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Neder JA, Santyr G, Zanette B, Kirby M, Pourafkari M, James MD, Vincent SG, Ferguson C, Wang CY, Domnik NJ, Phillips DB, Porszasz J, Stringer WW, O'Donnell DE. Beyond Spirometry: Linking Wasted Ventilation to Exertional Dyspnea in the Initial Stages of COPD. COPD 2024; 21:2301549. [PMID: 38348843 DOI: 10.1080/15412555.2023.2301549] [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: 10/15/2023] [Accepted: 12/29/2023] [Indexed: 02/15/2024]
Abstract
Exertional dyspnea, a key complaint of patients with chronic obstructive pulmonary disease (COPD), ultimately reflects an increased inspiratory neural drive to breathe. In non-hypoxemic patients with largely preserved lung mechanics - as those in the initial stages of the disease - the heightened inspiratory neural drive is strongly associated with an exaggerated ventilatory response to metabolic demand. Several lines of evidence indicate that the so-called excess ventilation (high ventilation-CO2 output relationship) primarily reflects poor gas exchange efficiency, namely increased physiological dead space. Pulmonary function tests estimating the extension of the wasted ventilation and selected cardiopulmonary exercise testing variables can, therefore, shed unique light on the genesis of patients' out-of-proportion dyspnea. After a succinct overview of the basis of gas exchange efficiency in health and inefficiency in COPD, we discuss how wasted ventilation translates into exertional dyspnea in individual patients. We then outline what is currently known about the structural basis of wasted ventilation in "minor/trivial" COPD vis-à-vis the contribution of emphysema versus a potential impairment in lung perfusion across non-emphysematous lung. After summarizing some unanswered questions on the field, we propose that functional imaging be amalgamated with pulmonary function tests beyond spirometry to improve our understanding of this deeply neglected cause of exertional dyspnea. Advances in the field will depend on our ability to develop robust platforms for deeply phenotyping (structurally and functionally), the dyspneic patients showing unordinary high wasted ventilation despite relatively preserved FEV1.
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Affiliation(s)
- J Alberto Neder
- Respiratory Investigation Unit, Division of Respirology, Department of Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, Canada
| | - Giles Santyr
- Translational Medicine Department, Faculty of Physiology and Experimental Medicine, Hospital for Sick Children, Toronto, Canada
| | - Brandon Zanette
- Translational Medicine Department, Faculty of Physiology and Experimental Medicine, Hospital for Sick Children, Toronto, Canada
| | - Miranda Kirby
- Department of Physics, Faculty of Science, Toronto Metropolitan University, Toronto, Canada
| | - Marina Pourafkari
- Department of Radiology and Diagnostic Imaging, Kingston Health Sciences Centre, Kingston, Canada
| | - Matthew D James
- Respiratory Investigation Unit, Division of Respirology, Department of Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, Canada
| | - Sandra G Vincent
- Respiratory Investigation Unit, Division of Respirology, Department of Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, Canada
| | - Carrie Ferguson
- The Lundquist Institute for Biomedical Innovation, Harbor U.C.L.A Medical Centre, Torrance, CA, USA
| | - Chu-Yi Wang
- The Lundquist Institute for Biomedical Innovation, Harbor U.C.L.A Medical Centre, Torrance, CA, USA
| | - Nicolle J Domnik
- Respiratory Investigation Unit, Division of Respirology, Department of Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, Canada
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, Canada
| | - Devin B Phillips
- School of Kinesiology and Health Science, York University, Toronto, Canada
| | - Janos Porszasz
- The Lundquist Institute for Biomedical Innovation, Harbor U.C.L.A Medical Centre, Torrance, CA, USA
| | - William W Stringer
- The Lundquist Institute for Biomedical Innovation, Harbor U.C.L.A Medical Centre, Torrance, CA, USA
| | - Denis E O'Donnell
- Respiratory Investigation Unit, Division of Respirology, Department of Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, Canada
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Shim J, Kang SH, Lee Y. Utility of block-matching and 3D filter for reproducibility of lung density and denoising in low-dose chest CT: A pilot study. Phys Med 2024; 124:103432. [PMID: 38996628 DOI: 10.1016/j.ejmp.2024.103432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 07/02/2024] [Accepted: 07/08/2024] [Indexed: 07/14/2024] Open
Abstract
PURPOSE This study aimed to acquire an image quality consistent with that of full-dose chest computed tomography (CT) when obtaining low-dose chest CT images and to analyze the effects of block-matching and 3D (BM3D) filters on lung density measurements and noise reduction in lung parenchyma. METHODS Using full-dose chest CT images, we evaluated lung density measurements and noise reduction in lung parenchyma images for low-dose chest CT. Three filters (median, Wiener, and the proposed BM3D) were applied to low-dose chest CT images for comparison and analysis with images from full-dose chest CT. To evaluate lung density measurements, we measured CT attenuation at the 15th percentile of the lung CT histogram. The coefficient of variation (COV) and contrast-to-noise ratio (CNR) were used to evaluate the noise level. RESULTS The 15th percentile of the lung CT histogram showed the smallest difference between full- and low-dose CT when applying the BM3D filter, and the highest difference between full- and low-dose CT without filters (full-dose = - 926.28 ± 0.32, BM3D = - 926.65 ± 0.32, and low-dose = - 959.43 ± 0.95) (p < 0.05). The COV was smallest when applying the BM3D filter, whereas the CNR was the highest (p < 0.05). CONCLUSIONS The results of the study prove that the BM3D filter can reduce image noise while increasing the reproducibility of the lung density, even for low-dose chest CT.
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Affiliation(s)
- Jina Shim
- Department of Diagnostic Radiology, Severance Hospital, Seoul, Republic of Korea
| | - Seong-Hyeon Kang
- Department of Radiological Science, Gachon University, Incheon, Republic of Korea.
| | - Youngjin Lee
- Department of Radiological Science, Gachon University, Incheon, Republic of Korea.
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Gerard SE, Dougherty TM, Nagpal P, Jin D, Han MK, Newell JD, Saha PK, Comellas AP, Cooper CB, Couper D, Fortis S, Guo J, Hansel NN, Kanner RE, Kazeroni EA, Martinez FJ, Motahari A, Paine R, Rennard S, Schroeder JD, Woodruff PG, Barr RG, Smith BM, Hoffman EA. Vessel and Airway Characteristics in One-Year Computed Tomography-defined Rapid Emphysema Progression: SPIROMICS. Ann Am Thorac Soc 2024; 21:1022-1033. [PMID: 38530051 DOI: 10.1513/annalsats.202304-383oc] [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: 04/27/2023] [Accepted: 03/22/2024] [Indexed: 03/27/2024] Open
Abstract
Rationale: Rates of emphysema progression vary in chronic obstructive pulmonary disease (COPD), and the relationships with vascular and airway pathophysiology remain unclear. Objectives: We sought to determine if indices of peripheral (segmental and beyond) pulmonary arterial dilation measured on computed tomography (CT) are associated with a 1-year index of emphysema (EI; percentage of voxels <-950 Hounsfield units) progression. Methods: Five hundred ninety-nine former and never-smokers (Global Initiative for Chronic Obstructive Lung Disease stages 0-3) were evaluated from the SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) cohort: rapid emphysema progressors (RPs; n = 188, 1-year ΔEI > 1%), nonprogressors (n = 301, 1-year ΔEI ± 0.5%), and never-smokers (n = 110). Segmental pulmonary arterial cross-sectional areas were standardized to associated airway luminal areas (segmental pulmonary artery-to-airway ratio [PAARseg]). Full-inspiratory CT scan-derived total (arteries and veins) pulmonary vascular volume (TPVV) was compared with small vessel volume (radius smaller than 0.75 mm). Ratios of airway to lung volume (an index of dysanapsis and COPD risk) were compared with ratios of TPVV to lung volume. Results: Compared with nonprogressors, RPs exhibited significantly larger PAARseg (0.73 ± 0.29 vs. 0.67 ± 0.23; P = 0.001), lower ratios of TPVV to lung volume (3.21 ± 0.42% vs. 3.48 ± 0.38%; P = 5.0 × 10-12), lower ratios of airway to lung volume (0.031 ± 0.003 vs. 0.034 ± 0.004; P = 6.1 × 10-13), and larger ratios of small vessel volume to TPVV (37.91 ± 4.26% vs. 35.53 ± 4.89%; P = 1.9 × 10-7). In adjusted analyses, an increment of 1 standard deviation in PAARseg was associated with a 98.4% higher rate of severe exacerbations (95% confidence interval, 29-206%; P = 0.002) and 79.3% higher odds of being in the RP group (95% confidence interval, 24-157%; P = 0.001). At 2-year follow-up, the CT-defined RP group demonstrated a significant decline in postbronchodilator percentage predicted forced expiratory volume in 1 second. Conclusions: Rapid one-year progression of emphysema was associated with indices indicative of higher peripheral pulmonary vascular resistance and a possible role played by pulmonary vascular-airway dysanapsis.
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Affiliation(s)
| | | | - Prashant Nagpal
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Dakai Jin
- Department of Electrical and Computer Engineering
| | | | - John D Newell
- Roy J. Carver Department of Biomedical Engineering
- Department of Radiology, and
| | - Punam K Saha
- Department of Electrical and Computer Engineering
- Department of Radiology, and
| | | | - Christopher B Cooper
- Department of Medicine, University of California, Los Angeles, Los Angeles, California
| | - David Couper
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
| | | | - Junfeng Guo
- Roy J. Carver Department of Biomedical Engineering
- Department of Radiology, and
| | - Nadia N Hansel
- Department of Medicine, The Johns Hopkins University, Baltimore, Maryland
| | | | - Ella A Kazeroni
- Department of Radiology, Medical School, University of Michigan, Ann Arbor, Michigan
| | | | | | | | - Stephen Rennard
- Department of Internal Medicine, University of Nebraska, Omaha, Nebraska
| | | | - Prescott G Woodruff
- Department of Medicine, University of California, San Francisco, San Francisco, California
| | - R Graham Barr
- Department of Medicine and
- Department of Epidemiology, College of Medicine, Columbia University, New York, New York; and
| | - Benjamin M Smith
- Department of Medicine and
- Department of Epidemiology, College of Medicine, Columbia University, New York, New York; and
- Department of Medicine, McGill University, Montreal, Quebec, Canada
| | - Eric A Hoffman
- Roy J. Carver Department of Biomedical Engineering
- Department of Radiology, and
- Department of Medicine, University of Iowa, Iowa City, Iowa
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Chaudhary MFA, Gerard SE, Christensen GE, Cooper CB, Schroeder JD, Hoffman EA, Reinhardt JM. LungViT: Ensembling Cascade of Texture Sensitive Hierarchical Vision Transformers for Cross-Volume Chest CT Image-to-Image Translation. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2448-2465. [PMID: 38373126 PMCID: PMC11227912 DOI: 10.1109/tmi.2024.3367321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Chest computed tomography (CT) at inspiration is often complemented by an expiratory CT to identify peripheral airways disease. Additionally, co-registered inspiratory-expiratory volumes can be used to derive various markers of lung function. Expiratory CT scans, however, may not be acquired due to dose or scan time considerations or may be inadequate due to motion or insufficient exhale; leading to a missed opportunity to evaluate underlying small airways disease. Here, we propose LungViT- a generative adversarial learning approach using hierarchical vision transformers for translating inspiratory CT intensities to corresponding expiratory CT intensities. LungViT addresses several limitations of the traditional generative models including slicewise discontinuities, limited size of generated volumes, and their inability to model texture transfer at volumetric level. We propose a shifted-window hierarchical vision transformer architecture with squeeze-and-excitation decoder blocks for modeling dependencies between features. We also propose a multiview texture similarity distance metric for texture and style transfer in 3D. To incorporate global information into the training process and refine the output of our model, we use ensemble cascading. LungViT is able to generate large 3D volumes of size 320×320×320 . We train and validate our model using a diverse cohort of 1500 subjects with varying disease severity. To assess model generalizability beyond the development set biases, we evaluate our model on an out-of-distribution external validation set of 200 subjects. Clinical validation on internal and external testing sets shows that synthetic volumes could be reliably adopted for deriving clinical endpoints of chronic obstructive pulmonary disease.
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Escalon JG, Girvin F. Smoking-Related Interstitial Lung Disease and Emphysema. Clin Chest Med 2024; 45:461-473. [PMID: 38816100 DOI: 10.1016/j.ccm.2023.08.016] [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] [Indexed: 06/01/2024]
Abstract
Diagnosis and treatment of patients with smoking-related lung diseases often requires multidisciplinary contributions to optimize care. Imaging plays a key role in characterizing the underlying disease, quantifying its severity, identifying potential complications, and directing management. The primary goal of this article is to provide an overview of the imaging findings and distinguishing features of smoking-related lung diseases, specifically, emphysema/chronic obstructive pulmonary disease, respiratory bronchiolitis-interstitial lung disease, smoking-related interstitial fibrosis, desquamative interstitial pneumonitis, combined pulmonary fibrosis and emphysema, pulmonary Langerhans cell histiocytosis, and E-cigarette or vaping related lung injury.
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Affiliation(s)
- Joanna G Escalon
- Department of Radiology, New York-Presbyterian Hospital-Weill Cornell Medical College, 525 E 68th Street, New York, NY 10065, USA.
| | - Francis Girvin
- Department of Radiology, New York-Presbyterian Hospital-Weill Cornell Medical College, 525 E 68th Street, New York, NY 10065, USA
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6
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Wang JM, Bell AJ, Ram S, Labaki WW, Hoff BA, Murray S, Kazerooni EA, Galban S, Hatt CR, Han MK, Galban CJ. Topologic Parametric Response Mapping Identifies Tissue Subtypes Associated with Emphysema Progression. Acad Radiol 2024; 31:1148-1159. [PMID: 37661554 PMCID: PMC11098545 DOI: 10.1016/j.acra.2023.08.003] [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: 06/09/2023] [Revised: 07/25/2023] [Accepted: 08/03/2023] [Indexed: 09/05/2023]
Abstract
RATIONALE AND OBJECTIVES Small airways disease (SAD) and emphysema are significant components of chronic obstructive pulmonary disease (COPD), a heterogenous disease where predicting progression is difficult. SAD, a principal cause of airflow obstruction in mild COPD, has been identified as a precursor to emphysema. Parametric Response Mapping (PRM) of chest computed tomography (CT) can help distinguish SAD from emphysema. Specifically, topologic PRM can define local patterns of both diseases to characterize how and in whom COPD progresses. We aimed to determine if distribution of CT-based PRM of functional SAD (fSAD) is associated with emphysema progression. MATERIALS AND METHODS We analyzed paired inspiratory-expiratory chest CT scans at baseline and 5-year follow up in 1495 COPDGene subjects using topological analyses of PRM classifications. By spatially aligning temporal scans, we mapped local emphysema at year five to baseline lobar PRM-derived topological readouts. K-means clustering was applied to all observations. Subjects were subtyped based on predominant PRM cluster assignments and assessed using non-parametric statistical tests to determine differences in PRM values, pulmonary function metrics, and clinical measures. RESULTS We identified distinct lobar imaging patterns and classified subjects into three radiologic subtypes: emphysema-dominant (ED), fSAD-dominant (FD), and fSAD-transition (FT: transition from healthy lung to fSAD). Relative to year five emphysema, FT showed rapid local emphysema progression (-57.5% ± 1.1) compared to FD (-49.9% ± 0.5) and ED (-33.1% ± 0.4). FT consisted primarily of at-risk subjects (roughly 60%) with normal spirometry. CONCLUSION The FT subtype of COPD may allow earlier identification of individuals without spirometrically-defined COPD at-risk for developing emphysema.
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Affiliation(s)
- Jennifer M Wang
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, Michigan (J.M.W., W.W.L., M.K.H.)
| | - Alexander J Bell
- Department of Radiology, University of Michigan, Ann Arbor, Michigan (A.J.B., S.R., B.A.H., E.A.K., S.G., C.R.H., C.J.G.)
| | - Sundaresh Ram
- Department of Radiology, University of Michigan, Ann Arbor, Michigan (A.J.B., S.R., B.A.H., E.A.K., S.G., C.R.H., C.J.G.); Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan (S.R.)
| | - Wassim W Labaki
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, Michigan (J.M.W., W.W.L., M.K.H.)
| | - Benjamin A Hoff
- Department of Radiology, University of Michigan, Ann Arbor, Michigan (A.J.B., S.R., B.A.H., E.A.K., S.G., C.R.H., C.J.G.)
| | - Susan Murray
- School of Public Health, University of Michigan, Ann Arbor, Michigan (S.M.)
| | - Ella A Kazerooni
- Department of Radiology, University of Michigan, Ann Arbor, Michigan (A.J.B., S.R., B.A.H., E.A.K., S.G., C.R.H., C.J.G.)
| | - Stefanie Galban
- Department of Radiology, University of Michigan, Ann Arbor, Michigan (A.J.B., S.R., B.A.H., E.A.K., S.G., C.R.H., C.J.G.)
| | - Charles R Hatt
- Department of Radiology, University of Michigan, Ann Arbor, Michigan (A.J.B., S.R., B.A.H., E.A.K., S.G., C.R.H., C.J.G.); Imbio, LLC, Minneapolis, Minnesota (C.R.H.)
| | - MeiLan K Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, Michigan (J.M.W., W.W.L., M.K.H.)
| | - Craig J Galban
- Department of Radiology, University of Michigan, Ann Arbor, Michigan (A.J.B., S.R., B.A.H., E.A.K., S.G., C.R.H., C.J.G.).
