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Choi B, Liu GY, Sheng Q, Amancherla K, Perry A, Huang X, San José Estépar R, Ash SY, Guan W, Jacobs DR, Martinez FJ, Rosas IO, Bowler RP, Kropski JA, Banovich NE, Khan SS, San José Estépar R, Shah R, Thyagarajan B, Kalhan R, Washko GR. Proteomic Biomarkers of Quantitative Interstitial Abnormalities in COPDGene and CARDIA Lung Study. Am J Respir Crit Care Med 2024; 209:1091-1100. [PMID: 38285918 DOI: 10.1164/rccm.202307-1129oc] [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: 07/03/2023] [Accepted: 01/29/2024] [Indexed: 01/31/2024] Open
Abstract
Rationale: Quantitative interstitial abnormalities (QIAs) are early measures of lung injury automatically detected on chest computed tomography scans. QIAs are associated with impaired respiratory health and share features with advanced lung diseases, but their biological underpinnings are not well understood. Objectives: To identify novel protein biomarkers of QIAs using high-throughput plasma proteomic panels within two multicenter cohorts. Methods: We measured the plasma proteomics of 4,383 participants in an older, ever-smoker cohort (COPDGene [Genetic Epidemiology of Chronic Obstructive Pulmonary Disease]) and 2,925 participants in a younger population cohort (CARDIA [Coronary Artery Disease Risk in Young Adults]) using the SomaLogic SomaScan assays. We measured QIAs using a local density histogram method. We assessed the associations between proteomic biomarker concentrations and QIAs using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, and study center (Benjamini-Hochberg false discovery rate-corrected P ⩽ 0.05). Measurements and Main Results: In total, 852 proteins were significantly associated with QIAs in COPDGene and 185 in CARDIA. Of the 144 proteins that overlapped between COPDGene and CARDIA, all but one shared directionalities and magnitudes. These proteins were enriched for 49 Gene Ontology pathways, including biological processes in inflammatory response, cell adhesion, immune response, ERK1/2 regulation, and signaling; cellular components in extracellular regions; and molecular functions including calcium ion and heparin binding. Conclusions: We identified the proteomic biomarkers of QIAs in an older, smoking population with a higher prevalence of pulmonary disease and in a younger, healthier community cohort. These proteomics features may be markers of early precursors of advanced lung diseases.
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Affiliation(s)
- Bina Choi
- Division of Pulmonary and Critical Care Medicine, Department of Medicine
- Applied Chest Imaging Laboratory, and
| | - Gabrielle Y Liu
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of California Davis, Sacramento, California
| | | | | | | | - Xiaoning Huang
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Ruben San José Estépar
- Applied Chest Imaging Laboratory, and
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Samuel Y Ash
- Department of Critical Care, South Shore Hospital, South Weymouth, Massachusetts
| | | | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, and
| | - Fernando J Martinez
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Ivan O Rosas
- Section of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Russell P Bowler
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, National Jewish Health, Denver, Colorado
| | - Jonathan A Kropski
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Sadiya S Khan
- Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Raúl San José Estépar
- Applied Chest Imaging Laboratory, and
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts
| | | | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota
| | - Ravi Kalhan
- Division of Pulmonary and Critical Care Medicine and
| | - George R Washko
- Division of Pulmonary and Critical Care Medicine, Department of Medicine
- Applied Chest Imaging Laboratory, and
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Shiraishi Y, Tanabe N, Sakamoto R, Maetani T, Kaji S, Shima H, Terada S, Terada K, Ikezoe K, Tanizawa K, Oguma T, Handa T, Sato S, Muro S, Hirai T. Longitudinal assessment of interstitial lung abnormalities on CT in patients with COPD using artificial intelligence-based segmentation: a prospective observational study. BMC Pulm Med 2024; 24:200. [PMID: 38654252 PMCID: PMC11036664 DOI: 10.1186/s12890-024-03002-z] [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: 12/18/2023] [Accepted: 04/09/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Interstitial lung abnormalities (ILAs) on CT may affect the clinical outcomes in patients with chronic obstructive pulmonary disease (COPD), but their quantification remains unestablished. This study examined whether artificial intelligence (AI)-based segmentation could be applied to identify ILAs using two COPD cohorts. METHODS ILAs were diagnosed visually based on the Fleischner Society definition. Using an AI-based method, ground-glass opacities, reticulations, and honeycombing were segmented, and their volumes were summed to obtain the percentage ratio of interstitial lung disease-associated volume to total lung volume (ILDvol%). The optimal ILDvol% threshold for ILA detection was determined in cross-sectional data of the discovery and validation cohorts. The 5-year longitudinal changes in ILDvol% were calculated in discovery cohort patients who underwent baseline and follow-up CT scans. RESULTS ILAs were found in 32 (14%) and 15 (10%) patients with COPD in the discovery (n = 234) and validation (n = 153) cohorts, respectively. ILDvol% was higher in patients with ILAs than in those without ILA in both cohorts. The optimal ILDvol% threshold in the discovery cohort was 1.203%, and good sensitivity and specificity (93.3% and 76.3%) were confirmed in the validation cohort. 