Computer reconstruction of a human lung boundary model from magnetic resonance images

A mathematical description of the morphology of the lung is necessary for modeling and analyzing the deposition of inhaled aerosols. A model of the lung boundary was generated from magnetic resonance images, with the goal of creating a framework for anatomically realistic morphological models of the human airway network. We used data visualization and analysis software to reconstruct the lung volume from a series of transverse magnetic resonance images collected at many vertical locations in the lung, ranging from apex to base. The lung model was then built using isosurface extraction techniques. These modeling methods may facilitate the creation of customized morphological models for individual subjects, resulting in improved interpretation of aerosol distribution data from single-photon- emission computed tomography (SPECT). Such customized models could be developed for children and for patients with respiratory diseases, thus aiding in the study of inhaled medications and environmental aerosols in these sensitive populations

Measurements of electrodynamic effects on the deposition of mdi and dpi aerosols in a replica cast of human oral-pharyngeal-laryngeal airways

Metered dose inhalers (MDIs) and dry powder inhalers (DPIs) are popular drug delivery devices used in the treatment of respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD). Integrated effects of electrostatic charges and aerodynamic sizes on the deposition of MDI and DPI particles in a replica cast of human oral-pharyngeal-laryngeal (OPL) airways were examined. Experimental aerosols were generated from commercially available MDI and DPI devices. They are the trademarked brands of the same pharmaceutical company, and contain the same amounts of different drugs. Inhalations were administered as boluses and characterized with an Electronic Single Particle Aerodynamic Relaxation Time (ESPART) analyzer before and after passing through the cadaver-based OPL cast. The MDI and DPI aerosols were not only of different sizes but also carried different positive, negative and zero electrostatic charges; 42.2 of the total number of DPI particles was charged in comparison to 6 of those produced by the MDI. Electrodynamic properties (e.g., charges and sizes) played significant roles on the behavior and deposition of aerosols in the OPL airways. As detailed herein, deposition fractions of the total (charged and uncharged) DPI aerosols were 21.5 in contrast to 2.8 for the MDI aerosols, whereas the charged particle deposition for the DPI was 46.7 in contrast to 22.5 for the MDI. Particle losses in the OPL passages were greater for the DPI than the MDI as the former generated more charged particles than the latter. This finding is consistent with results reported by other researchers but contradicts the observation of another investigator where MDI losses were reported as being higher than those for DPIs. The chief reason for this difference may be that the latter study did not account for the electrical properties of aerosol particles, but only for their mechanical properties. Because the measured deposition efficiencies of MDI and DPI aerosols were different, the data have important implications to inhalation therapy protocols. © Mary Ann Liebert, Inc. 2009

Estimation of Particle Deposition in the Airways from Different Inhaler Formulations Using an In Silico Model

The objective of these studies was to evaluate the use of an in silico model for predicting lung deposition of inhaled therapeutic aerosols. A range of input data derived from our own in vitro data and published clinical studies was utilized. The in silico model ran simulations for these propellant driven metered dose inhaler formulations across a range of conditions. Firstly, a range of pressurized metered dose inhaler formulations were evaluated in the in silico model and compared to the in vitro aerosol performance data. Limitations of using in vitro cascade impaction data were observed. Then, using in vivo data from healthy human subjects using metered dose inhalers, lung deposition profiles were compared with the in silico model predictions. Despite differences in oropharyngeal deposition the model predicted lung deposition accurately. We conclude that the in silico model can be applied to various conditions for particulate based inhalation aerosol systems

In silico modeling of asthma

The incidence of asthma is increasing throughout the world, especially among children, to the extent that it has become a medical issue of serious global concern. Appropriately, numerous pharmacologic drugs and clinical protocols for the treatment and prophylaxis of the disease have been reported. From a scientific perspective, a review of the literature suggests that the targeted delivery of an aerosol would, in a real sense, enhance the efficacy of an inhaled medicine. Therefore, in accordance with published data we have developed a mathematical description of disease-induced effects of disease on airway morphology. A morphological algorithm defining the heterogeneity of asthma has been integrated with a computer code that formulates the behavior and fate of inhaled drugs. In this work, predicted drug particle deposition patterns have been compared with SPECT images from experiments with healthy human subjects (controls) and asthmatic patients. The asthma drug delivery model simulations agree with observations from human testing. The results indicate that in silico modeling provides a technical foundation for addressing effects of disease on the administration of aerosolized drugs, and suggest that modeling should be used in a complementary manner with future inhalation therapy protocols

A computer model of lung morphology to analyze SPECT images

Measurement of the spatial distribution of aerosol deposition in human lungs can be performed using single photon emission computed tomography (SPECT). To relate deposition patterns to real lung structures, a computer model of the airway network has been developed. Computer simulations are presented that are compatible with the analysis of SPECT images. Computational techniques that are consistent with clinical procedures are used to analyze airways by type and number within transverse slices of the lung volume. The computer models serve as customized templates, which when analyzed alongside gamma scintigraphy images, can assist in the interpretation of human test data

Validation of the conceptual anatomical model of the lung airway

The conceptual anatomical model of the lung airway considers each lung volume divided into ten concentric shells. It specifies the volume of each airway generation in each shell, using Weibel morphometry. This study updates and validates the model and evaluates the errors obtained when using it to estimate inhaled aerosol deposition per generation from spatial imaging data. A comparison of different airway models describing the volume per generation, including data from CT images of a lung cast and a human subject, was performed. A revised version of the conceptual model was created, using the average volume per generation from these data. The new model was applied to derive the aerosol deposition per generation from 24 single photon emission computed tomography (SPECT) studies. Analysis errors were assessed by applying the same calculations but using airway models based on the minimum and maximum volumes per generation. The mean shell position of each generation in the average model was not significantly different from either CT model. However there were differences between the volumes per generation of the different models. The root mean square differences between bronchial airways deposition fraction (generations 2–8) obtained from the maximum and minimum models compared to the new average model was 0.66 percentage points (14%). For the conducting airways deposition fraction (generations 2–15) this was 1.66 percentage points (12%). The conceptual model is consistent with CT measurements of airway geometry. The errors resulting from using a generic airway model to interpret 3D radionuclide image data have been defined