A method for evaluating the murine pulmonary vasculature using micro-computed tomography
Abstract Introduction Significant mortality and morbidity is associated with alterations in the pulmonary vasculature. While techniques have been described for quantitative morphometry of whole-lung arterial trees in larger animals, no methods have been described in mice. We report a method for the...
Gespeichert in:
Veröffentlicht in: | The Journal of surgical research 2017-01, Vol.207, p.115-122 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Abstract Introduction Significant mortality and morbidity is associated with alterations in the pulmonary vasculature. While techniques have been described for quantitative morphometry of whole-lung arterial trees in larger animals, no methods have been described in mice. We report a method for the quantitative assessment of murine pulmonary arterial vasculature using high resolution CT scanning. Methods Mice were harvested at 2-weeks, 4-weeks, and 3-months of age. The pulmonary artery vascular tree was pressure perfused to maximal dilation with a radio-opaque casting material with viscosity and pressure set to prevent capillary transit and venous filling. The lungs were fixed and scanned on a specimen CT scanner at 8um resolution and the vessels segmented. Vessels were grouped into categories based upon lumen diameter and branch generation. Results Robust high-resolution segmentation was achieved, permitting detailed quantitation of pulmonary vascular morphometrics. As expected, postnatal lung development was associated with progressive increase in small-vessel number and arterial branching complexity. Conclusion These methods for quantitative analysis of the pulmonary vasculature in postnatal and adult mice provide a useful tool for the evaluation of mouse models of disease that affect the pulmonary vasculature. |
---|---|
ISSN: | 0022-4804 1095-8673 |
DOI: | 10.1016/j.jss.2016.08.074 |