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McGroder CF, Salvatore MM, D'Souza BM, Hoffman EA, Baldwin MR, Garcia CK. Improved pulmonary function and exercise tolerance despite persistent pulmonary fibrosis over 1 year after severe COVID-19 infection. Thorax 2024; 79:472-475. [PMID: 38514184 DOI: 10.1136/thorax-2023-220370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
We conducted a prospective single-centre cohort study of 104 multi-ethnic severe COVID-19 survivors from the first wave of the pandemic 15 months after hospitalisation. Of those who were assessed at 4 and 15 months, improvement of ground glass opacities correlated with worsened fibrotic reticulations. Despite a high prevalence of fibrotic patterns (64%), pulmonary function, grip strength, 6 min walk distance and frailty normalised. Overall, dyspnoea, cough and exhaustion did not improve and were not correlated with pulmonary function or radiographic fibrosis at 15 months, suggesting non-respiratory aetiologies. Monitoring persistent, and often subclinical, fibrotic interstitial abnormalities will be needed to determine their potential for future progression.
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Affiliation(s)
- Claire F McGroder
- Medicine/Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Mary M Salvatore
- Radiology, Columbia University Medical Center, New York, New York, USA
| | - Belinda M D'Souza
- Radiology, Columbia University Medical Center, New York, New York, USA
| | - Eric A Hoffman
- Radiology/Medicine/Biomedical Engineering, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Matthew R Baldwin
- Medicine/Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Christine Kim Garcia
- Medicine/Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Precision Medicine Initiative and the Center for Precision Medicine and Genomics, Columbia University, New York, NY, USA
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Li F, Zhang X, Comellas AP, Hoffman EA, Graham MM, Lin CL. Exploratory Study on COPD Phenotypes and their Progression: Integrating SPECT and qCT Imaging Analysis. medRxiv 2024:2024.04.10.24305577. [PMID: 38645219 PMCID: PMC11030493 DOI: 10.1101/2024.04.10.24305577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Background The objective of this study is to understand chronic obstructive pulmonary disease (COPD) phenotypes and their progressions by quantifying heterogeneities of lung ventilation from the single photon emission computed tomography (SPECT) images and establishing associations with the quantitative computed tomography (qCT) imaging-based clusters and variables. Methods Eight COPD patients completed a longitudinal study of three visits with intervals of about a year. CT scans of these subjects at residual volume, functional residual capacity, and total lung capacity were taken for all visits. The functional and structural qCT-based variables were derived, and the subjects were classified into the qCT-based clusters. In addition, the SPECT variables were derived to quantify the heterogeneity of lung ventilation. The correlations between the key qCT-based variables and SPECT-based variables were examined. Results The SPECT-based coefficient of variation (CV Total ), a measure of ventilation heterogeneity, showed strong correlations (|r| ≥ 0.7) with the qCT-based functional small airway disease percentage (fSAD% Total ) and emphysematous tissue percentage (Emph% Total ) in the total lung on cross-sectional data. As for the two-year changes, the SPECT-based maximum tracer concentration (TC max ), a measure of hot spots, exhibited strong negative correlations with fSAD% Total , Emph% Total , average airway diameter in the left upper lobe, and airflow distribution in the middle and lower lobes. Conclusion Small airway disease is highly associated with the heterogeneity of ventilation in COPD lungs. TC max is a more sensitive functional biomarker for COPD progression than CV Total . Besides fSAD% Total and Emph% Total , segmental airways narrowing and imbalanced ventilation between upper and lower lobes may contribute to the development of hot spots over time.
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Leung C, Fain SB, Hoffman EA, Fahy JV. Reply to Mozaffaripour et al.: Dose Modulation, BMI and CT-Air Trapping. Am J Respir Crit Care Med 2024. [PMID: 38574365 DOI: 10.1164/rccm.202402-0453le] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 04/03/2024] [Indexed: 04/06/2024] Open
Affiliation(s)
- Clarus Leung
- University of California San Francisco Department of Medicine, 166668, San Francisco, California, United States
| | - Sean B Fain
- University of Iowa, Department of Radiology, Iowa City, Iowa, United States
| | - Eric A Hoffman
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - John V Fahy
- University of California San Francisco, San Francisco, California, United States
- California, United States;
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Zhang X, Li F, Rajaraman PK, Comellas AP, Hoffman EA, Lin CL. Investigating distributions of inhaled aerosols in the lungs of post-COVID-19 clusters through a unified imaging and modeling approach. Eur J Pharm Sci 2024; 195:106724. [PMID: 38340875 PMCID: PMC10948263 DOI: 10.1016/j.ejps.2024.106724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 02/01/2024] [Accepted: 02/07/2024] [Indexed: 02/12/2024]
Abstract
BACKGROUND Recent studies, based on clinical data, have identified sex and age as significant factors associated with an increased risk of long COVID. These two factors align with the two post-COVID-19 clusters identified by a deep learning algorithm in computed tomography (CT) lung scans: Cluster 1 (C1), comprising predominantly females with small airway diseases, and Cluster 2 (C2), characterized by older individuals with fibrotic-like patterns. This study aims to assess the distributions of inhaled aerosols in these clusters. METHODS 140 COVID survivors examined around 112 days post-diagnosis, along with 105 uninfected, non-smoking healthy controls, were studied. Their demographic data and CT scans at full inspiration and expiration were analyzed using a combined imaging and modeling approach. A subject-specific CT-based computational model analysis was utilized to predict airway resistance and particle deposition among C1 and C2 subjects. The cluster-specific structure and function relationships were explored. RESULTS In C1 subjects, distinctive features included airway narrowing, a reduced homothety ratio of daughter over parent branch diameter, and increased airway resistance. Airway resistance was concentrated in the distal region, with a higher fraction of particle deposition in the proximal airways. On the other hand, C2 subjects exhibited airway dilation, an increased homothety ratio, reduced airway resistance, and a shift of resistance concentration towards the proximal region, allowing for deeper particle penetration into the lungs. CONCLUSIONS This study revealed unique mechanistic phenotypes of airway resistance and particle deposition in the two post-COVID-19 clusters. The implications of these findings for inhaled drug delivery effectiveness and susceptibility to air pollutants were explored.
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Affiliation(s)
- Xuan Zhang
- IIHR-Hydroscience & Engineering, University of Iowa, Iowa City, IA, USA; Department of Mechanical Engineering, University of Iowa, Iowa City, IA, USA
| | - Frank Li
- IIHR-Hydroscience & Engineering, University of Iowa, Iowa City, IA, USA; Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Prathish K Rajaraman
- IIHR-Hydroscience & Engineering, University of Iowa, Iowa City, IA, USA; Department of Mechanical Engineering, University of Iowa, Iowa City, IA, USA
| | | | - Eric A Hoffman
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA; Department of Radiology, University of Iowa, Iowa City, IA, USA
| | - Ching-Long Lin
- IIHR-Hydroscience & Engineering, University of Iowa, Iowa City, IA, USA; Department of Mechanical Engineering, University of Iowa, Iowa City, IA, USA; Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA; Department of Radiology, University of Iowa, Iowa City, IA, USA.
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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 Iii R, Rennard S, Schroeder JD, Woodruff PG, Barr RG, Smith BM, Hoffman EA. Vessel and Airway Characteristics in One-Year CT-defined Rapid Emphysema Progression: SPIROMICS. Ann Am Thorac Soc 2024. [PMID: 38530051 DOI: 10.1513/annalsats.202304-383oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [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 relationship with vascular and airway pathophysiology remain unclear. Objective: We sought to determine if indices of peripheral (segmental and beyond) pulmonary arterial (PA) dilation measured via computed tomography (CT) are associated with a 1-year index of emphysema (EI: %voxels<-950HU) progression. Methods: 599 GOLD 0-3 former and never-smokers were evaluated from the SubPopulations and InterMediate Outcome Measures in COPD Study (SPIROMICS) cohort: rapid-emphysema-progressors (RP, n=188; 1-year ΔEI>1%), non-progressors (NP, n=301; 1-year ΔEI±0.5%) and never-smokers (NS: N=110). Segmental PA cross-sectional areas were standardized to associated airway luminal areas (Segmental : Pulmonary Artery-to-Airway Ratio: PAARseg). Full inspiratory CT scan-derived total (arteries + veins) pulmonary vascular volume (TPVV) was compared to vessel volume with radius smaller than 0.75mm (SVV.75/TPVV). Airway-to-lung ratios (an index of dysanapsis and COPD risk) were compared to TPVV-lung-volume-ratios. Results: Compared with NP, RP exhibited significantly larger PAARseg (0.73±0.29 vs. 0.67±0.23; p=0.001), lower TPVV-to-lung-volume ratio (3.21%±0.42% vs. 3.48%±0.38%; p=5.0 x 10-12), lower airway-to-lung-volume ratio (0.031±0.003 vs. 0.034±0.004; p=6.1 x 10-13) and larger SVV.75/TPVV (37.91%±4.26% vs. 35.53±4.89; p=1.9 x 10-7). In adjusted analyses, a 1-SD increment in PAARseg was associated with a 98.4% higher rate of severe exacerbations (95%CI: 29 to 206%; p = 0.002) and 79.3% higher in odds of being in the rapid emphysema progression group (95%CI: 24% to 157%; p = 0.001). At year-2 followup, the CT-defined RP group demonstrated a significant decline in post-bronchodilator-FEV1% predicted. Conclusion: 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)
- Sarah E Gerard
- University of Iowa, Biomedical Engineering, Iowa City, Iowa, United States
| | | | - Prashant Nagpal
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - Dakai Jin
- University of Iowa, Electrical and Computer Engineering, Iowa City, Iowa, United States
| | - MeiLan K Han
- University of Michigan, Internal Medicine, Ann Arbor, Michigan, United States
| | - John D Newell
- University of Iowa, Radiology, Iowa City, Iowa, United States
| | - Punam K Saha
- University of Iowa, Electrical Engineering, Iowa City, Iowa, United States
| | - Alejandro P Comellas
- University of Iowa, 4083, Internal Medicine, Iowa City, Iowa, United States
- United States
| | | | - David Couper
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | - Spyridon Fortis
- University of Iowa Hospitals and Clinics, 21782, Division of Pulmonary, Critical Care and Occupation Medicine, Iowa City, Iowa, United States
| | - Junfeng Guo
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - Nadia N Hansel
- Johns Hopkins University, Medicine, Baltimore, Maryland, United States
| | - Richard E Kanner
- University of Utah, Internal Med/Res-Crit Care, Salt Lake City, Utah, United States
| | - Ella A Kazeroni
- University of Michigan, Radiology, Ann Arbor, Michigan, United States
| | | | - Amin Motahari
- University of Iowa, 4083, Radiology, Iowa City, Iowa, United States
| | | | | | - Joyce D Schroeder
- University of Utah Hospital, 114380, Division of Radiology and Imaging Sciences, Salt Lake City, Utah, United States
| | - Prescott G Woodruff
- UCSF, Division of Pulmonary and Critical Care Medicine, Department of Medicine and CVRI, San Francisco, California, United States
| | - R Graham Barr
- Columbia University, 5798, New York, New York, United States
| | - Benjamin M Smith
- McGill University, Respiratory Medicine, Montreal, Quebec, Canada
- Columbia University, Medicine, New York, New York, United States
| | - Eric A Hoffman
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States;
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Suri R, Markovic D, Woo H, Arjomandi M, Barr RG, Bowler RP, Criner G, Curtis JL, Dransfield MT, Drummond MB, Fortis S, Han MK, Hoffman EA, Kaner RJ, Kaufman JD, Krishnan JA, Martinez FJ, Ohar J, Ortega VE, Paine Iii R, Soler X, Woodruff PG, Hansel NN, Cooper CB, Tashkin DP, Buhr RG, Barjaktarevic IZ. The Effect of Chronic Altitude Exposure on COPD Outcomes in the SPIROMICS Cohort. Am J Respir Crit Care Med 2024. [PMID: 38507607 DOI: 10.1164/rccm.202310-1965oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 03/20/2024] [Indexed: 03/22/2024] Open
Abstract
RATIONALE Individuals with COPD have airflow obstruction and maldistribution of ventilation. For those living at high altitude, any gas exchange abnormality is compounded by reduced partial pressures of inspired oxygen. OBJECTIVES Does residence at higher-altitude exposure affect COPD outcomes, including lung function, imaging characteristics, symptoms, health status, functional exercise capacity, exacerbations, or mortality? METHODS From the SPIROMICS cohort, we identified individuals with COPD living below 1,000 ft (305 m) elevation (n= 1,367) versus above 4,000 ft (1,219 m) elevation (n= 288). Multivariable regression models were used to evaluate associations of exposure to high altitude with COPD-related outcomes. MEASUREMENTS AND MAIN RESULTS Living at higher altitude was associated with reduced functional exercise capacity as defined by 6MWD (-32.3 m, (-55.7 to -28.6)). There were no differences in patient-reported outcomes as defined by symptoms (CAT, mMRC), or health status (SGRQ). Higher altitude was not associated with a different rate of FEV1 decline. Higher altitude was associated with lower odds of severe exacerbations (IRR 0.65, (0.46 to 0.90)). There were no differences in small airway disease, air trapping, or emphysema. In longitudinal analyses, higher altitude was associated with increased mortality (HR 1.25, (1.0 to 1.55)); however, this association was no longer significant when accounting for air pollution. CONCLUSIONS Chronic altitude exposure is associated with reduced functional exercise capacity in individuals with COPD, but this did not translate into differences in symptoms or health status. Additionally, chronic high-altitude exposure did not affect progression of disease as defined by longitudinal changes in spirometry.
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Affiliation(s)
- Rajat Suri
- University of California San Diego, 8784, Pulmonary, Critical Care, and Sleep Medicine, La Jolla, California, United States;
| | - Daniela Markovic
- Ronald Reagan UCLA Medical Center, 21767, Medicine Statistics Core, Los Angeles, California, United States
| | - Han Woo
- Johns Hopkins University, 1466, Medicine, Baltimore, Maryland, United States
| | - Mehrdad Arjomandi
- UCSF Lung Biology Center, Medicine, San Francisco, California, United States
| | - R Graham Barr
- Columbia University, 5798, New York, New York, United States
| | - Russell P Bowler
- National Jewish Medical and Research Center, Department of Medicine, Denver, Colorado, United States
| | - Gerard Criner
- Temple University Hospital, Pulm & Crit Care Medicine, Philadelphia, Pennsylvania, United States
- Lewis Katz School of Medicine at Temple University, 12314, Philadelphia, Pennsylvania, United States
| | - Jeffrey L Curtis
- University of Michigan-Ann Arbor, 1259, Division of Pulmonary and Critical Care Medicine, Ann Arbor, Michigan, United States
- VA Ann Arbor Healthcare System, 20034, Medical Service, Ann Arbor, Michigan, United States
| | - Mark T Dransfield
- University of Alabama at Birmingham and the Birmingham VA Medical Center, Medicine/Pulmonary, Allergy and Critical Care, Birmingham, Alabama, United States
| | - M Bradley Drummond
- University of North Carolina at Chapel Hill, 2331, Chapel Hill, North Carolina, United States
| | - Spyridon Fortis
- University of Iowa Hospitals and Clinics, 21782, Division of Pulmonary, Critical Care and Occupation Medicine, Iowa City, Iowa, United States
| | - MeiLan K Han
- University of Michigan, Pulmonary & Critical Care, Ann Arbor, Michigan, United States
| | - Eric A Hoffman
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - Robert J Kaner
- Weill Cornell Medical College, Pulmonary and Critical Care Medicine; Genetic Medicine, New York, New York, United States
| | - Joel D Kaufman
- University of Washington, 7284, Department of Environmental and Occupational Health Sciences, Seattle, Washington, United States
| | - Jerry A Krishnan
- University of Illinois at Chicago, 14681, Chicago, Illinois, United States
| | | | - Jill Ohar
- Wake Forest School of Medicine, Internal Medicine, Division of Pulmonary, Critical Care, Allergy and Immunologic Diseases, Winston-Salem, North Carolina, United States
| | - Victor E Ortega
- Mayo Clinic, 6915, Internal Medicine, Division of Respiratory Medicine, Scottsdale, Arizona, United States
| | | | - Xavier Soler
- Regeneron Pharmaceuticals Inc, 7845, Tarrytown, New York, United States
| | - Prescott G Woodruff
- UCSF, Division of Pulmonary and Critical Care Medicine, Department of Medicine and CVRI, San Francisco, California, United States
| | - Nadia N Hansel
- Johns Hopkins University, Medicine, Baltimore, Maryland, United States
| | | | | | - Russell G Buhr
- University of California, Los Angeles, Division of Pulmonary & Critical Care, Department of Medicine, 90095, California, United States
| | - Igor Z Barjaktarevic
- University of California Los Angeles David Geffen School of Medicine, 12222, Medicine, Los Angeles, California, United States
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Vameghestahbanati M, Kingdom L, Hoffman EA, Kirby M, Allen NB, Angelini E, Bertoni A, Hamid Q, Hogg JC, Jacobs DR, Laine A, Maltais F, Michos ED, Sack C, Sin D, Watson KE, Wysoczanksi A, Couper D, Cooper C, Han M, Woodruff P, Tan WC, Bourbeau J, Barr RG, Smith BM. Airway tree caliber heterogeneity and airflow obstruction among older adults. J Appl Physiol (1985) 2024. [PMID: 38420676 DOI: 10.1152/japplphysiol.00694.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 02/22/2024] [Indexed: 03/02/2024] Open
Abstract
INTRODUCTION Smaller mean airway tree caliber is associated with airflow obstruction and chronic obstructive pulmonary disease (COPD). We investigated whether airway tree caliber heterogeneity was associated with airflow obstruction and COPD. METHODS Two community-based cohorts (MESA Lung, CanCOLD) and a longitudinal case-control study of COPD (SPIROMICS) performed spirometry and computed tomography measurements of airway lumen diameters at standard anatomic locations and total lung volume. Percent-predicted airway lumen diameters were calculated using sex-specific reference equations accounting for age, height and lung volume. The association of airway tree caliber heterogeneity, quantified as the standard deviation (SD) of percent-predicted airway lumen diameters, with baseline forced expired volume in 1-second (FEV1), FEV1/forced vital capacity (FEV1/FVC) and COPD, as well as longitudinal spirometry, were assessed using regression models adjusted for age, sex, height, race-ethnicity, and mean airway tree caliber. RESULTS Among 2,505 MESA Lung participants (mean±SD age: 69±9 years; 53% female, mean airway tree caliber: 99±10% predicted, airway tree caliber heterogeneity: 14±5%; median follow-up: 6.1 years), participants in the highest quartile of airway tree caliber heterogeneity exhibited lower FEV1 (adjusted mean difference: -125 ml, 95%CI:-171,-79), lower FEV1/FVC (adjusted mean difference: -0.01, 95%CI:-0.02,-0.01), and higher odds of COPD (adjusted OR 1.42, 95%CI:1.01-2.02) when compared with the lowest quartile, whereas longitudinal changes in FEV1 and FEV1/FVC did not differ significantly. Observations in CanCOLD and SPIROMICS were consistent. CONCLUSION Among older adults, airway tree caliber heterogeneity was associated with airflow obstruction and COPD at baseline but was not associated with longitudinal changes in spirometry.
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Grants
- HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- HHS | NIH | National Institute of Environmental Health Sciences (NIEHS)
- HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- COPD Foundation (Chronic Obstructive Pulmonary Disease Foundation)
- HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- COPD Foundation (Chronic Obstructive Pulmonary Disease Foundation)
- HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- COPD Foundation (Chronic Obstructive Pulmonary Disease Foundation)
- American Lung Association (ALA)
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Affiliation(s)
| | | | - Eric A Hoffman
- Department of Radiology, Internal Medicine and Biomedical Engineering, University of Iowa, Iowa City, IA, United States
| | | | | | - Elsa Angelini
- Imperial College Healthcare NHS Trust, Imperial College London, United Kingdom
| | - Alain Bertoni
- Wake Forest University, Winston-Salem, NC, United States
| | - Qutayba Hamid
- Department of Clinical Sciences, University of Sharjah, Sharjah, United Arab Emirates
| | - James C Hogg
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada
| | | | - Andrew Laine
- Columbia University, New York, NY, United States
| | | | - Erin D Michos
- Johns Hopkins Medicine, Baltimore, MD, United States
| | - Coralynn Sack
- University of Washington, Seattle, WA, United States
| | - Don Sin
- Centre for Heart Lung Innovation, St. Paul's Hospital, University of British Columbia, Vancouver, BC, Canada
| | - Karol E Watson
- University of California, Los Angeles, Los Angeles, CA, United States
| | | | - David Couper
- University of North Carolina Health Care, United States
| | - Christopher Cooper
- Department of Medicine, University of California, Los Angeles, CA, United States
| | - MeiLan Han
- Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan-Ann Arbor, Ann Arbor, MI, United States
| | - Prescott Woodruff
- University of California, San Francisco, San Francisco, CA, United States
| | - Wan C Tan
- Centre for Heart Lung Innovation, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jean Bourbeau
- Respiratory Division, McGill University, Montreal, Quebec, Canada
| | | | - Benjamin M Smith
- Department of Medicine, McGill University, Montreal, Quebec, Canada
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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 Trans Med Imaging 2024; PP:1-1. [PMID: 38373126 DOI: 10.1109/tmi.2024.3367321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [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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Buschur KL, Pottinger TD, Vogel-Claussen J, Powell CA, Aguet F, Allen NB, Ardlie K, Bluemke DA, Durda P, Hermann EA, Hoffman EA, Lima JAC, Liu Y, Malinsky D, Manichaikul A, Motahari A, Post WS, Prince MR, Rich SS, Rotter JI, Smith BM, Tracy RP, Watson K, Winther HB, Lappalainen T, Barr RG. Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease Study. Ann Am Thorac Soc 2024. [PMID: 38335160 DOI: 10.1513/annalsats.202305-417oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 02/08/2024] [Indexed: 02/12/2024] Open
Abstract
Rationale Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. Molecular mechanisms underlying these changes are poorly understood in patients due, in part, to the inaccessibility of the pulmonary vasculature. Peripheral blood mononuclear cells (PBMC) interact with the pulmonary endothelium. Objective To test the association between gene expression in PBMCs and pulmonary microvascular perfusion in COPD. Methods The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited two independent samples of COPD cases and controls with 10 or more pack-years. In both samples, pulmonary microvascular blood flow, pulmonary microvascular blood volume (PMBV), and mean transit time were assessed on contrast-enhanced MRI, and PBMC gene expression was assessed by microarray. Additional replication was performed in a third sample with PMBV measures on contrast-enhanced, dual-energy CT. Differential expression analyses were adjusted for age, gender, race-ethnicity, educational attainment, height, weight, smoking status, and pack-years. Results The 79 participants in the discovery sample had mean age of 69±6 years, 44% were female, 25% were non-white, 34% were current smokers and 66% had COPD. There were large PBMC gene expression signatures associated with pulmonary microvascular perfusion traits, with several replicated in the replication sets with MRI (n=47) or dual-energy CT scan (n=157) measures. Many of the identified genes are involved in inflammatory processes, including NF-κB and chemokine signaling pathways. Conclusions PBMC gene expression in NF-κB, inflammatory and chemokine signaling pathways was associated pulmonary microvascular perfusion in COPD, potentially offering new targetable candidates for novel therapies.
