Complexity of terminal airspace geometry assessed by lung computed tomography in normal subjects and patients with chronic obstructive pulmonary disease.

Increases in the low attenuation areas (LAA) of chest x-ray computed tomography images in patients with chronic obstructive pulmonary disease (COPD) have been reported to reflect the development of pathological emphysema. We examined the statistical properties of LAA clusters in COPD patients and in healthy subjects. In COPD patients, the percentage of the lung field occupied by LAAs (LAA%) ranged from 2.6 to 67.6. In contrast, LAA% was always <30% in healthy subjects. The cumulative size distribution of the LAA clusters followed a power law characterized by an exponent D. We show that D is a measure of the complexity of the terminal airspace geometry. The COPD patients with normal LAA% had significantly smaller D values than the healthy subjects, and the D values did not correlate with pulmonary function tests except for the diffusing capacity of the lung. We interpret these results by using a large elastic spring network model and find that the neighboring smaller LAA clusters tend to coalesce and form larger clusters as the weak elastic fibers separating them break under tension. This process leaves LAA% unchanged whereas it decreases the number of small clusters and increases the number of large clusters, which results in a reduction in D similar to that observed in early emphysema patients. These findings suggest that D is a sensitive and powerful parameter for the detection of the terminal airspace enlargement that occurs in early emphysema.

[1]  Albert-László Barabási,et al.  Avalanches and power-law behaviour in lung inflation , 1994, Nature.

[2]  C D Murray,et al.  The Physiological Principle of Minimum Work: I. The Vascular System and the Cost of Blood Volume. , 1926, Proceedings of the National Academy of Sciences of the United States of America.

[3]  H. Itoh,et al.  An automated method to assess the distribution of low attenuation areas on chest CT scans in chronic pulmonary emphysema patients. , 1994, Chest.

[4]  Thurlbeck Wm The incidence of pulmonary emphysema, with observations on the relative incidence and spatial distribution of various types of emphysema. , 1963 .

[5]  Jean Paul Rigaut,et al.  An empirical formulation relating boundary lengths to resolution in specimens showing ‘non‐ideally fractal’ dimensions , 1984 .

[6]  E. Nikkila Letter: Serum high-density-lipoprotein and coronary heart-disease. , 1976, Lancet.

[7]  N. Müller,et al.  Limited contribution of emphysema in advanced chronic obstructive pulmonary disease. , 1993, The American review of respiratory disease.

[8]  J E McNamee,et al.  Fractal perspectives in pulmonary physiology. , 1991, Journal of applied physiology.

[9]  M. Woldenberg,et al.  Diameters and cross‐sectional areas of branches in the human pulmonary arterial tree , 1989, The Anatomical record.

[10]  J. Best,et al.  DIAGNOSIS OF PULMONARY EMPHYSEMA BY COMPUTERISED TOMOGRAPHY , 1984, The Lancet.

[11]  R. Spragg,et al.  Fractal analysis of surfactant deposition in rabbit lungs. , 1995, Journal of applied physiology.

[12]  P. Paré,et al.  The diagnosis of emphysema. A computed tomographic-pathologic correlation. , 1986, The American review of respiratory disease.

[13]  B Suki,et al.  Branching design of the bronchial tree based on a diameter-flow relationship. , 1997, Journal of applied physiology.

[14]  T. Vicsek Fractal Growth Phenomena , 1989 .

[15]  E. Hoffman,et al.  Quantification of pulmonary emphysema from lung computed tomography images. , 1997, American journal of respiratory and critical care medicine.

[16]  R W Glenny,et al.  Fractal modeling of pulmonary blood flow heterogeneity. , 1991, Journal of applied physiology.

[17]  K. Horsfield,et al.  Diameters, generations, and orders of branches in the bronchial tree. , 1990, Journal of applied physiology.

[18]  R. Glenny,et al.  Fractal properties of pulmonary blood flow: characterization of spatial heterogeneity. , 1990, Journal of applied physiology.

[19]  J Ikezoe,et al.  Fractal analysis for classification of ground-glass opacity on high-resolution CT: an in vitro study. , 1997, Journal of computer assisted tomography.

[20]  V. Holý,et al.  High‐resolution x‐ray diffractometry of ZnTe layers at elevated temperatures , 1995 .

[21]  J. Bates,et al.  Assessment of acute pleural effusion in dogs by computed tomography. , 1994, Journal of applied physiology.

[22]  P De Vuyst,et al.  Pulmonary emphysema: quantitative CT during expiration. , 1996, Radiology.

[23]  K. Horsfield,et al.  Relation between diameter and flow in branches of the bronchial tree. , 1981, Bulletin of mathematical biology.

[24]  G. Laszlo,et al.  Computed tomography in pulmonary emphysema. , 1982, Clinical radiology.