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Sotoudeh-Paima S, Ho FC, Nejad MG, Kavuri A, O'Sullivan-Murphy B, Lynch DA, Segars WP, Samei E, Abadi E. Development and Application of a Virtual Imaging Trial Framework for Longitudinal Quantification of Emphysema in CT. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2024; 12925:129251H. [PMID: 38741597 PMCID: PMC11090051 DOI: 10.1117/12.3006925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Pulmonary emphysema is a progressive lung disease that requires accurate evaluation for optimal management. This task, possible using quantitative CT, is particularly challenging as scanner and patient attributes change over time, negatively impacting the CT-derived quantitative measures. Efforts to minimize such variations have been limited by the absence of ground truth in clinical data, thus necessitating reliance on clinical surrogates, which may not have one-to-one correspondence to CT-based findings. This study aimed to develop the first suite of human models with emphysema at multiple time points, enabling longitudinal assessment of disease progression with access to ground truth. A total of 14 virtual subjects were modeled across three time points. Each human model was virtually imaged using a validated imaging simulator (DukeSim), modeling an energy-integrating CT scanner. The models were scanned at two dose levels and reconstructed with two reconstruction kernels, slice thicknesses, and pixel sizes. The developed longitudinal models were further utilized to demonstrate utility in algorithm testing and development. Two previously developed image processing algorithms (CT-HARMONICA, EmphysemaSeg) were evaluated. The results demonstrated the efficacy of both algorithms in improving the accuracy and precision of longitudinal quantifications, from 6.1±6.3% to 1.1±1.1% and 1.6±2.2% across years 0-5. Further investigation in EmphysemaSeg identified that baseline emphysema severity, defined as >5% emphysema at year 0, contributed to its reduced performance. This finding highlights the value of virtual imaging trials in enhancing the explainability of algorithms. Overall, the developed longitudinal human models enabled ground-truth based assessment of image processing algorithms for lung quantifications.
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Affiliation(s)
- Saman Sotoudeh-Paima
- Department of Radiology, Duke University School of Medicine, Durham, NC
- Department of Electrical and Computer Engineering, Duke University, Durham, NC
| | - Fong Chi Ho
- Department of Radiology, Duke University School of Medicine, Durham, NC
- Department of Electrical and Computer Engineering, Duke University, Durham, NC
| | | | - Amar Kavuri
- Department of Radiology, Duke University School of Medicine, Durham, NC
| | | | - David A Lynch
- Department of Radiology, National Jewish Health, Denver, CO, USA
| | - W Paul Segars
- Department of Radiology, Duke University School of Medicine, Durham, NC
- Department of Biomedical Engineering, Duke University, Durham, NC
- Department Physics, Duke University, Durham, NC
| | - Ehsan Samei
- Department of Radiology, Duke University School of Medicine, Durham, NC
- Department of Electrical and Computer Engineering, Duke University, Durham, NC
- Department of Biomedical Engineering, Duke University, Durham, NC
- Department Physics, Duke University, Durham, NC
- Medical Physics Graduate Program, Duke University, Durham, NC
| | - Ehsan Abadi
- Department of Radiology, Duke University School of Medicine, Durham, NC
- Department of Electrical and Computer Engineering, Duke University, Durham, NC
- Medical Physics Graduate Program, Duke University, Durham, NC
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8
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Suryadevara R, Gregory A, Lu R, Xu Z, Masoomi A, Lutz SM, Berman S, Yun JH, Saferali A, Ryu MH, Moll M, Sin DD, Hersh CP, Silverman EK, Dy J, Pratte KA, Bowler RP, Castaldi PJ, Boueiz A. Blood-based Transcriptomic and Proteomic Biomarkers of Emphysema. Am J Respir Crit Care Med 2024; 209:273-287. [PMID: 37917913 PMCID: PMC10840768 DOI: 10.1164/rccm.202301-0067oc] [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: 01/12/2023] [Accepted: 11/02/2023] [Indexed: 11/04/2023] Open
Abstract
Rationale: Emphysema is a chronic obstructive pulmonary disease phenotype with important prognostic implications. Identifying blood-based biomarkers of emphysema will facilitate early diagnosis and development of targeted therapies. Objectives: To discover blood omics biomarkers for chest computed tomography-quantified emphysema and develop predictive biomarker panels. Methods: Emphysema blood biomarker discovery was performed using differential gene expression, alternative splicing, and protein association analyses in a training sample of 2,370 COPDGene participants with available blood RNA sequencing, plasma proteomics, and clinical data. Internal validation was conducted in a COPDGene testing sample (n = 1,016), and external validation was done in the ECLIPSE study (n = 526). Because low body mass index (BMI) and emphysema often co-occur, we performed a mediation analysis to quantify the effect of BMI on gene and protein associations with emphysema. Elastic net models with bootstrapping were also developed in the training sample sequentially using clinical, blood cell proportions, RNA-sequencing, and proteomic biomarkers to predict quantitative emphysema. Model accuracy was assessed by the area under the receiver operating characteristic curves for subjects stratified into tertiles of emphysema severity. Measurements and Main Results: Totals of 3,829 genes, 942 isoforms, 260 exons, and 714 proteins were significantly associated with emphysema (false discovery rate, 5%) and yielded 11 biological pathways. Seventy-four percent of these genes and 62% of these proteins showed mediation by BMI. Our prediction models demonstrated reasonable predictive performance in both COPDGene and ECLIPSE. The highest-performing model used clinical, blood cell, and protein data (area under the receiver operating characteristic curve in COPDGene testing, 0.90; 95% confidence interval, 0.85-0.90). Conclusions: Blood transcriptome and proteome-wide analyses revealed key biological pathways of emphysema and enhanced the prediction of emphysema.
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Affiliation(s)
| | | | - Robin Lu
- Channing Division of Network Medicine
| | | | - Aria Masoomi
- Department of Electrical and Computer Engineering, Northeastern University, Boston, Massachusetts
| | - Sharon M. Lutz
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | | | - Jeong H. Yun
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | | | | | - Matthew Moll
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
- Pulmonary, Critical Care, Allergy, and Sleep Medicine Section, Veterans Affairs Boston Healthcare System, West Roxbury, Massachusetts
| | - Don D. Sin
- Centre for Heart Lung Innovation, St. Paul’s Hospital, Vancouver, British Columbia, Canada
- Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; and
| | - Craig P. Hersh
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | - Edwin K. Silverman
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
| | - Jennifer Dy
- Department of Electrical and Computer Engineering, Northeastern University, Boston, Massachusetts
| | | | - Russell P. Bowler
- Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, Colorado
| | - Peter J. Castaldi
- Channing Division of Network Medicine
- Division of General Medicine and Primary Care, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Adel Boueiz
- Channing Division of Network Medicine
- Division of Pulmonary and Critical Care Medicine, and
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9
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Chen B, Liu Z, Lu J, Li Z, Kuang K, Yang J, Wang Z, Sun Y, Du B, Qi L, Li M. Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening. Respir Res 2023; 24:299. [PMID: 38017476 PMCID: PMC10683250 DOI: 10.1186/s12931-023-02611-2] [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: 09/01/2023] [Accepted: 11/16/2023] [Indexed: 11/30/2023] Open
Abstract
OBJECTIVES Parametric response mapping (PRM) enables the evaluation of small airway disease (SAD) at the voxel level, but requires both inspiratory and expiratory chest CT scans. We hypothesize that deep learning PRM from inspiratory chest CT scans can effectively evaluate SAD in individuals with normal spirometry. METHODS We included 537 participants with normal spirometry, a history of smoking or secondhand smoke exposure, and divided them into training, tuning, and test sets. A cascaded generative adversarial network generated expiratory CT from inspiratory CT, followed by a UNet-like network predicting PRM using real inspiratory CT and generated expiratory CT. The performance of the prediction is evaluated using SSIM, RMSE and dice coefficients. Pearson correlation evaluated the correlation between predicted and ground truth PRM. ROC curves evaluated predicted PRMfSAD (the volume percentage of functional small airway disease, fSAD) performance in stratifying SAD. RESULTS Our method can generate expiratory CT of good quality (SSIM 0.86, RMSE 80.13 HU). The predicted PRM dice coefficients for normal lung, emphysema, and fSAD regions are 0.85, 0.63, and 0.51, respectively. The volume percentages of emphysema and fSAD showed good correlation between predicted and ground truth PRM (|r| were 0.97 and 0.64, respectively, p < 0.05). Predicted PRMfSAD showed good SAD stratification performance with ground truth PRMfSAD at thresholds of 15%, 20% and 25% (AUCs were 0.84, 0.78, and 0.84, respectively, p < 0.001). CONCLUSION Our deep learning method generates high-quality PRM using inspiratory chest CT and effectively stratifies SAD in individuals with normal spirometry.
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Affiliation(s)
- Bin Chen
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221, Yanan West Road, Jingan Temple Street, Jingan District, Shanghai, China
- Zhang Guozhen Small Pulmonary Nodules Diagnosis and Treatment Center, Shanghai, China
| | - Ziyi Liu
- School of Computer Science, Wuhan University, LuoJiaShan, WuChang District, Wuhan, Hubei, China
- Artificial Intelligence Institute of Wuhan University, Wuhan, Hubei, China
- Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan, Hubei, China
| | - Jinjuan Lu
- Department of Radiology, Shanghai Geriatric Medical Center, Shanghai, China
| | - Zhihao Li
- School of Computer Science, Wuhan University, LuoJiaShan, WuChang District, Wuhan, Hubei, China
- Artificial Intelligence Institute of Wuhan University, Wuhan, Hubei, China
- Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan, Hubei, China
| | - Kaiming Kuang
- Dianei Technology, Shanghai, China
- University of California San Diego, La Jolla, USA
| | - Jiancheng Yang
- Dianei Technology, Shanghai, China
- Computer Vision Laboratory, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
| | - Zengmao Wang
- School of Computer Science, Wuhan University, LuoJiaShan, WuChang District, Wuhan, Hubei, China
- Artificial Intelligence Institute of Wuhan University, Wuhan, Hubei, China
- Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan, Hubei, China
| | - Yingli Sun
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221, Yanan West Road, Jingan Temple Street, Jingan District, Shanghai, China
- Zhang Guozhen Small Pulmonary Nodules Diagnosis and Treatment Center, Shanghai, China
| | - Bo Du
- School of Computer Science, Wuhan University, LuoJiaShan, WuChang District, Wuhan, Hubei, China.
- Artificial Intelligence Institute of Wuhan University, Wuhan, Hubei, China.
- Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan, Hubei, China.
| | - Lin Qi
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221, Yanan West Road, Jingan Temple Street, Jingan District, Shanghai, China.
- Zhang Guozhen Small Pulmonary Nodules Diagnosis and Treatment Center, Shanghai, China.
| | - Ming Li
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221, Yanan West Road, Jingan Temple Street, Jingan District, Shanghai, China.
- Zhang Guozhen Small Pulmonary Nodules Diagnosis and Treatment Center, Shanghai, China.
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10
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Makimoto K, Hogg JC, Bourbeau J, Tan WC, Kirby M. CT Imaging With Machine Learning for Predicting Progression to COPD in Individuals at Risk. Chest 2023; 164:1139-1149. [PMID: 37421974 DOI: 10.1016/j.chest.2023.06.008] [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: 01/19/2023] [Revised: 05/26/2023] [Accepted: 06/05/2023] [Indexed: 07/10/2023] Open
Abstract
BACKGROUND Identifying individuals at risk of progressing to COPD may allow for initiation of treatment to potentially slow the progression of the disease or the selection of subgroups for discovery of novel interventions. RESEARCH QUESTION Does the addition of CT imaging features, texture-based radiomic features, and established quantitative CT scan to conventional risk factors improve the performance for predicting progression to COPD in individuals who smoke with machine learning? STUDY DESIGN AND METHODS Participants at risk (individuals who currently or formerly smoked, without COPD) from the Canadian Cohort Obstructive Lung Disease (CanCOLD) population-based study underwent CT imaging at baseline and spirometry at baseline and follow-up. Various combinations of CT scan features, texture-based CT scan radiomics (n = 95), and established quantitative CT scan (n = 8), as well as demographic (n = 5) and spirometry (n = 3) measurements, with machine learning algorithms were evaluated to predict progression to COPD. Performance metrics included the area under the receiver operating characteristic curve (AUC) to evaluate the models. DeLong test was used to compare the performance of the models. RESULTS Among the 294 at-risk participants who were evaluated (mean age, 65.6 ± 9.2 years; 42% female; mean pack-years, 17.9 ± 18.7), 52 participants (23.7%) in the training data set and 17 participants (23.0%) in the testing data set progressed to spirometric COPD at follow-up (2.5 ± 0.9 years from baseline). Compared with machine learning models with demographics alone (AUC, 0.649), the addition of CT imaging features to demographics (AUC, 0.730; P < .05) or CT imaging features and spirometry to demographics (AUC, 0.877; P < .05) significantly improved the performance for predicting progression to COPD. INTERPRETATION Heterogeneous structural changes occur in the lungs of individuals at risk that can be quantified using CT imaging features, and evaluation of these features together with conventional risk factors improves performance for predicting progression to COPD.
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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.
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11
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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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12
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Shiraishi Y, Tanabe N, Shimizu K, Oguma A, Shima H, Sakamoto R, Yamazaki H, Oguma T, Sato A, Suzuki M, Makita H, Muro S, Nishimura M, Sato S, Konno S, Hirai T. Stronger Associations of Centrilobular Than Paraseptal Emphysema With Longitudinal Changes in Diffusing Capacity and Mortality in COPD. Chest 2023; 164:327-338. [PMID: 36736486 DOI: 10.1016/j.chest.2023.01.034] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/27/2022] [Accepted: 01/24/2023] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND The factors associated with longitudinal changes in diffusing capacity remain unclear among patients with COPD. Centrilobular emphysema (CLE) and paraseptal emphysema (PSE) are major emphysema subtypes that may have distinct clinical-physiological impacts in these patients. RESEARCH QUESTION Are CLE and PSE differently associated with longitudinal changes in diffusing capacity and mortality in patients with COPD? STUDY DESIGN AND METHODS This pooled analysis included 399 patients with COPD from two prospective observational COPD cohorts. CLE and PSE were visually assessed on CT scan according to the Fleischner Society statement. The diffusing capacity and transfer coefficient of the lung for carbon monoxide (Dlco and KCO) and FEV1 were evaluated at least annually over a 5-year period. Mortality was recorded over 10 years. Longitudinal changes in FEV1, Dlco, and KCO and mortality were compared between mild or less severe and moderate or more severe CLE and between present and absent PSE in each Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage. RESULTS The Dlco and KCO decline was weakly associated with FEV1 and greater in GOLD stage 3 or higher than in GOLD stages 1 and 2. Furthermore, moderate or more severe CLE, but not present PSE, was associated with steeper declines in Dlco for GOLD stages 1 and 3 or higher and KCO for all GOLD stages independent of age, sex, height, and smoking history. The moderate or more severe CLE, but not present PSE, was associated with additional FEV1 decline and higher 10-year mortality among patients with GOLD stage 3 or higher. INTERPRETATION A CT scan finding of moderate or more severe CLE, but not PSE, was associated with a subsequent accelerated impairment in diffusing capacity and higher long-term mortality in severe GOLD stage among patients with COPD.
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Affiliation(s)
- Yusuke Shiraishi
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Tanabe
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
| | - Kaoruko Shimizu
- Department of Respiratory Medicine, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Akira Oguma
- Department of Respiratory Medicine, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Hiroshi Shima
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryo Sakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Hajime Yamazaki
- Section of Clinical Epidemiology, Department of Community Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tsuyoshi Oguma
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsuyasu Sato
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Masaru Suzuki
- Department of Respiratory Medicine, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Hironi Makita
- Department of Respiratory Medicine, Faculty of Medicine, Hokkaido University, Sapporo, Japan; Hokkaido Medical Research Institute for Respiratory Diseases, Sapporo, Japan
| | - Shigeo Muro
- Department of Respiratory Medicine, Nara Medical University, Kashihara, Japan
| | - Masaharu Nishimura
- Department of Respiratory Medicine, Faculty of Medicine, Hokkaido University, Sapporo, Japan; Hokkaido Medical Research Institute for Respiratory Diseases, Sapporo, Japan
| | - Susumu Sato
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan; Department of Respiratory Care and Sleep Control Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Satoshi Konno
- Department of Respiratory Medicine, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Toyohiro Hirai
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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13
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Raoof S, Shah M, Braman S, Agrawal A, Allaqaband H, Bowler R, Castaldi P, DeMeo D, Fernando S, Hall CS, Han MK, Hogg J, Humphries S, Lee HY, Lee KS, Lynch D, Machnicki S, Mehta A, Mehta S, Mina B, Naidich D, Naidich J, Ohno Y, Regan E, van Beek EJR, Washko G, Make B. Lung Imaging in COPD Part 2: Emerging Concepts. Chest 2023; 164:339-354. [PMID: 36907375 PMCID: PMC10475822 DOI: 10.1016/j.chest.2023.02.049] [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: 10/06/2022] [Revised: 02/23/2023] [Accepted: 02/25/2023] [Indexed: 03/13/2023] Open
Abstract
The diagnosis, prognostication, and differentiation of phenotypes of COPD can be facilitated by CT scan imaging of the chest. CT scan imaging of the chest is a prerequisite for lung volume reduction surgery and lung transplantation. Quantitative analysis can be used to evaluate extent of disease progression. Evolving imaging techniques include micro-CT scan, ultra-high-resolution and photon-counting CT scan imaging, and MRI. Potential advantages of these newer techniques include improved resolution, prediction of reversibility, and obviation of radiation exposure. This article discusses important emerging techniques in imaging patients with COPD. The clinical usefulness of these emerging techniques as they stand today are tabulated for the benefit of the practicing pulmonologist.
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Affiliation(s)
- Suhail Raoof
- Northwell Health, Lenox Hill Hospital, New York, NY.
| | - Manav Shah
- Northwell Health, Lenox Hill Hospital, New York, NY
| | - Sidney Braman
- Icahn School of Medicine at Mount Sinai, New York, NY
| | | | | | | | | | - Dawn DeMeo
- Brigham and Women's Hospital, Boston, MA
| | | | | | | | - James Hogg
- University of British Columbia, Vancouver, BC, Canada
| | | | - Ho Yun Lee
- Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Department of Health Sciences and Technology, Sungkyunkwan University, ChangWon, South Korea
| | - Kyung Soo Lee
- Sungkyunkwan University School of Medicine, Samsung ChangWon Hospital, ChangWon, South Korea
| | | | | | | | | | - Bushra Mina
- Northwell Health, Lenox Hill Hospital, New York, NY
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14
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Colombi D, Adebanjo GAR, Delfanti R, Chiesa S, Morelli N, Capelli P, Franco C, Michieletti E. Association between Mortality and Lung Low Attenuation Areas in NSCLC Treated by Surgery. Life (Basel) 2023; 13:1377. [PMID: 37374159 DOI: 10.3390/life13061377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 06/08/2023] [Accepted: 06/09/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND to test the association with overall survival (OS) of low attenuation areas (LAAs) quantified by staging computed tomography (CT) of patients who underwent radical surgery for nonsmall-cell lung cancer (NSCLC). METHODS patients who underwent radical surgery for NSCLC at our institution between 1 January 2017 and 30 November 2021 were retrospectively evaluated. Patients who performed staging or follow-up CTs in other institutions, who received lung radiotherapy or chemotherapy, and who underwent previous lung surgery were excluded. At staging and 12-months follow-up CT, LAAs defined as voxels <-950 Hounsfield units, were extracted by software. The percent of LAAs relative to whole-lung volume (%LAAs) and the ratio between LAAs in the lobe to resect and whole-lung LAAs (%LAAs lobe ratio) were calculated. Cox proportional hazards regression analysis was used to test the association between OS and LAAs. RESULTS the final sample included 75 patients (median age 70 years, IQR 63-75 years; females 29/75, 39%). It identified a significant association with OS for pathological stage III (HR, 6.50; 95%CI, 1.11-37.92; p = 0.038), staging CT %LAAs ≥ 5% (HR, 7.27; 95%CI, 1.60-32.96; p = 0.010), and staging CT %LAA lobe ratio > 10% (HR, 0.24; 95%CI 0.05-0.94; p = 0.046). CONCLUSIONS in patients with NSCLC who underwent radical surgery, a %LAAs ≥ 5% and a %LAA lobe ratio > 10% at staging CT are predictors, respectively, of shorter and longer OS. The LAA ratio to the whole lung at staging CT could be a critical factor to predict the overall survival of the NSCLC patients treated by surgery.
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Affiliation(s)
- Davide Colombi
- Department of Radiological Functions, Radiology Unit, AUSL Piacenza, Via Taverna 49, 29121 Piacenza, Italy
| | | | - Rocco Delfanti
- Department of Surgery, General Surgery Unit, AUSL Piacenza, Via Taverna 49, 29121 Piacenza, Italy
| | - Sara Chiesa
- Emergency Department, Pulmonology Unit, AUSL Piacenza, Via Taverna 49, 29121 Piacenza, Italy
| | - Nicola Morelli
- Department of Radiological Functions, Radiology Unit, AUSL Piacenza, Via Taverna 49, 29121 Piacenza, Italy
| | - Patrizio Capelli
- Department of Surgery, General Surgery Unit, AUSL Piacenza, Via Taverna 49, 29121 Piacenza, Italy
| | - Cosimo Franco
- Emergency Department, Pulmonology Unit, AUSL Piacenza, Via Taverna 49, 29121 Piacenza, Italy
| | - Emanuele Michieletti
- Department of Radiological Functions, Radiology Unit, AUSL Piacenza, Via Taverna 49, 29121 Piacenza, Italy
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15
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Wang R, Huang C, Yang W, Wang C, Wang P, Guo L, Cao J, Huang L, Song H, Zhang C, Zhang Y, Shi G. Respiratory microbiota and radiomics features in the stable COPD patients. Respir Res 2023; 24:131. [PMID: 37173744 PMCID: PMC10176953 DOI: 10.1186/s12931-023-02434-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 04/25/2023] [Indexed: 05/15/2023] Open
Abstract
BACKGROUNDS The respiratory microbiota and radiomics correlate with the disease severity and prognosis of chronic obstructive pulmonary disease (COPD). We aim to characterize the respiratory microbiota and radiomics features of COPD patients and explore the relationship between them. METHODS Sputa from stable COPD patients were collected for bacterial 16 S rRNA gene sequencing and fungal Internal Transcribed Spacer (ITS) sequencing. Chest computed tomography (CT) and 3D-CT analysis were conducted for radiomics information, including the percentages of low attenuation area below - 950 Hounsfield Units (LAA%), wall thickness (WT), and intraluminal area (Ai). WT and Ai were adjusted by body surface area (BSA) to WT/[Formula: see text] and Ai/BSA, respectively. Some key pulmonary function indicators were collected, which included forced expiratory volume in one second (FEV1), forced vital capacity (FVC), diffusion lung carbon monoxide (DLco). Differences and correlations of microbiomics with radiomics and clinical indicators between different patient subgroups were assessed. RESULTS Two bacterial clusters dominated by Streptococcus and Rothia were identified. Chao and Shannon indices were higher in the Streptococcus cluster than that in the Rothia cluster. Principal Co-ordinates Analysis (PCoA) indicated significant differences between their community structures. Higher relative abundance of Actinobacteria was detected in the Rothia cluster. Some genera were more common in the Streptococcus cluster, mainly including Leptotrichia, Oribacterium, Peptostreptococcus. Peptostreptococcus was positively correlated with DLco per unit of alveolar volume as a percentage of predicted value (DLco/VA%pred). The patients with past-year exacerbations were more in the Streptococcus cluster. Fungal analysis revealed two clusters dominated by Aspergillus and Candida. Chao and Shannon indices of the Aspergillus cluster were higher than that in the Candida cluster. PCoA showed distinct community compositions between the two clusters. Greater abundance of Cladosporium and Penicillium was found in the Aspergillus cluster. The patients of the Candida cluster had upper FEV1 and FEV1/FVC levels. In radiomics, the patients of the Rothia cluster had higher LAA% and WT/[Formula: see text] than those of the Streptococcus cluster. Haemophilus, Neisseria and Cutaneotrichosporon positively correlated with Ai/BSA, but Cladosporium negatively correlated with Ai/BSA. CONCLUSIONS Among respiratory microbiota in stable COPD patients, Streptococcus dominance was associated with an increased risk of exacerbation, and Rothia dominance was relevant to worse emphysema and airway lesions. Peptostreptococcus, Haemophilus, Neisseria and Cutaneotrichosporon probably affected COPD progression and potentially could be disease prediction biomarkers.
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Affiliation(s)
- Rong Wang
- Department of Pulmonary and Critical Care Medicine, the Affiliated Hospital of Kunming University of Science and Technology, the First People's Hospital of Yunnan Province, Kunming, 650032, People's Republic of China
- Medical School, Kunming University of Science and Technology, Kunming, 650500, People's Republic of China
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine. Shanghai Key Laboratory of Emergency Prevention, Diagnosis and Treatment of Respiratory Infectious Diseases, Shanghai, 200025, People's Republic of China
| | - Chunrong Huang
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine. Shanghai Key Laboratory of Emergency Prevention, Diagnosis and Treatment of Respiratory Infectious Diseases, Shanghai, 200025, People's Republic of China
| | - Wenjie Yang
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, People's Republic of China
| | - Cui Wang
- Department of Pulmonary and Critical Care Medicine, the Third People's Hospital of Kunshan, Suzhou, 215300, People's Republic of China
| | - Ping Wang
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine. Shanghai Key Laboratory of Emergency Prevention, Diagnosis and Treatment of Respiratory Infectious Diseases, Shanghai, 200025, People's Republic of China
| | - Leixin Guo
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine. Shanghai Key Laboratory of Emergency Prevention, Diagnosis and Treatment of Respiratory Infectious Diseases, Shanghai, 200025, People's Republic of China
| | - Jin Cao
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine. Shanghai Key Laboratory of Emergency Prevention, Diagnosis and Treatment of Respiratory Infectious Diseases, Shanghai, 200025, People's Republic of China
| | - Lin Huang
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine. Shanghai Key Laboratory of Emergency Prevention, Diagnosis and Treatment of Respiratory Infectious Diseases, Shanghai, 200025, People's Republic of China
| | - Hejie Song
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine. Shanghai Key Laboratory of Emergency Prevention, Diagnosis and Treatment of Respiratory Infectious Diseases, Shanghai, 200025, People's Republic of China
| | - Chenhong Zhang
- State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
| | - Yunhui Zhang
- Department of Pulmonary and Critical Care Medicine, the Affiliated Hospital of Kunming University of Science and Technology, the First People's Hospital of Yunnan Province, Kunming, 650032, People's Republic of China.
| | - Guochao Shi
- Department of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. Institute of Respiratory Diseases, Shanghai Jiao Tong University School of Medicine. Shanghai Key Laboratory of Emergency Prevention, Diagnosis and Treatment of Respiratory Infectious Diseases, Shanghai, 200025, People's Republic of China.
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16
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Baraghoshi D, Strand M, Humphries SM, San José Estépar R, Vegas Sanchez-Ferrero G, Charbonnier JP, Latisenko R, Silverman EK, Crapo JD, Lynch DA. Quantitative CT Evaluation of Emphysema Progression over 10 Years in the COPDGene Study. Radiology 2023; 307:e222786. [PMID: 37039685 PMCID: PMC10286952 DOI: 10.1148/radiol.222786] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 02/02/2023] [Accepted: 02/16/2023] [Indexed: 04/12/2023]
Abstract
Background Long-term studies of chronic obstructive pulmonary disease (COPD) can evaluate emphysema progression. Adjustment for differences in equipment and scanning protocols of individual CT examinations have not been studied extensively. Purpose To evaluate emphysema progression in current and former smokers in the COPDGene cohort over three imaging points obtained at 5-year intervals accounting for individual CT parameters. Materials and Methods Current and former cigarette smokers enrolled between 2008 and 2011 from the COPDGene study were prospectively followed for 10 years between 2008 and 2020. Extent of emphysema as adjusted lung density (ALD) from quantitative CT was measured at baseline and at 5- and 10-year follow-up. Linear mixed models adjusted for CT technical characteristics were constructed to evaluate emphysema progression. Mean annual changes in ALD over consecutive 5-year study periods were estimated by smoking status and baseline emphysema. Results Of 8431 participants at baseline (mean age, 60 years ± 9 [SD]; 3905 female participants), 4913 were at 5-year follow-up and 1544 participants were at 10-year follow-up. There were 4134 (49%) participants who were current smokers, and 4449 (53%) participants had more than trace emphysema at baseline. Current smokers with more than trace emphysema showed the largest decline in ALD, with mean annual decreases of 1.4 g/L (95% CI: 1.2, 1.5) in the first 5 years and 0.9 g/L (95% CI: 0.7, 1.2) in the second 5 years. Accounting for CT noise, field of view, and scanner model improved model fit for estimation of emphysema progression (P < .001 by likelihood ratio test). Conclusion Evaluation at CT of emphysema progression in the COPDGene study showed that, during the span of 10 years, participants with pre-existing emphysema who continued smoking had the largest decline in ALD. Adjusting for CT equipment and protocol factors improved these longitudinal estimates. Clinical trial registration no. NCT00608764 © RSNA, 2023 Supplemental material is available for this article. See the editorial by Parraga and Kirby in this issue.
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Affiliation(s)
- David Baraghoshi
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
| | - Matthew Strand
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
| | - Stephen M. Humphries
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
| | - Raúl San José Estépar
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
| | - Gonzalo Vegas Sanchez-Ferrero
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
| | - Jean-Paul Charbonnier
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
| | - Rudolfs Latisenko
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
| | - Edwin K. Silverman
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
| | - James D. Crapo
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
| | - David A. Lynch
- From the Division of Biostatistics, Environment and Health (D.B.,
M.S.), Department of Radiology (S.M.H., D.A.L.), and Division of Pulmonary and
Critical Care Medicine, Department of Medicine (J.D.C.), National Jewish Health,
1400 Jackson St, Denver, CO 80206; Applied Chest Imaging Laboratory (R.S.J.E.,
G.V.S.F.), Department of Radiology (R.S.J.E., G.V.S.F.), Channing Division of
Network Medicine (E.K.S.), and Division of Pulmonary and Critical Care Medicine,
Department of Medicine (E.K.S.), Brigham and Women’s Hospital, Boston,
Mass; and Thirona, Nijmegen, the Netherlands (J.P.C., R.L.)
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17
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Zheng J, Zhou R, Zhang Y, Su K, Chen H, Li F, Hukportie DN, Niu F, Yiu KH, Wu X. Preserved Ratio Impaired Spirometry in Relationship to Cardiovascular Outcomes: A Large Prospective Cohort Study. Chest 2023; 163:610-623. [PMID: 36372304 DOI: 10.1016/j.chest.2022.11.003] [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: 09/14/2022] [Revised: 11/02/2022] [Accepted: 11/03/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Preserved ratio impaired spirometry (PRISm) findings are a heterogeneous condition characterized by a normal FEV1 to FVC ratio with underlying impairment of pulmonary function. Data relating to the association of baseline and trajectories of PRISm findings with diverse cardiovascular outcomes are sparse. RESEARCH QUESTION How do baseline and trajectories of PRISm findings impact subsequent cardiovascular events? STUDY DESIGN AND METHODS In the UK Biobank cohort study, we included participants free of cardiovascular disease (CVD) with spirometry (FEV1 and FVC values) at baseline (2006-2010). Participants with baseline spirometry and follow-up spirometry (2014-2020) were included in the lung function trajectory analysis. Cox proportional hazards multivariate regression was performed to evaluate the outcomes of major adverse cardiovascular events (MACEs), incident myocardial infarction (MI), stroke, heart failure (HF), and CVD mortality in association with lung function. RESULTS For baseline analysis (329,954 participants), the multivariate adjusted hazard ratios (HRs) for participants had PRISm findings (vs normal spirometry findings) were 1.26 (95% CI, 1.17-1.35) for MACE, 1.12 (95% CI, 1.01-1.25) for MI, 1.88 (95% CI, 1.72-2.05) for HF, 1.26 (95% CI, 1.13-1.40) for stroke, and 1.55 (95% CI, 1.37-1.76) for CVD mortality, respectively. A total of 22,781 participants underwent follow-up spirometry after an average of 8.9 years. Trajectory analysis showed that persistent PRISm findings (HR, 1.96; 95% CI, 1.24-3.09) and airflow obstruction (HR, 1.43; 95% CI, 1.00-2.04) was associated with a higher incidence of MACE vs consistently normal lung function. Compared with persistent PRISm findings, changing from PRISm to normal spirometry findings was associated with a lower incidence of MACE (HR, 0.42; 95% CI, 0.19-0.99). INTERPRETATION Individuals with baseline or persistent PRISm findings were at a higher risk of diverse cardiovascular outcomes even after adjusting for a wide range of confounding factors. However, individuals who transitioned from PRISm to normal findings showed a similar cardiovascular risk as those with normal lung function.