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Affiliation(s)
- Kristina L Buschur
- Columbia University Medical Center, 21611, Department of Medicine, New York, New York, United States
- New York Genome Center, 377591, New York, New York, United States;
| | - Tess D Pottinger
- Columbia University Medical Center, 21611, Department of Medicine, New York, New York, United States
| | - Jens Vogel-Claussen
- Hannover Medical School, 9177, Department of Diagnostic and Interventional Radiology, Hannover, Niedersachsen, Germany
- Johns Hopkins University School of Medicine, 1500, Department of Radiology, Baltimore, Maryland, United States
| | - Charles A Powell
- Mount Sinai Medical Center, 5944, Department of Medicine, New York, New York, United States
| | - Francois Aguet
- Broad Institute, 33577, Cambridge, Massachusetts, United States
| | - Norrina B Allen
- Northwestern University, 3270, Department of Preventive Medicine, Evanston, Illinois, United States
| | - Kristin Ardlie
- Broad Institute, 33577, Cambridge, Massachusetts, United States
| | - David A Bluemke
- University of Wisconsin-Madison School of Medicine and Public Health, 5232, Department of Radiology, Madison, Wisconsin, United States
| | - Peter Durda
- University of Vermont, Department of Pathology and Laboratory Medicine, Burlington, Vermont, United States
| | - Emilia A Hermann
- Columbia University Medical Center, 21611, Department of Medicine, New York, New York, United States
| | - Eric A Hoffman
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - João A C Lima
- Johns Hopkins University, Medicine/Division of Cardiology, Baltimore, United States
| | - Yongmei Liu
- Duke University School of Medicine, 12277, Medicine, Durham, North Carolina, United States
| | - Daniel Malinsky
- Columbia University Mailman School of Public Health, 33638, Department of Biostatistics, New York, New York, United States
| | - Ani Manichaikul
- University of Virginia, 2358, Center for Public Health Genomics, Charlottesville, Virginia, United States
| | - Amin Motahari
- University of Iowa, 4083, Radiology, Iowa City, Iowa, United States
| | - Wendy S Post
- Johns Hopkins University, Medicine, Baltimore, Maryland, United States
| | - Martin R Prince
- Columbia University Medical Center, 21611, Department of Radiology, New York, New York, United States
| | - Stephen S Rich
- University of Virginia, 2358, Center for Public Health Genomics, Charlottesville, Virginia, United States
| | - Jerome I Rotter
- Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 11The Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, Torrance, California, United States
| | - Benjamin M Smith
- Columbia University Medical Center, Department of Medicine, NY, New York, United States
- McGill University Health Centre, 54473, Research Institute, Montreal, Quebec, Canada
| | - Russell P Tracy
- University of Vermont, Pathology, Burlington , Vermont, United States
| | - Karol Watson
- University of California at Los Angeles, Medicine, Los Angeles, California, United States
| | - Hinrich B Winther
- Hannover Medical School, 9177, Department of Diagnostic and Interventional Radiology, Hannover, Niedersachsen, Germany
| | - Tuuli Lappalainen
- New York Genome Center, 377591, New York, New York, United States
- Columbia University, 5798, Systems Biology, New York, New York, United States
- KTH Royal Institute of Technology, 7655, Department of Gene Technology, Stockholm, Stockholm, Sweden
| | - R Graham Barr
- Columbia University Medical Center, 21611, Department of Medicine, New York, New York, United States
- Columbia University Medical Center, 21611, Department of Epidemiology, New York, New York, United States
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10
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Huang BK, Elicker BM, Henry TS, Kallianos KG, Hahn LD, Tang M, Heng F, McCulloch CE, Bhakta NR, Majumdar S, Choi J, Denlinger LC, Fain SB, Hastie AT, Hoffman EA, Israel E, Jarjour NN, Levy BD, Mauger DT, Sumino K, Wenzel SE, Castro M, Woodruff PG, Fahy JV, Sarp FTNSARP. Persistent mucus plugs in proximal airways are consequential for airflow limitation in asthma. JCI Insight 2024; 9:e174124. [PMID: 38127464 DOI: 10.1172/jci.insight.174124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 12/13/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUNDInformation about the size, airway location, and longitudinal behavior of mucus plugs in asthma is needed to understand their role in mechanisms of airflow obstruction and to rationally design muco-active treatments.METHODSCT lung scans from 57 patients with asthma were analyzed to quantify mucus plug size and airway location, and paired CT scans obtained 3 years apart were analyzed to determine plug behavior over time. Radiologist annotations of mucus plugs were incorporated in an image-processing pipeline to generate size and location information that was related to measures of airflow.RESULTSThe length distribution of 778 annotated mucus plugs was multimodal, and a 12 mm length defined short ("stubby", ≤12 mm) and long ("stringy", >12 mm) plug phenotypes. High mucus plug burden was disproportionately attributable to stringy mucus plugs. Mucus plugs localized predominantly to airway generations 6-9, and 47% of plugs in baseline scans persisted in the same airway for 3 years and fluctuated in length and volume. Mucus plugs in larger proximal generations had greater effects on spirometry measures than plugs in smaller distal generations, and a model of airflow that estimates the increased airway resistance attributable to plugs predicted a greater effect for proximal generations and more numerous mucus plugs.CONCLUSIONPersistent mucus plugs in proximal airway generations occur in asthma and demonstrate a stochastic process of formation and resolution over time. Proximal airway mucus plugs are consequential for airflow and are in locations amenable to treatment by inhaled muco-active drugs or bronchoscopy.TRIAL REGISTRATIONClinicaltrials.gov; NCT01718197, NCT01606826, NCT01750411, NCT01761058, NCT01761630, NCT01716494, and NCT01760915.FUNDINGAstraZeneca, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Sanofi-Genzyme-Regeneron, and TEVA provided financial support for study activities at the Coordinating and Clinical Centers beyond the third year of patient follow-up. These companies had no role in study design or data analysis, and the only restriction on the funds was that they be used to support the SARP initiative.
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Affiliation(s)
- Brendan K Huang
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, and
| | - Brett M Elicker
- Department of Radiology and Biomedical Imaging, UCSF, San Francisco, California, USA
| | - Travis S Henry
- Department of Radiology, Duke University, Durham, North Carolina, USA
| | - Kimberly G Kallianos
- Department of Radiology and Biomedical Imaging, UCSF, San Francisco, California, USA
| | - Lewis D Hahn
- Department of Radiology, UCSD, San Diego, California, USA
| | - Monica Tang
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, and
| | | | - Charles E McCulloch
- Department of Epidemiology and Biostatistics, UCSF, San Francisco, California, USA
| | - Nirav R Bhakta
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, and
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, UCSF, San Francisco, California, USA
| | - Jiwoong Choi
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Kansas School of Medicine, Kansas City, Kansas, USA
| | - Loren C Denlinger
- Division of Allergy, Pulmonary, and Critical Care Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Sean B Fain
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | - Annette T Hastie
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy and Immunology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | - Elliot Israel
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Nizar N Jarjour
- Division of Allergy, Pulmonary, and Critical Care Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Bruce D Levy
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Dave T Mauger
- Division of Biostatistics and Bioinformatics, Penn State College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania, USA
| | - Kaharu Sumino
- Division of Pulmonary and Critical Care Medicine, Washington University, St. Louis, USA
| | - Sally E Wenzel
- Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Mario Castro
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Kansas School of Medicine, Kansas City, Kansas, USA
| | - Prescott G Woodruff
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, and
- Cardiovascular Research Institute and
| | - John V Fahy
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, and
- Cardiovascular Research Institute and
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11
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Koch AL, Shing TL, Namen A, Couper D, Smith B, Barr RG, Bhatt S, Putcha N, Baugh A, Saha AK, Zeidler M, Comellas A, Cooper CB, Barjaktarevic I, Bowler RP, Han MK, Kim V, Paine, III R, Kanner RE, Krishnan JA, Martinez FJ, Woodruff PG, Hansel NN, Hoffman EA, Peters SP, Ortega VE. Lung Structure and Risk of Sleep Apnea in SPIROMICS. Chronic Obstr Pulm Dis 2024; 11:26-36. [PMID: 37931592 PMCID: PMC10913931 DOI: 10.15326/jcopdf.2023.0411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/23/2023] [Indexed: 11/08/2023]
Abstract
Rationale The SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS) is a prospective cohort study that enrolled 2981 participants with the goal of identifying new chronic obstructive pulmonary disease (COPD) subgroups and intermediate markers of disease progression. Individuals with COPD and obstructive sleep apnea (OSA) experience impaired quality of life and more frequent exacerbations. COPD severity also associates with computed tomography scan-based emphysema and alterations in airway dimensions. Objectives The objective was to determine whether the combination of lung function and structure influences the risk of OSA among current and former smokers. Methods Using 2 OSA risk scores, the Berlin Sleep Questionnaire (BSQ), and the DOISNORE50 (Diseases, Observed apnea, Insomnia, Snoring, Neck circumference > 18 inches, Obesity with body mass index [BMI] > 32, R = are you male, Excessive daytime sleepiness, 50 = age ≥ 50) (DIS), 1767 current and former smokers were evaluated for an association of lung structure and function with OSA risk. Measurements and Main Results The study cohort's mean age was 63 years, BMI was 28 kg/m2, and forced expiratory volume in 1 second (FEV1) was 74.8% predicted. The majority were male (55%), White (77%), former smokers (59%), and had COPD (63%). A high-risk OSA score was reported in 36% and 61% using DIS and BSQ respectively. There was a 9% increased odds of a high-risk DIS score (odds ratio [OR]=1.09, 95% confidence interval [CI]:1.03-1.14) and nominally increased odds of a high-risk BSQ score for every 10% decrease in FEV1 %predicted (OR=1.04, 95%CI: 0.998-1.09). Lung function-OSA risk associations persisted after additionally adjusting for lung structure measurements (%emphysema, %air trapping, parametric response mapping for functional small airways disease, , mean segmental wall area, tracheal %wall area, dysanapsis) for DIS (OR=1.12, 95%CI:1.03-1.22) and BSQ (OR=1.09, 95%CI:1.01-1.18). Conclusions Lower lung function independently associates with having high risk for OSA in current and former smokers. Lung structural elements, especially dysanapsis, functional small airways disease, and tracheal %wall area strengthened the effects on OSA risk.
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Affiliation(s)
- Abigail L. Koch
- Leonard M. Miller School of Medicine, University of Miami, Miami, Florida, United States
| | - Tracie L. Shing
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gilling’s School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States
| | - Andrew Namen
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine, Wake Forest, North Carolina, United States
| | - David Couper
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gilling’s School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States
| | - Benjamin Smith
- Department of Medicine, Columbia University Medical Center, New York, New York, United States
| | - R. Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, New York, United States
| | - Surya Bhatt
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Nirupama Putcha
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, United States
| | - Aaron Baugh
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California, United States
| | - Amit K. Saha
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine, Wake Forest, North Carolina, United States
| | - Michelle Zeidler
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, United States
| | - Alejandro Comellas
- Departments of Radiology, Medicine, and Bioengineering, University of Iowa, Iowa City, Iowa, United States
| | - Christopher B. Cooper
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, United States
| | - Igor Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, United States
| | - Russell P. Bowler
- Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, Colorado, United States
| | - MeiLan K. Han
- Division of Pulmonary and Critical Care Medicine, School of Medicine, University of Michigan, Ann Arbor, Michigan, United States
| | - Victor Kim
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Temple University School of Medicine, Philadelphia, Pennsylvania, United States
| | - Robert Paine, III
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, United States
| | - Richard E. Kanner
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, United States
| | - Jerry A. Krishnan
- Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Illinois at Chicago, Chicago, Illinois, United States
| | - Fernando J. Martinez
- Division of Pulmonary and Critical Care Medicine, Weill Cornell Medical College, New York, New York, United States
| | - Prescott G Woodruff
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California, United States
| | - Nadia N. Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, United States
| | - Eric A. Hoffman
- Departments of Radiology, Medicine, and Bioengineering, University of Iowa, Iowa City, Iowa, United States
| | - Stephen P. Peters
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine, Wake Forest, North Carolina, United States
| | - Victor E. Ortega
- Department of Internal Medicine, Division of Respiratory Diseases, Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona, United States
| | - for the SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS) Investigators
- Leonard M. Miller School of Medicine, University of Miami, Miami, Florida, United States
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gilling’s School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine, Wake Forest, North Carolina, United States
- Department of Medicine, Columbia University Medical Center, New York, New York, United States
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, United States
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California, United States
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, United States
- Departments of Radiology, Medicine, and Bioengineering, University of Iowa, Iowa City, Iowa, United States
- Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, Colorado, United States
- Division of Pulmonary and Critical Care Medicine, School of Medicine, University of Michigan, Ann Arbor, Michigan, United States
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Temple University School of Medicine, Philadelphia, Pennsylvania, United States
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, United States
- Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Illinois at Chicago, Chicago, Illinois, United States
- Division of Pulmonary and Critical Care Medicine, Weill Cornell Medical College, New York, New York, United States
- Department of Internal Medicine, Division of Respiratory Diseases, Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona, United States
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12
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Opron K, Begley LA, Erb-Downward JR, Li G, Alexis NE, Barjaktarevic I, Barr RG, Bleecker ER, Boucher R, Bowler RP, Christenson SA, Comellas AP, Criner G, Cooper CB, Couper D, Galban CJ, Han MK, Hastie A, Hatt C, Hoffman EA, Kaner RJ, Kesimer M, Krishnan JA, LaFon DC, Martinez FJ, Ortega VE, Peters SP, Paine Iii R, Putcha N, Woodruff PG, Huffnagle GB, Kozik AJ, Curtis JL, Huang YJ. Loss of Airway Phylogenetic Diversity Is Associated with Clinical and Pathobiological Markers of Disease Development in COPD. Am J Respir Crit Care Med 2024. [PMID: 38261629 DOI: 10.1164/rccm.202303-0489oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 01/19/2024] [Indexed: 01/25/2024] Open
Abstract
RATIONALE The airway microbiome has the potential to shape COPD pathogenesis, but its relationship to outcomes in milder disease is unestablished. OBJECTIVES Identify sputum microbiome characteristics associated with markers of COPD in participants of the SubPopulations and InteRmediate Outcome Measures of COPD Study (SPIROMICS). METHODS Sputum DNA from 877 participants were analyzed using 16S rRNA gene sequencing. Relationships between baseline airway microbiota composition and clinical, radiographic and muco-inflammatory markers, including longitudinal lung function trajectory, were examined. MEASUREMENTS AND MAIN RESULTS Participant data represented predominantly milder disease (GOLD 0-2: N=732/877). Phylogenetic diversity (range of different species within a sample) correlated positively with baseline lung function, declined with higher GOLD stage, and correlated negatively with symptom burden, radiographic markers of airway disease, and total mucin concentrations (p<0.001). In co-variate adjusted regression models, organisms robustly associated with better lung function included members of Alloprevotella, Oribacterium, and Veillonella. Conversely, lower lung function, greater symptoms and radiographic measures of small airway disease associated with enrichment in members of Streptococcus, Actinobacillus, Actinomyces, and other genera. Baseline sputum microbiota features also associated with lung function trajectory during SPIROMICS follow up (stable/improved, decliner, or rapid decliner). The 'stable/improved' group (slope of FEV1 regression ≥ 66th percentile) had higher bacterial diversity at baseline, associated with enrichment in Prevotella, Leptotrichia, and Neisseria. In contrast, the 'rapid decliner' group (FEV1 slope ≤ 33rd percentile) had significantly lower baseline diversity, associated with enrichment in Streptococcus. CONCLUSIONS In SPIROMICS baseline airway microbiota features demonstrate divergent associations with better or worse COPD-related outcomes.
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Affiliation(s)
- Kristopher Opron
- University of Michigan Medical School, 12266, Internal Medicine, Ann Arbor, Michigan, United States
| | - Lesa A Begley
- University of Michigan, 1259, Ann Arbor, Michigan, United States
| | - John R Erb-Downward
- University of Michigan, Internal Medicine, Ann Arbor, Michigan, United States
| | - Gen Li
- University of Michigan School of Public Health, 51329, Department of Biostatistics, Ann Arbor, Michigan, United States
| | - Neil E Alexis
- UNC Chapel Hill, Pediatrics, Chapel Hill, North Carolina, United States
| | - Igor Barjaktarevic
- University of California Los Angeles David Geffen School of Medicine, 12222, Medicine, Los Angeles, California, United States
| | - R Graham Barr
- Columbia University, 5798, New York, New York, United States
| | - Eugene R Bleecker
- The University of Arizona Arizona Health Sciences Center, 12217, Division of Genetics, Genomics and Precision Medicine, Tucson, Arizona, United States
| | - Richard Boucher
- University of North Carolina, Cystic Fibrosis/Pulmonary Research and Treatment Center, Chapel Hill,, North Carolina, United States
| | - Russell P Bowler
- National Jewish Medical and Research Center, Department of Medicine, Denver, Colorado, United States
| | - Stephanie A Christenson
- University of California, San Francisco, Pulmonary & Critical Care, San Francisco, California, United States
| | - Alejandro P Comellas
- University of Iowa, 4083, Internal Medicine, Iowa City, Iowa, United States
- United States
| | - Gerard Criner
- Temple University Hospital, Pulm & Crit Care Medicine, Philadelphia, Pennsylvania, United States
| | | | - David Couper
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | - Craig J Galban
- Center for Molecular Imaging, Ann Arbor, Michigan, United States
| | - MeiLan K Han
- University of Michigan, Pulmonary & Critical Care, Ann Arbor, Michigan, United States
| | - Annette Hastie
- Wake Forest University, Center for Genomics and Personalized Medicine Research, School of Medicine, Winston-Salem, North Carolina, United States
| | | | - Eric A Hoffman
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - Robert J Kaner
- Weill Cornell Medical College, Pulmonary and Critical Care Medicine; Genetic Medicine, New York, New York, United States
| | - Mehmet Kesimer
- University of North Carolina, Biochemistry and Biophysics, Chapel Hill, North Carolina, United States
| | - Jerry A Krishnan
- University of Illinois at Chicago, 14681, Chicago, Illinois, United States
| | - David C LaFon
- University of Alabama at Birmingham, 9968, Medicine-Pulmonary, Allergy, & Critical Care, Birmingham, Alabama, United States
| | | | - Victor E Ortega
- Mayo Clinic, 6915, Internal Medicine, Division of Respiratory Medicine, Scottsdale, Arizona, United States
| | - Stephen P Peters
- Wake Forest School of Medicine Medical Center, Section on Pulmonary, Critical Care, Allergy & Immunological Diseases, Winston-Salem, North Carolina, United States
| | | | - Nirupama Putcha
- Johns Hopkins University School of Medicine, Pulmonary and Critical Care Medicine, Baltimore, Maryland, United States
- Silver Spring, Maryland, United States
| | - Prescott G Woodruff
- UCSF, Division of Pulmonary and Critical Care Medicine, Department of Medicine and CVRI, San Francisco, California, United States
| | - Gary B Huffnagle
- University of Michigan , Internal Medicine, Ann Arbor, Michigan, United States
| | - Ariangela J Kozik
- University of Michigan-Ann Arbor, 1259, Molecular, Cellular, and Developmental Biology, Ann Arbor, Michigan, United States
- Michigan Medicine, 21614, Internal Medicine - Pulmonary and Critical Care Medicine, Ann Arbor, Michigan, United States
| | - Jeffrey L Curtis
- University of Michigan Health System, 21614, Internal Medicine, Ann Arbor, Michigan, United States
- VA Ann Arbor Healthcare System, 20034, Medical Service, Ann Arbor, Michigan, United States
| | - Yvonne J Huang
- University of Michigan, 1259, Dept of Internal Medicine-Pulmonary/Critical Care and Dept of Microbiology/Immunology, Ann Arbor, Michigan, United States;
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13
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Sack C, Wang M, Knutson V, Gassett A, Hoffman EA, Sheppard L, Barr RG, Kaufman JD, Smith B. Airway Tree Caliber and Susceptibility to Pollution-associated Emphysema: MESA Air and Lung Studies. Am J Respir Crit Care Med 2024. [PMID: 38226871 DOI: 10.1164/rccm.202307-1248oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 01/12/2024] [Indexed: 01/17/2024] Open
Abstract
RATIONALE Airway tree morphology varies in the general population and may modify the distribution and uptake of inhaled pollutants. OBJECTIVES We hypothesized that smaller airway caliber would be associated with emphysema progression and would increase susceptibility to air pollutant-associated emphysema progression. METHODS The Multi-Ethnic Study of Atherosclerosis (MESA) is a general population cohort of adults 45-84 years old from six U.S. communities. Airway tree caliber was quantified as the mean of airway lumen diameters measured from baseline cardiac computed tomography (CT) (2000-02). Percent emphysema, defined as percentage of lung pixels below -950 Hounsfield units, was assessed up to 5 times per participant via cardiac CT scan (2000-07) and equivalent regions on lung CT scan (2010-18). Long-term outdoor air pollutant concentrations (PM2.5, NOx, O3) were estimated at residential address with validated spatio-temporal models. Linear mixed models estimated the association between airway tree caliber and emphysema progression; modification of pollutant-associated emphysema progression was assessed using multiplicative interaction terms. MAIN RESULTS Among 6,793 participants (mean±SD age: 62±10 years), baseline airway tree caliber was 3.95±1.1 mm and median (interquartile range) of percent emphysema was 2.88 (1.21-5.68). In adjusted analyses, 10-year emphysema progression rate was 0.75 percentage points (95%CI 0.54-0.96%) higher in the smallest compared to largest airway tree caliber quartile. Airway tree caliber also modified air pollutant-associated emphysema progression. CONCLUSIONS Smaller airway tree caliber was associated with accelerated emphysema progression and modified air pollutant-associated emphysema progression. A better understanding of mechanisms of airway-alveolar homeostasis and air pollutant deposition are needed.