124 patients took follow-up CT scan during 5 ± 1 years. 8 out of 124 patients (7%) developed ILAs. In a multivariable model, an increase in ILDvol% was associated with ILA development after adjusting for age, sex, BMI, and smoking exposure. CONCLUSION AI-based CT quantification of ILDvol% may be a reproducible method for identifying and monitoring ILAs in patients with COPD.
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Affiliation(s)
- Yusuke Shiraishi
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Tanabe
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, 606-8507, Kyoto, Kyoto, Japan.
| | - Ryo Sakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tomoki Maetani
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Shizuo Kaji
- Institute of Mathematics for Industry, Kyusyu University, Fukuoka, Japan
| | - Hiroshi Shima
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Satoru Terada
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Respiratory Medicine and General Practice, Terada Clinic, Himeji, Hyogo, Japan
| | - Kunihiko Terada
- Respiratory Medicine and General Practice, Terada Clinic, Himeji, Hyogo, Japan
| | - Kohei Ikezoe
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Kiminobu Tanizawa
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tsuyoshi Oguma
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Respiratory Medicine, Kyoto City Hospital, Kyoto, Japan
| | - Tomohiro Handa
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Advanced Medicine for Respiratory Failure, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Sato
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Respiratory Care and Sleep Control Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Shigeo Muro
- Department of Respiratory Medicine, Nara Medical University, Kashihara, Nara, Japan
| | - Toyohiro Hirai
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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3
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Choi B, Díaz AA, San José Estépar R, Enzer N, Castro V, Han MK, Washko GR, San José Estépar R, Ash SY. Association of Acute Respiratory Disease Events with Quantitative Interstitial Abnormality Progression at CT in Individuals with a History of Smoking. Radiology 2024; 311:e231801. [PMID: 38687222 PMCID: PMC11070608 DOI: 10.1148/radiol.231801] [Citation(s) in RCA: 0] [Impact Index Per Article: 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: 07/21/2023] [Revised: 02/24/2024] [Accepted: 03/06/2024] [Indexed: 05/02/2024]
Abstract
Background Acute respiratory disease (ARD) events are often thought to be airway-disease related, but some may be related to quantitative interstitial abnormalities (QIAs), which are subtle parenchymal abnormalities on CT scans associated with morbidity and mortality in individuals with a smoking history. Purpose To determine whether QIA progression at CT is associated with ARD and severe ARD events in individuals with a history of smoking. Materials and Methods This secondary analysis of a prospective study included individuals with a 10 pack-years or greater smoking history recruited from multiple centers between November 2007 and July 2017. QIA progression was assessed between baseline (visit 1) and 5-year follow-up (visit 2) chest CT scans. Episodes of ARD were defined as increased cough or dyspnea lasting 48 hours and requiring antibiotics or corticosteroids, whereas severe ARD episodes were those requiring an emergency room visit or hospitalization. Episodes were recorded via questionnaires completed every 3 to 6 months. Multivariable logistic regression and zero-inflated negative binomial regression models adjusted for comorbidities (eg, emphysema, small airway disease) were used to assess the association between QIA progression and episodes between visits 1 and 2 (intercurrent) and after visit 2 (subsequent). Results A total of 3972 participants (mean age at baseline, 60.7 years ± 8.6 [SD]; 2120 [53.4%] women) were included. Annual percentage QIA progression was associated with increased odds of one or more intercurrent (odds ratio [OR] = 1.29 [95% CI: 1.06, 1.56]; P = .01) and subsequent (OR = 1.26 [95% CI: 1.05, 1.52]; P = .02) severe ARD events. Participants in the highest quartile of QIA progression (≥1.2%) had more frequent intercurrent ARD (incidence rate ratio [IRR] = 1.46 [95% CI: 1.14, 1.86]; P = .003) and severe ARD (IRR = 1.79 [95% CI: 1.18, 2.73]; P = .006) events than those in the lowest quartile (≤-1.7%). Conclusion QIA progression was independently associated with higher odds of severe ARD events during and after radiographic progression, with higher frequency of intercurrent severe events in those with faster progression. Clinical trial registration no. NCT00608764 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Little in this issue.
