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Original Research: COPD |

Diffusing Capacity for Carbon Monoxide Correlates Best With Tissue Volume From Quantitative CT Scanning AnalysisQuantitative Chest CT Scan Analysis in COPD FREE TO VIEW

Igor Barjaktarevic, MD; Steven Springmeyer, MD; Xavier Gonzalez, MD; William Sirokman, BS; Harvey O. Coxson, PhD; Christopher B. Cooper, MD, FCCP
Author and Funding Information

From the Division of Pulmonary and Critical Care Medicine (Drs Barjaktarevic and Cooper), Department of Medicine, and Department of Physiology (Dr Cooper), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA; Spiration, Inc (Drs Springmeyer and Gonzalez and Mr Sirokman), Redmond, WA; and Department of Radiology (Dr Coxson), UBC James Hogg Research Centre, Vancouver General Hospital, Vancouver, BC, Canada.

CORRESPONDENCE TO: Christopher B. Cooper, MD, FCCP, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, 10833 Le Conte Ave, 37-131 CHS, Los Angeles, CA 90095; e-mail: ccooper@mednet.ucla.edu


FUNDING/SUPPORT: This study was supported by Spiration Inc.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2015;147(6):1485-1493. doi:10.1378/chest.14-1693
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BACKGROUND:  Quantitative analysis of high-resolution chest CT scan (QCT) is an established method for determining the severity and distribution of lung parenchymal destruction in patients with emphysema. Diffusing capacity of the lung for carbon monoxide (Dlco) is a traditional physiologic measure of emphysema severity and is probably influenced more by destruction of the alveolar capillary bed than by membrane diffusion per se. We reasoned that Dlco should correlate with tissue volume from QCT.

METHODS:  A total of 460 patients with upper-lobe-predominant emphysema were enrolled in the study. The mean (SD) of percent predicted values for FEV1, total lung capacity, and Dlco were 30.6% (8.0%), 129.5% (18.1%), and 6.7% (13.1%), respectively. QCT was performed using custom software; the relationship between Dlco and various metrics from QCT were evaluated using Pearson correlation coefficients.

RESULTS:  On average, whole-body plethysmography volumes were higher by 841 mL compared with QCT-calculated total lung volume. However, there was a strong correlation between these measurements (r = 0.824, P < .0001). Dlco correlated with total lung volume (r = 0.314, P < .0001), total tissue volume (r = 0.498, P < .0001), and percentage of lung with low density (−950 Hounsfield units) (r = −0.337, P < .0001).

CONCLUSIONS:  In patients with severe emphysema, Dlco correlates best with total tissue volume, supporting the hypothesis that pulmonary capillary blood volume is the main determinant of Dlco in the human lung. The relationships between Dlco and various anatomic metrics of lung parenchymal destruction from QCT inform our understanding of the relationship between structure and function of the human lung.

Figures in this Article

Diffusing capacity of the lung for carbon monoxide (Dlco) is a traditional physiologic measure and is considered to be useful in the evaluation of emphysema severity.1 Dlco estimates the overall ability of the lung to transport gas into the blood across the alveolar-capillary interface and is determined by structural properties of the lung (eg, accessible alveolar gas volume, diffusion path length, alveolar capillary membrane surface area, and pulmonary capillary blood volume) as well as functional properties (eg, uniformity of ventilation and perfusion, composition of the alveolar gas, and binding properties of hemoglobin [Hb]).2 Diffusing capacity is estimated by measuring carbon monoxide (CO) uptake from the lung (transfer coefficient) and relating this to the volume of gas in the lung containing CO (effective alveolar volume).

Dlco was originally termed “transfer factor of the lung for CO.” The term diffusing capacity itself may be misleading, since gas transport is not exclusively determined by diffusion. The process of gas uptake depends on the two conductance properties: membrane conductance (DM), which reflects the diffusion properties of the alveolar capillary membrane, and the process of binding of gas and Hb, which can be represented as the product of the gas-Hb chemical reaction rate (θ) and the volume of Hb in alveolar capillary blood (Vc).2 Since these are conductances in series, their properties are classically represented by the following equation first described by Roughton and Forster (in which DL is diffusing capacity of the lung)3:
1DL=1DM+1θ×VC 

Understanding this concept is of exceptional value in certain situations (eg, patients with emphysema), where the destruction of alveolar walls directly affects the integrity of the capillary bed and, thus, reduces Dlco. Dlco is an excellent index of the degree of anatomic emphysema in smokers with airways obstruction.4 The reduction of Dlco in the patient with emphysema is probably influenced more by loss of alveolar capillary bed (1 / θ × Vc) and reduction of Vc than by membrane diffusion per se (1/DM). Applying this physiologic concept to pathology of patients with emphysema, we can hypothesize that a measurement of the lung parenchyma tissue volume would correlate well with Dlco in a patient with emphysema.

