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Integrative, three-dimensional \(in\) \(silico\) modeling of gas exchange in the human alveolus
(2024)
The lung plays a vital role by exchanging respiratory gases. At the core of this gas exchange is a simple yet crucial passive diffusion process occurring within the alveoli. These balloon-like structures, connected to the peripheral airways, are surrounded by a dense network
of small capillaries. Here, inhaled air comes into close proximity with deoxygenated blood coming from the heart, enabling the exchange of oxygen and carbon dioxide across their concentration gradients.
The efficiency of gas exchange can be measured through indicators such as the diffusion capacity of the lung for oxygen and the reaction half-time. A notable discrepancy exists in humans between physiological estimates of diffusion capacity and the theoretical maximum capacity under optimal structural conditions (morphological estimate). This discrepancy is influenced by a range of interrelated factors, including structural elements like the surface area and thickness of the diffusion barrier, as well as physiological factors such as blood flow dynamics. To unravel the different roles of these factors, we investigated how morphological and physiological properties of the human alveolar micro-environment collectively and individually influence the process of gas exchange. To this end, we developed an integrative in silico approach combining 3D morphological modeling and simulation of blood flow and of oxygen transport.
At the core of our approach lies the simulation software Alvin, serving as an interactive platform for the underlying mathematical model of oxygen transport within the alveolus. Developed by integrating and expanding existing mathematical models, our spatio-temporal model produces results in agreement with experimental data. Alvin allows for real-time parameter adjustments and the execution of multiple simultaneous simulation instances and provides detailed quantitative feedback, offering an immersive exploration of the simulated gas exchange process. The morphological and physiological parameters at play were further investigated with a focus on the microvasculature. By compiling a stereological database from the literature and 3D geometric modeling, we created a sheet-flow model as a realistic representation of the morphology of the human alveolar capillary network. Blood flow was simulated using computational fluid dynamics. Our findings were in line with previous estimations and highlighted the crucial role of viscosity models in predicting pressure drop across the microvasculature. Furthermore, we showcased how our approach can be harnessed to explore structural details, such as the connectivity of the alveolar capillary network with the vascular tree, using blood flow indices. It is important to emphasize that
so far we have relied on different data sources and that experimental validation is needed to move forward.
Integration of our findings into Alvin allowed quantification of the simulated gas exchange process through the diffusion capacity for oxygen and reaction half-time. In addition to evaluating the collective influences of the morphological and physiological properties, our interactive software facilitates the assessment of individual parameter value changes. Exploring blood volume and surface area available for gas exchange revealed linear correlations with diffusion capacity. The blood flow velocity had a positive, non-linear effect on diffusion capacity. The reaction half-time confirmed that under normal conditions, the gas exchange process is not diffusion-limited. Collectively, our alveolar model yielded a diffusion capacity value that fell in the middle of previous physiological and morphological estimates, implying that alveolar-level phenomena contribute to 50% of the diffusion capacity limitations that occur in vivo.
In summary, our integrative in silico approach disentangles various structural and functional influences on alveolar gas exchange, complementing traditional investigations in respiratory
research. We further showcase its utility in teaching and the interpretation of published data. To advance our understanding, future work should prioritize obtaining a cohesive experimental data set and identifying an appropriate viscosity model for blood flow simulations.
Background
Health-related and disease-specific quality of life (HRQoL) has been increasingly valued as relevant clinical parameter in cystic fibrosis (CF) clinical care and clinical trials. HRQoL measures should assess – among other domains – daily functioning from a patient’s perspective. However, validation studies for the most frequently used HRQoL questionnaire in CF, the Cystic Fibrosis Questionnaire (CFQ), have not included measures of physical activity or fitness. The objective of this study was, therefore, to determine the cross-sectional and longitudinal relationships between HRQoL, physical activity and fitness in patients with CF.
Methods
Baseline (n = 76) and 6-month follow-up data (n = 70) from patients with CF (age ≥12 years, FEV1 ≥35%) were analysed. Patients participated in two multi-centre exercise intervention studies with identical assessment methodology. Outcome variables included HRQoL (German revised multi-dimensional disease-specific CFQ (CFQ-R)), body composition, pulmonary function, physical activity, short-term muscle power, and aerobic fitness by peak oxygen uptake and aerobic power.
Results
Peak oxygen uptake was positively related to 7 of 13 HRQoL scales cross-sectionally (r = 0.30-0.46). Muscle power (r = 0.25-0.32) and peak aerobic power (r = 0.24-0.35) were positively related to 4 scales each, and reported physical activity to 1 scale (r = 0.29). Changes in HRQoL-scores were directly and significantly related to changes in reported activity (r = 0.35-0.39), peak aerobic power (r = 0.31-0.34), and peak oxygen uptake (r = 0.26-0.37) in 3 scales each. Established associates of HRQoL such as FEV1 or body mass index correlated positively with fewer scales (all 0.24 < r < 0.55).
Conclusions
HRQoL was associated with physical fitness, especially aerobic fitness, and to a lesser extent with reported physical activity. These findings underline the importance of physical fitness for HRQoL in CF and provide an additional rationale for exercise testing in this population.