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Affiliation(s)
- Jiazhen Zheng
- Bioscience and Biomedical Engineering Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangdong, China; Department of Epidemiology, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, China; Bioscience and Biomedical Engineering Thrust, Systems Hub, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR, China
| | - Rui Zhou
- Department of Epidemiology, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, China
| | - Yingchai Zhang
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR, China
| | - Kelei Su
- Department of Pulmonary and Critical Care Medicine, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Jiangsu, China
| | - Haowen Chen
- Department of Epidemiology, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, China; Institute of Applied Health Research, University of Birmingham, Birmingham, England
| | - Furong Li
- School of Public Health and Emergency Management, Southern University of Science and Technology, Guangdong, China
| | - Daniel Nyarko Hukportie
- Department of Epidemiology, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, China
| | - Fangbing Niu
- Department of Tuberculosis, Hebei Chest Hospital, Hebei, China
| | - Kai-Hang Yiu
- Cardiology Division, Department of Medicine, The University of Hong Kong Shen Zhen Hospital, Shenzhen, Guangdong, China; Cardiology Division, Department of Medicine, The University of Hong Kong, Queen Mary Hospital, Hong Kong Island, Hong Kong, China
| | - Xianbo Wu
- Department of Epidemiology, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, China.
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18
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Cosío BG, Casanova C, Soler-Cataluña JJ, Soriano JB, García-Río F, de Lucas P, Alfageme I, Rodríguez González-Moro JM, Sánchez G, Ancochea J, Miravitlles M. Unravelling young COPD and pre-COPD in the general population. ERJ Open Res 2023; 9:00334-2022. [PMID: 36814553 PMCID: PMC9940715 DOI: 10.1183/23120541.00334-2022] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 08/24/2022] [Indexed: 11/05/2022] Open
Abstract
Background Chronic obstructive pulmonary disease (COPD) is commonly diagnosed when the airflow limitation is well established and symptomatic. We aimed to identify individuals at risk of developing COPD according to the concept of pre-COPD and compare their clinical characteristics with 1) those who have developed the disease at a young age, and 2) the overall population with and without COPD. Methods The EPISCAN II study is a cross-sectional, population-based study that aims to investigate the prevalence of COPD in Spain in subjects ≥40 years of age. Pre-COPD was defined as the presence of emphysema >5% and/or bronchial thickening by computed chromatography (CT) scan and/or diffusing capacity of the lung for carbon monoxide (D LCO) <80% of predicted in subjects with respiratory symptoms and post-bronchodilator forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) >0.70. Young COPD was defined as FEV1/FVC <0.70 in a subject ≤50 years of age. Demographic and clinical characteristics were compared among pre-COPD, young COPD and the overall population with and without COPD. Results Among the 1077 individuals with FEV1/FVC <0.70, 65 (6.0%) were ≤50 years of age. Among the 8015 individuals with FEV1/FVC >0.70, 350 underwent both D LCO testing and chest CT scanning. Of those, 78 (22.3%) subjects fulfilled the definition of pre-COPD. Subjects with pre-COPD were older, predominantly women, less frequently active or ex-smokers, with less frequent previous diagnosis of asthma but with higher symptomatic burden than those with young COPD. Conclusions 22.3% of the studied population was at risk of developing COPD, with similar symptomatic and structural changes to those with well-established disease without airflow obstruction. This COPD at-risk population is different from those that develop COPD at a young age.
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Affiliation(s)
- Borja G. Cosío
- Department of Medicine, University of Balearic Islands, Palma, Spain,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain,These authors contributed equally,Corresponding author: Borja G. Cosío ()
| | - Ciro Casanova
- Servicio de Neumología, Hospital Universitario Nuestra Señora de Candelaria, Tenerife, Spain,These authors contributed equally
| | - Juan José Soler-Cataluña
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain,Servicio de Neumología, Hospital Arnau de Vilanova-Lliria, Valencia, Spain
| | - Joan B. Soriano
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain,Servicio de Neumología, Hospital Universitario La Princesa and Universidad Autónoma de Madrid, Madrid, Spain
| | - Francisco García-Río
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain,Servicio de Neumología, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Pilar de Lucas
- Servicio de Neumología, Hospital General Gregorio Marañon, Madrid, Spain
| | - Inmaculada Alfageme
- Unidad de Gestión Clínica de Neumología, Hospital Universitario Virgen de Valme, Universidad de Sevilla, Seville, Spain
| | | | | | - Julio Ancochea
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain,Servicio de Neumología, Hospital Universitario La Princesa and Universidad Autónoma de Madrid, Madrid, Spain
| | - Marc Miravitlles
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain,Pneumology Department, Hospital Universitari Vall dHebron/Vall d'Hebron Institut de Recerca, Barcelona, Spain
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19
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Bhatt SP, Bodduluri S, Dransfield MT, Reinhardt JM, Crapo JD, Silverman EK, Humphries S, Lynch DA, Strand MJ. Acute Exacerbations Are Associated with Progression of Emphysema. Ann Am Thorac Soc 2022; 19:2108-2111. [PMID: 35914221 PMCID: PMC9743469 DOI: 10.1513/annalsats.202112-1385rl] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
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20
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Miravitlles M, Anzueto A. Use of Computed Tomography Lung Densitometry as an Outcome Measure for Emphysema Progression: The Case of Losartan. Am J Respir Crit Care Med 2022; 206:804-806. [PMID: 35653703 PMCID: PMC9799282 DOI: 10.1164/rccm.202205-0927ed] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Marc Miravitlles
- Pneumology Department, Hospital Universitari Vall d’Hebron andVall d’Hebron Institut de Recerca (VHIR)Barcelona, Spain
| | - Antonio Anzueto
- Pulmonary Disease/Critical CareUniversity of Texas Health and South Texas Veterans Health Care SystemSan Antonio, Texas
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21
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Weikert T, Friebe L, Wilder-Smith A, Yang S, Sperl JI, Neumann D, Balachandran A, Bremerich J, Sauter AW. Automated quantification of airway wall thickness on chest CT using retina U-Nets - Performance evaluation and application to a large cohort of chest CTs of COPD patients. Eur J Radiol 2022; 155:110460. [PMID: 35963191 DOI: 10.1016/j.ejrad.2022.110460] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 07/17/2022] [Accepted: 07/31/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE Airway wall thickening is a consequence of chronic inflammatory processes and usually only qualitatively described in CT radiology reports. The purpose of this study is to automatically quantify airway wall thickness in multiple airway generations and assess the diagnostic potential of this parameter in a large cohort of patients with Chronic Obstructive Pulmonary Disease (COPD). MATERIALS AND METHODS This retrospective, single-center study included a series of unenhanced chest CTs. Inclusion criteria were the mentioning of an explicit COPD GOLD stage in the written radiology report and time period (01/2019-12/2021). A control group included chest CTs with completely unremarkable lungs according to the report. The DICOM images of all cases (axial orientation; slice-thickness: 1 mm; soft-tissue kernel) were processed by an AI algorithm pipeline consisting of (A) a 3D-U-Net for det detection and tracing of the bronchial tree centerlines (B) extraction of image patches perpendicular to the centerlines of the bronchi, and (C) a 2D U-Net for segmentation of airway walls on those patches. The performance of centerline detection and wall segmentation was assessed. The imaging parameter average wall thickness was calculated for bronchus generations 3-8 (AWT3-8) across the lungs. Mean AWT3-8 was compared between five groups (control, COPD Gold I-IV) using non-parametric statistics. Furthermore, the established emphysema score %LAV-950 was calculated and used to classify scans (normal vs. COPD) alone and in combination with AWT3-8. RESULTS: A total of 575 chest CTs were processed. Algorithm performance was very good (airway centerline detection sensitivity: 86.9%; airway wall segmentation Dice score: 0.86). AWT3-8 was statistically significantly greater in COPD patients compared to controls (2.03 vs. 1.87 mm, p < 0.001) and increased with COPD stage. The classifier that combined %LAV-950 and AWT3-8 was superior to the classifier using only %LAV-950 (AUC = 0.92 vs. 0.79). CONCLUSION Airway wall thickness increases in patients suffering from COPD and is automatically quantifiable. AWT3-8 could become a CT imaging parameter in COPD complementing the established emphysema biomarker %LAV-950. CLINICAL RELEVANCE STATEMENT Quantitative measurements considering the complete visible bronchial tree instead of qualitative description could enhance radiology reports, allow for precise monitoring of disease progression and diagnosis of early stages of disease.
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Affiliation(s)
- Thomas Weikert
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland.
| | - Liene Friebe
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
| | - Adrian Wilder-Smith
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
| | - Shan Yang
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
| | | | - Dominik Neumann
- Siemens Healthineers, Henkestrasse 127, 91052 Erlangen, Germany
| | | | - Jens Bremerich
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
| | - Alexander W Sauter
- Department of Radiology, University Hospital Basel, University of Basel, Petersgraben 4, 4031 Basel, Switzerland
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22
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Choi H, Kim H, Jin KN, Jeong YJ, Chae KJ, Lee KH, Yong HS, Gil B, Lee HJ, Lee KY, Jeon KN, Yi J, Seo S, Ahn C, Lee J, Oh K, Goo JM. A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography. J Thorac Imaging 2022; 37:253-261. [PMID: 35749623 DOI: 10.1097/rti.0000000000000647] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE We aimed to identify clinically relevant deep learning algorithms for emphysema quantification using low-dose chest computed tomography (LDCT) through an invitation-based competition. MATERIALS AND METHODS The Korean Society of Imaging Informatics in Medicine (KSIIM) organized a challenge for emphysema quantification between November 24, 2020 and January 26, 2021. Seven invited research teams participated in this challenge. In total, 558 pairs of computed tomography (CT) scans (468 pairs for the training set, and 90 pairs for the test set) from 9 hospitals were collected retrospectively or prospectively. CT acquisition followed the hospitals' protocols to reflect the real-world clinical setting. Using the training set, each team developed an algorithm that generated converted LDCT by changing the pixel values of LDCT to simulate those of standard-dose CT (SDCT). The agreement between SDCT and LDCT was evaluated using the intraclass correlation coefficient (ICC; 2-way random effects, absolute agreement, and single rater) for the percentage of low-attenuated area below -950 HU (LAA-950 HU), κ value for emphysema categorization (LAA-950 HU, <5%, 5% to 10%, and ≥10%) and cosine similarity of LAA-950 HU. RESULTS The mean LAA-950 HU of the test set was 14.2%±10.5% for SDCT, 25.4%±10.2% for unconverted LDCT, and 12.9%±10.4%, 11.7%±10.8%, and 12.4%±10.5% for converted LDCT (top 3 teams). The agreement between the SDCT and converted LDCT of the first-place team was 0.94 (95% confidence interval: 0.90, 0.97) for ICC, 0.71 (95% confidence interval: 0.58, 0.84) for categorical agreement, and 0.97 (interquartile range: 0.94 to 0.99) for cosine similarity. CONCLUSIONS Emphysema quantification with LDCT was feasible through deep learning-based CT conversion strategies.
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Affiliation(s)
- Hyewon Choi
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine
| | - Hyungjin Kim
- Department of Radiology, Seoul National University College of Medicine
| | - Kwang Nam Jin
- Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul
| | - Yeon Joo Jeong
- Department of Radiology and Biomedical Research Institute, Pusan National University Hospital, Busan
| | - Kum Ju Chae
- Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju
| | - Kyung Hee Lee
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do
| | - Hwan Seok Yong
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine
| | - Bomi Gil
- Department of Radiology, College of Medicine, The Catholic University of Korea
| | - Hye-Jeong Lee
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine
| | - Ki Yeol Lee
- Department of Radiology, Korea University College of Medicine
| | - Kyung Nyeo Jeon
- Department of Radiology, Gyeongsang National University, Jinju, Korea
| | | | | | | | | | - Kyuhyup Oh
- Bio Medical Research Center, Korea Testing Laboratory
| | - Jin Mo Goo
- Department of Radiology, Seoul National University College of Medicine
- Cancer Research Institute, Seoul National University, Seoul
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Lv R, Xie M, Jin H, Shu P, Ouyang M, Wang Y, Yao D, Yang L, Huang X, Wang Y. A Preliminary Study on the Relationship Between High-Resolution Computed Tomography and Pulmonary Function in People at Risk of Developing Chronic Obstructive Pulmonary Disease. Front Med (Lausanne) 2022; 9:855640. [PMID: 35602478 PMCID: PMC9115858 DOI: 10.3389/fmed.2022.855640] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 03/30/2022] [Indexed: 11/18/2022] Open
Abstract
Objectives Patients with chronic obstructive pulmonary disease (COPD) have high morbidity and mortality, the opportunity to carry out a thoracic high-resolution CT (HRCT) scan may increase the possibility to identify the group at risk of disease. The aim of our study was to explore the differences in HRCT emphysema parameters, air trapping parameters, and lung density parameters between high and low-risk patients of COPD and evaluate their correlation with pulmonary function parameters. Methods In this retrospective, single-center cohort study, we enrolled outpatients from the Physical Examination Center and Respiratory Medicine of The First Affiliated Hospital of Wenzhou Medical University. The patients who were ≥ 40 years-old, had chronic cough or sputum production, and/or had exposure to risk factors for the disease and had not reached the diagnostic criteria is considered people at risk of COPD. They were divided into low-risk group and high-risk group according to FEV1/FVC ≥ 80% and 80%>FEV1/FVC ≥ 70%. Data on clinical characteristics, clinical symptom score, pulmonary function, and HRCT were recorded. Results 72 COPD high-risk patients and 86 COPD low-risk patients were enrolled in the study, and the air trapping index of left, right, and bilateral lungs of the high-risk group were higher than those of the low-risk group. However, the result of mean expiratory lung density was opposite. The emphysema index of left, right, and bilateral lungs were negatively correlated with FEV1/FVC (correlation coefficients were -0.33, -0.22, -0.26). Consistently, the air trapping index of left and right lungs and bilateral lungs were negatively correlated with FEV1/FVC (correlation coefficients were -0.33, -0.23, -0.28). Additionally, the mean expiratory lung density of left and right lungs and bilateral lungs were positively correlated with FEV1/FVC (correlation coefficients were 0.31, 0.25, 0.29). Conclusion The emphysema index, air trapping index and the mean expiratory lung density shows significantly positive correlation with FEV1/FVC which can be used to assess the pulmonary function status of people at risk of COPD and provide a useful supplement for the early and comprehensive assessment of the disease.
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Affiliation(s)
- Rui Lv
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China.,Department of Intensive Care Unit, Ningbo First Hospital, Ningbo, China
| | - Mengyao Xie
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Huaqian Jin
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Pingping Shu
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Mingli Ouyang
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Yanmao Wang
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Dan Yao
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Lehe Yang
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Xiaoying Huang
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
| | - Yiran Wang
- Key Laboratory of Respiratory Circulation, Division of Pulmonary Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China
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Wang JM, Ram S, Labaki WW, Han MK, Galbán CJ. CT-Based Commercial Software Applications: Improving Patient Care Through Accurate COPD Subtyping. Int J Chron Obstruct Pulmon Dis 2022; 17:919-930. [PMID: 35502294 PMCID: PMC9056100 DOI: 10.2147/copd.s334592] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 04/03/2022] [Indexed: 12/14/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is heterogenous in its clinical manifestations and disease progression. Patients often have disease courses that are difficult to predict with readily available data, such as lung function testing. The ability to better classify COPD into well-defined groups will allow researchers and clinicians to tailor novel therapies, monitor their effects, and improve patient-centered outcomes. Different modalities of assessing these COPD phenotypes are actively being studied, and an area of great promise includes the use of quantitative computed tomography (QCT) techniques focused on key features such as airway anatomy, lung density, and vascular morphology. Over the last few decades, companies around the world have commercialized automated CT software packages that have proven immensely useful in these endeavors. This article reviews the key features of several commercial platforms, including the technologies they are based on, the metrics they can generate, and their clinical correlations and applications. While such tools are increasingly being used in research and clinical settings, they have yet to be consistently adopted for diagnostic work-up and treatment planning, and their full potential remains to be explored.