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Affiliation(s)
- Bina Choi
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
| | - Alejandro A. Díaz
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
| | - Ruben San José Estépar
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
| | - Nicholas Enzer
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
| | - Victor Castro
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
| | - MeiLan K. Han
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
| | - George R. Washko
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
| | - Raúl San José Estépar
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
| | - Samuel Y. Ash
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
| | - for the COPDGene Study
- From the Division of Pulmonary and Critical Care Medicine, Department
of Medicine (B.C., A.A.D., G.R.W.), Applied Chest Imaging Laboratory (B.C.,
A.A.D., Ruben San José Estépar, N.E., G.R.W., Raúl San
José Estépar), and Department of Radiology (Ruben San José
Estépar, Raúl San José Estépar), Brigham and
Women’s Hospital, 15 Francis St, Boston, MA 02115; Boston University
School of Medicine, Boston, Mass (V.C.); Division of Pulmonary and Critical Care
Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor,
Mich (M.K.H.); Department of Critical Care Medicine, South Shore Health, South
Weymouth, Mass (S.Y.A.); and Tufts University School of Medicine, Boston, Mass
(S.Y.A.)
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Ash S, Doyle TJ, Choi B, San Jose Estepar R, Castro V, Enzer N, Kalhan R, Liu G, Bowler R, Wilson DO, San Jose Estepar R, Rosas IO, Washko GR. Utility of peripheral protein biomarkers for the prediction of incident interstitial features: a multicentre retrospective cohort study. BMJ Open Respir Res 2024; 11:e002219. [PMID: 38485250 PMCID: PMC10941119 DOI: 10.1136/bmjresp-2023-002219] [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: 11/27/2023] [Accepted: 02/28/2024] [Indexed: 03/17/2024] Open
Abstract
INTRODUCTION/RATIONALE Protein biomarkers may help enable the prediction of incident interstitial features on chest CT. METHODS We identified which protein biomarkers in a cohort of smokers (COPDGene) differed between those with and without objectively measured interstitial features at baseline using a univariate screen (t-test false discovery rate, FDR p<0.001), and which of those were associated with interstitial features longitudinally (multivariable mixed effects model FDR p<0.05). To predict incident interstitial features, we trained four random forest classifiers in a two-thirds random subset of COPDGene: (1) imaging and demographic information, (2) univariate screen biomarkers, (3) multivariable confirmation biomarkers and (4) multivariable confirmation biomarkers available in a separate testing cohort (Pittsburgh Lung Screening Study (PLuSS)). We evaluated classifier performance in the remaining one-third of COPDGene, and, for the final model, also in PLuSS. RESULTS In COPDGene, 1305 biomarkers were available and 20 differed between those with and without interstitial features at baseline. Of these, 11 were associated with feature progression over a mean of 5.5 years of follow-up, and of these 4 were available in PLuSS, (angiopoietin-2, matrix metalloproteinase 7, macrophage inflammatory protein 1 alpha) over a mean of 8.8 years of follow-up. The area under the curve (AUC) of classifiers using demographics and imaging features in COPDGene and PLuSS were 0.69 and 0.59, respectively. In COPDGene, the AUC of the univariate screen classifier was 0.78 and of the multivariable confirmation classifier was 0.76. The AUC of the final classifier in COPDGene was 0.75 and in PLuSS was 0.76. The outcome for all of the models was the development of incident interstitial features. CONCLUSIONS Multiple novel and previously identified proteomic biomarkers are associated with interstitial features on chest CT and may enable the prediction of incident interstitial diseases such as idiopathic pulmonary fibrosis.
