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Original Research |
1 Department of Radiology, Royal Brompton Hospital, Sydney St., London SW3 6NP,
England.
2 Interstitial Lung Disease Unit, Royal Brompton Hospital, London,
England.
3 Department Of Radiology, King'S College Hospital, London, England.
4 Department of Radiology, The London Chest Hospital, London, England.
5 Department of Radiology, St. Mary's Hospital, London, England.
6 Department of Radiology, Christchurch Hospital, Auckland, New Zealand.
Received October 10, 2004;
accepted after revision December 8, 2004.
Address correspondence to Z. A. Aziz
(z.aziz{at}rbh.nthames.nhs.uk).
Abstract
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MATERIALS AND METHODS. The extent of emphysema on high-resolution CT was quantified by density masking in 101 patients. CT scans were evaluated for airway abnormalities (bronchial wall thickness, extent of bronchiectasis, bronchial dilatation, and evidence of small airways disease) and disease heterogeneity (uniformity, core-rind distribution, craniocaudal distribution, and lung texture). Stepwise regression analysis was used to determine CT features that influenced forced expiratory volume in 1 sec (FEV1) and the single-breath diffusing capacity for carbon monoxide (DLCO) for a given extent of emphysema.
RESULTS. The extent of emphysema using automated estimation was 28.4% ± 12.3% (mean ± SD). On univariate analysis the extent of emphysema correlated strongly with FEV1 (R = -0.63, p < 0.0005) and DLCO (R = -0.63, p < 0.0005) levels. Stepwise regression analysis revealed that bronchial wall thickness and the extent of emphysema were the strongest independent determinants of FEV1 (model R2 = 0.49; p = 0.002 and < 0.001, respectively); the extent of bronchiectasis and degree of bronchial dilation did not separately influence FEV1 levels. The only morphologic features linked to DLCO levels on multivariate analysis were increasingly extensive emphysema and a higher proportion of emphysema in the core region (model R2 = 0.45; p < 0.001 and 0.002, respectively).
CONCLUSION. The important additional CT abnormalities in individuals with emphysema that influence FEV1 and DLCO levels irrespective of disease extent are bronchial wall thickness and core-rind heterogeneity, respectively. These observations have implications for the accurate functional assessment of patients considered for lung volume reduction surgery.
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In the present study, we explored relationships between specific lung function parameters (FEV1 and DLCO) and morphologic features on CT. Both large- and small-airways abnormalities and the distribution of emphysema were evaluated. The specific aim was to determine whether these ancillary CT features influence airflow obstruction and gas transfer levels once the extent of emphysema is taken into account.
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1-antitrypsin deficiency (n = 4) were
excluded. Our ethics committee has given approval for retrospective analyses
of clinical and imaging data.
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CT Technique
CT scans were obtained on an electron beam CT scanner (Imatron, GE
Healthcare). Thin sections (1-3 mm) at 10-mm intervals were obtained in all
patients. Patients were scanned in the supine position with images obtained at
full inspiration. Images were reconstructed with a high-spatial-resolution
algorithm and photographed at appropriate window settings (level, -500 H;
width, 1,500 H). None of the patients received IV contrast material.
CT Estimation of Emphysema Extent: Automated Densitometric Quantification
The extent of emphysema was quantified on each CT section using an
automated "density mask" technique in which voxels with
attenuation values below a specific threshold are highlighted
[12,
13]. The technique involved
the segmentation of anatomic structures, the use of gradient correction to
compensate for the density differences in the lung parenchyma due to gravity,
and the application of a classification algorithm that identified and measured
the areas of decreased attenuation corresponding to diseased lung
[13]. The cutoff level between
normal lung density and abnormal low-attenuation lung was defined as -950 H,
because this value accurately predicts the macroscopic and microscopic extent
of emphysema [9,
14].
The percentage of low-attenuation emphysematous destruction was calculated for the whole lung.
Analysis of Airway Abnormalities
Two experienced chest radiologists independently scored the six lobes (the
lingula was regarded as a separate lobe). The extent of bronchiectasis was
graded as follows: grade 1, localized bronchiectasis affecting one or part of
one bronchopulmonary segment; grade 2, bronchiectasis in more than one
bronchopulmonary segment; and grade 3, generalized cystic bronchiectasis. The
severity of bronchial dilatation was quantified by comparing the internal
diameter of the bronchus to its adjacent pulmonary artery: grade 0, no
bronchiectasis; grade 0.5, trivial dilatation; grade 1, 100-200% arterial
diameter; grade 2, > 200-300% arterial diameter; and grade 3, > 300%
arterial diameter. Bronchial wall thickness was similarly quantified relative
to the adjacent pulmonary artery: grade 0, none; grade 0.5, trivial bronchial
wall thickening; grade 1, < 50% of the arterial diameter
(Fig. 1); grade 2, 50-100% of
the arterial diameter; and grade 3, > 100% of the arterial diameter. If a
mosaic attenuation pattern was present, the decreased attenuation component
that was attributable to small airways disease in each lobe was also
quantified using the following scale: grade 0, none; grade 1, 25%; grade 2,
26-50%; grade 3, 51-75%; grade 4, > 75-100%.
