title: Quantitative characterization of airspace enlargement in emphysema.
abstract: The mean linear intercept (L(m)) can be used to estimate the surface area for gas exchange in the lung. However, in recent years, it is most commonly used as an index for characterizing the enlargement of airspaces in emphysema and the associated severity of structural destruction in the lung. Specifically, an increase in L(m) is thought to result from an increase in airspace sizes. In this paper, we examined how accurately L(m) measures the linear dimensions of airspaces from histological sections and a variety of computer-generated test images. To this end, we developed an automated method for measuring linear intercepts from digitized images of tissue sections and calculate L(m) as their mean. We examined how the shape of airspaces and the variability of their sizes influence L(m) as well as the distribution of linear intercepts. We found that, for a relatively homogeneous enlargement of airspaces, L(m) was a reliable index for detecting emphysema. However, in the presence of spatial heterogeneities with a large variability of airspace sizes, L(m) did not significantly increase and sometimes even decreased compared with its value in normal tissue. We also developed an automated method for measuring the area and computed an equivalent diameter of each individual airspace that is independent of shape. Finally, we introduced new indexes based on the moments of diameter that we found to be more reliable than L(m) to characterize airspace enlargement in the presence of heterogeneities.
authors.affiliation: Department of Biomedical Engineering, Boston University, 44 Cummington St., Boston, Massachusetts 02215, USA.
authors.forename: Harikrishnan
authors.initials: H
authors.lastname: Parameswaran
authors.forename: Arnab
authors.initials: A
authors.lastname: Majumdar
authors.forename: Satoru
authors.initials: S
authors.lastname: Ito
authors.forename: Adriano M
authors.initials: AM
authors.lastname: Alencar
authors.forename: Béla
authors.initials: B
authors.lastname: Suki
mesh_terms: D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods*; D000818:Animals; D001185:Artificial Intelligence; D004646:Emphysema / Q000000981:diagnostic imaging* / Q000473:pathology*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008176:Lung Volume Measurements / Q000379:methods*; D051379:Mice; D010363:Pattern Recognition, Automated / Q000379:methods; D011650:Pulmonary Alveoli / Q000382:microbiology* / Q000473:pathology*; D011859:Radiography; D012720:Severity of Illness Index