CT scan measures of emphysema and airway disease have been correlated with lung function in cohorts of subjects with a range of COPD severity. The contribution of CT scan-assessed airway disease to objective measures of lung function and respiratory symptoms such as dyspnea in severe emphysema is less clear.
Using data from 338 subjects in the National Emphysema Treatment Trial (NETT) Genetics Ancillary Study, densitometric measures of emphysema using a threshold of −950 Hounsfield units (%LAA-950) and airway wall phenotypes of the wall thickness (WT) and the square root of wall area (SRWA) of a 10-mm luminal perimeter airway were calculated for each subject. Linear regression analysis was performed for outcome variables FEV1 and percent predicted value of FEV1 with CT scan measures of emphysema and airway disease.
In univariate analysis, there were significant negative correlations between %LAA-950 and both the WT (r = −0.28, p = 0.0001) and SRWA (r = −0.19, p = 0.0008). Airway wall thickness was weakly but significantly correlated with postbronchodilator FEV1% predicted (R = −0.12, p = 0.02). Multivariate analysis showed significant associations between either WT or SRWA (β = −5.2, p = 0.009; β = −2.6, p = 0.008, respectively) and %LAA-950 (β = −10.6, p = 0.03) with the postbronchodilator FEV1% predicted. Male subjects exhibited significantly thicker airway wall phenotypes (p = 0.007 for WT and p = 0.0006 for SRWA).
Airway disease and emphysema detected by CT scanning are inversely related in patients with severe COPD. Airway wall phenotypes were influenced by gender and associated with lung function in subjects with severe emphysema.
COPD is characterized by incompletely reversible expiratory airflow obstruction1 related to pathologic changes found in both the lung parenchyma and airways.2 CT scanning is a minimally invasive tool employed to characterize these structural changes in vivo3 and has been demonstrated repeatedly to be correlated with measures of airflow obstruction.4–7 CT imaging has also been employed to objectively classify an individual as having either emphysema or airway-predominant disease,8–10 and there is some suggestion that a subject's relative burden of airway and airspace disease may not be the result of totally independent processes.11
The National Emphysema Treatment Trial (NETT) consisted of subjects with severe emphysema who were randomly assigned to receive either lung volume reduction surgery or optimal medical therapy. At the time of study randomization, a CT scan of the chest was obtained in addition to standard measures of lung function and assessments of dyspnea. In the NETT cohort, some of the relationships between emphysema, health status, and lung function correlation have been reported previously,7,12 but quantitative airway phenotypes have not been investigated. Using CT-based measures of airway disease, we could assess the epidemiologic associations between CT phenotypes and clinical metrics of disease, including physiologic and functional measures as well as frequency of exacerbations.
Recently, Patel and colleagues11 reported that while there were independent functional correlations between both emphysema and airway disease with FEV1, there was a weak but statistically significant negative correlation between measures of these two disease processes. Using the NETT data, we sought to examine the functional contribution of CT scan measures of emphysema and airway disease to clinical metrics of disease and the frequency of acute exacerbations of COPD. In addition, the emphysema and airway disease measurements made by CT scanning could be examined to determine whether the inverse correlation previously reported between these two metrics could be replicated in a cohort of subjects selected for having severe bilateral emphysema with presumed parenchymal predominant disease.
Clinical Characterization of Study Subjects
The current analysis included 338 non-Hispanic, white subjects from the Genetics Ancillary Study of NETT.13 Selection of this cohort of subjects was based on CT scan availability and subsequent intended correlations of genetic information and CT measures of disease. Subjects enrolled in NETT had CT scan evidence of severe emphysematous destruction of the lung parenchyma and an FEV1 of ≤ 45% predicted.13 Spirometry was performed according to American Thoracic Society standards14 before and after albuterol administration. A subject's bronchodilator response was calculated as the difference between their FEV1 prior to and after the administration of two puffs of albuterol (180 μg total). This value was expressed as a percent of a subject's predicted FEV1.
Clinical assessment included dyspnea quantified by using the University of California, San Diego Shortness of Breath Questionnaire (UCSD SOBQ), a validated questionnaire assessing symptoms of breathlessness15 and a 6-minute walking test. A modified BODE index was calculated for each subject as performed previously by using a subject's FEV1 percent predicted, UCSD SOBQ, 6-minute walk distance, and body mass index (BMI).16 Using the Centers for Medicare and Medicaid Services claims data, COPD exacerbations were defined as one or more COPD-related emergency visits or hospitalizations occurring from 1 year prior to study enrollment through the 3 years following randomization.17,18 Finally, tobacco smoke exposure (pack-year history) was calculated as the average number of packs of cigarettes smoked per day multiplied by the number of years of smoking. The study was approved by institutional review boards at participating centers. All subjects provided written informed consent.
