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.

Three-dimensional simulations of airways within human lungs.

Information regarding the deposition patterns of inhaled particles has important implications to the fields of medicine and risk assessment. The former concerns the targeted delivery of inhaled pharmacological drugs (aerosol therapy); the latter concerns the risk assessment of inhaled air pollutants (inhalation toxicology). It is well documented in the literature that the behavior and fate of inhaled particles may be formulated using three families of variables: respiratory system morphologies, aerosol characteristics, and ventilatory parameters. It is straightforward to propose that the seminal role is played by morphology per se because the structures of individual airways and their spatial orientations within lungs affect the motion of air and the trajectories of transported particles. In previous efforts, we have developed original algorithms to describe airway networks within lungs and employed them as templates to interpret the results of single photon emission computed tomography (SPECTs) studies. In this work, we have advanced the process of mathematical modeling and computer simulations to produce three-dimensional (3D) images. We have tested the new in silico model by studying two different branching concepts: an inclusive (all airways present) system and a single "typical" pathway system. When viewed with the glasses supplied with this volume, the 3D nature of airway branching networks within lungs as displayed via our original computer graphics software is clear. We submit that the new technology will have numerous and seminal functions in future medical and toxicological regimens, the most fundamental being the creation of a platform to view natural 3D structures in vivo with related biological processes (e.g., disposition of inhaled pharmaceuticals).

Computer simulations of particle deposition in the lungs of chronic obstructive pulmonary disease patients.

Epidemiology data show that mortality rates for chronic obstructive pulmonary disease (COPD) patients increase with an increase in concentration of ambient particulate matter (PM). This is not seen for normal subjects. Therefore, the U.S. Environmental Protection Agency (EPA) has identified COPD patients as a susceptible subpopulation to be considered in regulatory standards. In the present study, a computer model was used to calculate deposition fractions of PM within the lungs of COPD patients. The morphology of COPD lungs was characterized by two distinct components: obstruction of airways (chronic bronchitis component), and degeneration of alveolar structure (emphysema component). The chronic bronchitis component was modeled by reducing airway diameters using airway resistance measurements in vivo, and the emphysema component was modeled by increasing alveolar volumes. Calculated results were compared with experimental data obtained from COPD patients for controlled breathing trials (tidal volume of 500 ml, respiratory time of 1 s) with a particle size of 1 microm. The model successfully depicts PM deposition patterns and their dependence on the severity of disease. The findings indicate that airway obstructions are the main cause for increased deposition in the COPD lung.

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.

Fluid dynamics in airway bifurcations: I. Primary flows.

The subject of fluid dynamics within human airways is of great importance for the risk assessment of air pollutants (inhalation toxicology) and the targeted delivery of inhaled pharmacologic drugs (aerosol therapy). As cited herein, experimental investigations of flow patterns have been performed on airway models and casts by a number of investigators. We have simulated flow patterns in human lung bifurcations and compared the results with the experimental data of Schreck (1972). The theoretical analyses were performed using a third-party software package, FIDAP, on the Cray T90 supercomputer. This effort is part of a systematic investigation where the effects of inlet conditions, Reynolds numbers, and dimensions and orientations of airways were addressed. This article focuses on primary flows using convective motion and isovelocity contour formats to describe fluid dynamics; subsequent articles in this issue consider secondary currents (Part II) and localized conditions (Part III). The agreement between calculated and measured results, for laminar flows with either parabolic or blunt inlet conditions to the bifurcations, was very good. To our knowledge, this work is the first to present such detailed comparisons of theoretical and experimental flow patterns in airway bifurcations. The agreement suggests that the methodologies can be employed to study factors affecting airflow patterns and particle behavior in human lungs.

Fluid dynamics in airway bifurcations: II. Secondary currents.

As the second component of a systematic investigation on flows in bifurcations reported in this journal, this work focused on secondary currents. The first article addressed primary flows and the third discusses localized conditions (both in this issue). Secondary flow patterns were studied in two lung bifurcation models (Schreck, 1972) using FIDAP with the Cray T90 supercomputer. The currents were examined at different prescribed distances distal to the carina. Effects of inlet conditions, Reynolds numbers, and diameter ratios and orientations of airways were addressed. The secondary currents caused by the presence of the carina and inclination of the daughter tubes exhibited symmetric, multivortex patterns. The intensities of the secondary currents became stronger for larger Reynolds numbers and larger angles of bifurcation.

Fluid dynamics in airway bifurcations: III. Localized flow conditions.

Localized flow conditions (e.g., backflows) in transition regions between parent and daughter airways of bifurcations were investigated using a computational fluid dynamics software code (FIDAP) with a Cray T90 supercomputer. The configurations of the bifurcations were based on Schreck s (1972) laboratory models. The flow intensities and spatial regions of reversed motion were simulated for different conditions. The effects of inlet velocity profiles, Reynolds numbers, and dimensions and orientations of airways were addressed. The computational results showed that backflow was increased for parabolic inlet conditions, larger Reynolds numbers, and larger daughter-to-parent diameter ratios. This article is the third in a systematic series addressed in this issue; the first addressed primary velocity patterns and the second discussed secondary currents.

A nonhuman primate aerosol deposition model for toxicological and pharmaceutical studies.