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Affiliation(s)
| | - Meng Wang
- University at Buffalo, 12292, Buffalo, New York, United States
| | - Victoria Knutson
- University of Washington, 7284, Seattle, Washington, United States
| | | | - Eric A Hoffman
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - Lianne Sheppard
- University of Washington School of Public Health, Seattle, Washington, United States
| | - R Graham Barr
- Columbia University, 5798, New York, New York, United States
| | - Joel D Kaufman
- University of Washington, 7284, Department of Environmental and Occupational Health Sciences, Seattle, Washington, United States
| | - Benjamin Smith
- Columbia University Medical Center, Medicine, NY, New York, United States
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14
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Ritchie AI, Donaldson GC, Hoffman EA, Allinson JP, Bloom CI, Bolton CE, Choudhury G, Gerard SE, Guo J, Alves-Moreira L, McGarvey L, Sapey E, Stockley RA, Yip KP, Singh D, Wilkinson T, Fageras M, Ostridge K, Jöns O, Bucchioni E, Compton CH, Jones P, Mezzi K, Vestbo J, Calverley PMA, Wedzicha JA. Structural Predictors of Lung Function Decline in Young Smokers with Normal Spirometry. Am J Respir Crit Care Med 2024. [PMID: 38175920 DOI: 10.1164/rccm.202307-1203oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 01/04/2024] [Indexed: 01/06/2024] Open
Abstract
RATIONALE Chronic obstructive pulmonary disease (COPD) due to tobacco smoking commonly presents when extensive lung damage has occurred. OBJECTIVES We hypothesised that structural change would be detected early in the natural history of COPD and would relate to loss of lung function with time. METHODS We recruited 431 current smokers (median age 39 years, 16 pack-years smoked) and recorded symptoms by the COPD Assessment Test (CAT), spirometry and quantitative thoracic CT (QCT) scans at study entry. These scans results were compared to 67 never smoking controls. 368 participants were followed every six months with measurement of post-bronchodilator spirometry for a median of 32 months. The rate of FEV1 decline, adjusted for current smoking status, age and sex was related to the initial QCT appearances and symptoms, measured with the CAT. MEASUREMENTS AND MAIN RESULTS There were no material differences in demography or subjective CT appearances between the young smokers and controls, but 55.7% of the former had a CAT score above 10 and 24.2% reported chronic bronchitis. QCT assessments of Disease Probability-defined functional small airways disease, ground glass opacification, bronchovascular prominence and small blood vessel to total pulmonary vessel volume ratio were increased compared to controls and were all associated with a faster FEV1 decline as was a higher CAT score. CONCLUSIONS Radiologic abnormalities on CT are already established in young smokers with normal lung function and is associated with FEV1 loss independently of the impact of symptoms. Structural abnormalities are present early in the natural history of COPD and are markers of disease progression. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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Affiliation(s)
- Andrew I Ritchie
- Imperial College London, Airway Disease Infection, London, United Kingdom of Great Britain and Northern Ireland
| | - Gavin C Donaldson
- Imperial College London, National Heart and Lung Institute, London, United Kingdom of Great Britain and Northern Ireland
- Imperial College London
| | - Eric A Hoffman
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - James P Allinson
- Imperial College London, National Heart and Lung Institute, London, United Kingdom of Great Britain and Northern Ireland
| | - Chloe I Bloom
- Imperial College London, National Heart and Lung Institute, London, United Kingdom of Great Britain and Northern Ireland
| | - Charlotte E Bolton
- Nottingham University, division of respiratory Medicine, Nottingham, United Kingdom of Great Britain and Northern Ireland
| | - Gourab Choudhury
- The University of Edinburgh, 3124, 8. ELEGI and COLT Laboratories, Queen's Medical Research Institute, 47 Little France Crescent, EH16 4TJ Edinburgh, UK, Edinburgh, United Kingdom of Great Britain and Northern Ireland
| | - Sarah E Gerard
- Harvard Medical School, 1811, Boston, Massachusetts, United States
| | - Junfeng Guo
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - Luana Alves-Moreira
- Imperial College London, Airway Disease Infection, London, United Kingdom of Great Britain and Northern Ireland
| | - Lorcan McGarvey
- Queen's University Belfast Faculty of Medicine Health and Life Sciences, 12209, Belfast, United Kingdom of Great Britain and Northern Ireland
| | - Elizabeth Sapey
- University of Birmingham, Institute of Inflammation and Ageing, Birmingham, United Kingdom of Great Britain and Northern Ireland
| | - Robert A Stockley
- University of Birmingham, 1724, Birmingham, United Kingdom of Great Britain and Northern Ireland
| | - K P Yip
- University of Birmingham, 1724, Birmingham Acute Care Research Group, Institute of Inflammation and Ageing, Birmingham, United Kingdom of Great Britain and Northern Ireland
| | - Dave Singh
- North West Lung Research Centre, Manchester, United Kingdom of Great Britain and Northern Ireland
| | - Tom Wilkinson
- University of Southampton Faculty of Medicine, 12211, CES, Southampton, United Kingdom of Great Britain and Northern Ireland
| | - Malin Fageras
- AstraZeneca, Respiratory, Inflammation and Autoimmune iMed, Molndal, Sweden
| | - Kristoffer Ostridge
- AstraZeneca R&D Gothenburg, 128698, Clinical Development, Research and Early Development, Respiratory & Immunology, Goteborg, Sweden
| | - Olaf Jöns
- Boehringer Ingelheim International GmbH, 60325, Ingelheim, Rheinland-Pfalz, Germany
| | | | - Chris H Compton
- GSK, Respiratory Medicine, Brentford, United Kingdom of Great Britain and Northern Ireland
| | - Paul Jones
- GlaxoSmithKline Plc, 1929, Brentford, London, United Kingdom of Great Britain and Northern Ireland
| | | | - Jørgen Vestbo
- The University of Manchester, 5292, Division of Infection, Immunity and Respiratory Medicine, Manchester, United Kingdom of Great Britain and Northern Ireland
- Manchester University NHS Foundation Trust, 5293, North West Lung Centre, Manchester, United Kingdom of Great Britain and Northern Ireland
| | - Peter M A Calverley
- University of Liverpool, Liverpool, United Kingdom of Great Britain and Northern Ireland
| | - Jadwiga A Wedzicha
- Imperial College London, National Heart and Lung Institute, London, United Kingdom of Great Britain and Northern Ireland;
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15
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Leung C, Tang M, Huang BK, Fain SB, Hoffman EA, Choi J, Dunican EM, Mauger DT, Denlinger LC, Jarjour NN, Israel E, Levy BD, Wenzel SE, Sumino K, Hastie AT, Schirm J, McCulloch CE, Peters MC, Woodruff PG, Sorkness RL, Castro M, Fahy JV. A Novel Air Trapping Segment Score Identifies Opposing Effects of Obesity and Eosinophilia on Air Trapping in Asthma. Am J Respir Crit Care Med 2023. [PMID: 38113166 DOI: 10.1164/rccm.202305-0802oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 12/18/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Density thresholds in computed tomography (CT) lung scans quantify air trapping (AT) at the whole lung level but are not informative for AT in specific bronchopulmonary segments. OBJECTIVES To apply a segment-based measure of AT in asthma to investigate the clinical determinants of AT in asthma. METHODS In each of 19 bronchopulmonary segments in CT lung scans from 199 asthma patients, AT was categorized as present if lung attenuation was < -856 Hounsfield units at expiration in ≥ 15% of lung area. The resulting AT segment score (0-19) was related to patient outcomes. RESULTS AT varied at the lung segment level and tended to persist at the patient and lung segment level over 3 years. Patients with widespread AT (>10 segments) had more severe asthma (p<0.05). The mean (± SD) AT segment score in patients with a BMI > 30 was lower than in patients with a BMI < 30 (3.5 ± 4.6 vs. 5.5 ± 6.3, p=0.008), and the frequency of AT in lower lobe segments in obese patients was less than in upper and middle lobe segments (35 vs. 46%, p=0.001). The AT segment score in patients with sputum eosinophil % > 2 was higher than in patients without sputum eosinophilia (7.0 ± 6.1 vs. 3.3 ± 4.9, p<0.0001). Lung segments with AT more frequently had airway mucus plugging than lung segments without AT (48 vs. 18%, p≤0.0001). CONCLUSIONS In patients with asthma, air trapping is more severe in those with airway eosinophilia and mucus plugging whereas those who are obese have less severe trapping because their lower lobe segments are spared.
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Affiliation(s)
- Clarus Leung
- University of California San Francisco, 8785, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, San Francisco, California, United States
| | - Monica Tang
- University of California San Francisco, 8785, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, San Francisco, California, United States
| | - Brendan K Huang
- University of California San Francisco, 8785, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, San Francisco, California, United States
| | - Sean B Fain
- University of Iowa, Department of Radiology, Iowa City, Iowa, United States
| | - Eric A Hoffman
- University of Iowa Carver College of Medicine, Radiology, Iowa City, Iowa, United States
| | - Jiwoong Choi
- University of Kansas School of Medicine, 12251, Division of Pulmonary, Critical Care and Sleep Medicine, Kansas City, Kansas, United States
| | - Eleanor M Dunican
- University College Dublin, 8797, School of Medicine, Dublin, Ireland
| | - David T Mauger
- The Pennsylvania State University, 8082, Division of Biostatistics and Bioinformatics, Penn State College of Medicine, University Park, Pennsylvania, United States
| | - Loren C Denlinger
- University of Wisconsin, Medicine-Allergy, Pulmonary and Critical Care Medicine, Madison, Wisconsin, United States
| | - Nizar N Jarjour
- University of Wisconsin, School of Medicine and Public Health, Madison, Wisconsin, United States
| | - Elliot Israel
- Brigham & Women's Hospital, Pulmonary and Critical Care Division, Boston, Massachusetts, United States
| | - Bruce D Levy
- Brigham and Women's Hospital Biomedical Research Institute, 278479, Pulmonary and Critical Care Medicine, Boston, Massachusetts, United States
| | - Sally E Wenzel
- University of Pittsburgh, Division of Pulmonary, Allergy and Critical Care Medicine, Pittsburgh, Pennsylvania, United States
- Dept of EOH, Pittsburgh, Pennsylvania, United States
| | - Kaharu Sumino
- Washington University School of Medicine, Division of Pulmonary and Critical Care Medicine, St. Louis, Missouri, United States
| | - Annette T Hastie
- Wake Forest University School of Medicine, 12279, Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy and Immunology, Winston-Salem, North Carolina, United States
| | - Joshua Schirm
- VIDA Diagnostics Inc., Coralville, Iowa, United States
| | - Charles E McCulloch
- University of California San Francisco, 8785, Department of Epidemiology and Biostatistics, San Francisco, California, United States
| | - Michael C Peters
- University of California San Francisco, 8785, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, San Francisco, California, United States
| | - Prescott G Woodruff
- University of California San Francisco, 8785, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, San Francisco, California, United States
- University of California San Francisco, 8785, Cardiovascular Research Institute, San Francisco, California, United States
| | - Ronald L Sorkness
- University of Wisconsin-Madison, 5228, School of Pharmacy, Madison, Wisconsin, United States
| | - Mario Castro
- University of Kansas School of Medicine, 12251, Division of Pulmonary, Critical Care and Sleep Medicine, Kansas City, Kansas, United States
| | - John V Fahy
- University of California San Francisco, 8785, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, San Francisco, California, United States
- University of California San Francisco, 8785, Cardiovascular Research Institute, San Francisco, California, United States;
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16
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Angelini ED, Yang J, Balte PP, Hoffman EA, Manichaikul AW, Sun Y, Shen W, Austin JHM, Allen NB, Bleecker ER, Bowler R, Cho MH, Cooper CS, Couper D, Dransfield MT, Garcia CK, Han MK, Hansel NN, Hughes E, Jacobs DR, Kasela S, Kaufman JD, Kim JS, Lappalainen T, Lima J, Malinsky D, Martinez FJ, Oelsner EC, Ortega VE, Paine R, Post W, Pottinger TD, Prince MR, Rich SS, Silverman EK, Smith BM, Swift AJ, Watson KE, Woodruff PG, Laine AF, Barr RG. Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans. Thorax 2023; 78:1067-1079. [PMID: 37268414 PMCID: PMC10592007 DOI: 10.1136/thorax-2022-219158] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 05/03/2023] [Indexed: 06/04/2023]
Abstract
BACKGROUND Treatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subtypes with distinct characteristics, prognoses and genetic associations. METHODS New CT emphysema subtypes were identified by unsupervised machine learning on only the texture and location of emphysematous regions on CT scans from 2853 participants in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), a COPD case-control study, followed by data reduction. Subtypes were compared with symptoms and physiology among 2949 participants in the population-based Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study and with prognosis among 6658 MESA participants. Associations with genome-wide single-nucleotide-polymorphisms were examined. RESULTS The algorithm discovered six reproducible (interlearner intraclass correlation coefficient, 0.91-1.00) CT emphysema subtypes. The most common subtype in SPIROMICS, the combined bronchitis-apical subtype, was associated with chronic bronchitis, accelerated lung function decline, hospitalisations, deaths, incident airflow limitation and a gene variant near DRD1, which is implicated in mucin hypersecretion (p=1.1 ×10-8). The second, the diffuse subtype was associated with lower weight, respiratory hospitalisations and deaths, and incident airflow limitation. The third was associated with age only. The fourth and fifth visually resembled combined pulmonary fibrosis emphysema and had distinct symptoms, physiology, prognosis and genetic associations. The sixth visually resembled vanishing lung syndrome. CONCLUSION Large-scale unsupervised machine learning on CT scans defined six reproducible, familiar CT emphysema subtypes that suggest paths to specific diagnosis and personalised therapies in COPD and pre-COPD.
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Affiliation(s)
- Elsa D Angelini
- Department of Biomedical Engineering, Columbia University, New York, New York, USA
- LTCI, Institut Polytechnique de Paris, Telecom Paris, Palaiseau, France
- NIHR Imperial Biomedical Research Centre, ITMAT Data Science Group, Imperial College, London, UK
| | - Jie Yang
- Department of Biomedical Engineering, Columbia University, New York, New York, USA
| | - Pallavi P Balte
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Eric A Hoffman
- Departments of Radiology, Medicine and Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Yifei Sun
- Department of Biostatistics, Columbia University Irving Medical Center, New York, New York, USA
| | - Wei Shen
- Department of Pediatrics, Institute of Human Nutrition, Columbia University Irving Medical Center, New York, New York, USA
- Columbia Magnetic Resonance Research Center (CMRRC), Columbia University Irving Medical Center, New York, New York, USA
| | - John H M Austin
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - Norrina B Allen
- Institute for Public Health and Medicine (IPHAM) - Center for Epidemiology and Population Health, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Eugene R Bleecker
- Department of Medicine, University of Arizona Health Sciences, Tucson, Arizona, USA
| | - Russell Bowler
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | | | - David Couper
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, USA
| | | | - Christine Kim Garcia
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - MeiLan K Han
- Department of Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Nadia N Hansel
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Emlyn Hughes
- Department of Physics, Columbia University, New York, New York, USA
| | - David R Jacobs
- Division of Epidemiology and Community Public Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Silva Kasela
- Department of Systems Biology, Columbia University Irving Medical Center, New York, New York, USA
- New York Genome Center, New York, New York, USA
| | - Joel Daniel Kaufman
- Departments of Environmental & Occupational Health Sciences, Medicine, and Epidemiology, University of Washington, Seattle, Washington, USA
| | - John Shinn Kim
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Tuuli Lappalainen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, New York, USA
| | - Joao Lima
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Daniel Malinsky
- Department of Biostatistics, Columbia University Irving Medical Center, New York, New York, USA
| | - Fernando J Martinez
- Department of Medicine, Cornell University Joan and Sanford I Weill Medical College, New York, New York, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Victor E Ortega
- Department of Pulmonary Medicine, Mayo Clinic, Phoenix, Arizona, USA
| | - Robert Paine
- Department of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Wendy Post
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Tess D Pottinger
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Martin R Prince
- Department of Radiology, Cornell University Joan and Sanford I Weill Medical College, New York, New York, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Benjamin M Smith
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Medicine, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
| | - Andrew J Swift
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, UK
| | - Karol E Watson
- Department of Medicine, University of California, Los Angeles, California, USA
| | - Prescott G Woodruff
- Department of Medicine, University of California, San Francisco, California, USA
| | - Andrew F Laine
- Department of Biomedical Engineering, Columbia University, New York, New York, USA
- Columbia Magnetic Resonance Research Center (CMRRC), Columbia University Irving Medical Center, New York, New York, USA
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Epidemiology, Columbia University Irving Medical Center, New York, New York, USA
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17
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Motahari A, Barr RG, Han MK, Anderson WH, Barjaktarevic I, Bleecker ER, Comellas AP, Cooper CB, Couper DJ, Hansel NN, Kanner RE, Kazerooni EA, Lynch DA, Martinez FJ, Newell JD, Schroeder JD, Smith BM, Woodruff PG, Hoffman EA. Repeatability of Pulmonary Quantitative Computed Tomography Measurements in Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 2023; 208:657-665. [PMID: 37490608 PMCID: PMC10515564 DOI: 10.1164/rccm.202209-1698pp] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 07/24/2023] [Indexed: 07/27/2023] Open
Affiliation(s)
| | - R. Graham Barr
- Department of Medicine and
- Department of Epidemiology, Columbia University College of Medicine, New York, New York
| | | | - Wayne H. Anderson
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Igor Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, University of California Los Angeles Medical Center, Los Angeles, California
| | | | - Alejandro P. Comellas
- Department of Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Christopher B. Cooper
- Department of Medicine and
- Department of Physiology, University of California Los Angeles, Los Angeles, California
| | - David J. Couper
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Nadia N. Hansel
- Department of Medicine, The Johns Hopkins University, Baltimore, Maryland
| | | | - Ella A. Kazerooni
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - David A. Lynch
- Department of Radiology, National Jewish Health, Denver, Colorado
| | | | - John D. Newell
- Department of Radiology and
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
| | | | - Benjamin M. Smith
- Department of Medicine and
- Department of Epidemiology, Columbia University College of Medicine, New York, New York
- Department of Medicine, McGill University, Montreal, Quebec, Canada; and
| | - Prescott G. Woodruff
- Department of Medicine, University of California San Francisco, San Francisco, California
| | - Eric A. Hoffman
- Department of Radiology and
- Department of Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
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18
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Gerard SE, Chaudhary MFA, Herrmann J, Christensen GE, Estépar RSJ, Reinhardt JM, Hoffman EA. Direct estimation of regional lung volume change from paired and single CT images using residual regression neural network. Med Phys 2023; 50:5698-5714. [PMID: 36929883 PMCID: PMC10743098 DOI: 10.1002/mp.16365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 02/11/2023] [Accepted: 03/01/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND Chest computed tomography (CT) enables characterization of pulmonary diseases by producing high-resolution and high-contrast images of the intricate lung structures. Deformable image registration is used to align chest CT scans at different lung volumes, yielding estimates of local tissue expansion and contraction. PURPOSE We investigated the utility of deep generative models for directly predicting local tissue volume change from lung CT images, bypassing computationally expensive iterative image registration and providing a method that can be utilized in scenarios where either one or two CT scans are available. METHODS A residual regression convolutional neural network, called Reg3DNet+, is proposed for directly regressing high-resolution images of local tissue volume change (i.e., Jacobian) from CT images. Image registration was performed between lung volumes at total lung capacity (TLC) and functional residual capacity (FRC) using a tissue mass- and structure-preserving registration algorithm. The Jacobian image was calculated from the registration-derived displacement field and used as the ground truth for local tissue volume change. Four separate Reg3DNet+ models were trained to predict Jacobian images using a multifactorial study design to compare the effects of network input (i.e., single image vs. paired images) and output space (i.e., FRC vs. TLC). The models were trained and evaluated on image datasets from the COPDGene study. Models were evaluated against the registration-derived Jacobian images using local, regional, and global evaluation metrics. RESULTS Statistical analysis revealed that both factors - network input and output space - were significant determinants for change in evaluation metrics. Paired-input models performed better than single-input models, and model performance was better in the output space of FRC rather than TLC. Mean structural similarity index for paired-input models was 0.959 and 0.956 for FRC and TLC output spaces, respectively, and for single-input models was 0.951 and 0.937. Global evaluation metrics demonstrated correlation between registration-derived Jacobian mean and predicted Jacobian mean: coefficient of determination (r2 ) for paired-input models was 0.974 and 0.938 for FRC and TLC output spaces, respectively, and for single-input models was 0.598 and 0.346. After correcting for effort, registration-derived lobar volume change was strongly correlated with the predicted lobar volume change: for paired-input models r2 was 0.899 for both FRC and TLC output spaces, and for single-input models r2 was 0.803 and 0.862, respectively. CONCLUSIONS Convolutional neural networks can be used to directly predict local tissue mechanics, eliminating the need for computationally expensive image registration. Networks that use paired CT images acquired at TLC and FRC allow for more accurate prediction of local tissue expansion compared to networks that use a single image. Networks that only require a single input image still show promising results, particularly after correcting for effort, and allow for local tissue expansion estimation in cases where multiple CT scans are not available. For single-input networks, the FRC image is more predictive of local tissue volume change compared to the TLC image.
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Affiliation(s)
- Sarah E. Gerard
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | | | - Jacob Herrmann
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
| | - Gary E. Christensen
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA
- Department of Radiation Oncology, University of Iowa, Iowa City, Iowa, USA
| | | | - Joseph M. Reinhardt
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | - Eric A. Hoffman
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
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19
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Althof ZW, Gerard SE, Eskandari A, Galizia MS, Hoffman EA, Reinhardt JM. Attention U-net for automated pulmonary fissure integrity analysis in lung computed tomography images. Sci Rep 2023; 13:14135. [PMID: 37644125 PMCID: PMC10465516 DOI: 10.1038/s41598-023-41322-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 08/24/2023] [Indexed: 08/31/2023] Open
Abstract
Computed Tomography (CT) imaging is routinely used for imaging of the lungs. Deep learning can effectively automate complex and laborious tasks in medical imaging. In this work, a deep learning technique is utilized to assess lobar fissure completeness (also known as fissure integrity) from pulmonary CT images. The human lungs are divided into five separate lobes, divided by the lobar fissures. Fissure integrity assessment is important to endobronchial valve treatment screening. Fissure integrity is known to be a biomarker of collateral ventilation between lobes impacting the efficacy of valves designed to block airflow to diseased lung regions. Fissure integrity is also likely to impact lobar sliding which has recently been shown to affect lung biomechanics. Further widescale study of fissure integrity's impact on disease susceptibility and progression requires rapid, reproducible, and noninvasive fissure integrity assessment. In this paper we describe IntegrityNet, an attention U-Net based automatic fissure integrity analysis tool. IntegrityNet is able to predict fissure integrity with an accuracy of 95.8%, 96.1%, and 89.8% for left oblique, right oblique, and right horizontal fissures, compared to manual analysis on a dataset of 82 subjects. We also show that our method is robust to COPD severity and reproducible across subject scans acquired at different time points.