Quantitative CT Scan Analysis
CT images of the chest were acquired at full inspiration with a minimum of 200 mA (greater in large subjects) and reconstructed using a high spatial frequency (bone) algorithm with a 1- to 2-mm collimation at 20-mm intervals. Densitometric measures of emphysema were analyzed by using a software program (Pulmonary Analysis Software Suite; PASS; Iowa City, IA) at a threshold of −950 Hounsfield units as described previously7,19 and reported as the percent emphysema (%LAA). Per this convention, subjects with greater %LAA were observed to have greater parenchymal destruction manifested as emphysema on their CT scan. Airway wall thickness (WT) and the square root of wall area (SRWA) were assessed by using a tool for airway morphometry and airway quantification (Airway Inspector; www.airwayinspector.org) at Brigham and Women's Hospital. Individual airways that appeared round on visual inspection were manually selected in the right and left upper lobes and right lower lobe. The full width at half-maximum method was used to measure the WT and SRWA of each airway. From these discrete measures, the WT and SRWA of a 10-mm luminal perimeter (Pi10-mm) airway was calculated.11,20 In this way, a subject's CT scan burden of airway disease could be expressed as a single metric where larger-derived measures of the WT and SRWA of the Pi10-mm airway represented greater CT scan burdens of airway disease.
The CT phenotypes tested included the percent emphysema (percent emphysema at a threshold of 950 Hounsfield units [%LAA-950]), WT, and SRWA of a derived Pi10-mm airway. For univariate analysis, Pearson correlation coefficients were calculated between CT scan phenotypes, and gender differences were evaluated using t tests. Multivariate analysis was performed by using linear regression models for post-bronchodilator therapy percent predicted values of FEV1 adjusting for subject's weight, pack-years of smoking, and the clinical center at which study enrollment occurred. To assess the influence of CT scan measures of airway disease on COPD exacerbations, exacerbations were defined as one or more COPD-related emergency visits or hospitalizations by using Centers for Medicare and Medicaid Services claims data and analyzed adjusting for age, gender, FEV1, pack-years of smoking, and surgery status. The influence of emphysema and airway WT in this dichotomized cohort was then assessed by using logistic regression. p Values of < 0.05 were considered statistically significant. Statistical analyses were performed by using a statistical software package (SAS; SAS Institute; Cary, NC).
Epidemiologic Data With Quantitative CT Scan Correlations
The demographic characteristics of the study cohort are provided in Table 1. Three hundred thirty-eight subjects were included in this analysis with a mean pre- and post-FEV1 of 25.0% and 28.2% predicted, respectively. The mean age of the cohort was 67.5 years and approximately 64% of the subjects were men. Densitometric measures of emphysema and CT scan measures of airway disease were available on 317 of the 338 subjects and within this group the mean percentage of emphysematous lung was 16.6. The mean WT and SRWA of the entire cohort were 1.53 mm and 4.6 mm2, respectively.
Table 1 Demographic Characteristics of the 338 Subjects in the NETT Genetics Ancillary Study
| Save Table
|Age, yr||67.5 ± 6.0|
|Male gender, No. (%)||217 (64.2)|
|Pack-years tobacco||67.6 ± 30.8|
|Before bronchodilator FEV1, % predicted||25.0 ± 6.6|
|After bronchodilator FEV1, % predicted||28.2 ± 7.4|
|%LAA-950 (n = 317)||16.6 ± 11.0|
|WT, mm||1.53 ± 0.25|
|SRWA, mm2||4.6 ± 0.5|
Male subjects were found to have significantly thicker airway walls than female subjects by using either the WT (p = 0.007) or the SRWA (p = 0.0006) of a Pi10-mm airway (Table 2). BMI was inversely correlated with %LAA-950 (R = −0.26, p < 0.0001) [Fig 1] and directly related to both WT and SRWA (R = 0.24, p < 0.0001; and R = 0.19, p = 0.0004, respectively). In addition, when adjusted for gender, BMI remained a significant predictor of the SRWA (p = 0.002). Finally, tobacco pack-year history was modestly but significantly inversely correlated with a subject's burden of emphysema (R = −0.12, p = 0.04), but its effect on WT did not reach statistical significance (R = 0.09, p = 0.09; and R = 0.09, p = 0.11 for WT and SRWA, respectively).
Table 2 Airway WT and the SRWA of a Derived Pi10-mm Airway
| Save Table
|WT, mm||1.56 ± 0.23||1.48 ± 0.27||0.007|
|SRWA, mm2||4.66 ± 0.47||4.47 ± 0.54||0.0006|
|%LAA-950||0.17 ± 0.10||0.16 ± 0.12||0.81|
Figure Jump LinkFigure 1 Relationship of %LAA and BMI.Grahic Jump Location
Quantitative CT Scanning and Subject Symptoms and Function
There were no significant associations between measures of airway WT and a subject's 6-minute walk distance or modified BODE index; however, there were significant associations between emphysema severity and 6-min walk distance (β = −438, p = 0.03), and between emphysema severity and modified BODE index (β = 2.3, p = 0.02) after adjusting for pack-years of smoking and clinical center. Similarly, neither CT scan measures of emphysema nor airway disease were predictive of a subject's symptoms as assessed by their UCSD SOBQ. Finally, there was no association between COPD exacerbations and the WT, SRWA, or %LAA-950 (p = 0.2, p = 0.5, and p = 0.5, respectively).