Quantitative analysis of high-resolution chest CT scan (QCT) of the lungs can provide investigators not only with spatial information about larger structures within the lung but also, through densitometry, information about the distribution of lung parenchymal destruction in patients with emphysema, and enables investigators to distinguish lung tissue and airspace. Emphysematous changes can be quantified using CT imaging based on identification of low attenuation areas (LAAs). These areas may reflect parenchymal destruction and enlargement of the airspaces5,6 The percentage of LAA per total lung volume (LAA%) has been shown to correlate with symptoms in patients with COPD and their pulmonary function.79

Multiple anatomic metrics derived from the attenuation values on CT scans have been claimed to reflect airway obstruction both in emphysema1,10,11 and COPD.1215 These indexes are shown to have good accuracy1,16,17 and repeatability.18 The severity of emphysema in the nonbullous parts of the lungs correlated well with measurements of airflow limitation and diffusing capacity.19 Correlation between total lung volumes measured by plethysmography and volume estimated by QCT has also been described.20 A low Dlco correlates highly with a low mean density of lung tissue on lung CT scans and with the degree of anatomic emphysema.2123

Smoking-related lung diseases represent a spectrum of changes to lung structure and function rather than a single disease.24 Therefore, there is a need for standardization of diagnostic criteria for conditions such as COPD.25 The potential of QCT scanning to assess both anatomic and physiologic aspects of lung disease makes it a desirable tool for the assessment of smoking-related lung diseases. Our goal was to explore correlations between parameters derived from QCT and Dlco.

Patient Selection

The patients reported in this analysis all presented with smoking-related, upper-lobe-predominant emphysema. They were evaluated and considered eligible for participation in one of five studies of bronchoscopic lung-volume reduction by implantation of intrabronchial valves (Spiration, Inc). The studies were carried out in North America, Europe, and South Africa (e-Tables 1, 2). Typical inclusion and exclusion criteria for these studies have been previously published23,2629 and are shown in Table 1. All centers received local ethics committee approval prior to enrolling patients in the trial. A total of 460 patients (263 men) with upper-lobe-predominant emphysema were enrolled in the five international clinical trials. The results of one of these studies have been published separately.28

Table Graphic Jump Location
TABLE 1 ]  Inclusion and Exclusion Criteria for Participation in the Study

Dlco = diffusing capacity of lung for carbon monoxide; PFT = pulmonary function test; RV = residual volume; Spo2 = arterial oxygen saturation; TLC = total lung capacity.

Radiologic Assessment

All patients underwent multislice CT scanning of the entire lung at suspended maximal inspiration in a supine position using GE Healthcare or Siemens Healthcare scanners. Contiguous slices (1.0 mm using Siemens Healthcare scanners, 1.25 mm using GE Healthcare scanners) were obtained using a standardized protocol (120 kVp, 130 mAs) and reconstructed using an intermediate reconstruction algorithm (Siemens b35f kernel, GE Healthcare standard kernel).30 All CT scans were analyzed using Pulmonary Workstation 2.0 software (VIDA Diagnostics Inc) (Fig 1). Briefly, the lungs were segmented from the thorax wall, the heart, and main pulmonary vessels, followed by segmentation of the individual lobes.31 The extent of emphysema (%LAA) was estimated using the threshold technique, quantifying the percent of the total lung voxels with an apparent radiograph attenuation value below −950 Hounsfield units.3134 Scans were excluded from quantitative image analysis if any radiographic abnormalities other than emphysema (eg, effusion, atelectasis, or consolidative processes) were present.