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Affiliation(s)
- Zachary W Althof
- 5601 Seamans Center for the Engineering Arts and Sciences, University of Iowa Roy J. Carver Department of Biomedical Engineering, Iowa City, IA, 52242, USA
| | - Sarah E Gerard
- University of Iowa Department of Radiology, Iowa City, IA, USA
| | - Ali Eskandari
- University of Iowa Department of Radiology, Iowa City, IA, USA
| | | | - Eric A Hoffman
- 5601 Seamans Center for the Engineering Arts and Sciences, University of Iowa Roy J. Carver Department of Biomedical Engineering, Iowa City, IA, 52242, USA
- University of Iowa Department of Radiology, Iowa City, IA, USA
| | - Joseph M Reinhardt
- 5601 Seamans Center for the Engineering Arts and Sciences, University of Iowa Roy J. Carver Department of Biomedical Engineering, Iowa City, IA, 52242, USA.
- University of Iowa Department of Radiology, Iowa City, IA, USA.
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20
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McKleroy W, Shing T, Anderson WH, Arjomandi M, Awan HA, Barjaktarevic I, Barr RG, Bleecker ER, Boscardin J, Bowler RP, Buhr RG, Criner GJ, Comellas AP, Curtis JL, Dransfield M, Doerschuk CM, Dolezal BA, Drummond MB, Han MK, Hansel NN, Helton K, Hoffman EA, Kaner RJ, Kanner RE, Krishnan JA, Lazarus SC, Martinez FJ, Ohar J, Ortega VE, Paine R, Peters SP, Reinhardt JM, Rennard S, Smith BM, Tashkin DP, Couper D, Cooper CB, Woodruff PG. Longitudinal Follow-Up of Participants With Tobacco Exposure and Preserved Spirometry. JAMA 2023; 330:442-453. [PMID: 37526720 PMCID: PMC10394572 DOI: 10.1001/jama.2023.11676] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 06/20/2023] [Indexed: 08/02/2023]
Abstract
Importance People who smoked cigarettes may experience respiratory symptoms without spirometric airflow obstruction. These individuals are typically excluded from chronic obstructive pulmonary disease (COPD) trials and lack evidence-based therapies. Objective To define the natural history of persons with tobacco exposure and preserved spirometry (TEPS) and symptoms (symptomatic TEPS). Design, Setting, and Participants SPIROMICS II was an extension of SPIROMICS I, a multicenter study of persons aged 40 to 80 years who smoked cigarettes (>20 pack-years) with or without COPD and controls without tobacco exposure or airflow obstruction. Participants were enrolled in SPIROMICS I and II from November 10, 2010, through July 31, 2015, and followed up through July 31, 2021. Exposures Participants in SPIROMICS I underwent spirometry, 6-minute walk distance testing, assessment of respiratory symptoms, and computed tomography of the chest at yearly visits for 3 to 4 years. Participants in SPIROMICS II had 1 additional in-person visit 5 to 7 years after enrollment in SPIROMICS I. Respiratory symptoms were assessed with the COPD Assessment Test (range, 0 to 40; higher scores indicate more severe symptoms). Participants with symptomatic TEPS had normal spirometry (postbronchodilator ratio of forced expiratory volume in the first second [FEV1] to forced vital capacity >0.70) and COPD Assessment Test scores of 10 or greater. Participants with asymptomatic TEPS had normal spirometry and COPD Assessment Test scores of less than 10. Patient-reported respiratory symptoms and exacerbations were assessed every 4 months via phone calls. Main Outcomes and Measures The primary outcome was assessment for accelerated decline in lung function (FEV1) in participants with symptomatic TEPS vs asymptomatic TEPS. Secondary outcomes included development of COPD defined by spirometry, respiratory symptoms, rates of respiratory exacerbations, and progression of computed tomographic-defined airway wall thickening or emphysema. Results Of 1397 study participants, 226 had symptomatic TEPS (mean age, 60.1 [SD, 9.8] years; 134 were women [59%]) and 269 had asymptomatic TEPS (mean age, 63.1 [SD, 9.1] years; 134 were women [50%]). At a median follow-up of 5.76 years, the decline in FEV1 was -31.3 mL/y for participants with symptomatic TEPS vs -38.8 mL/y for those with asymptomatic TEPS (between-group difference, -7.5 mL/y [95% CI, -16.6 to 1.6 mL/y]). The cumulative incidence of COPD was 33.0% among participants with symptomatic TEPS vs 31.6% among those with asymptomatic TEPS (hazard ratio, 1.05 [95% CI, 0.76 to 1.46]). Participants with symptomatic TEPS had significantly more respiratory exacerbations than those with asymptomatic TEPS (0.23 vs 0.08 exacerbations per person-year, respectively; rate ratio, 2.38 [95% CI, 1.71 to 3.31], P < .001). Conclusions and Relevance Participants with symptomatic TEPS did not have accelerated rates of decline in FEV1 or increased incidence of COPD vs those with asymptomatic TEPS, but participants with symptomatic TEPS did experience significantly more respiratory exacerbations over a median follow-up of 5.8 years.
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Affiliation(s)
- William McKleroy
- Division of Pulmonary, Critical Care, Sleep, and Allergy, Department of Medicine, School of Medicine, University of California, San Francisco
- Now with Department of Pulmonary and Critical Care Medicine, Kaiser Permanente San Francisco Medical Center, San Francisco, California
| | - Tracie Shing
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill
| | - Wayne H Anderson
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill
| | - Mehrdad Arjomandi
- Division of Pulmonary, Critical Care, Sleep, and Allergy, Department of Medicine, School of Medicine, University of California, San Francisco
- Division of Pulmonary and Critical Care Medicine, Medical Service, San Francisco VA Medical Center, San Francisco, California
| | - Hira Anees Awan
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City
| | - Igor Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles
| | - R Graham Barr
- Divisions of General Medicine and Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Columbia University Medical Center, New York, New York
- Department of Epidemiology, Columbia University Medical Center, New York, New York
| | - Eugene R Bleecker
- Division of Genetics, Genomics, and Precision Medicine, Department of Medicine, College of Medicine, University of Arizona, Tucson
- Division of Pharmacogenomics, Center for Applied Genetics and Genomic Medicine, University of Arizona, Tucson
| | - John Boscardin
- Department of Medicine and Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco
| | - Russell P Bowler
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, National Jewish Health, Denver, Colorado
| | - Russell G Buhr
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles
| | - Gerard J Criner
- Division of Thoracic Medicine and Surgery, Department of Medicine, Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania
| | - Alejandro P Comellas
- Division of Pulmonary, Critical Care, and Occupational Medicine, Department of Medicine, Carver College of Medicine, University of Iowa, Iowa City
| | - Jeffrey L Curtis
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, School of Medicine, University of Michigan, Ann Arbor
- Medical Service, VA Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Mark Dransfield
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, University of Alabama, Birmingham
| | - Claire M Doerschuk
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill
| | - Brett A Dolezal
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles
| | - M Bradley Drummond
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill
| | - MeiLan K Han
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, School of Medicine, University of Michigan, Ann Arbor
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Kinsey Helton
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill
| | - Eric A Hoffman
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City
- Division of Pulmonary, Critical Care, and Occupational Medicine, Department of Medicine, Carver College of Medicine, University of Iowa, Iowa City
- Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City
| | - Robert J Kaner
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medical College, New York, New York
| | - Richard E Kanner
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, School of Medicine, University of Utah, Salt Lake City
| | - Jerry A Krishnan
- Breathe Chicago Center, Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Illinois, Chicago
| | - Stephen C Lazarus
- Division of Pulmonary, Critical Care, Sleep, and Allergy, Department of Medicine, School of Medicine, University of California, San Francisco
- Cardiovascular Research Institute, University of California, San Francisco
| | - Fernando J Martinez
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medical College, New York, New York
| | - Jill Ohar
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Victor E Ortega
- Division of Pulmonary Medicine, Department of Medicine, Mayo Clinic, Phoenix, Arizona
| | - Robert Paine
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, School of Medicine, University of Utah, Salt Lake City
| | - Stephen P Peters
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Joseph M Reinhardt
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City
| | - Stephen Rennard
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, College of Medicine, University of Nebraska, Omaha
| | - Benjamin M Smith
- Divisions of General Medicine and Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Columbia University Medical Center, New York, New York
- Division of Experimental Medicine, McGill University, Montreal, Quebec, Canada
| | - Donald P Tashkin
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles
| | - David Couper
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill
| | - Christopher B Cooper
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles
- Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles
| | - Prescott G Woodruff
- Division of Pulmonary, Critical Care, Sleep, and Allergy, Department of Medicine, School of Medicine, University of California, San Francisco
- Cardiovascular Research Institute, University of California, San Francisco
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21
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Barjaktarevic I, Cooper CB, Shing T, Buhr RG, Hoffman EA, Woodruff PG, Drummond MB, Kanner RE, Han MK, Hansel NN, Bowler RP, Kinney GL, Jacobson S, Morris MA, Martinez FJ, Ohar J, Couper D, Tashkin DP. Impact of Marijuana Smoking on COPD Progression in a Cohort of Middle-Aged and Older Persons. Chronic Obstr Pulm Dis 2023; 10:234-247. [PMID: 37199732 PMCID: PMC10484485 DOI: 10.15326/jcopdf.2022.0378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/12/2023] [Indexed: 05/19/2023]
Abstract
Background Limited data are available regarding marijuana smoking's impact on the development or progression of chronic obstructive pulmonary disease (COPD) in middle-aged or older adults with a variable history of tobacco cigarette smoking. Methods We divided ever-tobacco smoking participants in the SubPopulations and InteRmediate Outcomes In COPD Study (SPIROMICS) into 3 groups based on self-reported marijuana use: current, former, or never marijuana smokers (CMSs, FMSs or NMSs, respectively). Longitudinal data were analyzed in participants with ≥2 visits over a period of ≥52 weeks. Measurements We compared CMSs, FMSs, and NMSs, and those with varying amounts of lifetime marijuana use. Mixed effects linear regression models were used to analyze changes in spirometry, symptoms, health status, and radiographic metrics; zero-inflated negative binomial models were used for exacerbation rates. All models were adjusted for age, sex, race, baseline tobacco smoking amount, and forced expiratory volume in 1 second (FEV1) %predicted. Results Most participants were followed for ≥4 years. Annual rates of change in FEV1, incident COPD, respiratory symptoms, health status, radiographic extent of emphysema or air trapping, and total or severe exacerbations were not different between CMSs or FMSs versus NMSs or between those with any lifetime amount of marijuana use versus NMSs. Conclusions Among SPIROMICS participants with or without COPD, neither former nor current marijuana smoking of any lifetime amount was associated with evidence of COPD progression or its development. Because of our study's limitations, these findings underscore the need for further studies to better understand longer-term effects of marijuana smoking in COPD.
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Affiliation(s)
- Igor Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, United States
| | - Christopher B. Cooper
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, United States
| | - Tracie Shing
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gilling’s School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States
| | - Russell G. Buhr
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, United States
- Center for the Study of Healthcare Innovation, Implementation, and Policy, Health Services Research and Development, Greater Los Angeles Veterans Affairs Healthcare System, Los Angeles, California, United States
| | - Eric A. Hoffman
- Departments of Radiology, Medicine and Bioengineering, University of Iowa, Iowa City, Iowa, United States
| | - Prescott G. Woodruff
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, California, United States
| | - M. Bradley Drummond
- Division of Pulmonary Diseases and Critical Care Medicine, Department of Medicine, University of North Carolina, Chapel Hill, North Carolina, United States
| | - Richard E. Kanner
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, United States
| | - MeiLan K. Han
- Division of Pulmonary and Critical Care Medicine, School of Medicine, University of Michigan, Ann Arbor, Michigan, United States
| | - Nadia N. Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, United States
| | - Russell P. Bowler
- Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, Colorado, United States
| | - Gregory L. Kinney
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Sean Jacobson
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Madeline A. Morris
- College of Nursing and Health Sciences, University of Vermont, Burlington, Vermont, United States
| | - Fernando J. Martinez
- Division of Pulmonary and Critical Care Medicine, Weill Cornell Medical College, New York, New York, United States
| | - Jill Ohar
- Division of Pulmonary, Critical Care, Allergy and Immunology, School of Medicine, Wake Forest University, Wake Forest, North Carolina, United States
| | - David Couper
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gilling’s School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States
| | - Donald P. Tashkin
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, United States
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22
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Arjomandi M, Zeng S, Chen J, Bhatt SP, Abtin F, Barjaktarevic I, Barr RG, Bleecker ER, Buhr RG, Criner GJ, Comellas AP, Couper DJ, Curtis JL, Dransfield MT, Fortis S, Han MK, Hansel NN, Hoffman EA, Hokanson JE, Kaner RJ, Kanner RE, Krishnan JA, Labaki WW, Lynch DA, Ortega VE, Peters SP, Woodruff PG, Cooper CB, Bowler RP, Paine III R, Rennard SI, Tashkin DP. Changes in Lung Volumes with Spirometric Disease Progression in COPD. Chronic Obstr Pulm Dis 2023; 10:270-285. [PMID: 37199719 PMCID: PMC10484496 DOI: 10.15326/jcopdf.2022.0363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/12/2023] [Indexed: 05/19/2023]
Abstract
Background Abnormal lung volumes representing air trapping identify the subset of smokers with preserved spirometry who develop spirometric chronic obstructive pulmonary disease (COPD) and adverse outcomes. However, how lung volumes evolve in early COPD as airflow obstruction develops remains unclear. Methods To establish how lung volumes change with the development of spirometric COPD, we examined lung volumes from the pulmonary function data (seated posture) available in the U.S. Department of Veterans Affairs electronic health records (n=71,356) and lung volumes measured by computed tomography (supine posture) available from the COPD Genetic Epidemiology (COPDGene®) study (n=7969) and the SubPopulations and InterMediate Outcome Measures In COPD Study (SPIROMICS) (n=2552) cohorts, and studied their cross-sectional distributions and longitudinal changes across the airflow obstruction spectrum. Patients with preserved ratio-impaired spirometry (PRISm) were excluded from this analysis. Results Lung volumes from all 3 cohorts showed similar patterns of distributions and longitudinal changes with worsening airflow obstruction. The distributions for total lung capacity (TLC), vital capacity (VC), and inspiratory capacity (IC) and their patterns of change were nonlinear and included different phases. When stratified by airflow obstruction using Global initiative for chronic Obstructive Lung Disease (GOLD) stages, patients with GOLD 1 (mild) COPD had larger lung volumes (TLC, VC, IC) compared to patients with GOLD 0 (smokers with preserved spirometry) or GOLD 2 (moderate) disease. In longitudinal follow-up of baseline GOLD 0 patients who progressed to spirometric COPD, those with an initially higher TLC and VC developed mild obstruction (GOLD 1) while those with an initially lower TLC and VC developed moderate obstruction (GOLD 2). Conclusions In COPD, TLC, and VC have biphasic distributions, change in nonlinear fashions as obstruction worsens, and could differentiate those GOLD 0 patients at risk for more rapid spirometric disease progression.
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Affiliation(s)
- Mehrdad Arjomandi
- San Francisco Veterans Affairs Healthcare System, San Francisco, California, United States
- Department of Medicine, University of California, San Francisco, California, United States
| | - Siyang Zeng
- San Francisco Veterans Affairs Healthcare System, San Francisco, California, United States
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, United States
| | - Jianhong Chen
- San Francisco Veterans Affairs Healthcare System, San Francisco, California, United States
- Department of Medicine, University of California, San Francisco, California, United States
| | - Surya P. Bhatt
- University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Fereidoun Abtin
- Department of Medicine, University of California, Los Angeles, California, United States
| | - Igor Barjaktarevic
- Department of Medicine, University of California, Los Angeles, California, United States
| | - R. Graham Barr
- Columbia-Presbyterian Medical Center, New York, New York, United States
| | - Eugene R. Bleecker
- University of Arizona, College of Medicine, Tucson, Arizona, United States
| | - Russell G. Buhr
- Department of Medicine, University of California, Los Angeles, California, United States
| | | | | | - David J. Couper
- University of North Carolina, Chapel Hill, North Carolina, United States
| | - Jeffrey L. Curtis
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States
- Medical Service, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan, United States
| | | | | | - MeiLan K. Han
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States
| | - Nadia N. Hansel
- Department of Medicine, Johns Hopkins University, Baltimore, United States
| | | | - John E. Hokanson
- Department of Epidemiology, School of Public Health, University of Colorado, United States
| | - Robert J. Kaner
- Weill Cornell Medical Center, New York, New York, United States
| | | | | | - Wassim W. Labaki
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States
| | - David A. Lynch
- Department of Radiology, National Jewish Health Systems, Denver, Colorado, United States
| | | | - Stephen P. Peters
- Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
| | - Prescott G. Woodruff
- Department of Medicine, University of California, San Francisco, California, United States
| | - Christopher B. Cooper
- Department of Medicine, University of California, Los Angeles, California, United States
| | - Russell P. Bowler
- Department of Medicine, National Jewish Health Systems, Denver, Colorado, United States
| | - Robert Paine III
- University of Utah, Salt Lake City, Utah, United States
- Department of Medicine, National Jewish Health Systems, Denver, Colorado, United States
| | | | - Donald P. Tashkin
- Columbia-Presbyterian Medical Center, New York, New York, United States
| | - the COPDGene and SPIROMICS Investigators.
- San Francisco Veterans Affairs Healthcare System, San Francisco, California, United States
- Department of Medicine, University of California, San Francisco, California, United States
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, United States
- University of Alabama at Birmingham, Birmingham, Alabama, United States
- Department of Medicine, University of California, Los Angeles, California, United States
- Columbia-Presbyterian Medical Center, New York, New York, United States
- University of Arizona, College of Medicine, Tucson, Arizona, United States
- Temple University, Philadelphia, Pennsylvania, United States
- University of Iowa, Iowa City, Iowa, United States
- University of North Carolina, Chapel Hill, North Carolina, United States
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States
- Medical Service, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan, United States
- Department of Medicine, Johns Hopkins University, Baltimore, United States
- Department of Epidemiology, School of Public Health, University of Colorado, United States
- Weill Cornell Medical Center, New York, New York, United States
- University of Utah, Salt Lake City, Utah, United States
- University of Illinois at Chicago, Chicago, Illinois, United States
- Department of Radiology, National Jewish Health Systems, Denver, Colorado, United States
- Mayo Clinic, Scottsdale, Arizona, United States
- Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
- Department of Medicine, National Jewish Health Systems, Denver, Colorado, United States
- University of Nebraska Medical Center, Omaha, Nebraska, United States
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23
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Izquierdo M, Marion CR, Genese F, Newell JD, O'Neal WK, Li X, Hawkins GA, Barjaktarevic I, Barr RG, Christenson S, Cooper CB, Couper D, Curtis J, Han MK, Hansel NN, Kanner RE, Martinez FJ, Paine III R, Tejwani V, Woodruff PG, Zein JG, Hoffman EA, Peters SP, Meyers DA, Bleecker ER, Ortega VE. Impact of Bronchiectasis on COPD Severity and Alpha-1 Antitrypsin Deficiency as a Risk Factor in Individuals with a Heavy Smoking History. Chronic Obstr Pulm Dis 2023; 10:199-210. [PMID: 37199731 PMCID: PMC10484491 DOI: 10.15326/jcopdf.2023.0388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/03/2023] [Indexed: 07/29/2023]
Abstract
Rationale Bronchiectasis is common among those with heavy smoking histories, but risk factors for bronchiectasis, including alpha-1 antitrypsin deficiency, and its implications for COPD severity are uncharacterized in such individuals. Objectives To characterize the impact of bronchiectasis on COPD and explore alpha-1antitrypsin as a risk factor for bronchiectasis. Methods SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) participants (N=914; ages 40-80 years; ≥20-pack-year smoking) had high-resolution computed tomography (CT) scans interpreted visually for bronchiectasis, based on airway dilation without fibrosis or cicatrization. We performed regression-based models of bronchiectasis with clinical outcomes and quantitative CT measures. We deeply sequenced the gene encoding -alpha-1 antitrypsin, SERPINA1, in 835 participants to test for rare variants, focusing on the PiZ genotype (Glu366Lys, rs28929474). Measurements and Main Results We identified bronchiectasis in 365 (40%) participants, more frequently in women (45% versus 36%, p=0.0045), older participants (mean age=66[standard deviation (SD)=8.3] versus 64[SD=9.1] years, p=0.0083), and those with lower lung function (forced expiratory volume in 1 second [FEV1 ] percentage predicted=66%[SD=27] versus 77%[SD=25], p<0.0001; FEV1 to forced vital capacity [FVC] ratio=0.54[0.17] versus 0.63[SD=0.16], p<0.0001). Participants with bronchiectasis had greater emphysema (%voxels ≤-950 Hounsfield units, 11%[SD=12] versus 6.3%[SD=9], p<0.0001) and parametric response mapping functional small airways disease (26[SD=15] versus 19[SD=15], p<0.0001). Bronchiectasis was more frequent in the combined PiZZ and PiMZ genotype groups compared to those without PiZ, PiS, or other rare pathogenic variants (N=21 of 40 [52%] versus N=283 of 707[40%], odds ratio [OR]=1.97; 95% confidence interval [CI]=1.002, 3.90, p=0.049), an association attributed to White individuals (OR=1.98; 95%CI = 0.9956, 3.9; p=0.051). Conclusions Bronchiectasis was common in those with heavy smoking histories and was associated with detrimental clinical and radiographic outcomes. Our findings support alpha-1antitrypsin guideline recommendations to screen for alpha-1 antitrypsin deficiency in an appropriate bronchiectasis subgroup with a significant smoking history.