In the cohort of 317 subjects in whom quantitative measures of both emphysema and airway disease were available, there were significant inverse correlations between %LAA-950 and both WT (r = −0.28, p < 0.0001) and SRWA (r = −0.19, p = 0.0008; Fig 2). Airway WT (WT R = −0.12, p = 0.03), but not the SRWA (R = −0.09, p = 0.09) or %LAA-950 (R = −0.07, p = 0.19), was significantly correlated with postbronchodilator FEV1% predicted. After adjusting for subjects' weight, pack-year tobacco history, and clinical center at which the subjects were enrolled, association of WT with postbronchodilator FEV1% predicted remained statistically significant (β = −5.2, p = 0.009), and SRWA and %LAA-950 became statistically significant (β = −2.6, p = 0.008; β = −10.6, p = 0.03, respectively).
Figure Jump LinkFigure 2 Relationship of the %LAA and SRWA Pi10 mm.Grahic Jump Location
In a multivariate model including WT and %LAA-950 as well as weight, pack-years, and clinical center, both WT and %LAA-950 were significantly associated with lung function (p = 0.01 and p = 0.01, respectively) [Table 3]. Airway wall and emphysema phenotypes were not predictive of bronchodilator responsiveness (p = 0.9, 0.6, and 0.4 for WT, SRWA, and %LAA-950, respectively) after adjusting age, gender, pack-years of smoking, and clinical center. These findings were replicated by using the phase congruency method for airway segmentation21 (data not shown) and as such are less likely to be an artifact of airway measurement technique.
Table 3 Association Analysis of Lung Function Revealed That Multivariate Models for Postbronchodilator FEV1% Predicted Was Associated With Either WT and LAA-950 (First Model) or the SRWA and LAA-950 (Second Model)
| Save Table
|First Model||β||p Value||Second Model||β||p Value|
|WT, mm||−5.2||0.01||SRWA, mm2||−2.4||0.02|
Chest CT scanning has been increasingly used to define distinct imaging phenotypes in COPD,4–7 including defining subjects as having either emphysema- or airway-predominant disease.8–10 Interestingly, there has been a recent suggestion that a subject's relative burden of airway and airspace disease may in part be related.11 Given these reports, we sought to examine the functional contribution of CT scan measures of airway disease in subjects with severe COPD and further determine if the findings of Patel and colleagues11 could be replicated in a cohort of subjects with severe emphysema and presumed parenchymal predominant disease. Detailed assessments of imaging features with functional parameters in large cohorts of well-defined COPD patients have been scarce. The NETT Genetics Ancillary Study provided access to a large cohort of patients who were highly characterized clinically and physiologically and who underwent standardized CT imaging. In the current report, CT scan-based measures of both airway and airspace disease were performed and correlated to both functional and symptom-based indexes of disease. The derived measures of airway disease analyzed were both the WT and the SRWA of a theoretical Pi10-mm airway. We found that (1) airway wall phenotypes were significantly influenced by subject gender; (2) while the cohort exhibited a preponderance of emphysematous destruction of the lung parenchyma, measures of airway disease remained predictive of measures of lung function; (3) emphysema severity was predictive of 6-minute walk distance and modified BODE index, whereas airway wall imaging phenotypes were not correlated with other physiologic (6-min walk distance) or functional measures (dyspnea, health status); and (4) imaging was not able to segregate patients who subsequently did or did not experience COPD exacerbations.
A novel finding of our work is documentation that gender strongly influences CT scan measures of airway abnormality. Previous reports12,22 have suggested that for an equal degree of airflow obstruction, men have significantly more emphysema than women. An initial examination of NETT patients suggested that women have proportionally more airway disease.12 Based on these observations, and what is known about the correlation between proximal airway wall area and distal small airway disease, women were expected to have thicker proximal airway walls on CT scan.21 Interestingly, in this subset of the NETT cohort, men had significantly thicker airway walls than women. The lack of standard prediction equations for airway wall measurements likely limits the interpretation of gender effects; it is possible that despite our finding of lower absolute airway WT measurements in women than men with COPD, that the percentage of predicted airway WT values could be greater in women.12 For emphysema severity, we did not see any gender difference, possibly because of smaller sample size than in the initial report.12
Importantly, we noted an inverse relationship between emphysema severity and airway WT. This negative correlation has been reported previously in another recent report in the multicenter International COPD Genetics Network.11 The etiology of this inverse relationship may be related to the pathobiology of disease, the mechanical interdependence of airway and airspace disease, or the lung volume at which the CT scan was performed. In the latter case, a loss of parenchymal tethering around the airway could lead to an observed increase in emphysema during inflation with minimal changes in the CT scan airway wall characteristics. Additional investigation is needed to clarify the reasons for the existence of such a relationship.
Our study also replicated reports of a significant association of airway phenotypes with lung function despite our cohort of parenchymal predominant disease subjects. The strength of these correlations was lower than previously reported11; however, the analysis of a cohort of subjects with severe emphysema may have attenuated the strength of this association. Similar correlations were not discovered between airway disease and either exercise capacity, bronchodilator response, or respiratory symptoms.