Figure Jump LinkFigure 1 –  CT scans were quantified using Pulmonary Workstation software (VIDA Diagnostics Inc). The lung is automatically segmented from the chest wall and subdivided into individual lobes. Each lobe is shown in the image using a different color and lobar volume is calculated by summing the number of CT scan voxels in each lobe and multiplying by the dimensions of the CT scan voxel. A, Three-dimensional lobar reconstruction of chest imaging of a study subject. B, The transverse, coronal, and sagittal images of the same patient.Grahic Jump Location
Pulmonary Function Testing

Physiologic measurements included FEV1, FVC, total lung capacity (TLC), residual volume (RV), and Dlco. FEV1 and FVC were obtained after administration of inhaled bronchodilator, TLC and RV were measured using body plethysmography, and Dlco was measured using the single-breath method. All pulmonary function testing was performed in accordance with American Thoracic Society and European Respiratory Society standards.2,35,36 Six-minute walking tests were also performed according to standardized guidelines.37

Health Status and Symptom Assessment

The St. George’s Respiratory Questionnaire (SGRQ) is a standardized, self-completed questionnaire for evaluation of health status, with scores ranging from 0 to 100 (higher scores indicate more impairment). The modified Medical Research Council (mMRC) scale was used as another subjective tool for the assessment of dyspnea in this cohort of patients. This scale has five statements that describe a range of respiratory disability, from none (grade 0) to almost complete incapacity (grade 4).

Statistical Analysis

Descriptive statistics for the study cohort are described by means and SDs. Comparison of QCT measurements with physiologic metrics was conducted using the Student t test. Correlations between structural and functional measures were explored using the Pearson correlation coefficient. The Wilcoxon signed-rank test was used if data were not normally distributed. The Spearman rank order correlation and Bland-Altman analysis were used for comparison of lung volumes measured by plethysmography and with QCT. Statistical significance was accepted if P < .05.

Baseline Patient Characteristics

The characteristics of patients (N = 460) are shown in Table 2. Their mean ± SD age was 64.2 ± 6.8 years, and mean BMI was 25.8 ± 5.0. Just over one-half of the cohort (57.2%) were men, and 42.8% of the patients were women. Pulmonary function testing was performed at the beginning of the study. Spirometry showed an average FEV1 / FVC of 32.8%. FEV1 was 30.6% ± 8.0% predicted and FVC was 71.8% ± 16.0% predicted. Patients had significant hyperinflation, with average TLC of 129.5% ± 18.1% predicted and markedly increased RV of 223.3% ± 56.5% predicted. Dlco was reduced at 36.7% ± 13.1% predicted.

Table Graphic Jump Location
TABLE 2 ]  Baseline Characteristics of the Subjects

6MWD = 6-min walking distance; mMRC = modified Medical Research Council; SGRQ = St George’s Respiratory Questionnaire. See Table 1 legend for expansion of other abbreviations.

Mean Pao2 was 67.6 ± 10.9 mm Hg, mean Paco2 was 40.2 ± 5.0 mm Hg, and average oxygen saturation (Spo2) was 93.7% ± 3.3%. The mean 6-min walking distance was 321.7 ± 93.3 m, average dyspnea score on the mMRC scale was 2.5 ± 0.8, and subjective evaluation of health status had a mean value of 57.2 ± 14.5 by the SGRQ.

Correlation Between QCT and Pulmonary Function

QCT parameters are presented in Table 3. Total (whole lung) volume measured by QCT was 6,717 ± 1,349 mL compared with average TLC measured by whole-body plethysmography (WBP) of 7,562 ± 1,512 mL. Accepting body plethysmography as a gold standard, on average, QCT underestimated total lung volume compared with plethysmography by 841 ± 860 mL (Fig 2). However, there was a strong correlation between these measurements (r = 0.82, P < .0001) (Fig 3). Mean TLC values were also compared with the total volume of air measured by QCT, and these values showed significant correlation as well (r = 0.81, P < .0001).

Table Graphic Jump Location
TABLE 3 ]  QCT Scan Findings for All Subjects

HU = Hounsfield units; QCT = quantitative analysis of high-resolution chest CT.

Figure Jump LinkFigure 2 –  Bland-Altman plot of the difference between TLC measured by QCT and WBP and mean TLC from both measurements (QCT + WBP) / 2. The mean (SD) bias was −841 (860) mL, indicating that QCT underestimates TLC compared with WBP. QCT = quantitative analysis of high-resolution chest CT; TLC = total lung capacity; WBP = whole-body plethysmography.Grahic Jump Location
Figure Jump LinkFigure 3 –  TLC derived from QCT plotted against TLC measured by WBP. See Figure 2 legend for expansion of abbreviations.Grahic Jump Location

Spirometric values (FEV1 and FVC) were compared with QCT parameters (Table 4), and these values showed significant correlations with volumes assessed by QCT: FVC correlated with whole lung volume (r = 0.562, P < .0001), tissue volume (r = 0.506, P < .0001), and air volume (r = 0.527, P < .0001). FEV1 showed the best correlation with total tissue volume measured by QCT (r = 0.488, P < .0001).