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Affiliation(s)
- Manuel Izquierdo
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine, Wake Forest, North Carolina, United States
| | - Chad R. Marion
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine, Wake Forest, North Carolina, United States
| | - Frank Genese
- Department of Pulmonary Disease, Rochester General Hospital, Rochester, New York, United States
| | - John D. Newell
- Departments of Radiology, Medicine, and Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States
| | - Wanda K. O'Neal
- Marisco Lung Institute, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | - Xingnan Li
- Department of Medicine, University of Arizona, Tucson, Arizona, United States
| | - Gregory A. Hawkins
- Center for Precision Medicine, Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
| | - Igor Barjaktarevic
- Department of Medicine, David Geffen School of Medicine, Los Angeles, California, United States
| | - R. Graham Barr
- Columbia University Medical Center, New York City, New York, United States
| | - Stephanie Christenson
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, California, United States
| | - Christopher B. Cooper
- Department of Medicine, David Geffen School of Medicine, Los Angeles, California, United States
| | - David Couper
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States
| | - Jeffrey Curtis
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan, United States
- Division of Pulmonary and Critical Care Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States
| | - Meilan K. Han
- Division of Pulmonary and Critical Care Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States
| | - Nadia N. Hansel
- School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States
| | - Richard E. Kanner
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah, United States
| | - Fernando J. Martinez
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medical College of Cornell University, New York City, New York, United States
| | - Robert Paine III
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah, United States
| | - Vickram Tejwani
- Respiratory Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States
| | - Prescott G. Woodruff
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, California, United States
| | - Joe G. Zein
- Respiratory Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States
| | - Eric A. Hoffman
- Departments of Radiology, Medicine, and Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States
| | - Stephen P. Peters
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine, Wake Forest, North Carolina, United States
| | - Deborah A. Meyers
- Department of Medicine, University of Arizona, Tucson, Arizona, United States
| | - Eugene R. Bleecker
- Department of Medicine, University of Arizona, Tucson, Arizona, United States
| | - Victor E. Ortega
- Department of Internal Medicine, Division of Respiratory Diseases, Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona, United States
| | - for the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) investigators.
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine, Wake Forest, North Carolina, United States
- Department of Pulmonary Disease, Rochester General Hospital, Rochester, New York, United States
- Departments of Radiology, Medicine, and Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States
- Marisco Lung Institute, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
- Department of Medicine, University of Arizona, Tucson, Arizona, United States
- Center for Precision Medicine, Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
- Department of Medicine, David Geffen School of Medicine, Los Angeles, California, United States
- Columbia University Medical Center, New York City, New York, United States
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, California, United States
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan, United States
- Division of Pulmonary and Critical Care Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States
- School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah, United States
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medical College of Cornell University, New York City, New York, United States
- Respiratory Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States
- Department of Internal Medicine, Division of Respiratory Diseases, Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona, United States
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24
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Rous JS, Lees PSJ, Koehler K, Buckley JP, Quirós-Alcalá L, Han MK, Hoffman EA, Labaki W, Barr RG, Peters SP, Paine R, Pirozzi C, Cooper CB, Dransfield MT, Comellas AP, Kanner RE, Drummond MB, Putcha N, Hansel NN, Paulin LM. Association of Occupational Exposures and Chronic Obstructive Pulmonary Disease Morbidity. J Occup Environ Med 2023; 65:e443-e452. [PMID: 36977360 PMCID: PMC10330008 DOI: 10.1097/jom.0000000000002850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
OBJECTIVE The aim of the study is to determine whether aggregate measures of occupational exposures are associated with chronic obstructive pulmonary disease (COPD) outcomes in the Subpopulations and Intermediate Outcome Measures in COPD study cohort. METHODS Individuals were assigned to six predetermined exposure hazard categories based on self-reported employment history. Multivariable regression, adjusted for age, sex, race, current smoking status, and smoking pack-years determined the association of such exposures to odds of COPD and morbidity measures. We compared these with the results of a single summary question regarding occupational exposure. RESULTS A total of 2772 individuals were included. Some exposure estimates, including "gases and vapors" and "dust and fumes" exposures resulted in associations with effect estimates over two times the estimated effect size when compared with a single summary question. CONCLUSIONS Use of occupational hazard categories can identify important associations with COPD morbidity while use of single-point measures may underestimate important differences in health risks.
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Affiliation(s)
- Jennifer S Rous
- From the Region VIII, Occupational Safety and Health Administration, Department of Labor, Denver, Colorado (J.S.R.); Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.S.R., P.S.J.L., K.K., J.P.B., L.Q.-A.); Department of Medicine, University of Michigan, Ann Arbor, Michigan (M.K.H., W.L.); Department of Radiology, University of Iowa, Iowa City, Iowa (E.A.H.); Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, New York (R.G.B.); Department of Medicine, Wake Forest University, Winston-Salem, North Carolina (S.P.P.); Department of Medicine, University of Utah, Salt Lake City, Utah (R.P., C.P., R.E.K.); Department of Medicine, University of California, Los Angeles, Los Angeles, California (C.B.C.); Department of Medicine, University of Alabama, Birmingham, Alabama (M.T.D..); Department of Medicine, University of Iowa, Iowa City, Iowa (A.P.C.); Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina (M.B.D.); Department of Medicine, Johns Hopkins University, Baltimore, Maryland (N.P., N.N.H.); and Department of Medicine, Dartmouth-Hitchcock Medical Center/Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire (L.M.P.)
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Philibert R, Moody J, Philibert W, Dogan MV, Hoffman EA. The Reversion of the Epigenetic Signature of Coronary Heart Disease in Response to Smoking Cessation. Genes (Basel) 2023; 14:1233. [PMID: 37372412 PMCID: PMC10297911 DOI: 10.3390/genes14061233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 06/29/2023] Open
Abstract
Coronary heart disease (CHD) is the leading cause of death worldwide. However, current diagnostic tools for CHD, such as coronary computed tomography angiography (CCTA), are poorly suited for monitoring treatment response. Recently, we have introduced an artificial-intelligence-guided integrated genetic-epigenetic test for CHD whose core consists of six assays that determine methylation in pathways known to moderate the pathogenesis of CHD. However, whether methylation at these six loci is sufficiently dynamic to guide CHD treatment response is unknown. To test that hypothesis, we examined the relationship of changes in these six loci to changes in cg05575921, a generally accepted marker of smoking intensity, using DNA from a cohort of 39 subjects undergoing a 90-day smoking cessation intervention and methylation-sensitive digital PCR (MSdPCR). We found that changes in epigenetic smoking intensity were significantly associated with reversion of the CHD-associated methylation signature at five of the six MSdPCR predictor sites: cg03725309, cg12586707, cg04988978, cg17901584, and cg21161138. We conclude that methylation-based approaches could be a scalable method for assessing the clinical effectiveness of CHD interventions, and that further studies to understand the responsiveness of these epigenetic measures to other forms of CHD treatment are in order.
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Affiliation(s)
- Robert Philibert
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (J.M.); (W.P.)
- Cardio Diagnostics Inc., Chicago, IL 60642, USA;
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA;
| | - Joanna Moody
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (J.M.); (W.P.)
| | - Willem Philibert
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (J.M.); (W.P.)
| | - Meeshanthini V. Dogan
- Cardio Diagnostics Inc., Chicago, IL 60642, USA;
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA;
| | - Eric A. Hoffman
- Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA;
- Department of Radiology, University of Iowa, Iowa City, IA 52242, USA
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26
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McGroder CF, Zhang D, Choudhury M, Podolanczuk AJ, Lederer D, Hoffman EA, Saqi A, Capaccione KM, D'Souza B, Salvatore MM, Garcia CK. Radiographic Lung Abnormalities in First-Degree Relatives of Patients With Different Subtypes of Pulmonary Fibrosis. Chest 2023; 163:1471-1475. [PMID: 36649755 PMCID: PMC10258432 DOI: 10.1016/j.chest.2023.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 01/10/2023] [Indexed: 01/15/2023] Open
Affiliation(s)
- Claire F McGroder
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY
| | - David Zhang
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY
| | - Mohammad Choudhury
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY
| | - Anna J Podolanczuk
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY
| | - David Lederer
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY
| | - Eric A Hoffman
- Departments of Radiology, Internal Medicine, and Biomedical Engineering, University of Iowa Carver College of Medicine, Iowa City, IA
| | - Anjali Saqi
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY
| | | | - Belinda D'Souza
- Department of Radiology, Columbia University Irving Medical Center, New York, NY
| | - Mary M Salvatore
- Department of Radiology, Columbia University Irving Medical Center, New York, NY
| | - Christine Kim Garcia
- Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Irving Medical Center, New York, NY; Department of Medicine, Center for Precision Medicine and Genomics, Columbia University Irving Medical Center, New York, NY; Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY.
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27
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Vameghestahbanati M, Sack C, Wysoczanski A, Hoffman EA, Angelini E, Allen NB, Bertoni AG, Guo J, Jacobs DR, Kaufman JD, Laine A, Lin CL, Malinsky D, Michos ED, Oelsner EC, Shea SJ, Watson KE, Benedetti A, Barr RG, Smith BM. Association of dysanapsis with mortality among older adults. Eur Respir J 2023; 61:2300551. [PMID: 37263750 PMCID: PMC10580540 DOI: 10.1183/13993003.00551-2023] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 04/27/2023] [Indexed: 06/03/2023]
Abstract
Dysanapsis – an anthropometric mismatch between airway tree calibre and lung size that is common in the general population – is strongly associated with all-cause mortality and increases susceptibility to tobacco smoking-related diseases https://bit.ly/42oDe8J
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Affiliation(s)
| | | | | | | | - Elsa Angelini
- Columbia University, New York, NY, USA
- NIHR Imperial Biomedical Research Centre, ITMAT Data Science Group, Imperial College London, London, UK
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Benjamin M Smith
- McGill University, Montreal, QC, Canada
- Columbia University, New York, NY, USA
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28
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Kim JS, Manichaikul AW, Hoffman EA, Balte P, Anderson MR, Bernstein EJ, Madahar P, Oelsner EC, Kawut SM, Wysoczanski A, Laine AF, Adegunsoye A, Ma JZ, Taub MA, Mathias RA, Rich SS, Rotter JI, Noth I, Garcia CK, Barr RG, Podolanczuk AJ. MUC5B, telomere length and longitudinal quantitative interstitial lung changes: the MESA Lung Study. Thorax 2023; 78:566-573. [PMID: 36690926 PMCID: PMC9899287 DOI: 10.1136/thorax-2021-218139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 07/11/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND The MUC5B promoter variant (rs35705950) and telomere length are linked to pulmonary fibrosis and CT-based qualitative assessments of interstitial abnormalities, but their associations with longitudinal quantitative changes of the lung interstitium among community-dwelling adults are unknown. METHODS We used data from participants in the Multi-Ethnic Study of Atherosclerosis with high-attenuation areas (HAAs, Examinations 1-6 (2000-2018)) and MUC5B genotype (n=4552) and telomere length (n=4488) assessments. HAA was defined as the per cent of imaged lung with attenuation of -600 to -250 Hounsfield units. We used linear mixed-effects models to examine associations of MUC5B risk allele (T) and telomere length with longitudinal changes in HAAs. Joint models were used to examine associations of longitudinal changes in HAAs with death and interstitial lung disease (ILD). RESULTS The MUC5B risk allele (T) was associated with an absolute change in HAAs of 2.60% (95% CI 0.36% to 4.86%) per 10 years overall. This association was stronger among those with a telomere length below an age-adjusted percentile of 5% (p value for interaction=0.008). A 1% increase in HAAs per year was associated with 7% increase in mortality risk (rate ratio (RR)=1.07, 95% CI 1.02 to 1.12) for overall death and 34% increase in ILD (RR=1.34, 95% CI 1.20 to 1.50). Longer baseline telomere length was cross-sectionally associated with less HAAs from baseline scans, but not with longitudinal changes in HAAs. CONCLUSIONS Longitudinal increases in HAAs were associated with the MUC5B risk allele and a higher risk of death and ILD.
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Affiliation(s)
- John S Kim
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Ani W Manichaikul
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | - Pallavi Balte
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Michaela R Anderson
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Elana J Bernstein
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Purnema Madahar
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Steven M Kawut
- Department of Medicine, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biostatistics and Epidemiology, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Artur Wysoczanski
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Andrew F Laine
- Department of Biomedical Engineering, Columbia University, New York, New York, USA
| | | | - Jennie Z Ma
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Margaret A Taub
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Rasika A Mathias
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Stephen S Rich
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Jerome I Rotter
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, USA
- The Institute for Translational Genomics and Population Sciences, The Lundquist Institute, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Imre Noth
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Christine Kim Garcia
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Anna J Podolanczuk
- Division of Pulmonary and Critical Care, Weill Cornell Medical College, New York, New York, USA
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29
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Comellas AP, Newell JD, Kirby M, Sieren JP, Peterson S, Hatt C, Galban CJ, Kazerooni EA, Lynch DA, Han MK, Hoffman EA. Residual Volume versus FRC Computed Tomography Assessment of Functional Small Airway Disease in Smokers with and without Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 2023; 207:1536-1539. [PMID: 36977314 PMCID: PMC11009613 DOI: 10.1164/rccm.202210-1852le] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023] Open
Affiliation(s)
| | - John D Newell
- Department of Radiology, and
- Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
| | - Miranda Kirby
- Department of Physics, Ryerson University, Toronto, Ontario, Canada
| | | | | | - Charles Hatt
- Imbio, Minneapolis, Minnesota
- Department of Radiology and
| | | | - Ella A Kazerooni
- Department of Radiology and
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan; and
| | - David A Lynch
- Department of Radiology, National Jewish Health, Denver, Colorado
| | - MeiLan K Han
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan; and
| | - Eric A Hoffman
- Department of Internal Medicine
- Department of Radiology, and
- Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa
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30
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DiLillo KM, Norman KC, Freeman CM, Christenson SA, Alexis NE, Anderson WH, Barjaktarevic IZ, Barr RG, Comellas AP, Bleecker ER, Boucher RC, Couper DJ, Criner GJ, Doerschuk CM, Wells JM, Han MK, Hoffman EA, Hansel NN, Hastie AT, Kaner RJ, Krishnan JA, Labaki WW, Martinez FJ, Meyers DA, O'Neal WK, Ortega VE, Paine R, Peters SP, Woodruff PG, Cooper CB, Bowler RP, Curtis JL, Arnold KB. A blood and bronchoalveolar lavage protein signature of rapid FEV 1 decline in smoking-associated COPD. Sci Rep 2023; 13:8228. [PMID: 37217548 PMCID: PMC10203309 DOI: 10.1038/s41598-023-32216-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 03/24/2023] [Indexed: 05/24/2023] Open
Abstract
Accelerated progression of chronic obstructive pulmonary disease (COPD) is associated with increased risks of hospitalization and death. Prognostic insights into mechanisms and markers of progression could facilitate development of disease-modifying therapies. Although individual biomarkers exhibit some predictive value, performance is modest and their univariate nature limits network-level insights. To overcome these limitations and gain insights into early pathways associated with rapid progression, we measured 1305 peripheral blood and 48 bronchoalveolar lavage proteins in individuals with COPD [n = 45, mean initial forced expiratory volume in one second (FEV1) 75.6 ± 17.4% predicted]. We applied a data-driven analysis pipeline, which enabled identification of protein signatures that predicted individuals at-risk for accelerated lung function decline (FEV1 decline ≥ 70 mL/year) ~ 6 years later, with high accuracy. Progression signatures suggested that early dysregulation in elements of the complement cascade is associated with accelerated decline. Our results propose potential biomarkers and early aberrant signaling mechanisms driving rapid progression in COPD.
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Affiliation(s)
- Katarina M DiLillo
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Katy C Norman
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Christine M Freeman
- Research Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Division of Pulmonary & Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
- Graduate Program in Immunology, University of Michigan, Ann Arbor, MI, USA
| | - Stephanie A Christenson
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Neil E Alexis
- Center for Environmental Medicine, Asthma, and Lung Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Wayne H Anderson
- Marsico Lung Institute/Pulmonary and Critical Care Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Igor Z Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Alejandro P Comellas
- Division of Pulmonary, Critical Care and Occupational Medicine, University of Iowa, Iowa City, IA, USA
| | - Eugene R Bleecker
- Division of Genetics, Genomics and Precision Medicine, University of Arizona Health Sciences, Tucson, AZ, USA
| | - Richard C Boucher
- Marsico Lung Institute/Cystic Fibrosis Research Center, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - David J Couper
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Gerard J Criner
- Department of Thoracic Medicine and Surgery, Temple University, Philadelphia, PA, USA
| | - Claire M Doerschuk
- Marsico Lung Institute/Cystic Fibrosis Research Center, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - J Michael Wells
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - MeiLan K Han
- Division of Pulmonary & Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, IA, USA
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Annette T Hastie
- Department of Internal Medicine, Wake Forest School of Medicine, Atrium Health, Wake Forest Baptist, Winston Salem, NC, USA
| | - Robert J Kaner
- Department of Medicine, Weill Cornell Medical Center, New York, NY, USA
| | - Jerry A Krishnan
- Division of Pulmonary, Critical Care, Sleep and Allergy, University of Illinois at Chicago, Chicago, IL, USA
| | - Wassim W Labaki
- Division of Pulmonary & Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
| | | | - Deborah A Meyers
- Division of Genetics, Genomics and Precision Medicine, University of Arizona Health Sciences, Tucson, AZ, USA
| | - Wanda K O'Neal
- Marsico Lung Institute/Cystic Fibrosis Research Center, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Victor E Ortega
- Department of Internal Medicine, Division of Respiratory Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - Robert Paine
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, University of Utah, Salt Lake City, UT, USA
| | - Stephen P Peters
- Department of Internal Medicine, Wake Forest School of Medicine, Atrium Health, Wake Forest Baptist, Winston Salem, NC, USA
| | - Prescott G Woodruff
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Christopher B Cooper
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Russell P Bowler
- Division of Pulmonary and Critical Care, National Jewish Health, Denver, CO, USA
| | - Jeffrey L Curtis
- Division of Pulmonary & Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
- Graduate Program in Immunology, University of Michigan, Ann Arbor, MI, USA
- Medical Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Kelly B Arnold
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
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31
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McGroder CF, Hansen S, Hinckley Stukovsky K, Zhang D, Nath PH, Salvatore MM, Sonavane SK, Terry N, Stowell JT, D'Souza BM, Leb JS, Dumeer S, Aziz MU, Batra K, Hoffman EA, Bernstein EJ, Kim JS, Podolanczuk AJ, Rotter JI, Manichaikul AW, Rich SS, Lederer DJ, Barr RG, McClelland RL, Garcia CK. Incidence of Interstitial Lung Abnormalities: The MESA Lung Study. Eur Respir J 2023; 61:2201950. [PMID: 37202153 PMCID: PMC10773573 DOI: 10.1183/13993003.01950-2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 01/18/2023] [Indexed: 05/20/2023]
Abstract
The incidence of newly developed interstitial lung abnormalities (ILA) and fibrotic ILA have not been previously reported.Trained thoracic radiologists evaluated 13 944 cardiac CT scans for the presence of ILA in 6197 Multi-Ethnic Study of Atherosclerosis longitudinal cohort study participants >45 years of age from 2000 to 2012. 5% of the scans were re-read by the same or a different observer in a blinded fashion. After exclusion of participants with ILA at baseline, incidence rates and incidence rate ratios for ILA and fibrotic ILA were calculated.The intra-reader agreement of ILA was 92.0% (Gwet AC1=0.912, ICC=0.982) and the inter-reader agreement of ILA was 83.5% (Gwet AC1=0.814; ICC=0.969). Incidence of ILA and fibrotic ILA was estimated to be 13.1 cases/1000 person-years and 3.5/1000 person-years, respectively. In multivariable analyses, age (HR 1.06 (1.05, 1.08), p <0.001; HR 1.08 (1.06, 1.11), p <0.001), high attenuation area (HAA) at baseline (HR 1.05 (1.03, 1.07), p <0.001; HR 1.06 (1.02, 1.10), p=0.002), and the MUC5B promoter SNP (HR 1.73 (1.17, 2.56) p=0.01; HR 4.96 (2.68, 9.15), p <0.001) were associated with incident ILA and fibrotic ILA, respectively. Ever smoking (HR 2.31 (1.34, 3.96), p= 0.002) and an IPF polygenic risk score (HR 2.09 (1.61-2.71), p<0.001) were associated only with incident fibrotic ILA.Incident ILA and fibrotic ILA were estimated by review of cardiac imaging studies. These findings may lead to wider application of a screening tool for atherosclerosis to identify preclinical lung disease.