The total lung score for each CT feature was derived by summing the scores for each lobe; the final scores used in analysis were the sum of the total lung scores of both observers.
Analysis of Heterogeneity of Emphysema
On the basis of previous studies, four aspects of disease heterogeneity
were visually scored. All images for analysis and the division of lung into
regions for method 1 and into core-rind areas for method 2 were preselected by
a third chest radiologist, who was not one of the two observers.
Method 1: overall uniformity (adapted from Wisser et al. [15])—The purpose of this scoring method was to quantify the overall uniformity of emphysematous destruction within the lungs. Three anatomic levels were defined: the upper border of the aortic arch, 2 cm below the level of the carina, and 2 cm above the highest diaphragmatic dome. At each level, each lung was divided into two regions by a horizontal line, its position ensuring that each lung was separated according to the most prominent difference in the extent of emphysema. Each region had to be at least 30% of the whole lung area. The amount of destroyed lung parenchyma (severity of emphysema) in all of the resulting 12 segments was graded: grade 0, normal lung; grade 1 (mild), 25% air space compared with lung; grade 2 (moderate), 25-50% air space; grade 3 (marked), 50% air space; or grade 4 (severe), no normal lung [16]. The difference between the median of the three highest scores and the median of the three lowest scores was calculated and used to express the overall degree of heterogeneity from 0 (homogeneous) to 4 (marked heterogeneity) (Figs. 2A, 2B, and 2C).
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Method 4: texture of lung—The aim was to identify individuals with a pattern of emphysema that was not diffuse, but clustered, with admixed islands of normal lung. Five levels were analyzed: The three levels used for the other methods and two further levels were chosen so that the five levels were equally spaced throughout the lung. At each level the right and left lungs were assessed separately and graded as follows: grade 1, predominantly centrilobular emphysema; grade 2, predominantly panacinar emphysema; or grade 3, contiguous areas of normal or near-normal lung that occupy and total between 25% and 65% of the lung being assessed. If grade 3 was scored, then the percentage of this area was approximated to the nearest 5%. The area of normal or near-normal lung was termed an "island" (Figs. 4, 5A, and 5B). For analysis, the percentage of islands for each patient was calculated (number of sections with islands / total number of sections with emphysema).
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Statistical Analysis
Population clinical characteristics, CT extent of emphysema, and pulmonary
function indexes are expressed as means or medians depending on data
distribution. Univariate correlations were examined using Spearman's rank
correlation coefficient (R). Independent relationships between CT
features and pulmonary function indexes were identified using stepwise
regression models, with individual functional indexes evaluated as the
dependent variables in separate models. The variance of the physiologic
variables accounted for by the CT features is expressed as the square of the
correlation coefficient (R2). The assumptions of multiple
linear regression were met in all analyses as judged by testing for
heteroscedasticity and omitted variables. A p value of less than 0.05
was taken to indicate statistical significance. Interobserver agreement in
categoric variables was quantified using the weighted kappa coefficient
(
w) [19].
All statistical analyses were performed using STATA software (version 4.0,
StataCorp).
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Interobserver agreement for global CT scores was good for bronchial wall
thickness (w = 0.67), extent of bronchiectasis
(w = 0.69), and bronchial dilatation (w =
0.69). The prevalence of high-resolution CT features of obliterative small
airways disease (n = 7) was too low to warrant analysis.
Interobserver agreement for heterogeneity scores on CT was good for
craniocaudal distribution of disease (method 3) (w = 0.79),
the assessment of overall uniformity of emphysematous destruction (method 1)
(w = 0.70), and core-rind heterogeneity (method 2)
(w = 0.65) and were moderate for the assessment of lung
texture (method 4) (w = 0.45).
As shown in Table 2, there were significant correlations between FEV1 and the overall uniformity of emphysematous destruction, the severity of bronchial wall thickening, and the extent of bronchiectasis. Similar relationships were observed between the first two CT variables and DLCO. Significant independent relationships, as identified by regression models between FEV1 and DLCO, and CT features are shown in Table 3. Stepwise regression analysis revealed that bronchial wall thickness and the extent of emphysema were the strongest independent determinants of FEV1 (R2 = 0.49; regression coefficient [RC] = -3.42 and -1.27, p = 0.002 and < 0.001, respectively). In the regression model, the extent of bronchiectasis and bronchial dilatation were not significant independent predictors of FEV1.