Table Graphic Jump Location
TABLE 4 ]  Correlation of Structural and Functional Measures of Emphysema

IC = inspiratory capacity. See Table 1, 2, and 3 legends for expansion of other abbreviations.

a 

Values represent Pearson correlation coefficient r value (P value).

Mean Dlco values correlated best with total tissue volume (r = 0.498, P < .0001) (Fig 4). Mean Dlco values also correlated with total lung volume (r = 0.314, P < .0001), total air volume (r = 0.265, P < .0001), average lung density (r = 0.268, P < .0001), and lung density scores below −950 Hounsfield units (r = −0.337, P < .0001) (Table 4).

Figure Jump LinkFigure 4 –  Correlation between Dlco percentage predicted and the total tissue volume measured by QCT. Dlco = diffusing capacity of the lung for carbon monoxide. See Figure 2 legend for expansion of other abbreviation.Grahic Jump Location

Our investigation of QCT scanning analysis in a large cohort of patients with severe emphysema has demonstrated that Dlco correlates best with total tissue volume, supporting the hypothesis that pulmonary capillary blood volume is the main determinant of Dlco in the human lung. The importance of pulmonary capillary blood volume as a determinant of Dlco is often underappreciated. However, Dlco depends not only on capillary blood volume and Hb binding but also on membrane properties and the distribution of the inspired air within the lung (ie, ventilation-perfusion relationships). Since our analysis shows that tissue volume accounts for only 25% of the variance in Dlco, these other factors are also likely to be important.

COPD is a disease of multiple phenotypes,38 and the pathophysiology of lung destruction has varying morphologic appearances.39 Anatomic differences between patients can help determine the management of COPD.40 For example, patients with a heterogeneous pattern of emphysema on CT scanning respond better to volume-reduction techniques than those with a homogeneous distribution.41 QCT imaging may play a significant role in differentiating phenotypes that may be amenable to bronchoscopic lung-volume reduction as opposed to conventional lung volume-reduction surgery.

QCT scanning of the lung is based on the absorbance of x-rays by lung tissue, which is directly related to the density of the lung, or the amount of tissue and air present in the lung.42 Previous studies have shown that the extent of emphysema present in the lung is directly correlated the percentage of radiographic attenuation values beyond a specific threshold.1,17,23,43,44 The use of QCT in studies of emphysema has become standard even though the relationship between physiologic measures, such as FVC, TLC, or RV, which assess function, and CT scan measurements can have widely varying results depending on the imaging techniques and software used.45,46 Our study included a large cohort of patients in which these correlations have been explored. Not only were we able to confirm various correlations but we were able to evaluate, with reasonable confidence, the relative strengths of these correlations. TLC measured by plethysmography correlates best with whole lung volume measured by QCT (r = 0.824, P < .0001) and correlates almost equally well with the total air volume assessed by QCT (r = 0.807, P < .0001) but not as well with the total tissue volume (r = 0.559, P < .0001). Comparing TLC measured via QCT and TLC measured with body plethysmography, we observed consistent differences. Other investigators have reported a discrepancy between TLC measured by body plethysmography and other techniques, suggesting that worsening airflow obstruction leads to increasing overestimation of TLC by plethysmography.47 TLC is expected to be lower in the supine vs upright posture, even when measured with the same technique.48 However, the reported difference in volumes between the two postures in normal subjects was considerably less (305 mL) than the difference in volumes we found comparing QCT with WBP in patients with COPD.48 As WBP assumes that the volume of abdominal gas is insignificant and not compressed, it is interesting to hypothesize that TLC measured by properly calibrated QCT may actually be a more accurate estimate of lung volumes in comparison with WBP.

Fairly good and statistically significant correlations between spirometric values (FVC and FEV1) and QCT-assessed lung volumes demonstrate the potential of an imaging tool to assess pulmonary function. The relatively high correlation of FVC and whole-lung volume measured by QCT agrees with previously published data.4951 However, an interesting new observation is that FEV1 best correlates inversely with total tissue volume (r = 0.49, P < .0001) in comparison with whole lung volume or air volume. This may be explained by the fact that significant deterioration in FEV1, one of key elements used in grading COPD severity,25 best reflects tissue destruction due to emphysema rather than air trapping or hyperinflation. The FEV1 has many limitations. Traditionally, it has been thought of as a measure of airway function, perhaps because of its potential responsiveness to bronchodilator therapy. Our study suggests that FEV1 is also determined, to an important degree, by lung elastic recoil. This reaffirms that lung compliance as well as airway resistance are both important determinants of the ease of lung emptying. Another study of dynamic hyperinflation induced by metronome-paced tachypnea showed that air trapping correlated better with Dlco than FEV1, leading to a similar conclusion.52