Access to highly characterized patients provided insight into imaging correlations. A subject's BMI significantly influenced airway WT and measures of emphysema10,11,23 whereby subjects with lower BMIs tended to have more emphysema and less airway disease. Given the reproducibility of this finding, it is unlikely to be an artifact of this study population, and subject BMI may be a potential indication of the cachexia experienced by subjects with parenchymal predominant disease. Interestingly, pack-years of smoking was inversely correlated with %LAA-950 and tended to directly influence airway WT. While the latter observation is congruous with the concept of chronic noxious stimuli leading to mural inflammation and airway remodeling, the inverse relationship between pack-years and emphysema is not as seemingly transparent. These findings may in part be due to the cohort under investigation. Only those subjects with severe COPD and emphysema on CT scan were included in the NETT. The homogeneity of such a study population may not provide the ideal cohort to examine the influences of smoking on CT scan metrics of disease. Alternatively, there may be a threshold of smoking exposure that increases the risk of emphysema, but increased smoking beyond that threshold may not further increase emphysema severity. This latter mechanism is purely speculative and would require further investigation within a cohort of subjects with a broader range of smoking history and functional impairment to substantiate.
Importantly, we did not record any impact of airway wall imaging phenotypes on other functional or symptomatic measures. In contrast, emphysema severity was associated with modified BODE and 6-minute walk distance. Association with modified BODE was shown in initial analysis with 1,053 NETT subjects.12 Others have suggested that UCSD SOBQ is impaired to a greater extent in subjects with more CT emphysema.10,24 In addition, others have suggested higher breathlessness in COPD subjects with greater emphysema.8,11 The variance in findings could reflect methodological differences in imaging protocols or the nature of the patient population of our cohort, which comprised subjects preselected to exhibit severe emphysema.
CT scanning is becoming a widely used noninvasive tool to evaluate the lumenal narrowing and airway wall thickening associated with airway disease in subjects with COPD. There are several different investigational methods used to investigate and express these characteristic morphologic changes including the wall area percent and wall area of common airways across the cohort.4,5 In cases such as ours where the CT images do not support such analysis, ie, have interval missing data such that common airways cannot be found in all subjects, derived measures of airway disease have been employed. The most standard of these is the SRWA of a 10-mm airway.11 For the purposes of this investigation, we used discrete measures of both the airway WT and the SRWA to generate both the WT and SRWA of a Pi10-mm airway for each subject.
There were several limitations to this study. The NETT population comprised a cohort of patients with advanced COPD and a clinical and subjective imaging diagnosis of emphysema. Furthermore, we analyzed selected subjects in the ancillary genetics study rather than the whole NETT patient cohort, which may lead to selection bias. Specifically, the Genetics Ancillary Study consisted of subjects surviving several years after enrollment into the NETT, who were still alive at the time of study cohort formation. Survivor bias may therefore limit the conclusions that can be drawn from this investigation for the larger NETT cohort. Subjects were also recruited from multiple centers with different CT scanners that may affect the CT scan parameters.25 Center effect may influence the associations despite our statistical adjustment for this effect. Despite this potential bias and multicenter recruitment effect, we observed weak but significant associations between FEV1 and airway phenotypes in those subjects whose airway data were measured.
The results of this investigation demonstrate that even in a relatively homogeneous cohort of subjects with severe COPD, CT scan measures of emphysema and airway disease are independently predictive of expiratory airflow obstruction. In addition, in a cohort of subjects with presumed parenchymal predominant disease, CT scan measures of emphysema and airway disease are inversely correlated. Additional investigation is needed to determine if the observed inverse relationship between emphysema and airway disease has a histopathologic basis or is simply an artifact of imaging.
body mass index
percent emphysema at a threshold of 950 Hounsfield units
National Emphysema Treatment Trial
10-mm luminal perimeter
square root wall area
University of California, San Diego Shortness of Breath Questionnaire
Author contributions: All authors contributed significantly to the creation of this manuscript and were part of the writing committee. In addition, Drs. Hoffman, Criner, Mosenifar, Sciurba, Make, Reilly, and Martinez were primary investigators in NETT and facilitated collection of the data presented. Drs. Hoffman and San José Estépar were responsible for software development, which facilitated the CT scan data presented. Dr. Diaz performed the CT analysis of the airways.
Financial/nonfinancial disclosures: Dr. Hoffman reports having a financial interest in VIDA Diagnostics, a company specializing in image analysis software. Drs. Kim, Silverman, Criner, Mosenifar, Sciurba, Make, Carey, San Jose Estepar, Diaz, Reilly, Martinez, and Washko have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.
Role of sponsors: This manuscript is subject to the National Institutes of Health Public Access Policy (http://publicaccess.nih.gov/).
Other contributions: We thank Arthur Gelb, MD, Lakewood Regional Medical Center, Lakewood, CA.
Members of the NETT Research Group
Office of the Chair of the Steering Committee, University of Pennsylvania, Philadelphia, PA:
Alfred P. Fishman, MD (Chair); Betsy Ann Bozzarello; Ameena Al-Amin.