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Affiliation(s)
- Claire F McGroder
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Spencer Hansen
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | | | - David Zhang
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - P Hrudaya Nath
- Department of Radiology, University of Alabama, Birmingham, AL, USA
| | - Mary M Salvatore
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | | | - Nina Terry
- Department of Radiology, University of Alabama, Birmingham, AL, USA
| | - Justin T Stowell
- Department of Radiology, Mayo Clinic at Jacksonville, Jacksonville, FL, USA
| | - Belinda M D'Souza
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | - Jay S Leb
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | - Shifali Dumeer
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | - Muhammad U Aziz
- Department of Radiology, University of Alabama, Birmingham, AL, USA
| | - Kiran Batra
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, IA, USA
| | - Elana J Bernstein
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - John S Kim
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Anna J Podolanczuk
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
- Department of Medicine, Weill Medical College of Cornell University, New York, NY, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ani W Manichaikul
- Department of Public Health Sciences, University of Virginia, Charlotte, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlotte, VA, USA
| | - Stephen S Rich
- Department of Public Health Sciences, University of Virginia, Charlotte, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlotte, VA, USA
| | - David J Lederer
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
- Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
- Department of Epidemiology, Columbia University Medical Center, New York, NY, USA
| | | | - Christine Kim Garcia
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
- Center for Precision Medicine and Genomics, Columbia University Medical Center, New York, NY, USA
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32
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Izquierdo M, Marion CR, Genese F, Newell JD, O'Neal WK, Li X, Hawkins GA, Barjaktarevic I, Barr RG, Christenson S, Cooper CB, Couper D, Curtis J, Han MK, Hansel NN, Kanner RE, Martinez FJ, Paine R, Tejwani V, Woodruff PG, Zein JG, Hoffman EA, Peters SP, Meyers DA, Bleecker ER, Ortega VE. Impact of Bronchiectasis on COPD Severity and Alpha-1 Antitrypsin Deficiency as a Risk Factor in Individuals with a Heavy Smoking History. Chronic Obstr Pulm Dis 2023. [PMID: 37199731 DOI: 10.15326/jcopdf.2022.0388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Rationale Bronchiectasis is common among those with heavy smoking histories, but risk factors for bronchiectasis, including α1-antitrypsin deficiency and its implications for COPD severity are uncharacterized in such individuals. Objectives To characterize the impact of bronchiectasis on COPD and explore α1-antitrypsin as a risk factor for bronchiectasis. Methods SPIROMICS participants (N=914; ages 40-80 years; ≥20 pack-years smoking) had HRCT scans interpreted visually for bronchiectasis, based on airway dilation without fibrosis or cicatrization. We performed regression-based models of bronchiectasis with clinical outcomes and quantitative CT measures. We deeply sequenced the gene encoding α1-antritrypsin, SERPINA1, in 835 participants to test for rare variants, focusing on PiZ (Glu366Lys, rs28929474). Measurements and Main Results We identified bronchiectasis in 365 (40%), more frequently in women (45% versus 36%, p=0.0045), older participants (mean age=66[SD=8.3] versus 64[SD=9.1] years, p=0.0083), and those with lower lung function (FEV1%predicted=66%[SD=27] versus 77%[SD=25], p<0.0001; FEV1/FVC=0.54[0.17] versus 0.63[SD=0.16], p<0.0001]. Participants with bronchiectasis had greater emphysema (%voxels ≤-950HFU, 11%[SD=12] versus 6.3%[SD=9], p<0.0001) and PRMfSAD (26[SD=15] versus 19[SD=15], p<0.0001). Bronchiectasis was more frequent in the combined PiZZ and PiMZ genotype groups compared to those without PiZ, PiS, or other rare pathogenic variants (N=21 of 40[52%] versus N=283 of 707[40%], OR=1.97; 95%CI=1.002, 3.90, p=0.049), an association attributed to whites (OR=1.98; 95%CI = 0.9956, 3.9; p=0.051). Conclusions Bronchiectasis was common in those with heavy smoking histories and was associated with detrimental clinical and radiographic outcomes. Our findings support α1-antitrypsin guideline recommendations to screen for α1-antitrypsin deficiency in an appropriate bronchiectasis subgroup with a significant smoking history.
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Affiliation(s)
- Manuel Izquierdo
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine Medical Center, Wake Forest, North Carolina, United States
| | - Chad R Marion
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine Medical Center, Wake Forest, North Carolina, United States
| | - Frank Genese
- Department of Pulmonary Disease, Rochester General Hospital, Rochester, New York, United States
| | - John D Newell
- Departments of Radiology, Medicine, and Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States
| | - Wanda K O'Neal
- Marisco Lung Institute, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | - Xingnan Li
- Department of Medicine, University of Arizona, Tucson, Arizona, United States
| | - Gregory A Hawkins
- Center for Precision Medicine, Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States
| | - Igor Barjaktarevic
- Department of Medicine, David Geffen School of Medicine, Los Angeles, California, United States
| | - R Graham Barr
- Columbia University Medical Center, New York City, New York, United States
| | - Stephanie Christenson
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, California, United States
| | - Christopher B Cooper
- Department of Medicine, David Geffen School of Medicine, Los Angeles, California, United States
| | - David Couper
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States
| | - Jeffrey Curtis
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan, United States
- Division of Pulmonary and Critical Care Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States
| | - Meilan K Han
- Division of Pulmonary and Critical Care Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, United States
| | - Nadia N Hansel
- Johns Hopkins University, Medicine, Baltimore, Maryland, United States
| | - Richard E Kanner
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah, United States
| | - Fernando J Martinez
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medical College of Cornell University, New York City, New York, United States
| | - Robert Paine
- Division of Respiratory, Critical Care, and Occupational Pulmonary Medicine, Department of Medicine, University of Utah Health Sciences Center, Salt Lake City, Utah, United States
| | - Vickram Tejwani
- Respiratory Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States
| | - Prescott G Woodruff
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Cardiovascular Research Institute, University of California, San Francisco, California, United States
| | - Joe G Zein
- Respiratory Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States
| | - Eric A Hoffman
- Departments of Radiology, Medicine, and Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States
| | - Stephen P Peters
- Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine Medical Center, Wake Forest, North Carolina, United States
| | - Deborah A Meyers
- Department of Medicine, University of Arizona, Tucson, Arizona, United States
| | - Eugene R Bleecker
- Department of Medicine, University of Arizona, Tucson, Arizona, United States
| | - Victor E Ortega
- Department of Internal Medicine, Division of Respiratory Diseases, Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona, United States
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Kim JS, Azarbarzin A, Podolanczuk AJ, Anderson MR, Cade BE, Kawut SM, Wysoczanski A, Laine AF, Hoffman EA, Gottlieb DJ, Garcia CK, Barr RG, Redline S. Obstructive Sleep Apnea and Longitudinal Changes in Interstitial Lung Imaging and Lung Function: The MESA Study. Ann Am Thorac Soc 2023; 20:728-737. [PMID: 36790913 PMCID: PMC10174121 DOI: 10.1513/annalsats.202208-719oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 02/15/2023] [Indexed: 02/16/2023] Open
Abstract
Rationale: Obstructive sleep apnea (OSA) has been hypothesized to be a risk factor in interstitial lung disease (ILD) and is associated with radiological markers that may represent the earlier stages of ILD. Prior studies have been limited by their cross-sectional design and potential confounding by body habitus. Objectives: To test the hypothesis that OSA severity is associated with more high-attenuation areas (HAAs) on computed tomography and worse lung function over time among older community-dwelling adults. Methods: We used data from participants in the MESA (Multi-Ethnic Study of Atherosclerosis) who had apnea-hypopnea index (AHI) measured from polysomnography (2010-2013), high attenuation areas (HAAs, -600 to -250 Hounsfield units, n = 784), assessments from exams 5 (2010-2012) and 6 (2016-2018) full-lung computed tomography scans, and spirometry assessments (n = 677). Linear mixed-effects models with random intercept were used to examine associations of OSA severity (i.e., AHI and hypoxic burden) with changes in HAAs, total lung volumes, and forced vital capacity (FVC) between exams 5 and 6. Potential confounders were adjusted for in the model, including age, sex, smoking history, height, and weight. Results: Among those with a higher AHI there were more men and a higher body mass index. Participants with AHI ⩾ 15 events/h and in the highest hypoxic burden quartile each had increases in HAAs of 11.30% (95% confidence interval [CI], 3.74-19.35%) and 9.85% (95% CI, 1.40-19.01%) per 10 years, respectively. There was a more rapid decline in total lung volumes imaged and FVC among those with AHI ⩾ 15 events/h of 220.2 ml (95% CI, 47.8-392.5 ml) and 3.63% (95% CI, 0.43-6.83%) per 10 years, respectively. Conclusions: A greater burden of hypoxia related to obstructive events during sleep was associated with increased lung densities over time and a more rapid decline in lung volumes regardless of body habitus. Our findings suggest OSA may be a contributing factor in the early stages of ILD.
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Affiliation(s)
- John S. Kim
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia
- Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York
| | - Ali Azarbarzin
- Division of Sleep and Circadian Sleep Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - Anna J. Podolanczuk
- Division of Pulmonary and Critical Care Medicine, Weill Cornell Medical Center, New York, New York
| | | | - Brian E. Cade
- Division of Sleep and Circadian Sleep Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Steven M. Kawut
- Department of Medicine, Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Artur Wysoczanski
- Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York
| | - Andrew F. Laine
- Department of Biomedical Engineering, Columbia University, New York, New York
| | - Eric A. Hoffman
- Department of Radiology
- Department of Medicine, and
- Department of Biomedical Engineering, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Daniel J. Gottlieb
- Veterans Affairs Boston Healthcare System, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Christine Kim Garcia
- Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York
| | - R. Graham Barr
- Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York
- Department of Epidemiology, Mailman School of Public Health, New York, New York; and
| | - Susan Redline
- Division of Sleep and Circadian Sleep Disorders, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
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Ensley JE, Tachau KH, Walsh SA, Zhang H, Simon G, Moser L, Atha J, Dilley P, Hoffman EA, Sonka M. Using computed tomography to recover hidden medieval fragments beneath early modern leather bindings, first results. Herit Sci 2023; 11:82. [PMID: 37113562 PMCID: PMC10123051 DOI: 10.1186/s40494-023-00912-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 03/22/2023] [Indexed: 06/19/2023]
Abstract
Medieval bindings fragments have become increasingly interesting to Humanities researchers as sources for the textual and material history of medieval Europeans. Later book binders used these discarded and repurposed pieces of earlier medieval manuscripts to reinforce the structures of other manuscripts and printed books. That many of these fragments are contained within and obscured by decorative bindings that cannot be dismantled ethically has limited their discovery and description. Although previous attempts to recover these texts using IRT and MA-XRF scanning have been successful, the extensive time required to scan a single book, and the need to modify or create specialized IRT or MA-XRF equipment for this method are drawbacks. Our research proposes and tests the capabilities of medical CT scanning technologies (commonly available at research university medical schools) for making visible and legible these fragments hidden under leather bindings. Our research team identified three sixteenth-century printed codices in our university libraries that were evidently bound in tawed leather by one workshop. The damaged cover of one of these three had revealed medieval manuscript fragments on the book spine; this codex served as a control for testing the other two volumes to see if they, too, contain fragments. The use of a medical CT scanner proved successful in visualizing interior book-spine structures and some letterforms, but not all of the text was made visible. The partial success of CT-scanning points to the value of further experimentation, given the relatively wide availability of medical imaging technologies, with their potential for short, non-destructive, 3D imaging times.
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Affiliation(s)
- J. Eric Ensley
- Special Collections & Archives, University of Iowa Libraries, Iowa City, IA 52242 USA
| | | | - Susan A. Walsh
- Small Animal Imaging Core, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA 52242 USA
| | - Honghai Zhang
- College of Engineering, University of Iowa, Iowa City, IA 52242 USA
- Visualization Lab, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA 52242 USA
| | - Giselle Simon
- Department of Conservation and Collections Care, University of Iowa Libraries, Iowa City, IA 52242 USA
| | - Laura Moser
- Department of Classics, University of Iowa, Iowa City, IA 52242 USA
| | - Jarron Atha
- Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City, IA 52242 USA
| | - Paul Dilley
- Department of Classics, University of Iowa, Iowa City, IA 52242 USA
- Department of Religious Studies, University of Iowa, Iowa City, IA 52242 USA
| | - Eric A. Hoffman
- Department of Radiology, Carver College of Medicine, University of Iowa, Iowa City, IA 52242 USA
| | - Milan Sonka
- College of Engineering, University of Iowa, Iowa City, IA 52242 USA
- Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, IA 52242 USA
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Wang JM, Labaki WW, Murray S, Martinez FJ, Curtis JL, Hoffman EA, Ram S, Bell AJ, Galban CJ, Han MK, Hatt C. Machine learning for screening of at-risk, mild and moderate COPD patients at risk of FEV 1 decline: results from COPDGene and SPIROMICS. Front Physiol 2023; 14:1144192. [PMID: 37153221 PMCID: PMC10161244 DOI: 10.3389/fphys.2023.1144192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 04/03/2023] [Indexed: 05/09/2023] Open
Abstract
Purpose: The purpose of this study was to train and validate machine learning models for predicting rapid decline of forced expiratory volume in 1 s (FEV1) in individuals with a smoking history at-risk-for chronic obstructive pulmonary disease (COPD), Global Initiative for Chronic Obstructive Lung Disease (GOLD 0), or with mild-to-moderate (GOLD 1-2) COPD. We trained multiple models to predict rapid FEV1 decline using demographic, clinical and radiologic biomarker data. Training and internal validation data were obtained from the COPDGene study and prediction models were validated against the SPIROMICS cohort. Methods: We used GOLD 0-2 participants (n = 3,821) from COPDGene (60.0 ± 8.8 years, 49.9% male) for variable selection and model training. Accelerated lung function decline was defined as a mean drop in FEV1% predicted of > 1.5%/year at 5-year follow-up. We built logistic regression models predicting accelerated decline based on 22 chest CT imaging biomarker, pulmonary function, symptom, and demographic features. Models were validated using n = 885 SPIROMICS subjects (63.6 ± 8.6 years, 47.8% male). Results: The most important variables for predicting FEV1 decline in GOLD 0 participants were bronchodilator responsiveness (BDR), post bronchodilator FEV1% predicted (FEV1.pp.post), and CT-derived expiratory lung volume; among GOLD 1 and 2 subjects, they were BDR, age, and PRMlower lobes fSAD. In the validation cohort, GOLD 0 and GOLD 1-2 full variable models had significant predictive performance with AUCs of 0.620 ± 0.081 (p = 0.041) and 0.640 ± 0.059 (p < 0.001). Subjects with higher model-derived risk scores had significantly greater odds of FEV1 decline than those with lower scores. Conclusion: Predicting FEV1 decline in at-risk patients remains challenging but a combination of clinical, physiologic and imaging variables provided the best performance across two COPD cohorts.
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Affiliation(s)
- Jennifer M. Wang
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Wassim W. Labaki
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Susan Murray
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | | | - Jeffrey L. Curtis
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, United States
- Medical Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, United States
| | - Eric A. Hoffman
- Department of Radiology, University of Iowa, Iowa City, IA, United States
| | - Sundaresh Ram
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
| | - Alexander J. Bell
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
| | - Craig J. Galban
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
| | - MeiLan K. Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Charles Hatt
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
- Imbio Inc., Minneapolis, MN, United States
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Kizhakke Puliyakote AS, Stapleton EM, Durairaj K, Karuppusamy K, Kathiresan GB, Shanmugam K, Abdul Rahim S, Navaneethakrishnan S, Bilas M, Huang R, Metwali N, Jeronimo M, Chan KS, Guo J, Nagpal P, Peters TM, Thorne PS, Comellas AP, Hoffman EA. Imaging-based assessment of lung function in a population cooking indoors with biomass fuel: a pilot study. J Appl Physiol (1985) 2023; 134:710-721. [PMID: 36759166 PMCID: PMC10027118 DOI: 10.1152/japplphysiol.00286.2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 02/02/2023] [Accepted: 02/03/2023] [Indexed: 02/11/2023] Open
Abstract
Biomass fuels (wood) are commonly used indoors in underventilated environments for cooking in the developing world, but the impact on lung physiology is poorly understood. Quantitative computed tomography (qCT) can provide sensitive metrics to compare the lungs of women cooking with wood vs. liquified petroleum gas (LPG). We prospectively assessed (qCT and spirometry) 23 primary female cooks (18 biomass, 5 LPG) with no history of cardiopulmonary disease in Thanjavur, India. CT was obtained at coached total lung capacity (TLC) and residual volume (RV). qCT assessment included texture-derived ground glass opacity [GGO: Adaptive Multiple Feature Method (AMFM)], air-trapping (expiratory voxels ≤ -856HU) and image registration-based assessment [Disease Probability Measure (DPM)] of emphysema, functional small airways disease (%AirTrapDPM), and regional lung mechanics. In addition, within-kitchen exposure assessments included particulate matter <2.5 μm(PM2.5), black carbon, β-(1, 3)-d-glucan (surrogate for fungi), and endotoxin. Air-trapping went undetected at RV via the threshold-based measure (voxels ≤ -856HU), possibly due to density shifts in the presence of inflammation. However, DPM, utilizing image-matching, demonstrated significant air-trapping in biomass vs. LPG cooks (P = 0.049). A subset of biomass cooks (6/18), identified using k-means clustering, had markedly altered DPM-metrics: greater air-trapping (P < 0.001), lower TLC-RV volume change (P < 0.001), a lower mean anisotropic deformation index (ADI; P < 0.001), and elevated % GGO (P < 0.02). Across all subjects, a texture measure of bronchovascular bundles was correlated to the log-transformed β-(1, 3)-d-glucan concentration (P = 0.026, R = 0.46), and black carbon (P = 0.04, R = 0.44). This pilot study identified environmental links with qCT-based lung pathologies and a cluster of biomass cooks (33%) with significant small airways disease.NEW & NOTEWORTHY Quantitative computed tomography has identified a cluster of women (33%) cooking with biomass fuels (wood) with image-based markers of functional small airways disease and associated alterations in regional lung mechanics. Texture and image registration-based metrics of lung function may allow for early detection of potential inflammatory processes that may arise in response to inhaled biomass smoke, and help identify phenotypes of chronic lung disease prevalent in nonsmoking women in the developing world.
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Affiliation(s)
- Abhilash S Kizhakke Puliyakote
- Department of Radiology, University of California, San Diego, La Jolla, California, United States
- Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States
| | - Emma M Stapleton
- Department of Internal Medicine, University of Iowa, Iowa City, Iowa, United States
| | - Kumar Durairaj
- Department of Physics, Periyar Maniammai Institute of Science and Technology, Thanjavur, India
| | - Kesavan Karuppusamy
- Department of Physics, Periyar Maniammai Institute of Science and Technology, Thanjavur, India
| | - Geetha B Kathiresan
- Department of Electronics and Communication Engineering, Periyar Maniammai Institute of Science and Technology, Thanjavur, India
| | - Kumaran Shanmugam
- Department of Biotechnology, Periyar Maniammai Institute of Science and Technology, Thanjavur, India
| | | | | | - Monalisa Bilas
- Department of Radiology, University of Iowa, Iowa City, Iowa, United States
| | - Rui Huang
- School of Economics, Nanjing University, Nanjing, People's Republic of China
| | - Nervana Metwali
- Department of Occupational and Environmental Health, University of Iowa, Iowa City, Iowa, United States
| | - Matthew Jeronimo
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Kung-Sik Chan
- Department of Statistics and Actuarial Science, University of Iowa, Iowa City, Iowa, United States
| | - Junfeng Guo
- Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States
- Department of Radiology, University of Iowa, Iowa City, Iowa, United States
| | - Prashant Nagpal
- Department of Radiology, University of Iowa, Iowa City, Iowa, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, United States
| | - Thomas M Peters
- Department of Occupational and Environmental Health, University of Iowa, Iowa City, Iowa, United States
| | - Peter S Thorne
- Department of Occupational and Environmental Health, University of Iowa, Iowa City, Iowa, United States
| | - Alejandro P Comellas
- Department of Internal Medicine, University of Iowa, Iowa City, Iowa, United States
| | - Eric A Hoffman
- Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States
- Department of Internal Medicine, University of Iowa, Iowa City, Iowa, United States
- Department of Radiology, University of Iowa, Iowa City, Iowa, United States
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Fortis S, Quibrera PM, Comellas AP, Bhatt SP, Tashkin DP, Hoffman EA, Criner GJ, Han MK, Barr RG, Arjomandi M, Dransfield MB, Peters SP, Dolezal BA, Kim V, Putcha N, Rennard SI, Paine R, Kanner RE, Curtis JL, Bowler RP, Martinez FJ, Hansel NN, Krishnan JA, Woodruff PG, Barjaktarevic IZ, Couper D, Anderson WH, Cooper CB. Bronchodilator Responsiveness in Tobacco-Exposed People With or Without COPD. Chest 2023; 163:502-514. [PMID: 36395858 PMCID: PMC9993341 DOI: 10.1016/j.chest.2022.11.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 11/04/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Bronchodilator responsiveness (BDR) in obstructive lung disease varies over time and may be associated with distinct clinical features. RESEARCH QUESTION Is consistent BDR over time (always present) differentially associated with obstructive lung disease features relative to inconsistent (sometimes present) or never (never present) BDR in tobacco-exposed people with or without COPD? STUDY DESIGN AND METHODS We retrospectively analyzed data from 2,269 tobacco-exposed participants in the Subpopulations and Intermediate Outcome Measures in COPD Study with or without COPD. We used various BDR definitions: change of ≥ 200 mL and ≥ 12% in FEV1 (FEV1-BDR), change in FVC (FVC-BDR), and change in in FEV1, FVC or both (ATS-BDR). Using generalized linear models adjusted for demographics, smoking history, FEV1 % predicted after bronchodilator administration, and number of visits that the participant completed, we assessed the association of BDR group: (1) consistent BDR, (2) inconsistent BDR, and (3) never BDR with asthma, CT scan features, blood eosinophil levels, and FEV1 decline in participants without COPD (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage 0) and the entire cohort (participants with or without COPD). RESULTS Both consistent and inconsistent ATS-BDR were associated with asthma history and greater small airways disease (%parametric response mapping functional small airways disease) relative to never ATS-BDR in participants with GOLD stage 0 disease and the entire cohort. We observed similar findings using FEV1-BDR and FVC-BDR definitions. Eosinophils did not vary consistently among BDR groups. Consistent BDR was associated with FEV1 decline over time relative to never BDR in the entire cohort. In participants with GOLD stage 0 disease, both the inconsistent ATS-BDR group (OR, 3.20; 95% CI, 2.21-4.66; P < .001) and consistent ATS-BDR group (OR, 9.48; 95% CI, 3.77-29.12; P < .001) were associated with progression to COPD relative to the never ATS-BDR group. INTERPRETATION Demonstration of BDR, even once, describes an obstructive lung disease phenotype with a history of asthma and greater small airways disease. Consistent demonstration of BDR indicated a high risk of lung function decline over time in the entire cohort and was associated with higher risk of progression to COPD in patients with GOLD stage 0 disease.
