of Medicine, and.,Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
| | | | | | - Prescott G Woodruff
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, California
| | - David J Couper
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Fernando J Martinez
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medical College, New York, New York
| | - Robert Paine
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, University of Utah School of Medicine, Salt Lake City, Utah
| | - Meilan K Han
- Division of Pulmonary and Critical Care Medicine, Michigan Medicine, Ann Arbor, Michigan
| | - Christopher Cooper
- Department of Medicine, and.,Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, California
| | - Mark T Dransfield
- Division of Pulmonary, Allergy, and Critical Care, University of Alabama at Birmingham, Birmingham, Alabama
| | - Gerard Criner
- Department of Thoracic Medicine, Temple University, Philadelphia, Pennsylvania
| | - Jerry A Krishnan
- Division of Pulmonary and Critical Care, University of Illinois, Chicago, Illinois
| | - Russell Bowler
- Division of Pulmonary and Critical Care, National Jewish, Denver, Colorado; and
| | | | - Stephen Peters
- Division of Pulmonary, Critical Care, Allergy, and Immunologic Medicine, Department of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | | | | | - R Graham Barr
- Department of Medicine, Columbia University College of Physicians & Surgeons, New York, New York
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Airway tapering: an objective image biomarker for bronchiectasis. Eur Radiol 2020; 30:2703-2711. [PMID: 32025831 PMCID: PMC7160094 DOI: 10.1007/s00330-019-06606-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 11/13/2019] [Accepted: 12/03/2019] [Indexed: 12/15/2022]
Abstract
Purpose To estimate airway tapering in control subjects and to assess the usability of tapering as a bronchiectasis biomarker in paediatric populations. Methods Airway tapering values were semi-automatically quantified in 156 children with control CTs collected in the Normal Chest CT Study Group. Airway tapering as a biomarker for bronchiectasis was assessed on spirometer-guided inspiratory CTs from 12 patients with bronchiectasis and 12 age- and sex-matched controls. Semi-automatic image analysis software was used to quantify intra-branch tapering (reduction in airway diameter along the branch), inter-branch tapering (reduction in airway diameter before and after bifurcation) and airway-artery ratios on chest CTs. Biomarkers were further stratified in small, medium and large airways based on three equal groups of the accompanying vessel size. Results Control subjects showed intra-branch tapering of 1% and inter-branch tapering of 24–39%. Subjects with bronchiectasis showed significantly reduced intra-branch of 0.8% and inter-branch tapering of 19–32% and increased airway–artery ratios compared with controls (p < 0.01). Tapering measurements were significantly different between diseased and controls across all airway sizes. Difference in airway–artery ratio was only significant in small airways. Conclusion Paediatric normal values for airway tapering were established in control subjects. Tapering showed to be a promising biomarker for bronchiectasis as subjects with bronchiectasis show significantly less airway tapering across all airway sizes compared with controls. Detecting less tapering in larger airways could potentially lead to earlier diagnosis of bronchiectasis. Additionally, compared with the conventional airway–artery ratio, this novel biomarker has the advantage that it does not require pairing with pulmonary arteries. Key Points • Tapering is a promising objective image biomarker for bronchiectasis that can be extracted semi-automatically and has good correlation with validated visual scoring methods. • Less airway tapering was observed in patients with bronchiectasis and can be observed sensitively throughout the bronchial tree, even in the more central airways. • Tapering values seemed to be less influenced by variety in scanning protocols and lung volume making it a more robust biomarker for bronchiectasis detection. Electronic supplementary material The online version of this article (10.1007/s00330-019-06606-w) contains supplementary material, which is available to authorized users.
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Nadeem SA, Hoffman EA, Comellas AP, Saha PK. Anatomical Labeling of Human Airway Branches using a Novel Two-Step Machine Learning and Hierarchical Features. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2020; 11313. [PMID: 34267414 DOI: 10.1117/12.2546004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is a common inflammatory disease associated with restricted lung airflow. Quantitative computed tomography (CT)-based bronchial measures are popularly used in COPD-related studies, which require both airway segmentation and anatomical branch labeling. This paper presents an algorithm for anatomical labeling of human airway tree branches using a novel two-step machine learning and hierarchical features. Anatomical labeling of airway branches allows standardized spatial referencing of airway phenotypes in large population-based studies. State-of-the-art anatomical labeling methods are associated with mandatory manual reviewing and correction for mislabeled branches-a time-consuming process susceptible to inter-observer variability. The new method is fully automated, and it uses hierarchical branch-level features from the current as well as ancestral and descendant branches. During the first machine learning step, it differentiates candidate anatomical branches from insignificant topological branches, often, responsible for variations in airway branching patterns. The second step is designed for lung lobe-based classification of anatomical labels for valid candidate branches. The machine learning classifiers has been designed, trained, and validated using total lung capacity (TLC) CT scans (n = 350) from the Iowa cohort of the nationwide COPDGene study during their baseline visits. One hundred TLC CT scans were used for training and validation, and a different set of 250 scans were used for testing and evaluative experiments. The new method achieved labeling accuracies of 98.4, 97.2, 92.3, 93.4, and 94.1% in the right upper, right middle, right lower, left upper, and left lower lobe, respectively, and an overall accuracy of 95.9%. For five clinically significant segmental branches, the method has achieved an accuracy of 95.2%.