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Affiliation(s)
- Jennifer M Wang
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Sundaresh Ram
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Wassim W Labaki
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
| | - MeiLan K Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Craig J Galbán
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA,Correspondence: Craig J Galbán, Department of Radiology, University of Michigan, BSRB, Room A506, 109 Zina Pitcher Place, Ann Arbor, MI, 48109-2200, USA, Tel +1 734-764-8726, Fax +1 734-615-1599, Email
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Zhu D, Qiao C, Dai H, Hu Y, Xi Q. Diagnostic efficacy of visual subtypes and low attenuation area based on HRCT in the diagnosis of COPD. BMC Pulm Med 2022; 22:81. [PMID: 35249542 PMCID: PMC8898461 DOI: 10.1186/s12890-022-01875-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 03/01/2022] [Indexed: 11/26/2022] Open
Abstract
Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease. Current gold standard criteria, pulmonary function tests (PFTs) may result in underdiagnosis of potential COPD patients. Therefore, we hypothesize that the combination of high-resolution computed tomography (HRCT) and clinical basic characteristics will enable the identification of more COPD patients. Methods A total of 284 patients with respiratory symptoms who were current or former smokers were included in the study, and were further divided into 5 groups of GOLD grade I–IV and non-COPD according to PFTs. All patients underwent inspiratory HRCT scanning and low attenuation area (LAA) was measured. Then they were divided into seven visual subtypes according to the Fleischner Society classification system. Non-parametric tests were used for exploring differences in basic characteristics and PFTs between different groups of enrolled patients and visual subtypes. Binary logistic regression was to find the influencing factors that affected the patients’ outcome (non-COPD vs GOLD I-IV). The area under the receiver operating characteristic curve (AUC-ROC) was to explore the diagnostic efficacy of LAA, visual subtypes, and combined basic characteristics related to COPD for COPD diagnosis. Finally, based on the cut-off values of ROC analysis, exploring HRCT features in patients who do not meet the diagnostic criteria but clinically suspected COPD. Results With the worsening severity of COPD, the visual subtypes gradually progressed (p < 0.01). There was a significant difference in LAA between GOLD II–IV and non-COPD (p < 0.0001). The diagnostic efficacy of LAA, visual subtypes, and LAA combined with visual subtypes for COPD were 0.742, 0.682 and 0.730 respectively. The diagnostic efficacy increased to 0.923–0.943 when basic characteristics were added (all p < 0.001). Based on the cut-off value of ROC analysis, LAA greater than 5.6, worsening of visual subtypes, combined with positive basic characteristics can help identify some potential COPD patients. Conclusion The heterogeneous phenotype of COPD requires a combination of multiple evaluation methods. The diagnostic efficacy of combining LAA, visual subtypes, and basic characteristics achieves good consistency with current diagnostic criteria.
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Yadav RS, Kant S, Tripathi PM, Pathak AK, Mahdi AA. Transcription factor NF-κB, interleukin-1β, and interleukin-8 expression and its association with tobacco smoking and severity in chronic obstructive pulmonary disease. GENE REPORTS 2022. [DOI: 10.1016/j.genrep.2021.101453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Retson TA, Hasenstab KA, Kligerman SJ, Jacobs KE, Yen AC, Brouha SS, Hahn LD, Hsiao A. Reader Perceptions and Impact of AI on CT Assessment of Air Trapping. Radiol Artif Intell 2022; 4:e210160. [PMID: 35391767 DOI: 10.1148/ryai.2021210160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 09/22/2021] [Accepted: 10/22/2021] [Indexed: 11/11/2022]
Abstract
Quantitative imaging measurements can be facilitated by artificial intelligence (AI) algorithms, but how they might impact decision-making and be perceived by radiologists remains uncertain. After creation of a dedicated inspiratory-expiratory CT examination and concurrent deployment of a quantitative AI algorithm for assessing air trapping, five cardiothoracic radiologists retrospectively evaluated severity of air trapping on 17 examination studies. Air trapping severity of each lobe was evaluated in three stages: qualitatively (visually); semiquantitatively, allowing manual region-of-interest measurements; and quantitatively, using results from an AI algorithm. Readers were surveyed on each case for their perceptions of the AI algorithm. The algorithm improved interreader agreement (intraclass correlation coefficients: visual, 0.28; semiquantitative, 0.40; quantitative, 0.84; P < .001) and improved correlation with pulmonary function testing (forced expiratory volume in 1 second-to-forced vital capacity ratio) (visual r = -0.26, semiquantitative r = -0.32, quantitative r = -0.44). Readers perceived moderate agreement with the AI algorithm (Likert scale average, 3.7 of 5), a mild impact on their final assessment (average, 2.6), and a neutral perception of overall utility (average, 3.5). Though the AI algorithm objectively improved interreader consistency and correlation with pulmonary function testing, individual readers did not immediately perceive this benefit, revealing a potential barrier to clinical adoption. Keywords: Technology Assessment, Quantification © RSNA, 2021.
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Affiliation(s)
- Tara A Retson
- Department of Radiology, University of California, San Diego, 9452 Medical Center Dr, 4th Floor, La Jolla, CA 92037 (T.A.R., S.J.K., K.E.J., A.C.Y., S.S.B., L.D.H., A.H.); and Department of Mathematics and Statistics, San Diego State University, San Diego, Calif (K.A.H.)
| | - Kyle A Hasenstab
- Department of Radiology, University of California, San Diego, 9452 Medical Center Dr, 4th Floor, La Jolla, CA 92037 (T.A.R., S.J.K., K.E.J., A.C.Y., S.S.B., L.D.H., A.H.); and Department of Mathematics and Statistics, San Diego State University, San Diego, Calif (K.A.H.)
| | - Seth J Kligerman
- Department of Radiology, University of California, San Diego, 9452 Medical Center Dr, 4th Floor, La Jolla, CA 92037 (T.A.R., S.J.K., K.E.J., A.C.Y., S.S.B., L.D.H., A.H.); and Department of Mathematics and Statistics, San Diego State University, San Diego, Calif (K.A.H.)
| | - Kathleen E Jacobs
- Department of Radiology, University of California, San Diego, 9452 Medical Center Dr, 4th Floor, La Jolla, CA 92037 (T.A.R., S.J.K., K.E.J., A.C.Y., S.S.B., L.D.H., A.H.); and Department of Mathematics and Statistics, San Diego State University, San Diego, Calif (K.A.H.)
| | - Andrew C Yen
- Department of Radiology, University of California, San Diego, 9452 Medical Center Dr, 4th Floor, La Jolla, CA 92037 (T.A.R., S.J.K., K.E.J., A.C.Y., S.S.B., L.D.H., A.H.); and Department of Mathematics and Statistics, San Diego State University, San Diego, Calif (K.A.H.)
| | - Sharon S Brouha
- Department of Radiology, University of California, San Diego, 9452 Medical Center Dr, 4th Floor, La Jolla, CA 92037 (T.A.R., S.J.K., K.E.J., A.C.Y., S.S.B., L.D.H., A.H.); and Department of Mathematics and Statistics, San Diego State University, San Diego, Calif (K.A.H.)
| | - Lewis D Hahn
- Department of Radiology, University of California, San Diego, 9452 Medical Center Dr, 4th Floor, La Jolla, CA 92037 (T.A.R., S.J.K., K.E.J., A.C.Y., S.S.B., L.D.H., A.H.); and Department of Mathematics and Statistics, San Diego State University, San Diego, Calif (K.A.H.)
| | - Albert Hsiao
- Department of Radiology, University of California, San Diego, 9452 Medical Center Dr, 4th Floor, La Jolla, CA 92037 (T.A.R., S.J.K., K.E.J., A.C.Y., S.S.B., L.D.H., A.H.); and Department of Mathematics and Statistics, San Diego State University, San Diego, Calif (K.A.H.)
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Park SW, Lim MN, Kim WJ, Bak SH. Quantitative assessment the longitudinal changes of pulmonary vascular counts in chronic obstructive pulmonary disease. Respir Res 2022; 23:29. [PMID: 35164757 PMCID: PMC8842934 DOI: 10.1186/s12931-022-01953-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 02/07/2022] [Indexed: 11/10/2022] Open
Abstract
Background Chest computed tomography (CT) is a widely used method to assess morphological and dynamic abnormalities in chronic obstructive pulmonary disease (COPD). The small pulmonary vascular cross-section (CSA), quantitatively extracted from volumetric CT, is a reliable indicator for predicting pulmonary vascular changes. CSA is associated with the severity of symptoms, pulmonary function tests (PFT) and emphysema and in COPD patients the severity increases over time. We analyzed the correlation longitudinal changes in pulmonary vascular parameters with clinical parameters in COPD patients. Materials and methods A total of 288 subjects with COPD were investigated during follow up period up to 6 years. CT images were classified into five subtypes from normal to severe emphysema according to percentage of low-attenuation areas less than -950 and -856 Hounsfield units (HU) on inspiratory and expiratory CT (LAA-950, LAA-856exp). Total number of vessels (Ntotal) and total number of vessels with area less than 5 mm2 (N<5 mm) per 1 cm2 of lung surface area (LSA) were measured at 6 mm from the pleural surface. Results Ntotal/LSA and N<5 mm/LSA changed from 1.16 ± 0.27 to 0.87 ± 0.2 and from 1.02 ± 0.22 to 0.78 ± 0.22, respectively, during Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage progression. Both parameters changed from normal to severe emphysema according to CT subtype from 1.39 ± 0.21 to 0.74 ± 0.17 and from 1.18 ± 0.19 to 0.67 ± 0.15, respectively. LAA-950 and LAA-856exp were negatively correlated with Ntotal/LSA (r = − 0.738, − 0.529) and N<5 mm /LSA (r = − 0.729, -− .497). On the other hand, pulmonary function test (PFT) results showed a weak correlation with Ntotal/LSA and N<5 mm/LSA (r = 0.205, 0.210). The depth in CT subtypes for longitudinal change both Ntotal/LSA and N<5 mm/LSA was (− 0.032, − 0.023) and (− 0.027) in normal and SAD, respectively. Conclusions Quantitative computed tomography features faithfully reflected pulmonary vessel alterations, showing in particular that pulmonary vascular alteration started. Supplementary Information The online version contains supplementary material available at 10.1186/s12931-022-01953-7.
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Higbee DH, Granell R, Davey Smith G, Dodd JW. Prevalence, risk factors, and clinical implications of preserved ratio impaired spirometry: a UK Biobank cohort analysis. THE LANCET. RESPIRATORY MEDICINE 2022; 10:149-157. [PMID: 34739861 DOI: 10.1016/s2213-2600(21)00369-6] [Citation(s) in RCA: 67] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/29/2021] [Accepted: 08/03/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND Preserved ratio impaired spirometry (PRISm) is defined as a FEV1 of less than 80% predicted and a FEV1/forced vital capacity (FVC) ratio of 0·70 or higher. Previous research has indicated that PRISm is associated with respiratory symptoms and is a precursor of chronic obstructive pulmonary disease (COPD). However, these findings are based on relatively small selective cohorts with short follow-up. We aimed to determine the prevalence, risk factors, clinical implications, and mortality of PRISm in a large adult general population. METHODS For this cohort analysis, we used data from the UKBiobank to assess PRISm prevalence, risk factors and associated symptoms, and associated comorbidities in a large adult population. Participants with spirometry deemed acceptable by an investigator (best measure FEV1 and FVC values) at baseline were included. Participants were excluded if they did not have acceptable spirometry or were missing data on body-mass index or smoking status. Control spirometry was defined as a FEV1 of 80% or more predicted and a FEV1/FVC ratio of 0·70 or higher. Airflow obstruction was defined as a FEV1/FVC ratio of less than 0·70. We used multivariable regression to determine risk factors for PRISm and associated comorbidities. Individuals who lived within close proximity to an assessment centre were invited for follow-up, with repeat spirometry. Only participants who had been included at baseline were examined in follow-up. This allowed for a longitudinal analysis of PRISm over time and risk factors for transition to airflow obstruction. We also did the survival analysis for a 12-year period. FINDINGS Participants were recruited by UK Biobank between Dec 19, 2006, and Oct 10, 2010. We included 351 874 UK Biobank participants (189 247 women and 162 627 men) in our study, with a median follow-up of 9·0 years (IQR 8·0-10·0). 38 639 (11·0%) of 351 874 participants had PRISm at baseline. After adjustment, PRISm was strongly associated with obesity (odds ratio [OR] 2·40 [2·26-2·55], p<0·0001), current smoking (1·48 [1·36-1·62], p<0·0001), and patient reported doctor-diagnosed asthma (1·76 [1·66-1·88], p<0·0001). Other risk factors identified included female sex, being overweight, trunk fat mass, and trunk fat percentage. PRISm was strongly associated with symptoms and comorbidity including increased risk of breathlessness (adjusted OR 2·0 [95% CI 1·91-2·14], p<0·0001) and cardiovascular disease (adjusted OR 1·71 [1·64-1·83], p<0·0001 for heart attack). Longitudinal analysis showed that 241 (12·2%) of 1973 participants who had PRISm at baseline had transitioned to airflow obstruction consistent with COPD. PRISm was associated with increased all-cause mortality (adjusted hazard ratio 1·61 [95% CI 1·53-1·69], p<0·0001) versus control participants. INTERPRETATION PRISm was associated with breathlessness, multimorbidity, and increased risk of death, which does not seem to be explained by smoking, obesity, or existing lung disease. Although for many patients PRISm is transient, it is important to understand which individuals are at risk of progressive lung function abnormalities. Further research into the genetic, structural and functional pathophysiology of PRISm is warranted. FUNDING UK Medical Research Council and University of Bristol.
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Affiliation(s)
- Daniel H Higbee
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Academic Respiratory Unit, University of Bristol, Southmead Hospital, Bristol, UK
| | - Raquel Granell
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - James W Dodd
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Academic Respiratory Unit, University of Bristol, Southmead Hospital, Bristol, UK.
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Lu J, Ge H, Qi L, Zhang S, Yang Y, Huang X, Li M. Subtyping preserved ratio impaired spirometry (PRISm) by using quantitative HRCT imaging characteristics. Respir Res 2022; 23:309. [PMID: 36369019 PMCID: PMC9652811 DOI: 10.1186/s12931-022-02113-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 07/15/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Preserved Ratio Impaired Spirometry (PRISm) is defined as FEV1/FVC ≥ 70% and FEV1 < 80%pred by pulmonary function test (PFT). It has highly prevalence and is associated with increased respiratory symptoms, systemic inflammation, and mortality. However, there are few radiological studies related to PRISm. The purpose of this study was to investigate the quantitative high-resolution computed tomography (HRCT) characteristics of PRISm and to evaluate the correlation between quantitative HRCT parameters and pulmonary function parameters, with the goal of establishing a nomogram model for predicting PRISm based on quantitative HRCT. METHODS A prospective and continuous study was performed in 488 respiratory outpatients from February 2020 to February 2021. All patients underwent both deep inspiratory and expiratory CT examinations, and received pulmonary function test (PFT) within 1 month. According to the exclusion criteria and Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification standard, 94 cases of normal pulmonary function, 51 cases of PRISm and 48 cases of mild to moderate chronic obstructive lung disease (COPD) were included in the study. The lung parenchyma, parametric response mapping (PRM), airway and vessel parameters were measured by automatic segmentation software (Aview). One-way analysis of variance (ANOVA) was used to compare the differences in clinical features, pulmonary function parameters and quantitative CT parameters. Spearman rank correlation analysis was used to evaluate the correlation between CT quantitative index and pulmonary function parameters. The predictors were obtained by binary logistics regression analysis respectively in normal and PRISm as well as PRISm and mild to moderate COPD, and the nomogram model was established. RESULTS There were significant differences in pulmonary function parameters among the three groups (P < 0.001). The differences in pulmonary parenchyma parameters such as emphysema index (EI), pixel indices-1 (PI-1) and PI-15 were mainly between mild to moderate COPD and the other two groups. The differences of airway parameters and pulmonary vascular parameters were mainly between normal and the other two groups, but were not found between PRISm and mild to moderate COPD. Especially there were significant differences in mean lung density (MLD) and the percent of normal in PRM (PRMNormal) among the three groups. Most of the pulmonary quantitative CT parameters had mild to moderate correlation with pulmonary function parameters. The predictors of the nomogram model using binary logistics regression analysis to distinguish normal from PRISm were smoking, MLD, the percent of functional small airways disease (fSAD) in PRM (PRMfSAD) and Lumen area. It had a good goodness of fit (χ2 = 0.31, P < 0.001) with the area under curve (AUC) value of 0.786. The predictor of distinguishing PRISm from mild to moderate COPD were PRMEmph (P < 0.001, AUC = 0.852). CONCLUSIONS PRISm was significantly different from subjects with normal pulmonary function in small airway and vessel lesions, which was more inclined to mild to moderate COPD, but there was no increase in pulmonary parenchymal attenuation. The nomogram based on quantitative HRCT parameters has good predictive value and provide more objective evidence for the early screening of PRISm.