Baylor College of Medicine, Houston, TX:
Marcia Katz, MD (Principal Investigator); Carolyn Wheeler, RN, BSN (Principal Clinic Coordinator); Elaine Baker, RRT, RPFT; Peter Barnard, PhD, RPFT; Phil Cagle, MD; James Carter, MD; Sophia Chatziioannou, MD; Karla Conejo-Gonzales; Kimberly Dubose, RRT; John Haddad, MD; David Hicks, RRT, RPFT; Neal Kleiman, MD; Mary Milburn-Barnes, CRTT; Chinh Nguyen, RPFT; Michael Reardon, MD; Joseph Reeves-Viets, MD; Steven Sax, MD; Amir Sharafkhaneh, MD; Owen Wilson, PhD; Christine Young, PT; Rafael Espada, MD (Principal Investigator: 1996–2002); Rose Butanda (1999–2001); Minnie Ellisor (2002); Pamela Fox, MD (1999–2001); Katherine Hale, MD (1998–2000); Everett Hood, RPFT (1998–2000); Amy Jahn (1998–2000); Satish Jhingran, MD (1998–2001); Karen King, RPFT (1998–1999); Charles Miller III, PhD (1996–1999); Imran Nizami, MD (Co-Principal Investigator: 2000–2001); Todd Officer (1998–2000); Jeannie Ricketts (1998–2000); Joe Rodarte, MD (Co-Principal Investigator: 1996–2000); Robert Teague, MD (Co-Principal Investigator: 1999–2000); Kedren Williams (1998–1999).
Brigham and Women's Hospital, Boston, MA:
John Reilly, MD (Principal Investigator); David Sugarbaker, MD (Co-Principal Investigator); Carol Fanning, RRT (Principal Clinic Coordinator); Simon Body, MD; Sabine Duffy, MD; Vladmir Formanek, MD; Anne Fuhlbrigge, MD; Philip Hartigan, MD; Sarah Hooper, EP; Andetta Hunsaker, MD; Francine Jacobson, MD; Marilyn Moy, MD; Susan Peterson, RRT; Roger Russell, MD; Diane Saunders; Scott Swanson, MD (Co-Principal Investigator: 1996–2001).
Cedars-Sinai Medical Center, Los Angeles, CA:
Rob McKenna, MD (Principal Investigator); Zab Mohsenifar, MD (Co-Principal Investigator); Carol Geaga, RN (Principal Clinic Coordinator); Manmohan Biring, MD; Susan Clark, RN, MN; Jennifer Cutler, MD; Robert Frantz, MD; Peter Julien, MD; Michael Lewis, MD; Jennifer Minkoff-Rau, MSW; Valentina Yegyan, BS, CPFT; Milton Joyner, BA (1996–2002).
Cleveland Clinic Foundation, Cleveland, OH:
Malcolm DeCamp, MD (Principal Investigator); James Stoller, MD (Co-Principal Investigator); Yvonne Meli, RN-C (Principal Clinic Coordinator); John Apostolakis, MD; Darryl Atwell, MD; Jeffrey Chapman, MD; Pierre DeVilliers, MD; Raed Dweik, MD; Erik Kraenzler, MD; Rosemary Lann, LISW; Nancy Kurokawa, RRT, CPFT; Scott Marlow, RRT; Kevin McCarthy, RCPT; Priscilla McCreight, RRT, CPFT; Atul Mehta, MD; Moulay Meziane, MD; Omar Minai, MD; Mindi Steiger, RRT; Kenneth White, RPFT; Janet Maurer, MD (Principal Investigator: 1996–2001); Terri Durr, RN (2000–2001); Charles Hearn, DO (1998–2001); Susan Lubell, PA-C (1999–2000); Peter O'Donovan, MD (1998–2003); Robert Schilz, DO (1998–2002).
Columbia University, New York, NY in consortium with Long Island Jewish Medical Center, New Hyde Park, NY:
Mark Ginsburg, MD (Principal Investigator); Byron Thomashow, MD (Co-Principal Investigator); Patricia Jellen, MSN, RN (Principal Clinic Coordinator); John Austin, MD; Matthew Bartels, MD; Yahya Berkmen, MD; Patricia Berkoski, MS, RRT (Site Coordinator, LIJ); Frances Brogan, MSN, RN; Amy Chong, BS, CRT; Glenda DeMercado, BSN; Angela DiMango, MD; Sandy Do, MS, PT; Bessie Kachulis, MD; Arfa Khan, MD; Berend Mets, MD; Mitchell O'Shea, BS, RT, CPFT; Gregory Pearson, MD; Leonard Rossoff, MD; Steven Scharf, MD, PhD (Co-Principal Investigator: 1998–2002); Maria Shiau, MD; Paul Simonelli, MD; Kim Stavrolakes, MS, PT; Donna Tsang, BS; Denise Vilotijevic, MS, PT; Chun Yip, MD; Mike Mantinaos, MD (1998–2001); Kerri McKeon, BS, RRT, RN (1998–1999); Jacqueline Pfeffer, MPH, PT (1997–2002).
Duke University Medical Center, Durham, NC:
Neil MacIntyre, MD (Principal Investigator); R. Duane Davis, MD (Co-Principal Investigator); John Howe, RN (Principal Clinic Coordinator); R. Edward Coleman, MD; Rebecca Crouch, RPT; Dora Greene; Katherine Grichnik, MD; David Harpole, Jr, MD; Abby Krichman, RRT; Brian Lawlor, RRT; Holman McAdams, MD; John Plankeel, MD; Susan Rinaldo-Gallo, MED; Sheila Shearer, RRT; Jeanne Smith, ACSW; Mark Stafford-Smith, MD; Victor Tapson, MD; Mark Steele, MD (1998–1999); Jennifer Norten, MD (1998–1999).