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Affiliation(s)
- Spyridon Fortis
- Center for Access & Delivery Research & Evaluation, Iowa City VA Health Care System, Iowa City, IA; Division of Pulmonary, Critical Care and Occupational Medicine, Department of Internal Medicine, University of Iowa Roy J. and Lucille A. Carver College of Medicine, Iowa City, IA.
| | - Pedro M Quibrera
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Alejandro P Comellas
- Division of Pulmonary, Critical Care and Occupational Medicine, Department of Internal Medicine, University of Iowa Roy J. and Lucille A. Carver College of Medicine, Iowa City, IA
| | - Surya P Bhatt
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham VA Medical Center, Birmingham, AL
| | - Donald P Tashkin
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA
| | - Eric A Hoffman
- Departments of Radiology, Biomedical Engineering and Medicine, University of Iowa, Iowa City, IA
| | - Gerard J Criner
- Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine at Temple University, Philadelphia, PA
| | - MeiLan K Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI
| | - R Graham Barr
- Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY
| | - Mehrdad Arjomandi
- Department of Medicine, University of California, San Francisco, CA; San Francisco Veterans Affairs Healthcare System, San Francisco, CA
| | - Mark B Dransfield
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham VA Medical Center, Birmingham, AL; Division of Pulmonary and Critical Care Medicine, Birmingham VA Medical Center, Birmingham, AL
| | - Stephen P Peters
- Section on Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Brett A Dolezal
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA
| | - Victor Kim
- Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine at Temple University, Philadelphia, PA
| | - Nirupama Putcha
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD
| | - Stephen I Rennard
- Division of Pulmonary and Critical Care Medicine, University of Nebraska Medical Center, Omaha, NE
| | - Robert Paine
- Division of Respiratory, Critical Care and Occupational Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, UT
| | - Richard E Kanner
- Division of Respiratory, Critical Care and Occupational Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, UT
| | - Jeffrey L Curtis
- Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI; Medicine Service, VA Ann Arbor Healthcare System, Ann Arbor, MI
| | - Russell P Bowler
- Department of Medicine, National Jewish Medical and Research Center, Denver, CO
| | - Fernando J Martinez
- Departments of Medicine and Genetic Medicine, Weill Cornell Medicine, New York, NY
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD
| | - Jerry A Krishnan
- Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Illinois at Chicago, Chicago, IL
| | | | - Igor Z Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA
| | - David Couper
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Wayne H Anderson
- Division of Pulmonary and Critical Care Medicine, Marsico Lung Institute, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Christopher B Cooper
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at the University of California, Los Angeles, CA
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Tattersall MC, Lee KE, Tsuchiya N, Osman F, Korcarz CE, Hansen KM, Peters MC, Fahy JV, Longhurst CA, Dunican E, Wentzel SE, Leader JK, Israel E, Levy BD, Castro M, Erzurum SC, Lempel J, Moore WC, Bleecker ER, Phillips BR, Mauger DT, Hoffman EA, Fain SB, Reeder SB, Sorkness RL, Jarjour NN, Denlinger LC, Schiebler ML. Skeletal Muscle Adiposity and Lung Function Trajectory in the Severe Asthma Research Program. Am J Respir Crit Care Med 2023; 207:475-484. [PMID: 36194556 PMCID: PMC9940151 DOI: 10.1164/rccm.202203-0597oc] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 10/04/2022] [Indexed: 01/05/2023] Open
Abstract
Rationale: Extrapulmonary manifestations of asthma, including fatty infiltration in tissues, may reflect systemic inflammation and influence lung function and disease severity. Objectives: To determine if skeletal muscle adiposity predicts lung function trajectory in asthma. Methods: Adult SARP III (Severe Asthma Research Program III) participants with baseline computed tomography imaging and longitudinal postbronchodilator FEV1% predicted (median follow-up 5 years [1,132 person-years]) were evaluated. The mean of left and right paraspinous muscle density (PSMD) at the 12th thoracic vertebral body was calculated (Hounsfield units [HU]). Lower PSMD reflects higher muscle adiposity. We derived PSMD reference ranges from healthy control subjects without asthma. A linear multivariable mixed-effects model was constructed to evaluate associations of baseline PSMD and lung function trajectory stratified by sex. Measurements and Main Results: Participants included 219 with asthma (67% women; mean [SD] body mass index, 32.3 [8.8] kg/m2) and 37 control subjects (51% women; mean [SD] body mass index, 26.3 [4.7] kg/m2). Participants with asthma had lower adjusted PSMD than control subjects (42.2 vs. 55.8 HU; P < 0.001). In adjusted models, PSMD predicted lung function trajectory in women with asthma (β = -0.47 Δ slope per 10-HU decrease; P = 0.03) but not men (β = 0.11 Δ slope per 10-HU decrease; P = 0.77). The highest PSMD tertile predicted a 2.9% improvement whereas the lowest tertile predicted a 1.8% decline in FEV1% predicted among women with asthma over 5 years. Conclusions: Participants with asthma have lower PSMD, reflecting greater muscle fat infiltration. Baseline PSMD predicted lung function decline among women with asthma but not men. These data support an important role of metabolic dysfunction in lung function decline.
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Affiliation(s)
| | | | - Nanae Tsuchiya
- Division of Cardiothoracic Imaging, Department of Radiology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin
- Department of Radiology, School of Medicine, University of the Ryukyus, Nishihara, Japan
| | | | | | | | - Michael C. Peters
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, San Francisco, California
| | - John V. Fahy
- Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Francisco, San Francisco, California
| | | | - Eleanor Dunican
- Department of Medicine, School of Medicine, University College Dublin, Dublin, Ireland
- St. Vincent’s Hospital Elm Park, Dublin, Ireland
| | - Sally E. Wentzel
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, and
| | - Joseph K. Leader
- Department of Radiology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Elliot Israel
- Division of Pulmonary and Critical Care and
- Division of Allergy and Immunology, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | | | - Mario Castro
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Kansas Medical Center, Kansas City, Kansas
| | | | - Jason Lempel
- Department of Radiology, Cleveland Clinic Foundation, Cleveland, Ohio
| | - Wendy C. Moore
- Section of Pulmonary, Critical Care, Allergy and Immunologic Diseases, Department of Internal Medicine, School of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Eugene R. Bleecker
- Division of Genetics and
- Division of Pharmacokinetics, Department of Medicine, College of Medicine, University of Arizona, Tucson, Arizona
| | - Brenda R. Phillips
- Department of Public Health Sciences, College of Medicine, Pennsylvania State University, Hershey, Pennsylvania; and
| | - David T. Mauger
- Department of Public Health Sciences, College of Medicine, Pennsylvania State University, Hershey, Pennsylvania; and
| | - Eric A. Hoffman
- Department of Biomedical Engineering
- Department of Radiology, and
- Department of Medicine, Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | | | | | | | - Nizar N. Jarjour
- Division of Pulmonary Medicine and Critical Care
- Department of Medicine
| | | | - Mark L. Schiebler
- Division of Cardiothoracic Imaging, Department of Radiology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, Wisconsin
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Chaudhary MFA, Hoffman EA, Guo J, Comellas AP, Newell JD, Nagpal P, Fortis S, Christensen GE, Gerard SE, Pan Y, Wang D, Abtin F, Barjaktarevic IZ, Barr RG, Bhatt SP, Bodduluri S, Cooper CB, Gravens-Mueller L, Han MK, Kazerooni EA, Martinez FJ, Menchaca MG, Ortega VE, Iii RP, Schroeder JD, Woodruff PG, Reinhardt JM. Predicting severe chronic obstructive pulmonary disease exacerbations using quantitative CT: a retrospective model development and external validation study. Lancet Digit Health 2023; 5:e83-e92. [PMID: 36707189 PMCID: PMC9896720 DOI: 10.1016/s2589-7500(22)00232-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 09/30/2022] [Accepted: 11/11/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND Quantitative CT is becoming increasingly common for the characterisation of lung disease; however, its added potential as a clinical tool for predicting severe exacerbations remains understudied. We aimed to develop and validate quantitative CT-based models for predicting severe chronic obstructive pulmonary disease (COPD) exacerbations. METHODS We analysed the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS) cohort, a multicentre study done at 12 clinical sites across the USA, of individuals aged 40-80 years from four strata: individuals who never smoked, individuals who smoked but had normal spirometry, individuals who smoked and had mild to moderate COPD, and individuals who smoked and had severe COPD. We used 3-year follow-up data to develop logistic regression classifiers for predicting severe exacerbations. Predictors included age, sex, race, BMI, pulmonary function, exacerbation history, smoking status, respiratory quality of life, and CT-based measures of density gradient texture and airway structure. We externally validated our models in a subset from the Genetic Epidemiology of COPD (COPDGene) cohort. Discriminative model performance was assessed using the area under the receiver operating characteristic curve (AUC), which was also compared with other predictors, including exacerbation history and the BMI, airflow obstruction, dyspnoea, and exercise capacity (BODE) index. We evaluated model calibration using calibration plots and Brier scores. FINDINGS Participants in SPIROMICS were enrolled between Nov 12, 2010, and July 31, 2015. Participants in COPDGene were enrolled between Jan 10, 2008, and April 15, 2011. We included 1956 participants from the SPIROMICS cohort who had complete 3-year follow-up data: the mean age of the cohort was 63·1 years (SD 9·2) and 1017 (52%) were men and 939 (48%) were women. Among the 1956 participants, 434 (22%) had a history of at least one severe exacerbation. For the CT-based models, the AUC was 0·854 (95% CI 0·852-0·855) for at least one severe exacerbation within 3 years and 0·931 (0·930-0·933) for consistent exacerbations (defined as ≥1 acute episode in each of the 3 years). Models were well calibrated with low Brier scores (0·121 for at least one severe exacerbation; 0·039 for consistent exacerbations). For the prediction of at least one severe event during 3-year follow-up, AUCs were significantly higher with CT biomarkers (0·854 [0·852-0·855]) than exacerbation history (0·823 [0·822-0·825]) and BODE index 0·812 [0·811-0·814]). 6965 participants were included in the external validation cohort, with a mean age of 60·5 years (SD 8·9). In this cohort, AUC for at least one severe exacerbation was 0·768 (0·767-0·769; Brier score 0·088). INTERPRETATION CT-based prediction models can be used for identification of patients with COPD who are at high risk of severe exacerbations. The newly identified CT biomarkers could potentially enable investigation into underlying disease mechanisms responsible for exacerbations. FUNDING National Institutes of Health and the National Heart, Lung, and Blood Institute.
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Affiliation(s)
- Muhammad F A Chaudhary
- The Roy J Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, IA, USA; Department of Internal Medicine, Division of Pulmonary, Critical Care and Occupational Medicine, University of Iowa, Iowa City, IA, USA; The Roy J Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Junfeng Guo
- Department of Radiology, University of Iowa, Iowa City, IA, USA; The Roy J Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Alejandro P Comellas
- Department of Internal Medicine, Division of Pulmonary, Critical Care and Occupational Medicine, University of Iowa, Iowa City, IA, USA
| | - John D Newell
- Department of Radiology, University of Iowa, Iowa City, IA, USA; The Roy J Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Prashant Nagpal
- Department of Radiology, University of Iowa, Iowa City, IA, USA; Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Spyridon Fortis
- Department of Internal Medicine, Division of Pulmonary, Critical Care and Occupational Medicine, University of Iowa, Iowa City, IA, USA
| | - Gary E Christensen
- Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA; Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
| | - Sarah E Gerard
- Department of Radiology, University of Iowa, Iowa City, IA, USA
| | - Yue Pan
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
| | - Di Wang
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, USA
| | - Fereidoun Abtin
- Department of Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Igor Z Barjaktarevic
- Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R Graham Barr
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Surya P Bhatt
- UAB Lung Imaging Lab, Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Sandeep Bodduluri
- UAB Lung Imaging Lab, Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Christopher B Cooper
- Department of Physiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Lisa Gravens-Mueller
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - MeiLan K Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Ella A Kazerooni
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Fernando J Martinez
- Division of Pulmonary Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Martha G Menchaca
- Department of Radiology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Victor E Ortega
- Department of Internal Medicine, Division of Respiratory Medicine, Mayo Clinic, Scottsdale, AZ, USA
| | - Robert Paine Iii
- Division of Respiratory, Critical Care and Occupational Pulmonary Medicine, University of Utah, Salt Lake City, UT, USA
| | - Joyce D Schroeder
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Prescott G Woodruff
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Joseph M Reinhardt
- Department of Radiology, University of Iowa, Iowa City, IA, USA; The Roy J Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA.
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Schiebler ML, Tsuchiya N, Hahn A, Fain S, Denlinger L, Jarjour N, Hoffman EA. Imaging Regional Airway Involvement of Asthma: Heterogeneity in Ventilation, Mucus Plugs and Remodeling. Adv Exp Med Biol 2023; 1426:163-184. [PMID: 37464121 DOI: 10.1007/978-3-031-32259-4_8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
The imaging of asthma using chest computed tomography (CT) is well-established (Jarjour et al., Am J Respir Crit Care Med 185(4):356-62, 2012; Castro et al., J Allergy Clin Immunol 128:467-78, 2011). Moreover, recent advances in functional imaging of the lungs with advanced computer analysis of both CT and magnetic resonance images (MRI) of the lungs have begun to play a role in quantifying regional obstruction. Specifically, quantitative measurements of the airways for bronchial wall thickening, luminal narrowing and distortion, the amount of mucus plugging, parenchymal density, and ventilation defects that could contribute to the patient's disease course are instructive for the entire care team. In this chapter, we will review common imaging methods and findings that relate to the heterogeneity of asthma. This information can help to guide treatment decisions. We will discuss mucous plugging, quantitative assessment of bronchial wall thickening, delta lumen phenomenon, parenchymal low-density lung on CT, and ventilation defect percentage on MRI as metrics for assessing regional ventilatory dysfunction.
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Affiliation(s)
- Mark L Schiebler
- Cardiothoracic imaging, Department of Radiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA.
| | - Nanae Tsuchiya
- Department of Radiology, School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Andrew Hahn
- Department of Radiology, University of Iowa, Iowa City, IA, USA
| | - Sean Fain
- Department of Radiology, Biomedical Engineering, and Human Physiology, University of Iowa, Iowa City, IA, USA
| | - Loren Denlinger
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Nizar Jarjour
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Eric A Hoffman
- Departments of Radiology, Medicine and Biomedical Engineering, University of Iowa, Iowa City, IA, USA
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Kim JS, Kim J, Yin X, Hiura GT, Anderson MR, Hoffman EA, Raghu G, Noth I, Manichaikul A, Rich SS, Smith BM, Podolanczuk AJ, Garcia CK, Barr RG, Prince MR, Oelsner EC. Associations of hiatus hernia with CT-based interstitial lung changes: the MESA Lung Study. Eur Respir J 2023; 61:2103173. [PMID: 35777776 PMCID: PMC10203882 DOI: 10.1183/13993003.03173-2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 06/02/2022] [Indexed: 02/01/2023]
Abstract
BACKGROUND Hiatus hernia (HH) is prevalent in adults with pulmonary fibrosis. We hypothesised that HH would be associated with markers of lung inflammation and fibrosis among community-dwelling adults and stronger among MUC5B (rs35705950) risk allele carriers. METHODS In the Multi-Ethnic Study of Atherosclerosis, HH was assessed from cardiac and full-lung computed tomography (CT) scans performed at Exam 1 (2000-2002, n=3342) and Exam 5 (2010-2012, n=3091), respectively. Percentage of high attenuation areas (HAAs; percentage of voxels with attenuation between -600 and -250 HU) was measured from cardiac and lung scans. Interstitial lung abnormalities (ILAs) were examined from Exam 5 scans (n=2380). Regression models were used to examine the associations of HH with HAAs, ILAs and serum matrix metalloproteinase-7 (MMP-7), and adjusted for age, sex, race/ethnicity, educational attainment, smoking, height, weight and scanner parameters for HAA analysis. RESULTS HH detected from Exam 5 scans was associated with a mean percentage difference in HAAs of 2.23% (95% CI 0.57-3.93%) and an increase of 0.48% (95% CI 0.07-0.89%) per year, particularly in MUC5B risk allele carriers (p-value for interaction=0.02). HH was associated with ILAs among those <80 years of age (OR for ILAs 1.78, 95% CI 1.14-2.80) and higher serum MMP-7 level among smokers (p-value for smoking interaction=0.04). CONCLUSIONS HH was associated with more HAAs over time, particularly among MUC5B risk allele carriers, and ILAs in younger adults, and may be a risk factor in the early stages of interstitial lung disease.
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Affiliation(s)
- John S Kim
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Jinhye Kim
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
- Department of Radiology, Westchester Medical Center, Valhalla, NY, USA
| | - Xiaorui Yin
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Grant T Hiura
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Eric A Hoffman
- Department of Radiology, Carver School of Medicine, University of Iowa, Iowa City, IA, USA
| | - Ganesh Raghu
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Imre Noth
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Ani Manichaikul
- Center for Public Health Genomics and Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Stephen S Rich
- Center for Public Health Genomics and Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Benjamin M Smith
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Medicine, McGill University, Montreal, QC, Canada
| | - Anna J Podolanczuk
- Division of Pulmonary and Critical Care, Weill Cornell Medical College, New York, NY, USA
| | - Christine Kim Garcia
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Martin R Prince
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
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Nadeem SA, Comellas AP, Hoffman EA, Saha PK. Airway Detection in COPD at Low-Dose CT Using Deep Learning and Multiparametric Freeze and Grow. Radiol Cardiothorac Imaging 2022; 4:e210311. [PMID: 36601453 PMCID: PMC9806731 DOI: 10.1148/ryct.210311] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 09/27/2022] [Accepted: 10/27/2022] [Indexed: 06/17/2023]
Abstract
PURPOSE To present and validate a fully automated airway detection method at low-dose CT in patients with chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS In this retrospective study, deep learning (DL) and freeze-and-grow (FG) methods were optimized and applied to automatically detect airways at low-dose CT. Four data sets were used: two data sets consisting of matching standard- and low-dose CT scans from the Genetic Epidemiology of COPD (COPDGene) phase II (2014-2017) cohort (n = 2 × 236; mean age ± SD, 70 years ± 9; 123 women); one data set consisting of low-dose CT scans from the COPDGene phase III (2018-2020) cohort (n = 335; mean age ± SD, 73 years ± 8; 173 women); and one data set consisting of low-dose, anonymized CT scans from the 2003 Dutch-Belgian Randomized Lung Cancer Screening trial (n = 55) acquired by using different CT scanners. Performance measures for different methods were computed and compared by using the Wilcoxon signed rank test. RESULTS At low-dose CT, 56 294 of 62 480 (90.1%) airways of the reference total airway count (TAC) and 32 109 of 37 864 (84.8%) airways of the peripheral TAC (TACp), detected at standard-dose CT, were detected. Significant losses (P < .001) of 14 526 of 76 453 (19.0%) airways and 884 of 6908 (12.8%) airways in the TAC and 12 256 of 43 462 (28.2%) airways and 699 of 3882 (18.0%) airways in the TACp were observed, respectively, for the multiprotocol and multiscanner data without retraining. When using the automated low-dose CT method, TAC values of 347, 342, 323, and 266 and TACp values of 205, 202, 289, and 141 were observed for those who have never smoked and participants at Global Initiative for Chronic Obstructive Lung Disease stages 0, 1, and 2, respectively, which were superior to the respective values previously reported for matching groups when using a semiautomated method at standard-dose CT. CONCLUSION A low-cost, automated CT-based airway detection method was suitable for investigation of airway phenotypes at low-dose CT.Keywords: Airway, Airway Count, Airway Detection, Chronic Obstructive Pulmonary Disease, CT, Deep Learning, Generalizability, Low-Dose CT, Segmentation, Thorax, LungClinical trial registration no. NCT00608764 Supplemental material is available for this article. © RSNA, 2022.
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43
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Bhatt SP, Bodduluri S, Nakhmani A, Kim YI, Reinhardt JM, Hoffman EA, Motahari A, Wilson CG, Humphries SM, Regan EA, DeMeo DL. Sex Differences in Airways at Chest CT: Results from the COPDGene Cohort. Radiology 2022; 305:699-708. [PMID: 35916677 PMCID: PMC9713451 DOI: 10.1148/radiol.212985] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 05/10/2022] [Accepted: 05/24/2022] [Indexed: 11/11/2022]
Abstract
Background The prevalence of chronic obstructive pulmonary disease (COPD) in women is fast approaching that in men, and women experience greater symptom burden. Although sex differences in emphysema have been reported, differences in airways have not been systematically characterized. Purpose To evaluate whether structural differences in airways may underlie some of the sex differences in COPD prevalence and clinical outcomes. Materials and Methods In a secondary analyses of a multicenter study of never-, current-, and former-smokers enrolled from January 2008 to June 2011 and followed up longitudinally until November 2020, airway disease on CT images was quantified using seven metrics: airway wall thickness, wall area percent, and square root of the wall thickness of a hypothetical airway with internal perimeter of 10 mm (referred to as Pi10) for airway wall; and lumen diameter, airway volume, total airway count, and airway fractal dimension for airway lumen. Least-squares mean values for each airway metric were calculated and adjusted for age, height, ethnicity, body mass index, pack-years of smoking, current smoking status, total lung capacity, display field of view, and scanner type. In ever-smokers, associations were tested between each airway metric and postbronchodilator forced expiratory volume in 1 second (FEV1)-to-forced vital capacity (FVC) ratio, modified Medical Research Council dyspnea scale, St George's Respiratory Questionnaire score, and 6-minute walk distance. Multivariable Cox proportional hazards models were created to evaluate the sex-specific association between each airway metric and mortality. Results In never-smokers (n = 420), men had thicker airway walls than women as quantified on CT images for segmental airway wall area percentage (least-squares mean, 47.68 ± 0.61 [standard error] vs 45.78 ± 0.55; difference, -1.90; P = .02), whereas airway lumen dimensions were lower in women than men after accounting for height and total lung capacity (segmental lumen diameter, 8.05 mm ± 0.14 vs 9.05 mm ± 0.16; difference, -1.00 mm; P < .001). In ever-smokers (n = 9363), men had greater segmental airway wall area percentage (least-squares mean, 52.19 ± 0.16 vs 48.89 ± 0.18; difference, -3.30; P < .001), whereas women had narrower segmental lumen diameter (7.80 mm ± 0.05 vs 8.69 mm ± 0.04; difference, -0.89; P < .001). A unit change in each of the airway metrics (higher wall or lower lumen measure) resulted in lower FEV1-to-FVC ratio, more dyspnea, poorer respiratory quality of life, lower 6-minute walk distance, and worse survival in women compared with men (all P < .01). Conclusion Airway lumen sizes quantified at chest CT were smaller in women than in men after accounting for height and lung size, and these lower baseline values in women conferred lower reserves against respiratory morbidity and mortality for equivalent changes compared with men. © RSNA, 2022 Online supplemental material is available for this article.
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Affiliation(s)
- Surya P. Bhatt
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Sandeep Bodduluri
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Arie Nakhmani
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Young-il Kim
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Joseph M. Reinhardt
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Eric A. Hoffman
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Amin Motahari
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Carla G. Wilson
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Stephen M. Humphries
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Elizabeth A. Regan
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
| | - Dawn L. DeMeo
- From the UAB Lung Imaging Lab (S.P.B., S.B., A.N.), UAB Lung Health
Center (S.P.B., S.B.), Division of Pulmonary, Allergy and Critical Care Medicine
(S.P.B., S.B.), Department of Electrical and Computer Engineering (A.N.), and
Division of Preventive Medicine (Y.I.K.), University of Alabama at Birmingham,
1720 2nd Ave S, THT 422, Birmingham, AL 35294; Roy J. Carver Department
of Biomedical Engineering (J.M.R.) and Department of Radiology (E.A.H., A.M.),
University of Iowa, Iowa City, Iowa; Departments of Biostatistics and
Bioinformatics (C.G.W.), Radiology (S.M.H.), and Medicine (E.A.R.), National
Jewish Health, Denver, Colo; and Channing Division of Network Medicine and the
Division of Pulmonary and Critical Care Medicine, Brigham and Women's
Hospital, Harvard Medical School, Boston, Mass (D.L.D.)