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In multivariate stepwise regression analysis, only core-rind heterogeneity independently predicted DLCO; a higher percentage of emphysema in the core was associated with a reduction in DLCO. The combination of the extent of emphysema and the percentage of emphysema in the core region accounted for 45% of the variability of DLCO (R2 = 0.45, RC = -1.01 and -0.52, p < 0.001 and 0.002, respectively). In the regression model, craniocaudal heterogeneity, overall uniformity, or lung texture were not retained as a significant determinant of DLCO.
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Our study has shown that bronchial wall thickness and the proportion of emphysema within the core, or central part of the lung, as judged by high-resolution CT modify the fundamental relationship between the overall extent of emphysema and FEV1 and DLCO levels, respectively. The correlation between the extent of emphysema and the severity of airflow obstruction is well recognized [2, 7, 26]. However, outliers are common, with many patients having severe airway obstruction (as measured by FEV1 and residual volume) but apparently limited emphysema on CT [7, 27]. Other studies have failed to show a direct relationship between the extent of alveolar wall destruction and the severity of airflow obstruction [28-30], suggesting that the extent of emphysema is not the only morphologic abnormality causing airflow obstruction.
In our study, significant correlations were observed between FEV1 and the uniformity of emphysema and between the extent of bronchiectasis and the degree of bronchial wall thickening, with regression analysis showing that bronchial wall thickness was the important determinant of FEV1. This feature and the extent of emphysema accounted for 49% of the variability of FEV1. The negative relationship between bronchial wall thickness and FEV1 is in agreement with a study by Nakano et al. [31]. In that study, the wall thickness of a single segmental airway (superior segment of right upper lobe) was measured using an airway analysis software program [31]. In our study, a global estimation was made of airway wall thickness, bronchial dilatation, and extent of bronchiectasis and small airways disease, which would seem appropriate when attempting to evaluate the contribution of airway abnormalities to parameters of airflow limitation.
Although pathologic studies have suggested a role for small airway disease in airflow limitation in emphysema [21, 32], we were unable to assess the contribution of small airway disease to airflow limitation in emphysema because of the small number of cases in which the presence of small airway disease was reported. A mosaic attenuation pattern on high-resolution CT representing small airway disease is difficult, if not impossible, to identify on an inhomogeneous background of widespread emphysema [33]. Consequently, it remains uncertain whether the low scores of mosaic attenuation pattern reflect a true or spuriously low prevalence of this pattern. The difficulty in distinguishing between the two conditions highlights a limitation of our study; the word-search method of selecting patients with emphysema may have resulted in some cases of obliterative small airway disease being included as "emphysema" cases. In addition, very subtle emphysema tends to be underreported, and these individuals would not have been identified by our word-search method.
Our results also showed that the severity of bronchial dilatation was not an independent predictor of FEV1. Nakano et al. [31] found that in patients with emphysema, those with a larger luminal area of the superior segmental bronchus of the right upper lobe had less severe airflow obstruction. Although this may be true for univariate analysis, in the regression model, bronchial dilatation was not a significant factor in determining the variability of FEV1. Our results also indicate that the distribution of emphysema does not independently influence FEV1.
The core-rind distribution of emphysema emerged as a determinant of gas transfer in the present study. We found that an increased percentage of emphysema within the core region was associated with a lower DLCO and this finding supports those of two previous studies [17, 34]. A potential explanation for this observation is that pulmonary blood flow is significantly greater in the central region of the lung compared with the periphery [35]; therefore, destruction of the lung in this region has a greater effect on gas transfer than similar changes in the periphery of the lung.
Strikingly, no other aspect of disease heterogeneity was found to influence DLCO. The finding that the craniocaudal distribution of disease did not independently predict the variability of gas transfer may at first appear surprising. Several previous studies have shown a stronger correlation between the percentage of emphysema within the lower zone and DLCO than with the upper zone [26, 34]; however, while the zonal distribution of emphysema may differentially affect DLCO, this effect vanishes when the overall extent of emphysema is taken into account in multivariate analysis. Similarly, the hypothesis that large islands of spared lung among emphysematous areas would result in relative preservation of gas transfer, compared with a uniform distribution of emphysema, was not supported by our findings.
The study design necessitated the inclusion of several methods of defining disease heterogeneity, which were modeled on methods used by previous investigators. Undoubtedly, there is an inherent subjectivity involved in the semiquantitative methods used; however, some of the variables assessed (particularly the analysis of lung texture) do not lend themselves to quantification using automated methods. In support of our methods, agreement between our two observers ranged from moderate to good for all analyses of disease heterogeneity.
In conclusion, we have shown that in patients with emphysema, bronchial wall thickness and core-rind heterogeneity are important high-resolution CT features that influence FEV1 and DLCO levels, respectively. These observations may explain the disparity that is sometimes encountered between the extent of emphysema at CT and measurements of airflow obstruction and gas transfer. Our observations should enable a more accurate functional assessment of patients being considered for lung volume reduction surgery.
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