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Affiliation(s)
- Samuel Ash
- Department of Critical Care Medicine, South Shore Hospital, South Weymouth, Massachusetts, USA
- Tufts University School of Medicine, Boston, Massachusetts, USA
| | - Tracy J Doyle
- Pulmonary and Critical Care Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Bina Choi
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | | | - Victor Castro
- Boston University School of Medicine, Boston, Massachusetts, USA
| | - Nicholas Enzer
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Ravi Kalhan
- Division of Pulmonary/Critical Care, Northwestern University, Chicago, Illinois, USA
| | - Gabrielle Liu
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | | | - David O Wilson
- Medicine, Pulmonary Division, University of Pittsburgh, pittsburgh, Pennsylvania, USA
| | - Raul San Jose Estepar
- Applied Chest Imaging Laboratory, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Ivan O Rosas
- Department of Medicine: Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - George R Washko
- Pulmonary and Critical Care Medicine, Brigham and Women's Hospital/Harvard Medical School, Boston, Massachusetts, USA
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5
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McDermott GC, Hayashi K, Yoshida K, Juge PA, Moll M, Cho MH, Doyle TJ, Kinney GL, Dellaripa PF, Wallace ZS, Regan EA, Hunninghake GM, Silverman EK, Ash SY, Estepar RSJ, Washko GR, Sparks JA. Rheumatoid arthritis, quantitative parenchymal lung features, and mortality among smokers. Rheumatology (Oxford) 2023:kead645. [PMID: 38048611 DOI: 10.1093/rheumatology/kead645] [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: 07/26/2023] [Revised: 10/31/2023] [Accepted: 11/05/2023] [Indexed: 12/06/2023] Open
Abstract
OBJECTIVES There have been limited investigations of the prevalence and mortality impact of quantitative computed tomography (QCT) parenchymal lung features in rheumatoid arthritis (RA). We examined the cross-sectional prevalence and mortality associations of QCT features, comparing RA and non-RA participants. METHODS We identified participants with and without RA in COPDGene, a multicentre cohort study of current or former smokers. Using a k-nearest neighbor quantifier, high resolution CT chest scans were scored for percentage of normal lung, interstitial changes, and emphysema. We examined associations between QCT features and RA using multivariable linear regression. After dichotomizing participants at the 75th percentile for each QCT feature among non-RA participants, we investigated mortality associations by RA/non-RA status and quartile 4 vs quartiles 1-3 of QCT features using Cox regression. We assessed for statistical interactions between RA and QCT features. RESULTS We identified 82 RA cases and 8820 non-RA comparators. In multivariable linear regression, RA was associated with higher percentage of interstitial changes (β = 1.7 ± 0.5, p= 0.0008) but not emphysema (β = 1.3 ± 1.7, p= 0.44). Participants with RA and >75th percentile of emphysema had significantly higher mortality than non-RA participants (HR 5.86, 95%CI 3.75-9.13) as well as RA participants (HR 5.56, 95%CI 2.71-11.38) with ≤75th percentile of emphysema. There were statistical interactions between RA and emphysema for mortality (multiplicative p= 0.014; attributable proportion 0.53, 95%CI 0.30-0.70). CONCLUSIONS Using machine learning-derived QCT data in a cohort of smokers, RA was associated with higher percentage of interstitial changes. The combination of RA and emphysema conferred >5-fold higher mortality.
