A semi-automated method for unbiased alveolar morphometry: Validation in a bronchopulmonary dysplasia model.

ABSTRACT: Reproducible and unbiased methods to quantify alveolar structure are important for research on many lung diseases. However, manually estimating alveolar structure through stereology is time consuming and inter-observer variability is high. The objective of this work was to develop and validate a fast, reproducible and accurate (semi-)automatic alternative. A FIJI-macro was designed that automatically segments lung images to binary masks, and counts the number of test points falling on tissue and the number of intersections of the air-tissue interface with a set of test lines. Manual selection remains necessary for the recognition of non-parenchymal tissue and alveolar exudates. Volume density of alveolar septa ([Formula: see text]) and mean linear intercept of the airspaces (Lm) as measure

SUBMITTER: Salaets T 

PROVIDER: S-EPMC7511023 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature