A lung dosimetry model of vapor uptake and tissue disposition.

Inhaled vapors may be absorbed at the alveolar-capillary membrane and enter arterial blood flow to be carried to other organs of the body. Thus, the biological effects of inhaled vapors depend on vapor uptake in the lung and distribution to the rest of the body. A mechanistic model of vapor uptake in the human lung and surrounding tissues was developed for soluble and reactive vapors during a single breath. Lung uptake and tissue disposition of inhaled formaldehyde, acrolein, and acetaldehyde were simulated for different solubilities and reactivities. Formaldehyde, a highly reactive and soluble vapor, was estimated to be taken up by the tissues in the upper tracheobronchial airways with shallow penetration into the lung. Vapors with moderate solubility such as acrolein and acetaldehyde were estimated to penetrate deeper into the lung, reaching the alveolar region where absorbed vapors had a much higher probability of passing through the thin alveolar-capillary membrane to reach the blood. For all vapors, tissue concentration reached its maximum at the end of inhalation at the air-tissue interface. The depth of peak concentration moved within the tissue layer due to vapor desorption during exhalation. The proposed vapor uptake model offers a mechanistic approach for calculations of lung vapor uptake, air:tissue flux, and tissue concentration profiles within the respiratory tract that can be correlated to local biological response in the lung. In addition, the uptake model provides the necessary input for pharmacokinetic models of inhaled chemicals in the body, thus reducing the need for estimating requisite parameters.

Derivation of mass transfer coefficients for transient uptake and tissue disposition of soluble and reactive vapors in lung airways.

Evaluation of vapor uptake by lung airways and subsequent dose to lung tissues provides the bridge connecting exposure episode to biological response. Respiratory vapor absorption depends on chemical properties of the inhaled material, including solubility, diffusivity, and metabolism/reactivity in lung tissues. Inter-dependent losses in the air and tissue phases require simultaneous calculation of vapor concentration in both phases. Previous models of lung vapor uptake assumed steady state, one-way transport into tissues with first-order clearance. A new approach to calculating lung dosimetry is proposed in which an overall mass transfer coefficient for vapor transport across the air-tissue interface is derived using air-phase mass transfer coefficients and analytical expressions for tissue-phase mass transfer coefficients describing unsteady transport by diffusion, first-order, and saturable pathways. Feasibility of the use of mass transfer coefficients was shown by calculating transient concentration levels of inhaled formaldehyde in the human tracheal airway and surrounding tissue. Formaldehyde tracheal air concentration and wall-flux declined throughout the breathing cycle. After the inhalation period, peak tissue concentration moved from the air-tissue interface into the tissue due to desorption into the air and continued diffusional transport across the tissue layer. While model predictions were performed for formaldehyde, which serves as a model of physiologically relevant, highly reactive vapors, the model is equally applicable to other soluble and reactive compounds.

3D in silico modeling of the human respiratory system for inhaled drug delivery and imaging analysis.

The efficacies of inhaled pharmacologic drugs could be improved if drugs could be targeted to appropriate sites within the human respiratory system. The spatial deposition patterns of particles can now be detected with a high degree of resolution using advanced techniques of imaging (e.g., SPECT). However, the effectiveness of such laboratory regimens has been limited by the inability to clearly identify airway composition within images. Therefore, we have developed a theoretical protocol to map airways within human lungs that is designed to be used in a complementary manner with laboratory investigations. The in silico model has two components: a mathematical model based on concepts of topology; and, a computer algorithm which tracks the millions of constituent lung airways. The in silico model produces 3D lung structures that are anatomically correct and can be customized to each patient. We have applied the protocol to a SPECT study where the interiors of lungs were partitioned into a series of ten nested shells. Airway composition in the respective shells provides a heretofore unavailable quantification of scintigraphy images. The protocol can be employed in a practical manner in the medical arena to aid in the interpretation of SPECT images, and to provide a platform for the design of human subject tests.

Computer simulations of lung airway structures using data-driven surface modeling techniques.

Knowledge of human lung morphology is a subject critical to many areas of medicine. The visualization of lung structures naturally lends itself to computer graphics modeling due to the large number of airways involved and the complexities of the branching systems. In this study, a method of generating three-dimensional computer simulations of human lung airway networks using data-driven, surface modeling techniques is presented. By simulating the tubular airway structures and realistic bifurcation shapes, anatomically accurate representations of human lungs are obtained. These computer models are designed for use in computational fluid dynamic applications and particle trajectory analyses, and to be complimentary to medical imaging (gamma scintigraphy) protocols.

Factors affecting the deposition of aerosolized insulin.

The inhalation of insulin for absorption into the bloodstream via the lung seems to be a promising technique for the treatment of diabetes mellitus. A fundamental issue to be resolved in the development of such insulin aerosol delivery systems is their efficiency (measured, for example, in terms of the amount of insulin absorbed in the blood compared to the total amount loaded into an inhalation device). A primary factor that could cause inefficiency of insulin absorption is deposition in the nonalveolated airways with subsequent removal from the lung via mucociliary clearance. Thus, a better understanding of the spatial distribution of insulin particle deposition in the lung can give guidance to the optimization of inhalation therapy. A mathematical model was used to study factors affecting the disposition of aerosolized insulin. The model calculates the trajectories of inhaled particles in the lung and has been validated by data from human subject experiments. Computer simulations were performed describing a wide range of patient breathing maneuvers. The results indicate significant variations in particle deposition patterns within lungs for different tidal volumes, inspiratory flow rates, and breath hold times. These findings indicate that particle sizes and ventilatory parameters are significant factors determining locations of particle deposition within human lungs, and thus the absorption of insulin into the blood stream via alveloated airways. Mathematical modeling is a valuable technique to complement clinical studies in the targeted delivery of inhaled insulin.

Lung models: strengths and limitations.

The most widely used particle dosimetry models are those proposed by the National Council on Radiation Protection, International Commission for Radiological Protection, and the Netherlands National Institute of Public Health and the Environment (the RIVM model). Those models have inherent problems that may be regarded as serious drawbacks: for example, they are not physiologically realistic. They ignore the presence and commensurate effects of naturally occurring structural elements of lungs (eg, cartilaginous rings, carinal ridges), which have been demonstrated to affect the motion of inhaled air. Most importantly, the surface structures have been shown to influence the trajectories of inhaled particles transported by air streams. Thus, the model presented herein by Martonen et al may be perhaps the most appropriate for human lung dosimetry. In its present form, the model's major "strengths" are that it could be used for diverse purposes in medical research and practice, including: to target the delivery of drugs for diseases of the respiratory tract (eg, cystic fibrosis, asthma, bronchogenic carcinoma); to selectively deposit drugs for systemic distribution (eg, insulin); to design clinical studies; to interpret scintigraphy data from human subject exposures; to determine laboratory conditions for animal testing (ie, extrapolation modeling); and to aid in aerosolized drug delivery to children (pediatric medicine). Based on our research, we have found very good agreement between the predictions of our model and the experimental data of Heyder et al, and therefore advocate its use in the clinical arena. In closing, we would note that for the simulations reported herein the data entered into our computer program were the actual conditions of the Heyder et al experiments. However, the deposition model is more versatile and can simulate many aerosol therapy scenarios. For example, the core model has many computer subroutines that can be enlisted to simulate the effects of aerosol polydispersity, aerosol hygroscopicity, patient ventilation, patient lung morphology, patient age, and patient airway disease.

Human lung morphology models for particle deposition studies.

Knowledge of human lung morphology is of paramount importance in calculating deposition patterns of inhaled particulate matter (PM) to be used in the definition of ambient air quality standards. Due to the inherently complex nature of the branching structure of the airway network, practical assumptions must be made for modeling purposes. The most commonly used mathematical models reported in the literature that describe PM deposition use Weibel's model A morphology. This assumes the airways of the lung to be a symmetric, dichotomously branching system. However, computer simulations of this model, when compared to scintigraphy images, have shown it to lack physiological realism (Martonen et al., 1994a). Therefore, a more physiologically realistic model of the lung is needed to improve the current PM dosimetry models. Herein, a morphological model is presented that is based on laboratory data from planar gamma camera and single-photon emission computed tomography (SPECT) images. Key elements of this model include: The parenchymal wall of the lung is defined in mathematical terms, the whole lung is divided into distinct left and right components, a set of branching angles is derived from experimental measurements, and the branching network is confined within the discrete left and right components (i.e., there is no overlapping of airways). In future work, this new, more physiologically realistic morphological model can be used to calculate PM deposition patterns for risk assessment protocols.