Functional imaging using computer methods to compare the effect of salbutamol and ipratropium bromide in patient-specific airway models of COPD.

BACKGROUND: Salbutamol and ipratropium bromide improve lung function in patients with chronic obstructive pulmonary disease (COPD). However, their bronchodilating effect has not yet been compared in the central and distal airways. Functional imaging using computational fluid dynamics offers the possibility of making such a comparison. The objective of this study was to assess the effects of salbutamol and ipratropium bromide on the geometry and computational fluid dynamics-based resistance of the central and distal airways. METHODS: Five patients with Global Initiative for Chronic Obstructive Lung Disease Stage III COPD were randomized to a single dose of salbutamol or ipratropium bromide in a crossover manner with a 1-week interval between treatments. Patients underwent lung function testing and a multislice computed tomography scan of the thorax that was used for functional imaging. Two hours after dosing, the patients again underwent lung function tests and repeat computed tomography. RESULTS: Lung function parameters, including forced expiratory volume in 1 second, vital capacity, overall airway resistance, and specific airway resistance, changed significantly after administration of each product. On functional imaging, the bronchodilating effect was greater in the distal airways, with a corresponding drop in airway resistance, compared with the central airways. Salbutamol and ipratropium bromide were equally effective at first glance when looking at lung function tests, but when viewed in more detail with functional imaging, hyporesponsiveness could be shown for salbutamol in one patient. Salbutamol was more effective in the other patients. CONCLUSION: This pilot study gives an innovative insight into the modes of action of salbutamol and ipratropium bromide in patients with COPD, using the new techniques of functional imaging and computational fluid dynamics.

Flow analyses in the lower airways: patient-specific model and boundary conditions.

Computational fluid dynamics (CFD) is increasingly applied in the respiratory domain. The ability to simulate the flow through a bifurcating tubular system has increased the insight into the internal flow dynamics and the particular characteristics of respiratory flows such as secondary motions and inertial effects. The next step in the evolution is to apply the technique to patient-specific cases, in order to provide more information about pathological airways. This study presents a patient-specific approach where both the geometry and the boundary conditions (BC) are based on individual imaging methods using computed tomography (CT). The internal flow distribution of a 73-year-old female suffering from chronic obstructive pulmonary disease (COPD) is assessed. The validation is performed through the comparison of lung ventilation with gamma scintigraphy. The results show that in order to obtain agreement within the accuracy limits of the gamma scintigraphy scan, both the patient-specific geometry and the BC (driving pressure) play a crucial role. A minimal invasive test (CT scan) supplied enough information to perform an accurate CFD analysis. In the end it was possible to capture the pathological features of the respiratory system using the imaging and computational fluid dynamics techniques. This brings the introduction of this new technique in the clinical practice one step closer.

Computational fluid dynamics can detect changes in airway resistance in asthmatics after acute bronchodilation.

The effect of a bronchodilator in asthmatics is only partially described by changes in spirometric values since no information on regional differences can be obtained. Imaging techniques like high-resolution computed tomography (HRCT) provide further information but lack detailed information on specific airway responses. The aim of the present study was to improve the actual imaging techniques by subsequent analysis of the imaging data using computational fluid dynamics (CFD). We studied 14 mild to moderately severe asthmatics. Ten patients underwent HRCT before and 4h after inhalation of a novel long acting beta(2) agonist (LABA) that acts shortly after inhalation. Four patients were studied for chronic effects and underwent CT scans twice after adequate wash-out of bronchodilators. In the active group, a significant bronchodilator response was seen with a forced expiratory volume in 1s (FEV1) increase of 8.78 +/- -6.27% pred vs -3.38 +/- 6.87% pred in the control group. The changes in FEV1 correlated significantly with the changes in distal airway volume (r = 0.69, p = 0.007), total airway resistance (r = -0.73, p = 0.003) and distal airway resistance (r = -0.76, p = 0.002) as calculated with the CFD method. The changes in distal R(aw) were not fully homogeneous. In some patients with normal FEV1 at baseline, CFD-based changes in R(aw) were still detectable. We conclude that CFD calculations, based on airway geometries of asthmatic patients, provide additional information about changes in regional R(aw). All changes in the CFD-based calculated R(aw) significantly correlate with the observed changes in spirometric values therefore validating the CFD method for the studied application.

Functional imaging using computational fluid dynamics to predict treatment success of mandibular advancement devices in sleep-disordered breathing.

Mandibular advancement devices (MADs) have emerged as a popular alternative for the treatment of sleep-disordered breathing. These devices bring the mandibula forward in order to increase upper airway (UA) volume and prevent total UA collapse during sleep. However, the precise mechanism of action appears to be quite complex and is not yet completely understood; this might explain interindividual variation in treatment success. We examined whether an UA model, that combines imaging techniques and computational fluid dynamics (CFD), allows for a prediction of the treatment outcome with MADs. Ten patients that were treated with a custom-made mandibular advancement device (MAD), underwent split-night polysomnography. The morning after the sleep study, a low radiation dose CT scan was scheduled with and without the MAD. The CT examinations allowed for a comparison between the change in UA volume and the anatomical characteristics through the conversion to three-dimensional computer models. Furthermore, the change in UA resistance could be calculated through flow simulations with CFD. Boundary conditions for the model such as mass flow rate and pressure distributions were obtained during the split-night polysomnography. Therefore, the flow modeling was based on a patient specific geometry and patient specific boundary conditions. The results indicated that a decrease in UA resistance and an increase in UA volume correlate with both a clinical and an objective improvement. The results of this pilot study suggest that the outcome of MAD treatment can be predicted using the described UA model.