Mayo Foundation, Rochester, MN:
James Utz, MD (Principal Investigator); Claude Deschamps, MD (Co-Principal Investigator); Kathy Mieras, CCRP (Principal Clinic Coordinator); Martin Abel, MD; Mark Allen, MD; Deb Andrist, RN; Gregory Aughenbaugh, MD; Sharon Bendel, RN; Eric Edell, MD; Marlene Edgar; Bonnie Edwards; Beth Elliot, MD; James Garrett, RRT; Delmar Gillespie, MD; Judd Gurney, MD; Boleyn Hammel; Karen Hanson, RRT; Lori Hanson, RRT; Gordon Harms, MD; June Hart; Thomas Hartman, MD; Robert Hyatt, MD; Eric Jensen, MD; Nicole Jenson, RRT; Sanjay Kalra, MD; Philip Karsell, MD; Jennifer Lamb; David Midthun, MD; Carl Mottram, RRT; Stephen Swensen, MD; Anne-Marie Sykes, MD; Karen Taylor; Norman Torres, MD; Rolf Hubmayr, MD (1998–2000); Daniel Miller, MD (1999–2002); Sara Bartling, RN (1998–2000); Kris Bradt (1998–2002).
National Jewish Medical and Research Center, Denver, CO:
Barry Make, MD (Principal Investigator); Marvin Pomerantz, MD (Co-Principal Investigator); Mary Gilmartin, RN, RRT (Principal Clinic Coordinator); Joyce Canterbury; Martin Carlos; Phyllis Dibbern, PT; Enrique Fernandez, MD; Lisa Geyman, MSPT; Connie Hudson; David Lynch, MD; John Newell, MD; Robert Quaife, MD; Jennifer Propst, RN; Cynthia Raymond, MS; Jane Whalen-Price, PT; Kathy Winner, OTR; Martin Zamora, MD; Reuben Cherniack, MD (Principal Investigator: 1997–2000).
Ohio State University, Columbus, OH:
Philip Diaz, MD (Principal Investigator); Patrick Ross, MD (Co-Principal Investigator); Tina Bees (Principal Clinic Coordinator); Jan Drake; Charles Emery, PhD; Mark Gerhardt, MD, PhD; Mark King, MD; David Rittinger; Mahasti Rittinger.
Saint Louis University, Saint Louis, MO:
Keith Naunheim, MD (Principal Investigator); Robert Gerber, MD (Co-Principal Investigator); Joan Osterloh, RN, MSN (Principal Clinic Coordinator); Susan Borosh; Willard Chamberlain, DO; Sally Frese; Alan Hibbit; Mary Ellen Kleinhenz, MD; Gregg Ruppel; Cary Stolar, MD; Janice Willey; Francisco Alvarez, MD (Co-Principal Investigator: 1999–2002); Cesar Keller, MD (Co-Principal Investigator: 1996–2000).
Temple University, Philadelphia, PA:
Gerard Criner, MD (Principal Investigator); Satoshi Furukawa, MD (Co-Principal Investigator); Anne Marie Kuzma, RN, MSN (Principal Clinic Coordinator); Roger Barnette, MD; Neil Brister, MD; Kevin Carney, RN, CCTC; Wissam Chatila, MD; Francis Cordova, MD; Gilbert D'Alonzo, DO; Michael Keresztury, MD; Karen Kirsch; Chul Kwak, MD; Kathy Lautensack, RN, BSN; Madelina Lorenzon, CPFT; Ubaldo Martin, MD; Peter Rising, MS; Scott Schartel, MD; John Travaline, MD; Gwendolyn Vance, RN, CCTC; Phillip Boiselle, MD (1997–2000); Gerald O'Brien, MD (1997–2000).
University of California, San Diego, San Diego, CA:
Andrew Ries, MD, MPH (Principal Investigator); Robert Kaplan, PhD (Co-Principal Investigator); Catherine Ramirez, BS, RCP (Principal Clinic Coordinator); David Frankville, MD; Paul Friedman, MD; James Harrell, MD; Jeffery Johnson; David Kapelanski, MD; David Kupferberg, MD, MPH; Catherine Larsen, MPH; Trina Limberg, RRT; Michael Magliocca, RN, CNP; Frank J. Papatheofanis, MD, PhD; Dawn Sassi-Dambron, RN; Melissa Weeks.
University of Maryland at Baltimore, Baltimore, MD in consortium with Johns Hopkins Hospital, Baltimore, MD:
Mark Krasna, MD (Principal Investigator); Henry Fessler, MD (Co-Principal Investigator); Iris Moskowitz (Principal Clinic Coordinator); Timothy Gilbert, MD; Jonathan Orens, MD; Steven Scharf, MD, PhD; David Shade; Stanley Siegelman, MD; Kenneth Silver, MD; Clarence Weir; Charles White, MD.
University of Michigan, Ann Arbor, MI:
Fernando Martinez, MD (Principal Investigator); Mark Iannettoni, MD (Co-Principal Investigator); Catherine Meldrum, BSN, RN, CCRN (Principal Clinic Coordinator); William Bria, MD; Kelly Campbell; Paul Christensen, MD; Kevin Flaherty, MD; Steven Gay, MD; Paramjit Gill, RN; Paul Kazanjian, MD; Ella Kazerooni, MD; Vivian Knieper; Tammy Ojo, MD; Lewis Poole; Leslie Quint, MD; Paul Rysso; Thomas Sisson, MD; Mercedes True; Brian Woodcock, MD; Lori Zaremba, RN.
