Figure 1.
Study design and flow of patients through the study.
Figure 2.
Histogram of emphysema severity.
LAA% was assessed in 70 patients with COPD. LAA% in all current smokers was <35%. Severe emphysema was defined as ≥35% of LAA%, and former smokers with severe emphysema were excluded from the study.
Figure 3.
Schematic explanation of model simulation.
Representative CT images from current smokers are shown as binary images, in which black and gray represent pixels with low attenuation and normal density, respectively (A). One pixel was selected from all pixels with normal density and changed to new low attenuation according to two models. Probabilities of selecting pixels between extant low attenuation clusters leading to their coalescence were determined in advance for both models. According to coalescence rates, pixels with normal density were changed into new pixels with low attenuation leading to coalescence or appearance/enlargement of low attenuation clusters (yellow and green pixels, respectively). New, low-attenuation pixels were randomly selected from among all pixels with normal density in the random model (B). Normal density pixels were identified (C) among local advanced emphysematous lesions (blue pixels) in the damage-dependent model, and then new low attenuation pixels were randomly selected from these relatively damaged local lesions (D).
Table 1.
Characteristics of study patients at baseline computed tomography scan (n = 53).
Table 2.
Annual changes in lung function and computed tomography parameters in current and former smokers (n = 53).
Table 3.
Multivariate regression analysis of relative contribution of each variable to predict annual changes in CT parameters of emphysema (n = 53).
Figure 4.
Relationships between annual changes in lung volume and emphysema parameters.
A, B, and C show relationships between annual changes in CT-TLV and LAA%, D, and LAN, respectively, in 22 current and 31 former smokers with mild to moderate emphysema. Closed and open circles, current and former smokers, respectively. Solid and dashed regression lines, current and former smokers, respectively. Changes in CT-TLV in current and former smokers significantly correlated with those in LAA% (r = 0.45, p = 0.03 and r = 0.62, p = 0.002, respectively), but not in D (r = −0.11, p = 0.64, and r = −0.08, p = 0.66, respectively). Changes in LAN and CT-TLV significantly correlated in former smokers, and tended to correlate in current smokers (r = 0.47, p = 0.008, and r = 0.40, p = 0.06, respectively).
Figure 5.
Relationships among annual changes in CT parameters of emphysema.
A and B show relationships between the changes in LAA% and D and between those in LAA% and LAN, respectively, in 22 current and 31 former smokers with mild to moderate emphysema. Closed and open circles, current and former smokers, respectively. Solid and dashed regression lines, current and former smokers, respectively. Changes in LAA% in current and former smokers significantly correlated with those in D (r = −0.77, p<0.0001; r = −0.53, p = 0.002, respectively) and LAN (r = 0.88, p<0.0001 and r = 0.90, p<0.0001, respectively). Smoking status and change in LAA% significantly interacted to elicit changes in D (p = 0.03), but not in LAN (p = 0.48).
Figure 6.
Changes in LAA%, D and LAN determined from model simulations and current smokers.
Crosses, current smokers; dashed line, regression calculated from current smokers. Closed and open symbols, random and damage-dependent models, respectively. Triangles, without coalescence of low attenuation clusters; circles and diamonds, 15% and 30% cluster coalescence, respectively. Decreases in D obtained from random and damage-dependent models with 30% and 15% coalescence, respectively, were similar to actual data from current smokers (A). LAN increased when LAA% increased in damage-dependent model with 15% coalescence, which closely agreed with data from current smokers (B).