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Affiliation(s)
- Syed Ahmed Nadeem
- Department of Electrical and Computer Engineering, College of Engineering, University of Iowa, Iowa City, Iowa, USA 52242
| | - Eric A Hoffman
- Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA 52242
| | - Alejandro P Comellas
- Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA 52242
| | - Punam K Saha
- Department of Electrical and Computer Engineering, College of Engineering, University of Iowa, Iowa City, Iowa, USA 52242.,Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA 52242
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Refaee T, Wu G, Ibrahim A, Halilaj I, Leijenaar RTH, Rogers W, Gietema HA, Hendriks LEL, Lambin P, Woodruff HC. The Emerging Role of Radiomics in COPD and Lung Cancer. Respiration 2020; 99:99-107. [PMID: 31991420 DOI: 10.1159/000505429] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 12/12/2019] [Indexed: 12/24/2022] Open
Abstract
Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial intelligence in medical imaging has transformed medical images into mineable data, by extracting and correlating quantitative imaging features with patients' outcomes and tumor phenotype - a process termed radiomics. While this process has already been widely researched in lung oncology, the evaluation of COPD in this fashion remains in its infancy. Here we outline the main applications of radiomics in lung cancer and briefly review the workflow from image acquisition to the evaluation of model performance. Finally, we discuss the current assessments of COPD and the potential application of radiomics in COPD.
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Affiliation(s)
- Turkey Refaee
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands, .,Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia,
| | - Guangyao Wu
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Abdallah Ibrahim
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands.,Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, Centre Hospitalier Universitaire de Liège, Liège, Belgium.,Department of Nuclear Medicine and Comprehensive Diagnostic Center Aachen (CDCA), University Hospital RWTH Aachen University, Aachen, Germany
| | - Iva Halilaj
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Ralph T H Leijenaar
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - William Rogers
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.,Department of Thoracic Oncology, IRCCS Foundation National Cancer Institute, Milan, Italy
| | - Hester A Gietema
- Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Lizza E L Hendriks
- Department of Pulmonary Diseases, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
| | - Philippe Lambin
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Henry C Woodruff
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.,Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands
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Quantitative CT detects progression in COPD patients with severe emphysema in a 3-month interval. Eur Radiol 2020; 30:2502-2512. [PMID: 31965260 DOI: 10.1007/s00330-019-06577-y] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 09/26/2019] [Accepted: 11/07/2019] [Indexed: 10/25/2022]
Abstract
OBJECTIVES Chronic obstructive pulmonary disease (COPD) is characterized by variable contributions of emphysema and airway disease on computed tomography (CT), and still little is known on their temporal evolution. We hypothesized that quantitative CT (QCT) is able to detect short-time changes in a cohort of patients with very severe COPD. METHODS Two paired in- and expiratory CT each from 70 patients with avg. GOLD stage of 3.6 (mean age = 66 ± 7.5, mean FEV1/FVC = 35.28 ± 7.75) were taken 3 months apart and analyzed by fully automatic software computing emphysema (emphysema index (EI), mean lung density (MLD)), air-trapping (ratio expiration to inspiration of mean lung attenuation (E/I MLA), relative volume change between - 856 HU and - 950 HU (RVC856-950)), and parametric response mapping (PRM) parameters for each lobe separately and the whole lung. Airway metrics measured were wall thickness (WT) and lumen area (LA) for each airway generation and the whole lung. RESULTS The average of the emphysema parameters (EI, MLD) increased significantly by 1.5% (p < 0.001) for the whole lung, whereas air-trapping parameters (E/I MLA, RVC856-950) were stable. PRMEmph increased from 34.3 to 35.7% (p < 0.001), whereas PRMNormal decrased from 23.6% to 22.8% (p = 0.012). WT decreased significantly from 1.17 ± 0.18 to 1.14 ± 0.19 mm (p = 0.036) and LA increased significantly from 25.08 ± 4.49 to 25.84 ± 4.87 mm2 (p = 0.041) for the whole lung. The generation-based analysis showed heterogeneous results. CONCLUSION QCT detects short-time progression of emphysema in severe COPD. The changes were partly different among lung lobes and airway generations, indicating that QCT is useful to address the heterogeneity of COPD progression. KEY POINTS • QCT detects short-time progression of emphysema in severe COPD in a 3-month period. • QCT is able to quantify even slight parenchymal changes, which were not detected by spirometry. • QCT is able to address the heterogeneity of COPD, revealing inconsistent changes individual lung lobes and airway generations.
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Bhatt SP, Washko GR, Hoffman EA, Newell JD, Bodduluri S, Diaz AA, Galban CJ, Silverman EK, San José Estépar R, Lynch DA. Imaging Advances in Chronic Obstructive Pulmonary Disease. Insights from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) Study. Am J Respir Crit Care Med 2019; 199:286-301. [PMID: 30304637 DOI: 10.1164/rccm.201807-1351so] [Citation(s) in RCA: 86] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.
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Affiliation(s)
- Surya P Bhatt
- 1 UAB Lung Imaging Core and UAB Lung Health Center, Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham School of Medicine, Birmingham, Alabama
| | | | - Eric A Hoffman
- 3 Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - John D Newell
- 3 Department of Radiology, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Sandeep Bodduluri
- 1 UAB Lung Imaging Core and UAB Lung Health Center, Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham School of Medicine, Birmingham, Alabama
| | | | - Craig J Galban
- 4 Department of Radiology and Center for Molecular Imaging, University of Michigan, Ann Arbor, Michigan; and
| | | | - Raúl San José Estépar
- 6 Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - David A Lynch
- 7 Department of Radiology, National Jewish Health, Denver, Colorado
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Tanabe N, Shima H, Sato S, Oguma T, Kubo T, Kozawa S, Koizumi K, Sato A, Togashi K, Hirai T. Direct evaluation of peripheral airways using ultra-high-resolution CT in chronic obstructive pulmonary disease. Eur J Radiol 2019; 120:108687. [DOI: 10.1016/j.ejrad.2019.108687] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 09/04/2019] [Accepted: 09/17/2019] [Indexed: 11/16/2022]
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