University of Pennsylvania, Philadelphia, PA:
Larry Kaiser, MD (Principal Investigator); John Hansen-Flaschen, MD (Co-Principal Investigator); Mary Louise Dempsey, BSN, RN (Principal Clinic Coordinator); Abass Alavi, MD; Theresa Alcorn, Selim Arcasoy, MD; Judith Aronchick, MD; Stanley Aukberg, MD; Bryan Benedict, RRT; Susan Craemer, BS, RRT, CPFT; Ron Daniele, MD; Jeffrey Edelman, MD; Warren Gefter, MD; Laura Kotler-Klein, MSS; Robert Kotloff, MD; David Lipson, MD; Wallace Miller, Jr., MD; Richard O'Connell, RPFT; Staci Opelman, MSW; Harold Palevsky, MD; William Russell, RPFT; Heather Sheaffer, MSW; Rodney Simcox, BSRT, RRT; Susanne Snedeker, RRT, CPFT; Jennifer Stone-Wynne, MSW; Gregory Tino, MD; Peter Wahl; James Walter, RPFT; Patricia Ward; David Zisman, MD; James Mendez, MSN, CRNP (1997–2001); Angela Wurster, MSN, CRNP (1997–1999).
University of Pittsburgh, Pittsburgh, PA:
Frank Sciurba, MD (Principal Investigator); James Luketich, MD (Co-Principal Investigator); Colleen Witt, MS (Principal Clinic Coordinator); Gerald Ayres; Michael Donahoe, MD; Carl Fuhrman, MD; Robert Hoffman, MD; Joan Lacomis, MD; Joan Sexton; William Slivka; Diane Strollo, MD; Erin Sullivan, MD; Tomeka Simon; Catherine Wrona, RN, BSN; Gerene Bauldoff, RN, MSN (1997–2000); Manuel Brown, MD (1997–2002); Elisabeth George, RN, MSN (Principal Clinic Coordinator: 1997–2001); Robert Keenan, MD (Co-Principal Investigator: 1997–2000); Theodore Kopp, MS (1997–1999); Laurie Silfies (1997–2001).
University of Washington, Seattle, WA:
Joshua Benditt, MD (Principal Investigator), Douglas Wood, MD (Co-Principal Investigator); Margaret Snyder, MN (Principal Clinic Coordinator); Kymberley Anable; Nancy Battaglia; Louie Boitano; Andrew Bowdle, MD; Leighton Chan, MD; Cindy Chwalik; Bruce Culver, MD; Thurman Gillespy, MD; David Godwin, MD; Jeanne Hoffman; Andra Ibrahim, MD; Diane Lockhart; Stephen Marglin, MD; Kenneth Martay, MD; Patricia McDowell; Donald Oxorn, MD; Liz Roessler; Michelle Toshima; Susan Golden (1998–2000).
Agency for Healthcare Research and Quality, Rockville, MD:
Lynn Bosco, MD, MPH; Yen-Pin Chiang, PhD; Carolyn Clancy, MD; Harry Handelsman, DO.
Centers for Medicare and Medicaid Services, Baltimore, MD:
Steven M. Berkowitz, PhD; Tanisha Carino, PhD; Joe Chin, MD; JoAnna Baldwin; Karen McVearry; Anthony Norris; Sarah Shirey; Claudette Sikora; Steven Sheingold, PhD (1997–2004).
Coordinating Center, The Johns Hopkins University, Baltimore, MD:
Steven Piantadosi, MD, PhD (Principal Investigator); James Tonascia, PhD (Co-Principal Investigator); Patricia Belt; Amanda Blackford, ScM; Karen Collins; Betty Collison; Ryan Colvin, MPH; John Dodge; Michele Donithan, MHS; Vera Edmonds; Gregory L. Foster, MA; Julie Fuller; Judith Harle; Rosetta Jackson; Shing Lee, ScM; Charlene Levine; Hope Livingston; Jill Meinert; Jennifer Meyers; Deborah Nowakowski; Kapreena Owens; Shangqian Qi, MD; Michael Smith; Brett Simon, MD; Paul Smith; Alice Sternberg, ScM; Mark Van Natta, MHS; Laura Wilson, ScM; Robert Wise, MD.
Cost Effectiveness Subcommittee:
Robert M. Kaplan, PhD (Chair); J. Sanford Schwartz, MD (Co-Chair); Yen-Pin Chiang, PhD; Marianne C. Fahs, PhD; A. Mark Fendrick, MD; Alan J. Moskowitz, MD; Dev Pathak, PhD; Scott Ramsey, MD, PhD; Steven Sheingold, PhD; A. Laurie Shroyer, PhD; Judith Wagner, PhD; Roger Yusen, MD.
Cost Effectiveness Data Center, Fred Hutchinson Cancer Research Center, Seattle, WA:
Scott Ramsey, MD, PhD (Principal Investigator); Ruth Etzioni, PhD; Sean Sullivan, PhD; Douglas Wood, MD; Thomas Schroeder, MA; Karma Kreizenbeck; Kristin Berry, MS; Nadia Howlader, MS.
