Application of Euclidean distance mapping for assessment of basement membrane thickness distribution in asthma

This report describes an automated, unbiased approach which uses color segmentation to identify structures of interest on stained sections and Euclidean distance mapping to measure the thickness distribution of airway structures. This method was applied to study the thickness distribution of the basement membrane and airway epithelium in lungs donated for research from seven nonasthmatic and eight asthmatic age- and sex-matched donors. A total of 60 airways were assessed. We report that the thickness and thickness distribution of the basement membrane and airway epithelium are increased in large and small airways of asthmatics compared with nonasthmatics. Using this method we were able to demonstrate the heterogeneity in the thickness of the basement membrane and airway epithelium within individual airways of asthmatic subjects. This new computational method enables comprehensive and objective quantification of airway structures, which can be used to quantify heterogeneity of airway remodeling in obstructive lung diseases such as asthma and chronic obstructive pulmonary disease. NEW & NOTEWORTHY The described application of Euclidean distance mapping provides an unbiased approach to study the extent and thickness distribution of changes in tissue structures. This approach will enable researchers to use computer-aided analysis of structural changes within lung tissue to understand the heterogeneity of airway remodeling in lung diseases.
Source: Journal of Applied Physiology - Category: Physiology Authors: Tags: INNOVATIVE METHODOLOGY Source Type: research