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Affiliation(s)
- Gregory C McDermott
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Keigo Hayashi
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Kazuki Yoshida
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Pierre-Antoine Juge
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Université de Paris Cité, INSERM UMR 1152, Paris, F-75018, France
- Service de Rhumatologie, Hôpital Bichat-Claude Bernard, AP-HP, Paris, F-75018, France
| | - Matthew Moll
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Pulmonary, Allergy, Sleep and Critical Care Medicine Section, Department of Medicine, VA Boston Healthcare System, West Roxbury, USA, MA
| | - Michael H Cho
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Tracy J Doyle
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Gregory L Kinney
- Colorado School of Public Health, Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Paul F Dellaripa
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Zachary S Wallace
- Harvard Medical School, Boston, MA, USA
- Rheumatology Unit, Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Gary M Hunninghake
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Edwin K Silverman
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Samuel Y Ash
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Raul San Jose Estepar
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - George R Washko
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Jeffrey A Sparks
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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6
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Kim JS, Montesi SB, Adegunsoye A, Humphries SM, Salisbury ML, Hariri LP, Kropski JA, Richeldi L, Wells AU, Walsh S, Jenkins RG, Rosas I, Noth I, Hunninghake GM, Martinez FJ, Podolanczuk AJ. Approach to Clinical Trials for the Prevention of Pulmonary Fibrosis. Ann Am Thorac Soc 2023; 20:1683-1693. [PMID: 37703509 PMCID: PMC10704236 DOI: 10.1513/annalsats.202303-188ps] [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: 03/02/2023] [Accepted: 09/13/2023] [Indexed: 09/15/2023] Open
Affiliation(s)
- John S. Kim
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | | | - Ayodeji Adegunsoye
- Department of Medicine, The University of Chicago Medicine, Chicago, Illinois
| | | | - Margaret L. Salisbury
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Lida P. Hariri
- Division of Pulmonary and Critical Care Medicine, and
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jonathan A. Kropski
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Luca Richeldi
- Fondazione Policlinico Universitario Agostino Gemelli Istituto di Ricovero e Cura a Carattere Scientifico, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Athol U. Wells
- Department of Radiology, and
- Interstitial Lung Disease Service, Royal Brompton Hospital, London, United Kingdom
| | - Simon Walsh
- National Heart and Lung Institute, Imperial College, London, United Kingdom
| | - R. Gisli Jenkins
- National Heart and Lung Institute, Imperial College, London, United Kingdom
| | - Ivan Rosas
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Imre Noth
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, Virginia
| | - Gary M. Hunninghake
- Pulmonary and Critical Care Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts; and
| | - Fernando J. Martinez
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Anna J. Podolanczuk
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, New York
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7
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Choi B, San José Estépar R, Godbole S, Curtis JL, Wang JM, San José Estépar R, Rosas IO, Mayers JR, Hobbs BD, Hersh CP, Ash SY, Han MK, Bowler RP, Stringer KA, Washko GR, Labaki WW. Plasma metabolomics and quantitative interstitial abnormalities in ever-smokers. Respir Res 2023; 24:265. [PMID: 37925418 PMCID: PMC10625195 DOI: 10.1186/s12931-023-02576-2] [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: 09/12/2023] [Accepted: 10/23/2023] [Indexed: 11/06/2023] Open
Abstract
BACKGROUND Quantitative interstitial abnormalities (QIA) are an automated computed tomography (CT) finding of early parenchymal lung disease, associated with worse lung function, reduced exercise capacity, increased respiratory symptoms, and death. The metabolomic perturbations associated with QIA are not well known. We sought to identify plasma metabolites associated with QIA in smokers. We also sought to identify shared and differentiating metabolomics features between QIA and emphysema, another smoking-related advanced radiographic abnormality. METHODS In 928 former and current smokers in the Genetic Epidemiology of COPD cohort, we measured QIA and emphysema using an automated local density histogram method and generated metabolite profiles from plasma samples using liquid chromatography-mass spectrometry (Metabolon). We assessed the associations between metabolite levels and QIA using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, pack-years, and inhaled corticosteroid use, at a Benjamini-Hochberg False Discovery Rate p-value of ≤ 0.05. Using multinomial regression models adjusted for these covariates, we assessed the associations between metabolite levels and the following CT phenotypes: QIA-predominant, emphysema-predominant, combined-predominant, and neither- predominant. Pathway enrichment analyses were performed using MetaboAnalyst. RESULTS We found 85 metabolites significantly associated with QIA, with overrepresentation of the nicotinate and nicotinamide, histidine, starch and sucrose, pyrimidine, phosphatidylcholine, lysophospholipid, and sphingomyelin pathways. These included metabolites involved in inflammation and immune response, extracellular matrix remodeling, surfactant, and muscle cachexia. There were 75 metabolites significantly different between QIA-predominant and emphysema-predominant phenotypes, with overrepresentation of the phosphatidylethanolamine, nicotinate and nicotinamide, aminoacyl-tRNA, arginine, proline, alanine, aspartate, and glutamate pathways. CONCLUSIONS Metabolomic correlates may lend insight to the biologic perturbations and pathways that underlie clinically meaningful quantitative CT measurements like QIA in smokers.