CT Scan Image Storage and Analysis Center, University of Iowa, Iowa City, IA:
Eric Hoffman, PhD (Principal Investigator); Janice Cook-Granroth, BS; Angela Delsing, RT; Junfeng Guo, PhD; Geoffrey McLennan, MD; Brian Mullan, MD; Chris Piker, BS; Joseph Reinhardt, PhD; Blake Wood; Jered Sieren, RTR; William Stanford, MD.
Data and Safety Monitoring Board:
John A. Waldhausen, MD (Chair); Gordon Bernard, MD; David DeMets, PhD; Mark Ferguson, MD; Eddie Hoover, MD; Robert Levine, MD; Donald Mahler, MD; A. John McSweeny, PhD; Jeanine Wiener-Kronish, MD; O. Dale Williams, PhD; Magdy Younes, MD.
Marketing Center, Temple University, Philadelphia, PA:
Gerard Criner, MD (Principal Investigator); Charles Soltoff, MBA.
Project Office, National Heart, Lung, and Blood Institute, Bethesda, MD:
Gail Weinmann, MD (Project Officer); Joanne Deshler (Contracting Officer); Dean Follmann, PhD; James Kiley, PhD; Margaret Wu, PhD (1996–2001).
Rabe KF, Hurd S, Anzueto A, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med.
2007;176:532-555. [PubMed] [CrossRef]
Hogg JC. Pathophysiology of airflow limitation in chronic obstructive pulmonary disease. Lancet.
de Jong PA, Muller NL, Pare PD, et al. Computed tomographic imaging of the airways: relationship to structure and function. Eur Respir J.
Nakano Y, Muro S, Sakai H, et al. Computed tomographic measurements of airway dimensions and emphysema in smokers: correlation with lung function. Am J Respir Crit Care Med.
Hasegawa M, Nasuhara Y, Onodera Y, et al. Airflow limitation and airway dimensions in chronic obstructive pulmonary disease. Am J Respir Crit Care Med.
Orlandi I, Moroni C, Camiciottoli G, et al. Chronic obstructive pulmonary disease: thin-section CT measurement of airway wall thickness and lung attenuation. Radiology.
Washko GR, Criner GJ, Mohsenifar Z, et al. Computed tomographic-based quantification of emphysema and correlation to pulmonary function and mechanics. COPD.
Boschetto P, Miniati M, Miotto D, et al. Predominant emphysema phenotype in chronic obstructive pulmonary disease patients. Eur Respir J.
Snoeck-Stroband JB, Lapperre TS, Gosman MME, et al. Chronic bronchitis sub-phenotype within COPD: inflammation in sputum and biopsies. Eur Respir J.
Makita H, Nasuhara Y, Nagai K, et al. Characterisation of phenotypes based on severity of emphysema in chronic obstructive pulmonary disease. Thorax.
Patel BD, Coxson HO, Pillai SG, et al. Airway wall thickening and emphysema show independent familial aggregation in COPD. Am J Respir Crit Care Med.
Martinez FJ, Curtis JL, Sciurba F, et al. Sex differences in severe pulmonary emphysema. Am J Respir Crit Care Med.
Fishman A, Martinez F, Naunheim K, et al. A randomized trial comparing lung-volume-reduction surgery with medical therapy for severe emphysema. N Engl J Med.
American Thoracic Society Standardization of spirometry, 1994 update. Am J Respir Crit Care Med.
Eakin EG, Resnikoff PM, Prewitt LM, et al. Validation of a new dyspnea measure: the UCSD Shortness of Breath Questionnaire, University of California, San Diego. Chest.
Martinez FJ, Foster G, Curtis JL, et al. Predictors of mortality in patients with emphysema and severe airflow obstruction. Am J Respir Crit Care Med.
Washko GR, Fan VS, Ramsey SD, et al. The effect of lung volume reduction surgery on chronic obstructive pulmonary disease exacerbations. Am J Respir Crit Care Med.
Foreman MG, DeMeo DL, Hersh CP, et al. Polymorphic variation in surfactant protein B is associated with COPD exacerbations. Eur Respir J.
DeMeo DL, Hersh CP, Hoffman EA, et al. Genetic determinants of emphysema distribution in the National Emphysema Treatment Trial. Am J Respir Crit Care Med.
Nakano Y, Wong JC, de Jong PA, et al. The prediction of small airway dimensions using computed tomography. Am J Respir Crit Care Med.
San José Estépar R, Washko G, Silverman E, et al. Accurate airway wall estimation using phase congruency. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv. 2006;9:125-134
Dransfield MT, Washko GR, Foreman MG, et al. Gender differences in the severity of CT emphysema in COPD. Chest.
Ogawa E, Nakano Y, Ohara T, et al. Body mass index in male patients with COPD: correlation with low attenuation areas on CT. Thorax.
Miniati M, Filippi E, Falaschi F, et al. Radiologic evaluation of emphysema in patients with chronic obstructive pulmonary disease. Chest radiography versus high resolution computed tomography. Am J Respir Crit Care Med.
Yuan R, Mayo JR, Hogg JC, et al. The effects of radiation dose and CT manufacturer on measurements of lung densitometry. Chest.