Lung clearance index (LCI) is a widely reported marker of gas mixing inefficiency within the airways that is derived using the multiple breath inert gas washout (MBW) technique.
Heterogeneity in asthma is evident in every aspect of the disease process. Quantitative computed tomography (QCT) has emerged as a reliable, noninvasive tool for assessment of proximal airway remodeling and air trapping in asthma. We have identified three asthma clusters based on QCT indices, using factor and cluster analysis.
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Cross-disciplinary collaborations have become an increasingly important part of science. They are seen as key if we are to find solutions to pressing, global-scale societal challenges, including green technologies, sustainable food production, and drug development. Regulators and policy-makers have realized the power of such collaborations, for example, in the 80 billion Euro "Horizon 2020" EU Framework Programme for Research and Innovation. This programme puts special emphasis on “breaking down barriers to create a genuine single market for knowledge, research and innovation”
Lung clearance index (LCI) is a widely reported marker of ventilation heterogeneity (VH) derived from multiple breath inert gas washout.
It is well known that ventilation and parenchymal tissue deformation are intimately linked. However, the impact of alterations during disease, such as airway narrowing or changes in tissue properties, on regional ventilation and tissue stresses are not well understood. In order to investigate this, we have developed a poroelastic model to represent the coupling between lung parenchymal (alveolar) tissue deformation and ventilation. In this study we have applied the model to investigate the impact of airway narrowing during obstructive lung diseases on tissue mechanics and regional ventilatory function.
