AUTHOR=Matuszak Jasmin , Tabuchi Arata , Kuebler Wolfgang M. TITLE=Ventilation and Perfusion at the Alveolar Level: Insights From Lung Intravital Microscopy JOURNAL=Frontiers in Physiology VOLUME=Volume 11 - 2020 YEAR=2020 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2020.00291 DOI=10.3389/fphys.2020.00291 ISSN=1664-042X ABSTRACT=Intravital microscopy (IVM) offers unique possibilities for the observation of biological processes and disease related mechanisms in vivo. Especially for anatomically complex and dynamic organs such as the lung and its main functional unit, the alveolus, IVM provides unique advantages in terms of spatial and temporal resolution. By the use of lung windows, which have advanced and improved over time, direct access to the lung surface is provided. In this review we will discuss two main topics, namely alveolar dynamics and perfusion from the perspective of IVM-based studies. Of special interest are unanswered questions regarding alveolar dynamics such as: What are physiologic alveolar dynamics? How do these dynamics change under pathologic conditions and how do those changes contribute to ventilator-induced lung injury? How can alveolar dynamics be manipulated in a beneficial way? In the field of alveolar perfusion IVM propelled the understanding of the pulmonary microcirculation and its perfusion, as well as pulmonary vasoreactivity, permeability and immunological aspects. Whereas the general mechanism behind those processes are understood, we are still lacking a proper understanding of the complex, multidimensional interactions under physiologic and pathologic conditions regarding the interplay between ventilation and changes in perfusion, capillary recruitment or the involvement of the immune system within the pulmonary microcirculation. Those are only part of the unanswered question and problems which we still have to overcome. IVM as the tool of choice might allow us to answer part of those questions within the next years or decades. Yet as every method IVM has advantages as well as limitations which have to be taken into account for data analysis and interpretation, and will be addressed in this review.