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Affiliation(s)
- Bina Choi
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, 75 Francis Street, Pulmonary-PBB-CA-3, Boston, MA, 02115, USA.
- Applied Chest Imaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA.
| | - Raúl San José Estépar
- Applied Chest Imaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | - Suneeta Godbole
- Anschutz Medical Campus, Department of Biostatistics and Informatics, University of Colorado, Aurora, CO, USA
| | - Jeffrey L Curtis
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Medical Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Jennifer M Wang
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Rubén San José Estépar
- Applied Chest Imaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Jared R Mayers
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, 75 Francis Street, Pulmonary-PBB-CA-3, Boston, MA, 02115, USA
| | - Brian D Hobbs
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, 75 Francis Street, Pulmonary-PBB-CA-3, Boston, MA, 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Craig P Hersh
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, 75 Francis Street, Pulmonary-PBB-CA-3, Boston, MA, 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Samuel Y Ash
- Applied Chest Imaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Department of Critical Care, South Shore Hospital, South Weymouth, MA, USA
| | - MeiLan K Han
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Russell P Bowler
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, National Jewish Health, Denver, CO, USA
| | - Kathleen A Stringer
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, USA
| | - George R Washko
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, 75 Francis Street, Pulmonary-PBB-CA-3, Boston, MA, 02115, USA
- Applied Chest Imaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
| | - Wassim W Labaki
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
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8
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Handa T. The potential role of artificial intelligence in the clinical practice of interstitial lung disease. Respir Investig 2023; 61:702-710. [PMID: 37708636 DOI: 10.1016/j.resinv.2023.08.006] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 07/26/2023] [Accepted: 08/09/2023] [Indexed: 09/16/2023]
Abstract
Artificial intelligence (AI) is being widely applied in the field of medicine, in areas such as drug discovery, diagnostic support, and assistance with medical practice. Among these, medical imaging is an area where AI is expected to make a significant contribution. In Japan, as of November 2022, 23 AI medical devices have received regulatory approval; all these devices are related to image analysis. In interstitial lung diseases, technologies have been developed that use AI to analyze high-resolution computed tomography and pathological images, and gene expression patterns in tissue taken from transbronchial lung biopsies to assist in the diagnosis of idiopathic pulmonary fibrosis. Some of these technologies are already being used in clinical practice in the United States. AI is expected to reduce the burden on physicians, improve reproducibility, and advance personalized medicine. Obtaining sufficient data for diseases with a small number of patients is difficult. Additionally, certain issues must be addressed in order for AI to be applied in healthcare. These issues include taking responsibility for the AI results output, updating software after the launch of technology, and adapting to new imaging technologies. Establishing research infrastructures such as large-scale databases and common platforms is important for the development of AI technology: their use requires an understanding of the characteristics and limitations of the systems. CLINICAL TRIAL REGISTRATION: Not applicable.
