The overall long-term goal of these studies is to understand the mechanisms by which pulmonary blood flow is controlled, and how that control contributes to gas exchange defects or optimization in health and disease. The specific goal is to use a novel MRI technique to quantify the spatial and temporal dynamics of blood flow in the normal human lung. Temporal heterogeneity in a number of physiological systems has been found to be a mark of healthy function, yet little is known about the temporal dynamics of blood flow in the human lung because the appropriate tools for measuring temporal heterogeneity have not been available. Recently we developed a noninvasive MRI technique that provides quantitative measurements of pulmonary blood flow with a spatial resolution of <1 cm3 and a temporal resolution of ~10 s in the human lung, permitting us to examine spatial-temporal heterogeneity in the human lung for the first time.
The Specific Aims are designed to systematically explore the normal spectrum of spatial-temporal heterogeneity, testing: 1) the effects of altered inspired gas (O2 and CO2) in healthy subjects;2) the effects of exercise;3) the effects of ageing;and 4) the effects of altered O2 and CO2 in the lungs of subjects susceptible to high altitude pulmonary edema. This will be the first systematic, quantitative study of the spatial and temporal dynamics of pulmonary blood flow in human subjects, and will lay a foundation for applying these methods in the early detection and characterization of disease.
Oxygenation of the blood in the lungs depends on a close matching of ventilation and blood flow: fresh gas and blood flow need to be at the same place and at the same time. We have developed a novel imaging technique for measuring the distribution of blood flow in the human lung not only spatially, but also over time, a measurement that has not been possible before. In this work we will explore the normal dynamics of blood flow as a foundation for applying these methods to identify, and to better understand, the underlying mechanisms of disease.
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|Burrowes, K S; Buxton, R B; Prisk, G K (2012) Assessing potential errors of MRI-based measurements of pulmonary blood flow using a detailed network flow model. J Appl Physiol 113:130-41|
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