One of the most interesting findings in this study was the correlation between the extent of lung tissue destruction and the Dlco. Dlco correlated with QCT measures of lung volume, tissue volume, air volume, and lung density scores. Similar to the FEV1, tissue volume was the measure with the strongest correlation with Dlco (r = 0.498, P < .0001). This finding supports the hypothesis that pulmonary capillary blood volume is the main determinant of Dlco in the human lung. More importantly, the strong correlation between Dlco and various anatomic metrics of lung parenchymal destruction from QCT may raise additional interest in the further development and evaluation of QCT as a tool for understanding the relationship between structure and function of the human lung.

The use of QCT for the evaluation of lung structure and function has certain limitations. Besides the cost and patient exposure to radiation, QCT measurements may be influenced by technical problems such as suboptimal inspiration or expiration. Low-dose CT scanning can reduce radiation exposure to acceptable levels for one-time patient assessment53; however, for longitudinal follow-up, cumulative radiation exposure will remain problematic, along with image registration to allow accurate comparison and detection of meaningful change. The number and thickness of scanner cuts, as well as the software generating measured parameters, need additional standardization. One of the major limitations of our study is the narrow clinical characteristics of the population of patients studied. All patients had advanced upper-lobe-predominant emphysema. Our findings might not necessarily apply to other COPD phenotypes, such as those with predominant airway disease increased airway wall thickening.54

In conclusion, our study is one of the largest studies evaluating QCT chest scanning of subjects with advanced COPD and emphysema. Our data confirm previously reported correlations between lung volumes measured by WBP and QCT. In addition, we have shown that other lung function parameters, such as spirometric volumes and Dlco, correlate with structural measures from QCT. Most importantly, our data support the hypothesis that Dlco is most strongly influenced by pulmonary capillary blood volume, since the strongest correlation with Dlco is the inverse relationship with tissue volume from QCT. QCT will continue to be evaluated as a means of linking lung structure with physiologic function, thus helping us develop a better understanding of different COPD phenotypes and potential treatment approaches.

Author contributions: C. B. C. had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. I. B. served as principal author. S. S., X. G., H. O. C., and C. B. C. contributed to the study concept and design; data acquisition, analysis, and interpretation; and manuscript revision; I. B. contributed to data analysis and revision and writing the manuscript; and W. S. contributed to data analysis and manuscript revision.

Financial/nonfinancial disclosures: The authors have reported to CHEST the following conflicts of interest: Dr Springmeyer was the medical director of Spiration Inc from July 2001 through May 2013. Dr Gonzalez is a full-time employee and chief scientific officer for Spiration Inc, part of Olympus Medical (Olympus America Inc); he is listed on several patents for the IBV Valve System; however, the patent rights are owned by the company. Dr Coxson was the nominated principal investigator on a Canadian Institutes of Health Research grant from 2009 to 2014, served on the steering committee for the ECLIPSE project for GlaxoSmithKline plc in 2011-2012, had a service agreement with Spiration Inc to measure changes in lung volume in subjects with severe emphysema, and was the recipient of a GlaxoSmithKline plc Clinical Scientist Award in 2010. Dr Cooper currently serves on the scientific steering committee for an ongoing Spiration Inc clinical trial and has received consulting fees over the past 3 years for his participation, and has received research consulting fees for analysis of data relating to IBV clinical trials. Dr Barjaktarevic and Mr Sirokman have reported that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Role of sponsors: Aside from providing access to the data from its clinical trials, the sponsor did not have any other involvement in the analysis or writing of this paper other than through the contributions of the coauthors that have been described in the Author contributions section.

Additional information: The e-Tables can be found in the Supplemental Materials section of the online article.