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Affiliation(s)
- Tomohiro Handa
- Department of Advanced Medicine for Respiratory Failure and Graduate School of Medicine, Kyoto University, Kyoto, Japan; Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
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9
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Park S, Choe J, Hwang HJ, Noh HN, Jung YJ, Lee JB, Do KH, Chae EJ, Seo JB. Long-Term Follow-Up of Interstitial Lung Abnormality: Implication in Follow-Up Strategy and Risk Thresholds. Am J Respir Crit Care Med 2023; 208:858-867. [PMID: 37590877 DOI: 10.1164/rccm.202303-0410oc] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [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: 03/09/2023] [Accepted: 08/17/2023] [Indexed: 08/19/2023] Open
Abstract
Rationale: The optimal follow-up computed tomography (CT) interval for detecting the progression of interstitial lung abnormality (ILA) is unknown. Objectives: To identify optimal follow-up strategies and extent thresholds on CT relevant to outcomes. Methods: This retrospective study included self-referred screening participants aged 50 years or older, including nonsmokers, who had imaging findings relevant to ILA on chest CT scans. Consecutive CT scans were evaluated to determine the dates of the initial CT showing ILA and the CT showing progression. Deep learning-based ILA quantification was performed. Cox regression was used to identify risk factors for the time to ILA progression and progression to usual interstitial pneumonia (UIP). Measurements and Main Results: Of the 305 participants with a median follow-up duration of 11.3 years (interquartile range, 8.4-14.3 yr), 239 (78.4%) had ILA on at least one CT scan. In participants with serial follow-up CT studies, ILA progression was observed in 80.5% (161 of 200), and progression to UIP was observed in 17.3% (31 of 179), with median times to progression of 3.2 years (95% confidence interval [CI], 3.0-3.4 yr) and 11.8 years (95% CI, 10.8-13.0 yr), respectively. The extent of fibrosis on CT was an independent risk factor for ILA progression (hazard ratio, 1.12 [95% CI, 1.02-1.23]) and progression to UIP (hazard ratio, 1.39 [95% CI, 1.07-1.80]). Risk groups based on honeycombing and extent of fibrosis (1% in the whole lung or 5% per lung zone) showed significant differences in 10-year overall survival (P = 0.02). Conclusions: For individuals with initially detected ILA, follow-up CT at 3-year intervals may be appropriate to monitor radiologic progression; however, those at high risk of adverse outcomes on the basis of the quantified extent of fibrotic ILA and the presence of honeycombing may benefit from shortening the interval for follow-up scans.
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Affiliation(s)
- Sohee Park
- Department of Radiology and Research Institute of Radiology
| | - Jooae Choe
- Department of Radiology and Research Institute of Radiology
| | - Hye Jeon Hwang
- Department of Radiology and Research Institute of Radiology
| | - Han Na Noh
- Health Screening and Promotion Center, and
| | | | - Jung-Bok Lee
- Department of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Kyung-Hyun Do
- Department of Radiology and Research Institute of Radiology
| | - Eun Jin Chae
- Department of Radiology and Research Institute of Radiology
| | - Joon Beom Seo
- Department of Radiology and Research Institute of Radiology
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10
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Liu GY, Colangelo LA, San Jose Estepar R, Esposito AJ, Ash SY, Choi B, Jacobs DR, Carnethon MR, Washko GR, Kalhan R. Low-Normal FVC Trajectory Starting in Early Adulthood and Risk of Future Interstitial Abnormalities. Am J Respir Crit Care Med 2023; 208:816-818. [PMID: 37490649 PMCID: PMC10563195 DOI: 10.1164/rccm.202304-0771le] [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: 04/27/2023] [Accepted: 07/25/2023] [Indexed: 07/27/2023] Open
Affiliation(s)
| | - Laura A. Colangelo
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | | | | | - Samuel Y. Ash
- Critical Care, South Shore Hospital, Weymouth, Massachusetts; and
| | - Bina Choi
- Applied Chest Imaging Laboratory
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - David R. Jacobs
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota
| | - Mercedes R. Carnethon
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - George R. Washko
- Applied Chest Imaging Laboratory
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Ravi Kalhan
- Division of Pulmonary and Critical Care Medicine and
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
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