Alterations of the pulmonary vasculature are an important feature of human lung diseases such as chronic obstructive pulmonary disease, pulmonary hypertension, and bronchopulmonary dysplasia. Experimental studies to investigate the pathogenesis or a therapeutic intervention in animal models of these diseases often require robust, meaningful, and efficient morphometric data that allow for appropriate statistical testing. The gold standard for obtaining such data is design-based stereology. However, certain morphological characteristics of the pulmonary vasculature make the implementation of stereological methods challenging. For example, the alveolar capillary network functions according to the sheet flow principle, thus making unbiased length estimations impossible and requiring other strategies to obtain mechanistic morphometric data. Another example is the location of pathological changes along the branches of the vascular tree. For developmental defects like in bronchopulmonary dysplasia or for pulmonary hypertension, it is important to know whether certain segments of the vascular tree are preferentially altered. This cannot be overcome by traditional stereological methods but requires the combination of a three-dimensional data set and stereology. The present review aims at highlighting the great potential while discussing the major challenges (such as time consumption and data volume) of this combined approach. We hope to raise interest in the potential of this approach and thus stimulate solutions to overcome the existing challenges.
Keywords: 3-D reconstruction; alveolar capillary network; design-based stereology; pulmonary vasculature.