CO

carbon monoxide

Dlco

diffusing capacity of the lung for carbon monoxide

Hb

hemoglobin

LAA

low attenuation area

mMRC

modified Medical Research Council

QCT

quantitative analysis of high-resolution chest CT scan

RV

residual volume

SGRQ

St. George’s Respiratory Questionnaire

Spo2

arterial oxygen saturation

TLC

total lung capacity

Vc

pulmonary capillary blood volume

WPB

whole-body plethysmography

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Coxson HO, Dirksen A, Edwards LD, et al; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Investigators. The presence and progression of emphysema in COPD as determined by CT scanning and biomarker expression: a prospective analysis from the ECLIPSE study. Lancet Respir Med. 2013;1(2):129-136. [CrossRef] [PubMed]
 
Sciurba FC, Ernst A, Herth FJ, et al; VENT Study Research Group. A randomized study of endobronchial valves for advanced emphysema. N Engl J Med. 2010;363(13):1233-1244. [CrossRef] [PubMed]
 
Gietema HA, Müller NL, Fauerbach PV, et al; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) investigators. Quantifying the extent of emphysema: factors associated with radiologists’ estimations and quantitative indices of emphysema severity using the ECLIPSE cohort. Acad Radiol. 2011;18(6):661-671. [CrossRef] [PubMed]
 
Miller MR, Hankinson J, Brusasco V, et al; ATS/ERS Task Force. Standardisation of spirometry. Eur Respir J. 2005;26(2):319-338. [CrossRef] [PubMed]
 
Wanger J, Clausen JL, Coates A, et al. Standardisation of the measurement of lung volumes. Eur Respir J. 2005;26(3):511-522. [CrossRef] [PubMed]
 
ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med. 2002;166(1):111-117. [CrossRef] [PubMed]
 
Reilly JJ. COPD and declining FEV1—time to divide and conquer? N Engl J Med. 2008;359(15):1616-1618. [CrossRef] [PubMed]
 
Takahashi M, Fukuoka J, Nitta N, et al. Imaging of pulmonary emphysema: a pictorial review. Int J Chron Obstruct Pulmon Dis. 2008;3(2):193-204. [PubMed]
 
Coxson HO. Computed tomography and monitoring of emphysema. Eur Respir J. 2007;29(6):1075-1077. [CrossRef] [PubMed]
 
Fishman A, Martinez F, Naunheim K, et al; National Emphysema Treatment Trial Research Group. A randomized trial comparing lung-volume-reduction surgery with medical therapy for severe emphysema. N Engl J Med. 2003;348(21):2059-2073. [CrossRef] [PubMed]
 
Hedlund LW, Anderson RF, Goulding PL, Beck JW, Effmann EL, Putman CE. Two methods for isolating the lung area of a CT scan for density information. Radiology. 1982;144(2):353-357. [CrossRef] [PubMed]
 
Gevenois PA, Yernault JC. Can computed tomography quantify pulmonary emphysema? Eur Respir J. 1995;8(5):843-848. [PubMed]
 
Madani A, Zanen J, de Maertelaer V, Gevenois PA. Pulmonary emphysema: objective quantification at multi-detector row CT—comparison with macroscopic and microscopic morphometry. Radiology. 2006;238(3):1036-1043. [CrossRef] [PubMed]
 
Yasunaga K, Cherot-Kornobis N, Edme JL, Sobaszek A, Boulenguez C, Duhamel A, et al. Emphysema in asymptomatic smokers: quantitative CT evaluation in correlation with pulmonary function tests. Diagn Interv Imaging. 2013;94(6):609-617. [CrossRef] [PubMed]
 
Garfield JL, Marchetti N, Gaughan JP, Steiner RM, Criner GJ. Total lung capacity by plethysmography and high-resolution computed tomography in COPD. Int J Chron Obstruct Pulmon Dis. 2012;7:119-126. [CrossRef] [PubMed]
 
O’Donnell CR, Bankier AA, Stiebellehner L, Reilly JJ, Brown R, Loring SH. Comparison of plethysmographic and helium dilution lung volumes: which is best for COPD? Chest. 2010;137(5):1108-1115. [CrossRef] [PubMed]
 
Whitfield AG, Waterhouse JA, Arnott WM. The total lung volume and its subdivisions; a study in physiological norms; the effect of posture. Br J Soc Med. 1950;4(2):86-97. [PubMed]
 
Jang YM, Oh YM, Seo JB, et al. Quantitatively assessed dynamic contrast-enhanced magnetic resonance imaging in patients with chronic obstructive pulmonary disease: correlation of perfusion parameters with pulmonary function test and quantitative computed tomography. Invest Radiol. 2008;43(6):403-410. [CrossRef] [PubMed]
 
Lee YK, Oh YM, Lee JH, et al; KOLD Study Group. Quantitative assessment of emphysema, air trapping, and airway thickening on computed tomography. Lung. 2008;186(3):157-165. [CrossRef] [PubMed]
 
Mets OM, Murphy K, Zanen P, et al. The relationship between lung function impairment and quantitative computed tomography in chronic obstructive pulmonary disease. Eur Radiol. 2012;22(1):120-128. [CrossRef] [PubMed]
 
Weigt SS, Abrazado M, Kleerup EC, Tashkin DP, Cooper CB. Time course and degree of hyperinflation with metronome-paced tachypnea in COPD patients. COPD. 2008;5(5):298-304. [CrossRef] [PubMed]
 
Bull DA, Fann JI; AATS Centennial Committee. Historical perspectives of The American Association for Thoracic Surgery: Frank Gerbode (1907-1984). J Thorac Cardiovasc Surg. 2013;146(6):1317-1320. [CrossRef] [PubMed]
 
Fan L, Xia Y, Guan Y, Zhang TF, Liu SY. Characteristic features of pulmonary function test, CT volume analysis and MR perfusion imaging in COPD patients with different HRCT phenotypes. Clin Respir J. 2014;8(1):45-54. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1 –  CT scans were quantified using Pulmonary Workstation software (VIDA Diagnostics Inc). The lung is automatically segmented from the chest wall and subdivided into individual lobes. Each lobe is shown in the image using a different color and lobar volume is calculated by summing the number of CT scan voxels in each lobe and multiplying by the dimensions of the CT scan voxel. A, Three-dimensional lobar reconstruction of chest imaging of a study subject. B, The transverse, coronal, and sagittal images of the same patient.Grahic Jump Location
Figure Jump LinkFigure 2 –  Bland-Altman plot of the difference between TLC measured by QCT and WBP and mean TLC from both measurements (QCT + WBP) / 2. The mean (SD) bias was −841 (860) mL, indicating that QCT underestimates TLC compared with WBP. QCT = quantitative analysis of high-resolution chest CT; TLC = total lung capacity; WBP = whole-body plethysmography.Grahic Jump Location
Figure Jump LinkFigure 3 –  TLC derived from QCT plotted against TLC measured by WBP. See Figure 2 legend for expansion of abbreviations.Grahic Jump Location
Figure Jump LinkFigure 4 –  Correlation between Dlco percentage predicted and the total tissue volume measured by QCT. Dlco = diffusing capacity of the lung for carbon monoxide. See Figure 2 legend for expansion of other abbreviation.Grahic Jump Location

Tables

Table Graphic Jump Location
TABLE 1 ]  Inclusion and Exclusion Criteria for Participation in the Study

Dlco = diffusing capacity of lung for carbon monoxide; PFT = pulmonary function test; RV = residual volume; Spo2 = arterial oxygen saturation; TLC = total lung capacity.

Table Graphic Jump Location
TABLE 2 ]  Baseline Characteristics of the Subjects

6MWD = 6-min walking distance; mMRC = modified Medical Research Council; SGRQ = St George’s Respiratory Questionnaire. See Table 1 legend for expansion of other abbreviations.

Table Graphic Jump Location
TABLE 3 ]  QCT Scan Findings for All Subjects

HU = Hounsfield units; QCT = quantitative analysis of high-resolution chest CT.

Table Graphic Jump Location
TABLE 4 ]  Correlation of Structural and Functional Measures of Emphysema

IC = inspiratory capacity. See Table 1, 2, and 3 legends for expansion of other abbreviations.

a 

Values represent Pearson correlation coefficient r value (P value).

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Coxson HO, Nasute Fauerbach PV, Storness-Bliss C, et al. Computed tomography assessment of lung volume changes after bronchial valve treatment. Eur Respir J. 2008;32(6):1443-1450. [CrossRef] [PubMed]
 
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Coxson HO, Dirksen A, Edwards LD, et al; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Investigators. The presence and progression of emphysema in COPD as determined by CT scanning and biomarker expression: a prospective analysis from the ECLIPSE study. Lancet Respir Med. 2013;1(2):129-136. [CrossRef] [PubMed]
 
Sciurba FC, Ernst A, Herth FJ, et al; VENT Study Research Group. A randomized study of endobronchial valves for advanced emphysema. N Engl J Med. 2010;363(13):1233-1244. [CrossRef] [PubMed]
 
Gietema HA, Müller NL, Fauerbach PV, et al; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) investigators. Quantifying the extent of emphysema: factors associated with radiologists’ estimations and quantitative indices of emphysema severity using the ECLIPSE cohort. Acad Radiol. 2011;18(6):661-671. [CrossRef] [PubMed]
 
Miller MR, Hankinson J, Brusasco V, et al; ATS/ERS Task Force. Standardisation of spirometry. Eur Respir J. 2005;26(2):319-338. [CrossRef] [PubMed]
 