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Affiliation(s)
- Jinjuan Lu
- grid.413597.d0000 0004 1757 8802Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221 West Yanan Road, Jingan District, Shanghai, 200040 China
| | - Haiyan Ge
- grid.413597.d0000 0004 1757 8802Department of Respiratory Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Lin Qi
- grid.413597.d0000 0004 1757 8802Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221 West Yanan Road, Jingan District, Shanghai, 200040 China
| | - Shaojie Zhang
- grid.413597.d0000 0004 1757 8802Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221 West Yanan Road, Jingan District, Shanghai, 200040 China
| | - Yuling Yang
- grid.413597.d0000 0004 1757 8802Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221 West Yanan Road, Jingan District, Shanghai, 200040 China
| | - Xuemei Huang
- grid.413597.d0000 0004 1757 8802Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221 West Yanan Road, Jingan District, Shanghai, 200040 China
| | - Ming Li
- grid.413597.d0000 0004 1757 8802Department of Radiology, Huadong Hospital Affiliated to Fudan University, 221 West Yanan Road, Jingan District, Shanghai, 200040 China
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Hasenstab KA, Tabalon J, Yuan N, Retson T, Hsiao A. CNN-based Deformable Registration Facilitates Fast and Accurate Air Trapping Measurements at Inspiratory and Expiratory CT. Radiol Artif Intell 2022; 4:e210211. [PMID: 35146437 PMCID: PMC8823452 DOI: 10.1148/ryai.2021210211] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 10/05/2021] [Accepted: 10/22/2021] [Indexed: 06/14/2023]
Abstract
PURPOSE To develop a convolutional neural network (CNN)-based deformable lung registration algorithm to reduce computation time and assess its potential for lobar air trapping quantification. MATERIALS AND METHODS In this retrospective study, a CNN algorithm was developed to perform deformable registration of lung CT (LungReg) using data on 9118 patients from the COPDGene Study (data collected between 2007 and 2012). Loss function constraints included cross-correlation, displacement field regularization, lobar segmentation overlap, and the Jacobian determinant. LungReg was compared with a standard diffeomorphic registration (SyN) for lobar Dice overlap, percentage voxels with nonpositive Jacobian determinants, and inference runtime using paired t tests. Landmark colocalization error (LCE) across 10 patients was compared using a random effects model. Agreement between LungReg and SyN air trapping measurements was assessed using intraclass correlation coefficient. The ability of LungReg versus SyN emphysema and air trapping measurements to predict Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages was compared using area under the receiver operating characteristic curves. RESULTS Average performance of LungReg versus SyN showed lobar Dice overlap score of 0.91-0.97 versus 0.89-0.95, respectively (P < .001); percentage voxels with nonpositive Jacobian determinant of 0.04 versus 0.10, respectively (P < .001); inference run time of 0.99 second (graphics processing unit) and 2.27 seconds (central processing unit) versus 418.46 seconds (central processing unit) (P < .001); and LCE of 7.21 mm versus 6.93 mm (P < .001). LungReg and SyN whole-lung and lobar air trapping measurements achieved excellent agreement (intraclass correlation coefficients > 0.98). LungReg versus SyN area under the receiver operating characteristic curves for predicting GOLD stage were not statistically different (range, 0.88-0.95 vs 0.88-0.95, respectively; P = .31-.95). CONCLUSION CNN-based deformable lung registration is accurate and fully automated, with runtime feasible for clinical lobar air trapping quantification, and has potential to improve diagnosis of small airway diseases.Keywords: Air Trapping, Convolutional Neural Network, Deformable Registration, Small Airway Disease, CT, Lung, Semisupervised Learning, Unsupervised Learning Supplemental material is available for this article. © RSNA, 2021 An earlier incorrect version of this article appeared online. This article was corrected on December 22, 2021.
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Abstract
This commentary reviews the contribution of imaging by CT and MRI to functional assessment in chronic obstructive pulmonary disease (COPD). CT can help individualize the assessment of COPD by quantifying emphysema, air trapping and airway wall thickening, potentially leading to more specific treatments for these distinct components of COPD. Longitudinal changes in these metrics can help assess progression or improvement. On hyperpolarized gas MRI, the apparent diffusion coefficient of provides an index of airspace enlargement reflecting emphysema. Perfusion imaging and measurement of pulmonary vascular volume on non-contrast CT provide insight into the contribution of pulmonary vascular disease to pulmonary impairment. Functional imaging is particularly valuable in detecting early lung dysfunction in subjects with inhalational exposures.
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Affiliation(s)
- David A Lynch
- Department of Radiology, National Jewish Health, Denver, CO, United States
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Polverino F, Wu TD, Rojas-Quintero J, Wang X, Mayo J, Tomchaney M, Tram J, Packard S, Zhang D, Cleveland KH, Cordoba-Lanus E, Owen CA, Fawzy A, Kinney GL, Hersh CP, Hansel NN, Doubleday K, Sauler M, Tesfaigzi Y, Ledford JG, Casanova C, Zmijewski J, Konhilas J, Langlais PR, Schnellmann R, Rahman I, McCormack M, Celli B. Metformin: Experimental and Clinical Evidence for a Potential Role in Emphysema Treatment. Am J Respir Crit Care Med 2021; 204:651-666. [PMID: 34033525 PMCID: PMC8521702 DOI: 10.1164/rccm.202012-4510oc] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Rationale: Cigarette smoke (CS) inhalation triggers oxidative stress and inflammation, leading to accelerated lung aging, apoptosis, and emphysema, as well as systemic pathologies. Metformin is beneficial for protecting against aging-related diseases. Objectives: We sought to investigate whether metformin may ameliorate CS-induced pathologies of emphysematous chronic obstructive pulmonary disease (COPD). Methods: Mice were exposed chronically to CS and fed metformin-enriched chow for the second half of exposure. Lung, kidney, and muscle pathologies, lung proteostasis, endoplasmic reticulum (ER) stress, mitochondrial function, and mediators of metformin effects in vivo and/or in vitro were studied. We evaluated the association of metformin use with indices of emphysema progression over 5 years of follow-up among the COPDGene (Genetic Epidemiology of COPD) study participants. The association of metformin use with the percentage of emphysema and adjusted lung density was estimated by using a linear mixed model. Measurements and Main Results: Metformin protected against CS-induced pulmonary inflammation and airspace enlargement; small airway remodeling, glomerular shrinkage, oxidative stress, apoptosis, telomere damage, aging, dysmetabolism in vivo and in vitro; and ER stress. The AMPK (AMP-activated protein kinase) pathway was central to metformin's protective action. Within COPDGene, participants receiving metformin compared with those not receiving it had a slower progression of emphysema (-0.92%; 95% confidence interval [CI], -1.7% to -0.14%; P = 0.02) and a slower adjusted lung density decrease (2.2 g/L; 95% CI, 0.43 to 4.0 g/L; P = 0.01). Conclusions: Metformin protected against CS-induced lung, renal, and muscle injury; mitochondrial dysfunction; and unfolded protein responses and ER stress in mice. In humans, metformin use was associated with lesser emphysema progression over time. Our results provide a rationale for clinical trials testing the efficacy of metformin in limiting emphysema progression and its systemic consequences.
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Affiliation(s)
| | - Tianshi David Wu
- Section of Pulmonary, Critical Care, and Sleep Medicine, Baylor College of Medicine, Houston, Texas;,Center for Innovations in Quality, Effectiveness, and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas
| | | | - Xiaoyun Wang
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia and Charlie Norwood VA Medical Center, Augusta, Georgia
| | | | | | - Judy Tram
- Asthma and Airway Disease Research Center and
| | | | | | | | - Elizabeth Cordoba-Lanus
- Servicio de Neumología, Unidad de Investigación, Hospital Universitario La Candelaria, Santa Cruz de Tenerife, Tenerife, Spain
| | | | - Ashraf Fawzy
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Greg L. Kinney
- Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado
| | - Craig P. Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Nadia N. Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
| | | | - Maor Sauler
- Pulmonary Division, School of Medicine, Yale University, New Haven, Connecticut
| | | | | | - Ciro Casanova
- Servicio de Neumología, Unidad de Investigación, Hospital Universitario La Candelaria, Santa Cruz de Tenerife, Tenerife, Spain
| | - Jaroslaw Zmijewski
- Pulmonary and Critical Care Medicine, Department of Medicine, University of Alabama, Birmingham, Alabama; and
| | - John Konhilas
- Department of Physiology, University of Arizona, Tucson, Arizona
| | | | | | - Irfan Rahman
- Department of Environmental Medicine, University of Rochester Medical Center, Rochester, New York
| | - Meredith McCormack
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
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Grenier PA. Spatial Compactness of Emphysema at CT and Disease Severity. Radiology 2021; 301:710-711. [PMID: 34519582 DOI: 10.1148/radiol.2021211673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Philippe A Grenier
- From the Department of Clinical Research and Innovation, Hôpital Foch, 40 rue Worth, 92150 Suresnes, France
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Li T, Zhou HP, Zhou ZJ, Guo LQ, Zhou L. Computed tomography-identified phenotypes of small airway obstructions in chronic obstructive pulmonary disease. Chin Med J (Engl) 2021; 134:2025-2036. [PMID: 34517376 PMCID: PMC8440009 DOI: 10.1097/cm9.0000000000001724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Indexed: 12/02/2022] Open
Abstract
ABSTRACT Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characteristic of small airway inflammation, obstruction, and emphysema. It is well known that spirometry alone cannot differentiate each separate component. Computed tomography (CT) is widely used to determine the extent of emphysema and small airway involvement in COPD. Compared with the pulmonary function test, small airway CT phenotypes can accurately reflect disease severity in patients with COPD, which is conducive to improving the prognosis of this disease. CT measurement of central airway morphology has been applied in clinical, epidemiologic, and genetic investigations as an inference of the presence and severity of small airway disease. This review will focus on presenting the current knowledge and methodologies in chest CT that aid in identifying discrete COPD phenotypes.
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Affiliation(s)
- Tao Li
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Department of Respiratory Medicine, Xuzhou First People's Hospital, Xuzhou, Jiangsu 221116, China
| | - Hao-Peng Zhou
- Department of Medicine, Jiangsu University School of Medicine, Zhenjiang, Jiangsu 212013, China
| | - Zhi-Jun Zhou
- Institute of Radio Frequency & Optical Electronics-Integrated Circuits, School of Information and Engineering, Southeast University, Nanjing, Jiangsu 210096, China
| | - Li-Quan Guo
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China
| | - Linfu Zhou
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China
- Institute of Integrative Medicine, Nanjing Medical University, Nanjing, Jiangsu 210029, China
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Tejwani V, Fawzy A, Putcha N, Castaldi P, Cho MH, Pratte KA, Bhatt SP, Lynch DA, Humphries SM, Kinney GL, D'Alessio FR, Hansel NN. Emphysema Progression and Lung Function Decline Among Angiotensin Converting Enzyme Inhibitors and Angiotensin-Receptor Blockade Users in the COPDGene Cohort. Chest 2021; 160:1245-1254. [PMID: 34029566 DOI: 10.1016/j.chest.2021.05.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 04/30/2021] [Accepted: 05/04/2021] [Indexed: 10/21/2022] Open
Abstract
BACKGROUND Attenuation of transforming growth factor β by blocking angiotensin II has been shown to reduce emphysema in a murine model. General population studies have demonstrated that the use of angiotensin converting enzyme inhibitors (ACEis) and angiotensin-receptor blockers (ARBs) is associated with reduction of emphysema progression in former smokers and that the use of ACEis is associated with reduction of FEV1 progression in current smokers. RESEARCH QUESTION Is use of ACEi and ARB associated with less progression of emphysema and FEV1 decline among individuals with COPD or baseline emphysema? METHODS Former and current smokers from the Genetic Epidemiology of COPD Study who attended baseline and 5-year follow-up visits, did not change smoking status, and underwent chest CT imaging were included. Adjusted linear mixed models were used to evaluate progression of adjusted lung density (ALD), percent emphysema (%total lung volume <-950 Hounsfield units [HU]), 15th percentile of the attenuation histogram (attenuation [in HU] below which 15% of voxels are situated plus 1,000 HU), and lung function decline over 5 years between ACEi and ARB users and nonusers in those with spirometry-confirmed COPD, as well as all participants and those with baseline emphysema. Effect modification by smoking status also was investigated. RESULTS Over 5 years of follow-up, compared with nonusers, ACEi and ARB users with COPD showed slower ALD progression (adjusted mean difference [aMD], 1.6; 95% CI, 0.34-2.9). Slowed lung function decline was not observed based on phase 1 medication (aMD of FEV1 % predicted, 0.83; 95% CI, -0.62 to 2.3), but was when analysis was limited to consistent ACEi and ARB users (aMD of FEV1 % predicted, 1.9; 95% CI, 0.14-3.6). No effect modification by smoking status was found for radiographic outcomes, and the lung function effect was more pronounced in former smokers. Results were similar among participants with baseline emphysema. INTERPRETATION Among participants with spirometry-confirmed COPD or baseline emphysema, ACEi and ARB use was associated with slower progression of emphysema and lung function decline. TRIAL REGISTRY ClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov.
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Affiliation(s)
- Vickram Tejwani
- Division of Pulmonary and Critical Care, Johns Hopkins University, Baltimore, MD.
| | - Ashraf Fawzy
- Division of Pulmonary and Critical Care, Johns Hopkins University, Baltimore, MD
| | - Nirupama Putcha
- Division of Pulmonary and Critical Care, Johns Hopkins University, Baltimore, MD
| | | | - Michael H Cho
- Division of Pulmonary and Critical Care Medicine, Boston, MA; Harvard Medical School, Boston, MA
| | | | - Surya P Bhatt
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - David A Lynch
- Department of Radiology, National Jewish Health, Denver, CO
| | | | - Gregory L Kinney
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO
| | - Franco R D'Alessio
- Division of Pulmonary and Critical Care, Johns Hopkins University, Baltimore, MD
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care, Johns Hopkins University, Baltimore, MD
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Characteristics of chronic obstructive pulmonary disease patients with robust progression of emphysematous change. Sci Rep 2021; 11:9548. [PMID: 33953210 PMCID: PMC8099884 DOI: 10.1038/s41598-021-87724-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 03/22/2021] [Indexed: 11/18/2022] Open
Abstract
Emphysema is a major pathological change in chronic obstructive pulmonary disease (COPD). However, the annual changes in the progression of emphysematous have not been investigated. We aimed to determine possible baseline predicting factors of the change in emphysematous progression in a subgroup of COPD patients who demonstrated rapid progression. In this observational study, we analyzed patients with COPD who were followed up by computed tomography (CT) at least two times over a 3-year period (n = 217). We divided the annual change in the low attenuation area percentage (LAA%) into quartiles and defined a rapid progression group (n = 54) and a non-progression group (n = 163). Predictors of future changes in emphysematous progression differed from predictors of high LAA% at baseline. On multivariate logistic regression analysis, low blood eosinophilic count (odds ratio [OR], 3.22; P = 0.04) and having osteoporosis (OR, 2.13; P = 0.03) were related to rapid changes in emphysematous progression. There was no difference in baseline nutritional parameters, but nutritional parameters deteriorated in parallel with changes in emphysematous progression. Herein, we clarified the predictors of changes in emphysematous progression and concomitant deterioration of nutritional status in COPD patients.
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Pompe E, Moore CM, Mohamed Hoesein FA, de Jong PA, Charbonnier JP, Han MK, Humphries SM, Hatt CR, Galbán CJ, Silverman EK, Crapo JD, Washko GR, Regan EA, Make B, Strand M, Lammers JWJ, van Rikxoort EM, Lynch DA. Progression of Emphysema and Small Airways Disease in Cigarette Smokers. CHRONIC OBSTRUCTIVE PULMONARY DISEASES (MIAMI, FLA.) 2021; 8:198-212. [PMID: 33290645 PMCID: PMC8237975 DOI: 10.15326/jcopdf.2020.0140] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/19/2020] [Indexed: 11/21/2022]
Abstract
BACKGROUND Little is known about factors associated with emphysema progression in cigarette smokers. We evaluated factors associated with change in emphysema and forced expiratory volume in 1 second (FEV1) in participants with and without chronic obstructive pulmonary disease (COPD). METHODS This retrospective study included individuals participating in the COPD Genetic Epidemiology study who completed the 5-year follow-up, including inspiratory and expiratory computed tomography (CT) and spirometry. All paired CT scans were analyzed using micro-mapping, which classifies individual voxels as emphysema or functional small airway disease (fSAD). Presence and progression of emphysema and FEV1 were determined based on comparison to nonsmoker values. Logistic regression analyses were used to identify clinical parameters associated with disease progression. RESULTS A total of 3088 participants were included with a mean ± SD age of 60.7±8.9 years, including 72 nonsmokers. In all Global initiative for chronic Obstructive Lung Disease (GOLD) stages, the presence of emphysema at baseline was associated with emphysema progression (odds ratio [OR]: GOLD 0: 4.32; preserved ratio-impaired spirometry [PRISm]; 5.73; GOLD 1: 5.16; GOLD 2: 5.69; GOLD 3/4: 5.55; all p ≤0.01). If there was no emphysema at baseline, the amount of fSAD at baseline was associated with emphysema progression (OR for 1% increase: GOLD 0: 1.06; PRISm: 1.20; GOLD 1: 1.7; GOLD 3/4: 1.08; all p ≤ 0.03).In 1735 participants without spirometric COPD, progression in emphysema occurred in 105 (6.1%) participants and only 21 (1.2%) had progression in both emphysema and FEV1. CONCLUSIONS The presence of emphysema is an important predictor of emphysema progression. In patients without emphysema, fSAD is associated with the development of emphysema. In participants without spirometric COPD, emphysema progression occurred independently of FEV1 decline.