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Shankar SS, Felice N, Hoffman EA, Atha J, Sieren JC, Samei E, Abadi E. Task-based validation and application of a scanner-specific CT simulator using an anthropomorphic phantom. Med Phys 2022; 49:7447-7457. [PMID: 36097259 PMCID: PMC9792443 DOI: 10.1002/mp.15967] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 08/23/2022] [Accepted: 08/24/2022] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Quantitative analysis of computed tomography (CT) images traditionally utilizes real patient data that can pose challenges with replicability, efficiency, and radiation exposure. Instead, virtual imaging trials (VITs) can overcome these hurdles through computer simulations of models of patients and imaging systems. DukeSim is a scanner-specific CT imaging simulator that has previously been validated with simple cylindrical phantoms, but not with anthropomorphic conditions and clinically relevant measurements. PURPOSE To validate a scanner-specific CT simulator (DukeSim) for the assessment of lung imaging biomarkers under clinically relevant conditions across multiple scanners using an anthropomorphic chest phantom, and to demonstrate the utility of virtual trials by studying the effects or radiation dose and reconstruction kernels on the lung imaging quantifications. METHODS An anthropomorphic chest phantom with customized tube inserts was imaged with two commercial scanners (Siemens Force and Siemens Flash) at 28 dose and reconstruction conditions. A computational version of the chest phantom was used with a scanner-specific CT simulator (DukeSim) to simulate virtual images corresponding to the settings of the real acquisitions. Lung imaging biomarkers were computed from both real and simulated CT images and quantitatively compared across all imaging conditions. The VIT framework was further utilized to investigate the effects of radiation dose (20-300 mAs) and reconstruction settings (Qr32f, Qr40f, and Qr69f reconstruction kernels using ADMIRE strength 3) on the accuracy of lung imaging biomarkers, compared against the ground-truth values modeled in the computational chest phantom. RESULTS The simulated CT images matched closely the real images for both scanners and all imaging conditions qualitatively and quantitatively, with the average biomarker percent error of 3.51% (range 0.002%-18.91%). The VIT study showed that sharper reconstruction kernels had lower accuracy with errors in mean lung HU of 84-94 HU, lung volume of 797-3785 cm3 , and lung mass of -800 to 1751 g. Lower tube currents had the lower accuracy with errors in mean lung HU of 6-84 HU, lung volume of 66-3785 cm3 , and lung mass of 170-1751 g. Other imaging biomarkers were consistent under the studied reconstruction settings and tube currents. CONCLUSION We comprehensively evaluated the realism of DukeSim in an anthropomorphic setup across a diverse range of imaging conditions. This study paves the way toward utilizing VITs more reliably for conducting medical imaging experiments that are not practical using actual patient images.
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Affiliation(s)
- Sachin S. Shankar
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University
- Department of Electrical and Computer Engineering, Duke University
| | - Nicholas Felice
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University
| | - Eric A. Hoffman
- Department of Radiology, University of Iowa
- Department of Biomedical Engineering, University of Iowa
| | | | - Jessica C. Sieren
- Department of Radiology, University of Iowa
- Department of Biomedical Engineering, University of Iowa
| | - Ehsan Samei
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University
- Department of Electrical and Computer Engineering, Duke University
| | - Ehsan Abadi
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University
- Department of Electrical and Computer Engineering, Duke University
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Pan Y, Wang D, Chaudhary MFA, Shao W, Gerard SE, Durumeric OC, Bhatt SP, Barr RG, Hoffman EA, Reinhardt JM, Christensen GE. Robust Measures of Image-Registration-Derived Lung Biomechanics in SPIROMICS. J Imaging 2022; 8:309. [PMID: 36422058 PMCID: PMC9693030 DOI: 10.3390/jimaging8110309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/03/2022] [Accepted: 11/08/2022] [Indexed: 11/18/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is an umbrella term used to define a collection of inflammatory lung diseases that cause airflow obstruction and severe damage to the lung parenchyma. This study investigated the robustness of image-registration-based local biomechanical properties of the lung in individuals with COPD as a function of Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage. Image registration was used to estimate the pointwise correspondences between the inspiration (total lung capacity) and expiration (residual volume) computed tomography (CT) images of the lung for each subject. In total, three biomechanical measures were computed from the correspondence map: the Jacobian determinant; the anisotropic deformation index (ADI); and the slab-rod index (SRI). CT scans from 245 subjects with varying GOLD stages were analyzed from the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS). Results show monotonic increasing or decreasing trends in the three biomechanical measures as a function of GOLD stage for the entire lung and on a lobe-by-lobe basis. Furthermore, these trends held across all five image registration algorithms. The consistency of the five image registration algorithms on a per individual basis is shown using Bland-Altman plots.
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Affiliation(s)
- Yue Pan
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Di Wang
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Muhammad F. A. Chaudhary
- The Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Wei Shao
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Sarah E. Gerard
- The Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Oguz C. Durumeric
- Department of Mathematics, University of Iowa, Iowa City, IA 52242, USA
| | - Surya P. Bhatt
- UAB Lung Imaging Core, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - R. Graham Barr
- Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY 10032, USA
| | - Eric A. Hoffman
- The Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Radiology, University of Iowa, Iowa City, IA 52242, USA
| | - Joseph M. Reinhardt
- The Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Radiology, University of Iowa, Iowa City, IA 52242, USA
| | - Gary E. Christensen
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
- Department of Radiology, University of Iowa, Iowa City, IA 52242, USA
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46
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Tejwani V, Woo H, Liu C, Tillery AK, Gassett AJ, Kanner RE, Hoffman EA, Martinez FJ, Woodruff PG, Barr RG, Fawzy A, Koehler K, Curtis JL, Freeman CM, Cooper CB, Comellas AP, Pirozzi C, Paine R, Tashkin D, Krishnan JA, Sack C, Putcha N, Paulin LM, Zusman M, Kaufman JD, Alexis NE, Hansel NN. Black carbon content in airway macrophages is associated with increased severe exacerbations and worse COPD morbidity in SPIROMICS. Respir Res 2022; 23:310. [PMID: 36376879 PMCID: PMC9664618 DOI: 10.1186/s12931-022-02225-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 10/19/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Airway macrophages (AM), crucial for the immune response in chronic obstructive pulmonary disease (COPD), are exposed to environmental particulate matter (PM), which they retain in their cytoplasm as black carbon (BC). However, whether AM BC accurately reflects environmental PM2.5 exposure, and can serve as a biomarker of COPD outcomes, is unknown. METHODS We analyzed induced sputum from participants at 7 of 12 sites SPIROMICS sites for AM BC content, which we related to exposures and to lung function and respiratory outcomes. Models were adjusted for batch (first vs. second), age, race (white vs. non-white), income (<$35,000, $35,000~$74,999, ≥$75,000, decline to answer), BMI, and use of long-acting beta-agonist/long-acting muscarinic antagonists, with sensitivity analysis performed with inclusion of urinary cotinine and lung function as covariates. RESULTS Of 324 participants, 143 were current smokers and 201 had spirometric-confirmed COPD. Modeled indoor fine (< 2.5 μm in aerodynamic diameter) particulate matter (PM2.5) and urinary cotinine were associated with higher AM BC. Other assessed indoor and ambient pollutant exposures were not associated with higher AM BC. Higher AM BC was associated with worse lung function and odds of severe exacerbation, as well as worse functional status, respiratory symptoms and quality of life. CONCLUSION Indoor PM2.5 and cigarette smoke exposure may lead to increased AM BC deposition. Black carbon content in AMs is associated with worse COPD morbidity in current and former smokers, which remained after sensitivity analysis adjusting for cigarette smoke burden. Airway macrophage BC, which may alter macrophage function, could serve as a predictor of experiencing worse respiratory symptoms and impaired lung function.
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Affiliation(s)
- Vickram Tejwani
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD, USA.
- Respiratory Institute, Cleveland Clinic, 9500 Euclid Avenue, A90, 44195, Cleveland, OH, USA.
| | - Han Woo
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Chen Liu
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Anna K Tillery
- Center for Environmental Medicine, Asthma, and Lung Biology, Division of Allergy and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda J Gassett
- Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, WA, USA
| | - Richard E Kanner
- Division of Respiratory, Critical Care and Occupational Medicine, University of Utah, Salt Lake City, UT, USA
| | - Eric A Hoffman
- Department of Radiology, Medicine and Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Fernando J Martinez
- Division of Pulmonology and Critical Care Medicine, Weill-Cornell Medical Center, Cornell University, New York, NY, USA
| | - Prescott G Woodruff
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California San Francisco, San Francisco, CA, USA
| | - R Graham Barr
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York, USA
| | - Ashraf Fawzy
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Kirsten Koehler
- Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jeffrey L Curtis
- Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA
- Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Christine M Freeman
- Pulmonary and Critical Care Medicine Division, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI, USA
- Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Christopher B Cooper
- Division of Pulmonary and Critical Care Medicine, University of California Los Angeles Medical Center, Los Angeles, CA, USA
| | - Alejandro P Comellas
- Division of Pulmonary, Critical Care, and Occupational Medicine, College of Medicine, University of Iowa, Iowa City, IA, USA
| | | | - Robert Paine
- University of Utah Hospital, Salt Lake City, UT, USA
| | - Donald Tashkin
- Division of Pulmonary and Critical Care Medicine, University of California Los Angeles Medical Center, Los Angeles, CA, USA
| | - Jerry A Krishnan
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Coralynn Sack
- Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, WA, USA
| | - Nirupama Putcha
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Laura M Paulin
- Pulmonary/Critical Care, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA
| | - Marina Zusman
- Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, WA, USA
| | - Joel D Kaufman
- Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, WA, USA
| | - Neil E Alexis
- Center for Environmental Medicine, Asthma, and Lung Biology, Division of Allergy and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD, USA
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Garg I, Vidholia A, Garg A, Singh S, Agahi A, Laroia A, Saboo SS, Comellas AP, Hoffman EA, Nagpal P. E-cigarette or vaping product use-associated lung injury: A review of clinico-radio-pathological characteristics. Respir Investig 2022; 60:738-749. [PMID: 35963780 DOI: 10.1016/j.resinv.2022.06.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 06/01/2022] [Accepted: 06/16/2022] [Indexed: 01/12/2023]
Abstract
Aggressive, albeit false marketing of electronic nicotine delivery systems (ENDS) or vaping devices as safer alternatives to cigarette smoking, combined with lack of regulations, has led to its mass adoption, especially among youth. A sudden increase in acute lung injuries was noted in 2019 which was linked to ENDS. It was termed by the Centers for Disease Control and Prevention (CDC) as electronic cigarette or vaping product use-associated lung injury (EVALI). Analysis of bronchoalveolar lavage fluid samples linked EVALI to vitamin E acetate (VEA), which is used as a diluting agent for marijuana oils. Patients with EVALI present with a combination of non-specific respiratory, gastrointestinal, and systemic symptoms. Laboratory results may show elevated inflammatory biomarkers. EVALI is a diagnosis of exclusion and must meet the following criteria: i) history of vaping within last 90 days, ii) abnormal chest imaging, iii) negative evaluation for infection, and iv) no other plausible diagnosis. A spectrum of computed tomography (CT) chest findings has been reported in EVALI, ranging from diffuse alveolar damage to organizing pneumonia, characterized by bilateral ground-glass opacities, consolidation, and septal thickening. A similar spectrum is seen on histopathology, characterized by lipid-laden alveolar macrophages, with varying degrees of infiltrative inflammatory cells and fibrin deposition. Early and accurate identification of the EVALI pattern can help optimize patient care. For example, in diffuse alveolar damage (DAD), a lower threshold for ventilation support and corticosteroid may improve outcomes. Here, we review the etiopathogenesis, clinical management, histopathology, and imaging features of EVALI.
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Affiliation(s)
- Ishan Garg
- Pathology, Arkana Laboratories, 10810 Executive Center Dr #100, Little Rock, AR 72211, USA
| | - Aditi Vidholia
- Department of Pathology, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Ankita Garg
- Department of Anesthesiology, Dr Ram Manohar Lohia Hospital & Post Graduate Institute of Medical Education and Research, Baba Kharak Singh Rd, Connaught Place, New Delhi 110001, India
| | - Shuchita Singh
- Shanti Hospital, Rajeev Nagar, Agra, Uttar Pradesh 282005, India
| | - Alireza Agahi
- Department of Pathology, Mayo Clinic, 201 1(st) St SW, Rochester, MN 55905, USA
| | - Archana Laroia
- Department of Radiology, University of Iowa Hospitals and Clinics, 200 Hawkins Dr, Iowa City, IA 52242, USA
| | - Sachin S Saboo
- Radiology, South Texas Radiology Group, San Antonio, TX 78230, USA
| | - Alejandro P Comellas
- Department of Internal Medicine, University of Iowa Carver College of Medicine, 375 Newton Rd, Iowa City, IA 52242, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa Hospitals and Clinics, 200 Hawkins Dr, Iowa City, IA 52242, USA; Department of Internal Medicine, University of Iowa Carver College of Medicine, 375 Newton Rd, Iowa City, IA 52242, USA; Roy J. Carver Department of Biomedical Engineering, University of Iowa College of Engineering, 375 Newton Rd, Iowa City, IA 52242, USA
| | - Prashant Nagpal
- Department of Radiology, University of Iowa Hospitals and Clinics, 200 Hawkins Dr, Iowa City, IA 52242, USA; Department of Radiology, University of Wisconsin-Madison, Madison, WI 53706, USA.
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48
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Li F, Zhang X, Comellas AP, Hoffman EA, Yang T, Lin CL. Contrastive learning and subtyping of post-COVID-19 lung computed tomography images. Front Physiol 2022; 13:999263. [PMID: 36304574 PMCID: PMC9593072 DOI: 10.3389/fphys.2022.999263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 09/27/2022] [Indexed: 11/30/2022] Open
Abstract
Patients who recovered from the novel coronavirus disease 2019 (COVID-19) may experience a range of long-term symptoms. Since the lung is the most common site of the infection, pulmonary sequelae may present persistently in COVID-19 survivors. To better understand the symptoms associated with impaired lung function in patients with post-COVID-19, we aimed to build a deep learning model which conducts two tasks: to differentiate post-COVID-19 from healthy subjects and to identify post-COVID-19 subtypes, based on the latent representations of lung computed tomography (CT) scans. CT scans of 140 post-COVID-19 subjects and 105 healthy controls were analyzed. A novel contrastive learning model was developed by introducing a lung volume transform to learn latent features of disease phenotypes from CT scans at inspiration and expiration of the same subjects. The model achieved 90% accuracy for the differentiation of the post-COVID-19 subjects from the healthy controls. Two clusters (C1 and C2) with distinct characteristics were identified among the post-COVID-19 subjects. C1 exhibited increased air-trapping caused by small airways disease (4.10%, p = 0.008) and diffusing capacity for carbon monoxide %predicted (DLCO %predicted, 101.95%, p < 0.001), while C2 had decreased lung volume (4.40L, p < 0.001) and increased ground glass opacity (GGO%, 15.85%, p < 0.001). The contrastive learning model is able to capture the latent features of two post-COVID-19 subtypes characterized by air-trapping due to small airways disease and airway-associated interstitial fibrotic-like patterns, respectively. The discovery of post-COVID-19 subtypes suggests the need for different managements and treatments of long-term sequelae of patients with post-COVID-19.
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Affiliation(s)
- Frank Li
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States
- IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, IA, United States
| | - Xuan Zhang
- IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, IA, United States
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA, United States
| | | | - Eric A. Hoffman
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States
- Department of Radiology, University of Iowa, Iowa City, IA, United States
| | - Tianbao Yang
- Department of Computer Science, University of Iowa, Iowa City, IA, United States
| | - Ching-Long Lin
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States
- IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, IA, United States
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA, United States
- Department of Radiology, University of Iowa, Iowa City, IA, United States
- *Correspondence: Ching-Long Lin,
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49
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Choi J, Chae KJ, Jin GY, Lin CL, Laroia AT, Hoffman EA, Lee CH. CT-based lung motion differences in patients with usual interstitial pneumonia and nonspecific interstitial pneumonia. Front Physiol 2022; 13:867473. [PMID: 36267579 PMCID: PMC9577177 DOI: 10.3389/fphys.2022.867473] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 08/19/2022] [Indexed: 01/28/2023] Open
Abstract
We applied quantitative CT image matching to assess the degree of motion in the idiopathic ILD such as usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). Twenty-one normal subjects and 42 idiopathic ILD (31 UIP and 11 NSIP) patients were retrospectively included. Inspiratory and expiratory CT images, reviewed by two experienced radiologists, were used to compute displacement vectors at local lung regions matched by image registration. Normalized three-dimensional and two-dimensional (dorsal-basal) displacements were computed at a sub-acinar scale. Displacements, volume changes, and tissue fractions in the whole lung and the lobes were compared between normal, UIP, and NSIP subjects. The dorsal-basal displacement in lower lobes was smaller in UIP patients than in NSIP or normal subjects (p = 0.03, p = 0.04). UIP and NSIP were not differentiated by volume changes in the whole lung or upper and lower lobes (p = 0.53, p = 0.12, p = 0.97), whereas the lower lobe air volume change was smaller in both UIP and NSIP than normal subjects (p = 0.02, p = 0.001). Regional expiratory tissue fractions and displacements showed positive correlations in normal and UIP subjects but not in NSIP subjects. In summary, lung motionography quantified by image registration-based lower lobe dorsal-basal displacement may be used to assess the degree of motion, reflecting limited motion due to fibrosis in the ILD such as UIP and NSIP.
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Affiliation(s)
- Jiwoong Choi
- Department of Internal Medicine, University of Kansas School of Medicine, Kansas City, KS, United States,Department of Bioengineering, University of Kansas, Lawrence, KS, United States,Department of Mechanical Engineering, University of Iowa, Iowa City, IA, United States
| | - Kum Ju Chae
- Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University and Medical School, Jeonju, South Korea
| | - Gong Yong Jin
- Department of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonbuk National University and Medical School, Jeonju, South Korea
| | - Ching-Long Lin
- Department of Mechanical Engineering, University of Iowa, Iowa City, IA, United States,IIIHR-Hydroscience & Engineering, University of Iowa, Iowa City, IA, United States,Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States
| | - Archana T. Laroia
- Department of Radiology, University of Iowa, University of Iowa Hospitals and Clinics, Iowa, IA, United States
| | - Eric A. Hoffman
- Department of Radiology, University of Iowa, University of Iowa Hospitals and Clinics, Iowa, IA, United States
| | - Chang Hyun Lee
- Department of Radiology, University of Iowa, University of Iowa Hospitals and Clinics, Iowa, IA, United States,Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, South Korea,*Correspondence: Chang Hyun Lee,
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Zhang X, Angelini ED, Haghpanah FS, Laine AF, Sun Y, Hiura GT, Dashnaw SM, Prince MR, Hoffman EA, Ambale-Venkatesh B, Lima JA, Wild JM, Hughes EW, Barr RG, Shen W. Quantification of lung ventilation defects on hyperpolarized MRI: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD study. Magn Reson Imaging 2022; 92:140-149. [PMID: 35777684 PMCID: PMC9957614 DOI: 10.1016/j.mri.2022.06.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/11/2022] [Accepted: 06/23/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE To develop an end-to-end deep learning (DL) framework to segment ventilation defects on pulmonary hyperpolarized MRI. MATERIALS AND METHODS The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease (COPD) study is a nested longitudinal case-control study in older smokers. Between February 2016 and July 2017, 56 participants (age, mean ± SD, 74 ± 8 years; 34 men) underwent same breath-hold proton (1H) and helium (3He) MRI, which were annotated for non-ventilated, hypo-ventilated, and normal-ventilated lungs. In this retrospective DL study, 820 1H and 3He slices from 42/56 (75%) participants were randomly selected for training, with the remaining 14/56 (25%) for test. Full lung masks were segmented using a traditional U-Net on 1H MRI and were imported into a cascaded U-Net, which were used to segment ventilation defects on 3He MRI. Models were trained with conventional data augmentation (DA) and generative adversarial networks (GAN)-DA. RESULTS Conventional-DA improved 1H and 3He MRI segmentation over the non-DA model (P = 0.007 to 0.03) but GAN-DA did not yield further improvement. The cascaded U-Net improved non-ventilated lung segmentation (P < 0.005). Dice similarity coefficients (DSC) between manually and DL-segmented full lung, non-ventilated, hypo-ventilated, and normal-ventilated regions were 0.965 ± 0.010, 0.840 ± 0.057, 0.715 ± 0.175, and 0.883 ± 0.060, respectively. We observed no statistically significant difference in DCSs between participants with and without COPD (P = 0.41, 0.06, and 0.18 for non-ventilated, hypo-ventilated, and normal-ventilated regions, respectively). CONCLUSION The proposed cascaded U-Net framework generated fully-automated segmentation of ventilation defects on 3He MRI among older smokers with and without COPD that is consistent with our reference method.
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Affiliation(s)
- Xuzhe Zhang
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Elsa D Angelini
- Department of Biomedical Engineering, Columbia University, New York, NY, USA; NIHR Imperial BRC, ITMAT Data Science Group, Department of Metabolism, Digestion and Reproduction, Imperial College, London, UK
| | - Fateme S Haghpanah
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
| | - Andrew F Laine
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Yanping Sun
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Grant T Hiura
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Stephen M Dashnaw
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Martin R Prince
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA; Department of Radiology, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, IA, USA; Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA; Department of Medicine, University of Iowa, Iowa City, IA, USA
| | | | - Joao A Lima
- School of Medicine, John Hopkins University, Baltimore, MD, USA
| | - Jim M Wild
- POLARIS, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Emlyn W Hughes
- Department of Physics, Columbia University, New York, NY, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA; Department of Epidemiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Wei Shen
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Columbia University Irving Medical Center, New York, NY, USA; Institute of Human Nutrition, Columbia University Irving Medical Center, New York, NY, USA; Columbia Magnetic Resonance Research Center (CMRRC), Columbia University, New York, NY, USA.
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