Wanger J, Clausen JL, Coates A, et al. Standardisation of the measurement of lung volumes. Eur Respir J. 2005;26(3):511-522. [CrossRef] [PubMed]
 
ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med. 2002;166(1):111-117. [CrossRef] [PubMed]
 
Reilly JJ. COPD and declining FEV1—time to divide and conquer? N Engl J Med. 2008;359(15):1616-1618. [CrossRef] [PubMed]
 
Takahashi M, Fukuoka J, Nitta N, et al. Imaging of pulmonary emphysema: a pictorial review. Int J Chron Obstruct Pulmon Dis. 2008;3(2):193-204. [PubMed]
 
Coxson HO. Computed tomography and monitoring of emphysema. Eur Respir J. 2007;29(6):1075-1077. [CrossRef] [PubMed]
 
Fishman A, Martinez F, Naunheim K, et al; National Emphysema Treatment Trial Research Group. A randomized trial comparing lung-volume-reduction surgery with medical therapy for severe emphysema. N Engl J Med. 2003;348(21):2059-2073. [CrossRef] [PubMed]
 
Hedlund LW, Anderson RF, Goulding PL, Beck JW, Effmann EL, Putman CE. Two methods for isolating the lung area of a CT scan for density information. Radiology. 1982;144(2):353-357. [CrossRef] [PubMed]
 
Gevenois PA, Yernault JC. Can computed tomography quantify pulmonary emphysema? Eur Respir J. 1995;8(5):843-848. [PubMed]
 
Madani A, Zanen J, de Maertelaer V, Gevenois PA. Pulmonary emphysema: objective quantification at multi-detector row CT—comparison with macroscopic and microscopic morphometry. Radiology. 2006;238(3):1036-1043. [CrossRef] [PubMed]
 
Yasunaga K, Cherot-Kornobis N, Edme JL, Sobaszek A, Boulenguez C, Duhamel A, et al. Emphysema in asymptomatic smokers: quantitative CT evaluation in correlation with pulmonary function tests. Diagn Interv Imaging. 2013;94(6):609-617. [CrossRef] [PubMed]
 
Garfield JL, Marchetti N, Gaughan JP, Steiner RM, Criner GJ. Total lung capacity by plethysmography and high-resolution computed tomography in COPD. Int J Chron Obstruct Pulmon Dis. 2012;7:119-126. [CrossRef] [PubMed]
 
O’Donnell CR, Bankier AA, Stiebellehner L, Reilly JJ, Brown R, Loring SH. Comparison of plethysmographic and helium dilution lung volumes: which is best for COPD? Chest. 2010;137(5):1108-1115. [CrossRef] [PubMed]
 
Whitfield AG, Waterhouse JA, Arnott WM. The total lung volume and its subdivisions; a study in physiological norms; the effect of posture. Br J Soc Med. 1950;4(2):86-97. [PubMed]
 
Jang YM, Oh YM, Seo JB, et al. Quantitatively assessed dynamic contrast-enhanced magnetic resonance imaging in patients with chronic obstructive pulmonary disease: correlation of perfusion parameters with pulmonary function test and quantitative computed tomography. Invest Radiol. 2008;43(6):403-410. [CrossRef] [PubMed]
 
Lee YK, Oh YM, Lee JH, et al; KOLD Study Group. Quantitative assessment of emphysema, air trapping, and airway thickening on computed tomography. Lung. 2008;186(3):157-165. [CrossRef] [PubMed]
 
Mets OM, Murphy K, Zanen P, et al. The relationship between lung function impairment and quantitative computed tomography in chronic obstructive pulmonary disease. Eur Radiol. 2012;22(1):120-128. [CrossRef] [PubMed]
 
Weigt SS, Abrazado M, Kleerup EC, Tashkin DP, Cooper CB. Time course and degree of hyperinflation with metronome-paced tachypnea in COPD patients. COPD. 2008;5(5):298-304. [CrossRef] [PubMed]
 
Bull DA, Fann JI; AATS Centennial Committee. Historical perspectives of The American Association for Thoracic Surgery: Frank Gerbode (1907-1984). J Thorac Cardiovasc Surg. 2013;146(6):1317-1320. [CrossRef] [PubMed]
 
Fan L, Xia Y, Guan Y, Zhang TF, Liu SY. Characteristic features of pulmonary function test, CT volume analysis and MR perfusion imaging in COPD patients with different HRCT phenotypes. Clin Respir J. 2014;8(1):45-54. [CrossRef] [PubMed]
 
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