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Affiliation(s)
- Esther Pompe
- Imaging Department, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Camille M. Moore
- Division of Biostatistics, Environment and Health, National Jewish Health, Denver, Colorado, United States
| | | | - Pim A. de Jong
- Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jean-Paul Charbonnier
- Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, the Netherlands
| | - MeiLan K. Han
- Division of Pulmonary and Critical Care, University of Michigan Health System, Ann Arbor, Michigan, United States
| | - Steven M. Humphries
- Department of Radiology, National Jewish Health, Denver, Colorado, United States
| | | | - Craig J. Galbán
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, United States
- Center for Molecular Imaging, University of Michigan, Ann Arbor, Michigan, United States
| | - Ed K. Silverman
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States
| | - James D. Crapo
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, National Jewish Health, Denver, Colorado, United States
| | - George R. Washko
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States
| | - Elisabeth A. Regan
- Division of Rheumatology, Department of Medicine, National Jewish Health, Denver, Colorado, United States
| | - Barry Make
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, National Jewish Health, Denver, Colorado, United States
| | - Matthew Strand
- Division of Biostatistics, Environment and Health, National Jewish Health, Denver, Colorado, United States
| | | | - Eva M. van Rikxoort
- Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, the Netherlands
| | - David A. Lynch
- Department of Radiology, National Jewish Health, Denver, Colorado, United States
| | - on behalf of the COPDGene® investigators
- Imaging Department, University Medical Center Utrecht, Utrecht, the Netherlands
- Division of Biostatistics, Environment and Health, National Jewish Health, Denver, Colorado, United States
- Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands
- Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, the Netherlands
- Division of Pulmonary and Critical Care, University of Michigan Health System, Ann Arbor, Michigan, United States
- Department of Radiology, National Jewish Health, Denver, Colorado, United States
- Imbio LLC, Minneapolis, Minnesota, United States
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, United States
- Center for Molecular Imaging, University of Michigan, Ann Arbor, Michigan, United States
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, National Jewish Health, Denver, Colorado, United States
- Division of Rheumatology, Department of Medicine, National Jewish Health, Denver, Colorado, United States
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Hatt CR, Oh AS, Obuchowski NA, Charbonnier JP, Lynch DA, Humphries SM. Comparison of CT Lung Density Measurements between Standard Full-Dose and Reduced-Dose Protocols. Radiol Cardiothorac Imaging 2021; 3:e200503. [PMID: 33969308 DOI: 10.1148/ryct.2021200503] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 01/31/2021] [Accepted: 02/09/2021] [Indexed: 11/11/2022]
Abstract
Purpose To evaluate the reproducibility and predicted clinical outcomes of CT-based quantitative lung density measurements using standard fixed-dose (FD) and reduced-dose (RD) scans. Materials and Methods In this retrospective analysis of prospectively acquired data, 1205 participants (mean age, 65 years ± 9 [standard deviation]; 618 men) enrolled in the COPDGene study who underwent FD and RD CT image acquisition protocols between November 2014 and July 2017 were included. Of these, the RD scans of 640 participants were also reconstructed using iterative reconstruction (IR). Median filtering was applied to the RD scans (RD-MF) to investigate an alternative noise reduction strategy. CT attenuation at the 15th percentile of the lung CT histogram (Perc15) was computed for all image types (FD, RD, RD-MF, and RD-IR). Reproducibility coefficients were calculated to quantify the measurement differences between FD and RD scans. The ability of Perc15 to predict chronic obstructive pulmonary disease (COPD) diagnosis and exacerbation frequency was investigated using receiver operating characteristic analysis. Results The Perc15 reproducibility coefficients with and without volume adjustment were as follows: RD, 29.43 HU ± 0.62 versus 32.81 HU ± 1.70; RD-MF, 7.42 HU ± 0.42 versus 19.40 HU ± 2.65; and RD-IR, 7.10 HU ± 0.52 versus 22.46 HU ± 3.91. Receiver operating characteristic curve analysis indicated that Perc15 on volume-adjusted FD and RD scans were both predictive for COPD diagnosis (area under the receiver operating characteristic curve [AUC]: FD, 0.724 ± 0.045; RD, 0.739 ± 0.045) and for having one or more exacerbation per year (AUCs: FD, 0.593 ± 0.068; RD, 0.589 ± 0.066). Similar trends were observed when volume adjustment was not applied. Conclusion A combination of volume adjustment and noise reduction filtering improved the reproducibility of lung density measurements computed using serial FD and RD CT scans.Supplemental material is available for this article.© RSNA, 2021.
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Affiliation(s)
- Charles R Hatt
- Imbio LLC, 1015 Glenwood Ave, Minneapolis, MN 55405 (C.R.H.); School of Medicine and Public Health, Division of Radiology, University of Michigan, Ann Arbor, Mich (C.R.H.); Department of Radiology, National Jewish Health, Denver, Colo (A.S.O., D.A.L., S.M.H.); Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio (N.A.O.); and Thirona, Nijmegen, the Netherlands (J.P.C.)
| | - Andrea S Oh
- Imbio LLC, 1015 Glenwood Ave, Minneapolis, MN 55405 (C.R.H.); School of Medicine and Public Health, Division of Radiology, University of Michigan, Ann Arbor, Mich (C.R.H.); Department of Radiology, National Jewish Health, Denver, Colo (A.S.O., D.A.L., S.M.H.); Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio (N.A.O.); and Thirona, Nijmegen, the Netherlands (J.P.C.)
| | - Nancy A Obuchowski
- Imbio LLC, 1015 Glenwood Ave, Minneapolis, MN 55405 (C.R.H.); School of Medicine and Public Health, Division of Radiology, University of Michigan, Ann Arbor, Mich (C.R.H.); Department of Radiology, National Jewish Health, Denver, Colo (A.S.O., D.A.L., S.M.H.); Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio (N.A.O.); and Thirona, Nijmegen, the Netherlands (J.P.C.)
| | - Jean-Paul Charbonnier
- Imbio LLC, 1015 Glenwood Ave, Minneapolis, MN 55405 (C.R.H.); School of Medicine and Public Health, Division of Radiology, University of Michigan, Ann Arbor, Mich (C.R.H.); Department of Radiology, National Jewish Health, Denver, Colo (A.S.O., D.A.L., S.M.H.); Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio (N.A.O.); and Thirona, Nijmegen, the Netherlands (J.P.C.)
| | - David A Lynch
- Imbio LLC, 1015 Glenwood Ave, Minneapolis, MN 55405 (C.R.H.); School of Medicine and Public Health, Division of Radiology, University of Michigan, Ann Arbor, Mich (C.R.H.); Department of Radiology, National Jewish Health, Denver, Colo (A.S.O., D.A.L., S.M.H.); Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio (N.A.O.); and Thirona, Nijmegen, the Netherlands (J.P.C.)
| | - Stephen M Humphries
- Imbio LLC, 1015 Glenwood Ave, Minneapolis, MN 55405 (C.R.H.); School of Medicine and Public Health, Division of Radiology, University of Michigan, Ann Arbor, Mich (C.R.H.); Department of Radiology, National Jewish Health, Denver, Colo (A.S.O., D.A.L., S.M.H.); Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio (N.A.O.); and Thirona, Nijmegen, the Netherlands (J.P.C.)
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CT Pulmonary Vessels and MRI Ventilation in Chronic Obstructive Pulmonary Disease: Relationship with worsening FEV 1 in the TINCan cohort study. Acad Radiol 2021; 28:495-506. [PMID: 32303446 DOI: 10.1016/j.acra.2020.03.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 03/05/2020] [Accepted: 03/05/2020] [Indexed: 12/20/2022]
Abstract
RATIONALE AND OBJECTIVES The relationships between computed tomography (CT) pulmonary vascularity and MRI ventilation is not well-understood in chronic obstructive pulmonary disease (COPD) patients. Our objective was to evaluate CT pulmonary vascular and MRI ventilation measurements in ex-smokers and to investigate their associations and how such measurements change over time. MATERIALS AND METHODS Ninety ex-smokers (n = 41 without COPD 71 ± 10 years and n = 49 COPD 71 ± 8 years) provided written informed-consent to an ethics-board approved protocol and underwent imaging and pulmonary-function-tests twice, 31 ± 7 months apart. 3He MRI was acquired to generate ventilation-defect-percent (VDP). CT measurements of the relative area-of-the-lung with attenuation <-950 Hounsfield units (RA950), pulmonary vascular total-blood-volume (TBV) and percent of vessels with radius < one voxel (PV1) were evaluated. RESULTS At baseline, there were significant differences in RA950 (p = 0.0001), VDP (p = 0.0001), total-blood-volume (p = 0.0001) and PV1 (p = 0.01) between ex-smokers and COPD participants as well as for VDP (p = 0.0001) in COPD participants with and without emphysema. The annual FEV1 change (-40 ± 93 mL/year) was not different among participant subgroups (p = 0.87), but the annual RA950 (p = 0.01) and PV1 (p = 0.007) changes were significantly different in participants with an accelerated annual FEV1 decline as compared to participants with a diminished annual FEV1 decline. There were significant but weak relationships for PV1 with FEV1%pred (p = 0.02), FEV1/FVC (p = 0.001), and log RA950 (p = 0.0001), but not VDP (p=0.20). The mean change in PV1 was also weakly but significantly related to the change in RA950 (p = 0.02). CONCLUSION CT pulmonary vascular measurements were significantly different in ex-smokers and participants with COPD and related to RA950 but not VDP worsening over 2.5 years.
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Crapo J, Gupta A, Lynch DA, Vogel-Claussen J, Watz H, Turner AM, Mroz RM, Janssens W, Ludwig-Sengpiel A, Beck M, Langellier B, Ittrich C, Risse F, Diefenbach C. FOOTPRINTS study protocol: rationale and methodology of a 3-year longitudinal observational study to phenotype patients with COPD. BMJ Open 2021; 11:e042526. [PMID: 33753437 PMCID: PMC7986686 DOI: 10.1136/bmjopen-2020-042526] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 12/01/2020] [Accepted: 02/18/2021] [Indexed: 01/09/2023] Open
Abstract
INTRODUCTION A better understanding is needed of the different phenotypes that exist for patients with chronic obstructive pulmonary disease (COPD), their relationship with the pathogenesis of COPD and how they may affect disease progression. Biomarkers, including those associated with emphysema, may assist in characterising patients and in predicting and monitoring the course of disease. The FOOTPRINTS study (study 352.2069) aims to identify biomarkers associated with emphysema, over a 3-year period. METHODS AND ANALYSIS The FOOTPRINTS study is a prospective, longitudinal, multinational (12 countries), multicentre (51 sites) biomarker study, which has enrolled a total of 463 ex-smokers, including subjects without airflow limitation (as defined by the 2015 Global Initiative for Chronic Obstructive Lung Disease (GOLD) strategy report), patients with COPD across the GOLD stages 1-3 and patients with COPD and alpha1-antitrypsin deficiency. The study has an observational period lasting 156 weeks that includes seven site visits and additional phone interviews. Biomarkers in blood and sputum, imaging data (CT and magnetic resonance), clinical parameters, medical events of special interest and safety are being assessed at regular visits. Disease progression based on biomarker values and COPD phenotypes are being assessed using multivariate statistical prediction models. ETHICS AND DISSEMINATION The study protocol was approved by the authorities and ethics committees/institutional review boards of the respective institutions where applicable, which included study sites in Belgium, Canada, Denmark, Finland, Germany, Japan, Korea, Poland, Spain, Sweden, UK and USA; written informed consent has been obtained from all study participants. Ethics committee approval was obtained for all participating sites prior to enrolment of the study participants. The study results will be reported in peer-reviewed publications. TRIAL REGISTRATION NUMBER NCT02719184.
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Affiliation(s)
- James Crapo
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
| | - Abhya Gupta
- TA Inflammation Med, Boehringer Ingelheim International GmbH, Biberach an der Riss, Germany
| | - David A Lynch
- Department of Radiology, National Jewish Health, Denver, Colorado, USA
| | - Jens Vogel-Claussen
- Department of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
- Biomedical research in endstage and obstructive lung disease Hannover (BREATH), German Center for Lung Research (DZL), Hannover, Germany
| | - Henrik Watz
- Pulmonary Research Institute, LungenClinic Grosshansdorf, Grosshansdorf, Germany
- Airway Research Center North (ARCN), German Center for Lung Research (DZL), Grosshansdorf, Germany
| | - Alice M Turner
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Robert M Mroz
- 2nd Department of Lung Diseases and Tuberculosis, Bialystok Medical University, Bialystok, Poland
| | - Wim Janssens
- Department of Chronic Diseases, Metabolism and Ageing (CHROMETA), Laboratory of Respiratory Diseases and Thoracic surgery (BREATH), University Hospital Leuven, KU Leuven, Belgium
| | | | - Markus Beck
- Department of Clinical Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | | | - Carina Ittrich
- Global Department of Biostatistics and Data Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | - Frank Risse
- Department of Translational Medicine and Clinical Pharmacology, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | - Claudia Diefenbach
- Department of Translational Medicine and Clinical Pharmacology, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
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Gillenwater LA, Kechris KJ, Pratte KA, Reisdorph N, Petrache I, Labaki WW, O’Neal W, Krishnan JA, Ortega VE, DeMeo DL, Bowler RP. Metabolomic Profiling Reveals Sex Specific Associations with Chronic Obstructive Pulmonary Disease and Emphysema. Metabolites 2021; 11:161. [PMID: 33799786 PMCID: PMC7999201 DOI: 10.3390/metabo11030161] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 02/25/2021] [Accepted: 03/08/2021] [Indexed: 12/12/2022] Open
Abstract
Susceptibility and progression of lung disease, as well as response to treatment, often differ by sex, yet the metabolic mechanisms driving these sex-specific differences are still poorly understood. Women with chronic obstructive pulmonary disease (COPD) have less emphysema and more small airway disease on average than men, though these differences become less pronounced with more severe airflow limitation. While small studies of targeted metabolites have identified compounds differing by sex and COPD status, the sex-specific effect of COPD on systemic metabolism has yet to be interrogated. Significant sex differences were observed in 9 of the 11 modules identified in COPDGene. Sex-specific associations by COPD status and emphysema were observed in 3 modules for each phenotype. Sex stratified individual metabolite associations with COPD demonstrated male-specific associations in sphingomyelins and female-specific associations in acyl carnitines and phosphatidylethanolamines. There was high preservation of module assignments in SPIROMICS (SubPopulations and InteRmediate Outcome Measures In COPD Study) and similar female-specific shift in acyl carnitines. Several COPD associated metabolites differed by sex. Acyl carnitines and sphingomyelins demonstrate sex-specific abundances and may represent important metabolic signatures of sex differences in COPD. Accurately characterizing the sex-specific molecular differences in COPD is vital for personalized diagnostics and therapeutics.
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Affiliation(s)
- Lucas A. Gillenwater
- Computational Bioscience Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
| | - Katerina J. Kechris
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
| | - Katherine A. Pratte
- Division of Medicine, National Jewish Health, Denver, CO 80206, USA; (K.A.P.); (I.P.); (R.P.B.)
| | - Nichole Reisdorph
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
| | - Irina Petrache
- Division of Medicine, National Jewish Health, Denver, CO 80206, USA; (K.A.P.); (I.P.); (R.P.B.)
- School of Medicine, University of Colorado, Aurora, CO 80045, USA
| | - Wassim W. Labaki
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI 48109, USA;
| | - Wanda O’Neal
- Cystic Fibrosis/Pulmonary Research and Treatment Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jerry A. Krishnan
- Breathe Chicago Center, University of Illinois at Chicago, Chicago, IL 60608, USA;
| | - Victor E. Ortega
- Center for Precision Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA;
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, and Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Russell P. Bowler
- Division of Medicine, National Jewish Health, Denver, CO 80206, USA; (K.A.P.); (I.P.); (R.P.B.)
- School of Medicine, University of Colorado, Aurora, CO 80045, USA
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Kang HS, Bak SH, Oh HY, Lim MN, Cha YK, Yoon HJ, Kim WJ. Computed tomography-based visual assessment of chronic obstructive pulmonary disease: comparison with pulmonary function test and quantitative computed tomography. J Thorac Dis 2021; 13:1495-1506. [PMID: 33841942 PMCID: PMC8024830 DOI: 10.21037/jtd-20-3041] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Chronic obstructive pulmonary disease (COPD) has variable subtypes involving mixture of large airway inflammation, small airway disease, and emphysema. This study evaluated the relationship between visually assessed computed tomography (CT) subtypes and clinical/imaging characteristics. Methods In total, 452 participants were enrolled in this study between 2012 and 2017. Seven subtypes were defined by visual evaluation of CT images using Fleischner Society classification: normal, paraseptal emphysema (PSE), bronchial disease, and centrilobular emphysema (trace, mild, moderate and confluent/advanced destructive). The differences in several variables, including clinical, laboratory, spirometric, and quantitative CT features among CT-based visual subtypes, were compared using the chi-square tests and one-way analysis of variance. Results Subjects who had PSE had better forced expiratory volume in 1 second (FEV1) (P=0.03) percentage and higher lung density (P<0.05) than those with moderate to confluent/advanced destructive centrilobular emphysema. As the visual grade of centrilobular emphysema worsened, pulmonary function declined and modified Medical Research Council, COPD assessment test (CAT) score, and quantitative assessment (emphysema index and air trapping) increased. The bronchial subtype was associated with higher body mass index (BMI), better lung function and higher lung density. Participants with trace emphysema showed a rapid increase in functional small airway disease. Conclusions Classifying subtypes using visual CT imaging features can reflect heterogeneity and pathological processes of COPD.
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Affiliation(s)
- Han Sol Kang
- Department of Radiology, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Republic of Korea
| | - So Hyeon Bak
- Department of Radiology, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Republic of Korea
| | - Ha Yeun Oh
- Department of Radiology, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Republic of Korea
| | - Myoung-Nam Lim
- Biomedical Research Institute, Kangwon National University Hospital, Chuncheon, Republic of Korea
| | - Yoon Ki Cha
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hyun Jung Yoon
- Department of Radiology, Veterans Health Service Medical Center, Seoul, Republic of Korea
| | - Woo Jin Kim
- Department of Internal Medicine and Environmental Health Center, School of Medicine, Kangwon National University, Chuncheon, Republic of Korea
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Lee KS, Park HY. Progression of Emphysema at CT in Smokers and Its Relationship to Mortality. Radiology 2021; 299:232-233. [PMID: 33595394 DOI: 10.1148/radiol.2021204460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Kyung Soo Lee
- From the Department of Radiology (K.S.L.) and Division of Respiratory and Critical Care Medicine, Department of Internal Medicine (H.Y.P.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Kangnam-Ku, Seoul 135-710, Korea
| | - Hye Yun Park
- From the Department of Radiology (K.S.L.) and Division of Respiratory and Critical Care Medicine, Department of Internal Medicine (H.Y.P.), Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Kangnam-Ku, Seoul 135-710, Korea
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Ash SY, San José Estépar R, Fain SB, Tal-Singer R, Stockley RA, Nordenmark LH, Rennard S, Han MK, Merrill D, Humphries SM, Diaz AA, Mason SE, Rahaghi FN, Pistenmaa CL, Sciurba FC, Vegas-Sánchez-Ferrero G, Lynch DA, Washko GR. Relationship between Emphysema Progression at CT and Mortality in Ever-Smokers: Results from the COPDGene and ECLIPSE Cohorts. Radiology 2021; 299:222-231. [PMID: 33591891 PMCID: PMC7997617 DOI: 10.1148/radiol.2021203531] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background The relationship between emphysema progression and long-term outcomes is unclear. Purpose To determine the relationship between emphysema progression at CT and mortality among participants with emphysema. Materials and Methods In a secondary analysis of two prospective observational studies, COPDGene (clinicaltrials.gov, NCT00608764) and Evaluation of Chronic Obstructive Pulmonary Disease Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE; clinicaltrials.gov, NCT00292552), emphysema was measured at CT at two points by using the volume-adjusted lung density at the 15th percentile of the lung density histogram (hereafter, lung density perc15) method. The association between emphysema progression rate and all-cause mortality was analyzed by using Cox regression adjusted for ethnicity, sex, baseline age, pack-years, and lung density, baseline and change in smoking status, forced expiratory volume in 1 second, and 6-minute walk distance. In COPDGene, respiratory mortality was analyzed by using the Fine and Gray method. Results A total of 5143 participants (2613 men [51%]; mean age, 60 years ± 9 [standard deviation]) in COPDGene and 1549 participants (973 men [63%]; mean age, 62 years ± 8) in ECLIPSE were evaluated, of which 2097 (40.8%) and 1179 (76.1%) had emphysema, respectively. Baseline imaging was performed between January 2008 and December 2010 for COPDGene and January 2006 and August 2007 for ECLIPSE. Follow-up imaging was performed after 5.5 years ± 0.6 in COPDGene and 3.0 years ± 0.2 in ECLIPSE, and mortality was assessed over the ensuing 5 years in both. For every 1 g/L per year faster rate of decline in lung density perc15, all-cause mortality increased by 8% in COPDGene (hazard ratio [HR], 1.08; 95% CI: 1.01, 1.16; P = .03) and 6% in ECLIPSE (HR, 1.06; 95% CI: 1.00, 1.13; P = .045). In COPDGene, respiratory mortality increased by 22% (HR, 1.22; 95% CI: 1.13, 1.31; P < .001) for the same increase in the rate of change in lung density perc15. Conclusion In ever-smokers with emphysema, emphysema progression at CT was associated with increased all-cause and respiratory mortality. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Lee and Park in this issue.
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Affiliation(s)
- Samuel Y Ash
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Raúl San José Estépar
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Sean B Fain
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Ruth Tal-Singer
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Robert A Stockley
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Lars H Nordenmark
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Stephen Rennard
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - MeiLan K Han
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Debora Merrill
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Stephen M Humphries
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Alejandro A Diaz
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Stefanie E Mason
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Farbod N Rahaghi
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Carrie L Pistenmaa
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Frank C Sciurba
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - Gonzalo Vegas-Sánchez-Ferrero
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - David A Lynch
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
| | - George R Washko
- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
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- From the Division of Pulmonary and Critical Care Medicine, Department of Medicine (S.Y.A., A.A.D., S.E.M., F.N.R., C.L.P., G.R.W.), Applied Chest Imaging Laboratory (S.Y.A., R.S.J.E., A.A.D., S.E.M., F.N.R., C.L.P., G.V.S.F., G.R.W.), and Department of Radiology (R.S.J.E., G.V.S.F.), Brigham and Women's Hospital, 75 Francis St, PBB, CA-3, Boston, MA 02130; Departments of Biomedical Engineering and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wis (S.B.F.); COPD Foundation, Washington, DC (R.T.S., D.M.); Lung Investigation Unit, Medicine, University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital Birmingham, Birmingham, England (R.A.S.); Respiratory and Inflammation Therapy Area, Clinical Development, AstraZeneca, Mölndal, Sweden (L.H.N.); Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Nebraska Medical Center, Omaha, Neb (S.R.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Mich (M.K.H.); Department of Radiology, National Jewish Health, Denver, Colo (S.M.H., D.A.L.); and Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Department of Medicine, University of Pittsburgh, Pittsburgh, Pa (F.C.S.)
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El Kaddouri B, Strand MJ, Baraghoshi D, Humphries SM, Charbonnier JP, van Rikxoort EM, Lynch DA. Fleischner Society Visual Emphysema CT Patterns Help Predict Progression of Emphysema in Current and Former Smokers: Results from the COPDGene Study. Radiology 2021; 298:441-449. [PMID: 33320065 PMCID: PMC8824777 DOI: 10.1148/radiol.2020200563] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background The correlation between visual emphysema patterns and subsequent progression of disease may provide a way to enrich a study population for treatment trials of emphysema. Purpose To evaluate the potential relationship between emphysema visual subtypes and progression of emphysema and gas trapping. Materials and Methods Current and former smokers with and without chronic obstructive pulmonary disease (COPD) enrolled in the prospective Genetic Epidemiology of COPD (COPDGene) study (ClinicalTrials.gov identifier: NCT02445183) between 2008 and 2011 had their Fleischner Society visual CT scores assessed at baseline, quantitative inspiratory, and expiratory CT and at 5 years. They also underwent pulmonary function testing at baseline CT and at 5 years. The dependent variables were inspiratory lung density at 15th percentile (adjusted for lung volume) as a measure of emphysema and percentage of lung volume with attenuation less than -856 HU at expiratory CT as a measure of air trapping. Statistical analysis used a linear mixed model, adjusted for age, height, sex, race, smoking status, and scanner make. Results A total of 4166 participants (mean age, 60 years ± 9 [standard deviation]; 2091 [50%] men) were evaluated. In participants with COPD (1655 participants, 40%), those with visual presence of mild, moderate, and confluent emphysema at baseline CT showed a mean decline in lung density of 4.6 g/L ± 1.1 (P < .001), 6.7 g/L ± 1.1 (P < .001), and 6.4 g/L ± 1.2 (P < .001), respectively, compared with 2.4 g/L ± 1.3 (P < .001) for those with trace emphysema. For participants without COPD, those with visual presence of mild and moderate emphysema at baseline CT showed a mean decline in lung density of 3.6 g/L ± 1.0 (P < .001) and 3.1 g/L ± 1.6 (P < .001), respectively, compared with 1.8 g/L ± 1.0 (P < .001) for those with trace emphysema. Conclusion The pattern of parenchymal emphysema at baseline CT was an independent predictor of subsequent progression of emphysema in participants who are current or former cigarette smokers with and without chronic obstructive pulmonary disease. © RSNA, 2020 Online supplemental material is available for this article.
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Affiliation(s)
- Bilal El Kaddouri
- From the Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium (B.E.K.); Division of Biostatistics & Bioinformatics (M.J.S., D.B.) and Department of Radiology (S.H., D.A.L.), National Jewish Health, Denver, Colo; and Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (J.P.C., E.M.v.R.)
| | - Matthew J Strand
- From the Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium (B.E.K.); Division of Biostatistics & Bioinformatics (M.J.S., D.B.) and Department of Radiology (S.H., D.A.L.), National Jewish Health, Denver, Colo; and Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (J.P.C., E.M.v.R.)
| | - David Baraghoshi
- From the Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium (B.E.K.); Division of Biostatistics & Bioinformatics (M.J.S., D.B.) and Department of Radiology (S.H., D.A.L.), National Jewish Health, Denver, Colo; and Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (J.P.C., E.M.v.R.)
| | - Stephen M Humphries
- From the Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium (B.E.K.); Division of Biostatistics & Bioinformatics (M.J.S., D.B.) and Department of Radiology (S.H., D.A.L.), National Jewish Health, Denver, Colo; and Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (J.P.C., E.M.v.R.)
| | - Jean-Paul Charbonnier
- From the Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium (B.E.K.); Division of Biostatistics & Bioinformatics (M.J.S., D.B.) and Department of Radiology (S.H., D.A.L.), National Jewish Health, Denver, Colo; and Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (J.P.C., E.M.v.R.)
| | - Eva M van Rikxoort
- From the Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium (B.E.K.); Division of Biostatistics & Bioinformatics (M.J.S., D.B.) and Department of Radiology (S.H., D.A.L.), National Jewish Health, Denver, Colo; and Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (J.P.C., E.M.v.R.)
| | - David A Lynch
- From the Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070 Brussels, Belgium (B.E.K.); Division of Biostatistics & Bioinformatics (M.J.S., D.B.) and Department of Radiology (S.H., D.A.L.), National Jewish Health, Denver, Colo; and Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (J.P.C., E.M.v.R.)
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Lange P, Ahmed E, Lahmar ZM, Martinez FJ, Bourdin A. Natural history and mechanisms of COPD. Respirology 2021; 26:298-321. [PMID: 33506971 DOI: 10.1111/resp.14007] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 01/04/2021] [Indexed: 12/17/2022]
Abstract
The natural history of COPD is complex, and the disease is best understood as a syndrome resulting from numerous interacting factors throughout the life cycle with smoking being the strongest inciting feature. Unfortunately, diagnosis is often delayed with several longitudinal cohort studies shedding light on the long 'preclinical' period of COPD. It is now accepted that individuals presenting with different COPD phenotypes may experience varying natural history of their disease. This includes its inception, early stages and progression to established disease. Several scenarios regarding lung function course are possible, but it may conceptually be helpful to distinguish between individuals with normal maximally attained lung function in their early adulthood who thereafter experience faster than normal FEV1 decline, and those who may achieve a lower than normal maximally attained lung function. This may be the main mechanism behind COPD in the latter group, as the decline in FEV1 during their adult life may be normal or only slightly faster than normal. Regardless of the FEV1 trajectory, continuous smoking is strongly associated with disease progression, development of structural lung disease and poor prognosis. In developing countries, factors such as exposure to biomass and sequelae after tuberculosis may lead to a more airway-centred COPD phenotype than seen in smokers. Mechanistically, COPD is characterized by a combination of structural and inflammatory changes. It is unlikely that all patients share the same individual or combined mechanisms given the heterogeneity of resultant phenotypes. Lung explants, bronchial biopsies and other tissue studies have revealed important features. At the small airway level, progression of COPD is clinically imperceptible, and the pathological course of the disease is poorly described. Asthmatic features can further add confusion. However, the small airway epithelium is likely to represent a key focus of the disease, combining impaired subepithelial crosstalk and structural/inflammatory changes. Insufficient resolution of inflammatory processes may facilitate these changes. Pathologically, epithelial metaplasia, inversion of the goblet to ciliated cell ratio, enlargement of the submucosal glands and neutrophil and CD8-T-cell infiltration can be detected. Evidence of type 2 inflammation is gaining interest in the light of new therapeutic agents. Alarmin biology is a promising area that may permit control of inflammation and partial reversal of structural changes in COPD. Here, we review the latest work describing the development and progression of COPD with a focus on lung function trajectories, exacerbations and survival. We also review mechanisms focusing on epithelial changes associated with COPD and lack of resolution characterizing the underlying inflammatory processes.
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Affiliation(s)
- Peter Lange
- Department of Internal Medicine, Section of Respiratory Medicine, Copenhagen University Hospital - Herlev, Herlev, Denmark.,Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
| | - Engi Ahmed
- IRMB, University of Montpellier, INSERM, CHU Montpellier, Montpellier, France.,Department of Respiratory Diseases, University of Montpellier, CHU Montpellier, INSERM, Montpellier, France
| | - Zakaria Mohamed Lahmar
- Department of Respiratory Diseases, University of Montpellier, CHU Montpellier, INSERM, Montpellier, France
| | - Fernando J Martinez
- Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Arnaud Bourdin
- Department of Respiratory Diseases, University of Montpellier, CHU Montpellier, INSERM, Montpellier, France.,PhyMedExp, University of Montpellier, INSERM U1046, CNRS UMR 9214, Montpellier, France
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48
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Grenier PA. Emphysema at CT in Smokers with Normal Spirometry: Why It Is Clinically Significant. Radiology 2020; 296:650-651. [PMID: 32639194 DOI: 10.1148/radiol.2020202576] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Philippe A Grenier
- From the Department of Radiology, Hôpital FOCH, 40 rue Worth, 92150 Suresnes, France
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49
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Rangaraju M, Turner AM. Why is Disease Penetration so Variable in Alpha-1 Antitrypsin Deficiency? The Contribution of Environmental Factors. CHRONIC OBSTRUCTIVE PULMONARY DISEASES-JOURNAL OF THE COPD FOUNDATION 2020; 7:280-289. [PMID: 32698254 DOI: 10.15326/jcopdf.7.3.2019.0177] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Environmental influences on clinical phenotype in alpha-1 antitrypsin deficiency (AATD) include cigarette smoke, occupational exposures, airway/sputum bacteria and outdoor air pollution. This narrative review describes the impact of the major environmental exposures and summarizes their effect on clinical phenotype and outcomes. In general, patients with AATD are more susceptible to pulmonary damage as a result of the relatively unopposed action of neutrophil elastase, in the context of neutrophilic inflammation stimulated by environmental factors. However, the amount of phenotypic variability explicable by environmental factors is insufficient to account for the wide range of clinical presentations observed, suggesting that a combination of genetic and environmental factors is likely to be responsible.
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Affiliation(s)
- Madhu Rangaraju
- University Hospitals, Birmingham National Health Service Foundation Trust, Birmingham, United Kingdom
| | - Alice M Turner
- University Hospitals, Birmingham National Health Service Foundation Trust, Birmingham, United Kingdom.,Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom
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