Nonhuman primates may be used as human surrogates in inhalation exposure studies to assess either the (1) adverse health effects of airborne particulate matter or (2) therapeutic effects of aerosolized drugs and proteins. Mathematical models describing the behavior and fate of inhaled aerosols may be used to complement such laboratory investigations. For example, the optimal conditions, in terms of ventilatory parameters (e.g., breathing frequency and tidal volume) and aerosol characteristics (e.g., geometric size and density), necessary to target drug delivery to specific sites within the respiratory tract may be estimated a priori with models. In this work a mathematical description of the rhesus monkey (Macaca mulatta) lung is presented for use with an aerosol deposition model. Deposition patterns of 0.01- to 5-microm-diameter monodisperse aerosols within lungs were calculated for 3 monkey lung models (using different descriptions of alveolated regions) and compared to human lung results obtained using a previously validated mathematical model of deposition physics. Our findings suggest that there are significant differences between deposition patterns in monkeys and humans. The nonhuman primates had greater exposures to inhaled substances, particularly on the basis of deposition per unit airway surface area. However, the different alveolar volumes in the rhesus monkey models had only minor effects on aerosol dosimetry within those lungs. By being aware of such quantitative differences, investigators can employ the respective primate models (human and nonhuman) to more effectively design and interpret the results of future inhalation exposure experiments.

Effects of tumors on inhaled pharmacologic drugs: I. Flow patterns.

Lung carcinomas are now the most common form of cancer. Clinical data suggest that tumors are found preferentially in upper airways, perhaps specifically at carina within bifurcations. The disease can be treated by aerosolized pharmacologic drugs. To enhance their efficacies site-specific drugs must be deposited selectively. Since inhaled particles are transported by air, flow patterns will naturally affect their trajectories. Therefore, in Part I of a systematic investigation, we focused on tumor-induced effects on airstreams, in Part II (the following article [p. 245]), particle trajectories were determined. To facilitate the targeted delivery of inhaled drugs, we simulated bifurcations with tumors on carinas using a commercial computational fluid dynamics (CFD) software package (FIDAP) with a Cray T90 supercomputer and studied effects of tumor sizes and ventilatory parameters on localized flow patterns. Critical tumor sizes existed; e.g., tumors had dominant effects when r/R > or = 0.8 for bifurcation 3-4 and r/R > or = 0.6 for bifurcation 7-8 (r = tumor radius and R = airway radius). The findings suggest that computer modeling is a means to integrate alterations to airway structures caused by diseases into aerosol therapy protocols.

Effects of tumors on inhaled pharmacologic drugs: II. Particle motion.

Computer simulations were conducted to describe drug particle motion in human lung bifurcations with tumors. The computations used FIDAP with a Cray T90 supercomputer. The objective was to better understand particle behavior as affected by particle characteristics, airflow conditions, and disease-modified airway geometries. The results indicated that increases in particle sizes, breathing intensities and tumor sizes could enhance drug deposition on the tumors. The modeling suggested that targeted drug delivery could be achieved by regulating breathing parameters and designing (selecting physical features of) aerosolized drugs. We present the theoretical work as a step towards improving aerosol therapy protocols. Since modeling describes factors affecting dose, it is complementary to considerations of the molecular aspects of drug formulation and pharmacokinetics.

Three-dimensional computer modeling of the human upper respiratory tract.

Computer simulations of airflow and particle-transport phenomena within the human respiratory system have important applications to aerosol therapy (e.g., the targeted delivery of inhaled drugs) and inhalation toxicology (e.g., the risk assessment of air pollutants). A detailed description of airway morphology is necessary for these simulations to accurately reflect conditions in vivo. Therefore, a three-dimensional (3D) physiologically realistic computer model of the human upper-respiratory tract (URT) has been developed. The URT morphological model consists of the extrathoracic (ET) region (nasal, oral, pharyngeal, and laryngeal passages) and upper airways (trachea and main bronchi) of the lung. The computer representation evolved from a silicone rubber impression of a medical school teaching model of the human head and throat. A mold of this ET system was sliced into 2-mm serial sections, scanned, and digitized. Numerical grids, for use in future computational fluid dynamics (CFD) simulations, were generated for each slice using commercially available software (CFX-F3D), AEA Technology, Harwell, UK. The meshed sections were subsequently aligned and connected to be consistent with the anatomical model. Finally, a 3D curvilinear grid and a multiblock method were employed to generate the complete computational mesh defined by the cross-sections. The computer reconstruction of the trachea and main bronchi was based on data from the literature (cited herein). The final unified 3D computer model may have significant applications to aerosol medicine and inhalation toxicology, and serve as a cornerstone for computer simulations of air flow and particle-transport processes in the human respiratory system.

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.

Evaluation of the accuracy and precision of lung aerosol deposition measurements from single-photon emission computed tomography using simulation.

Single-photon emission computed tomography (SPECT) imaging is being increasingly used to assess inhaled aerosol deposition. This study uses simulation to evaluate the errors involved in such measurements and to compare them with those from conventional planar imaging. SPECT images of known theoretical distributions of radioaerosol in the lung have been simulated using lung models derived from magnetic resonance studies in human subjects. Total lung activity was evaluated from the simulated images. A spherical transform of the lung distributions was performed, and the absolute penetration index (PI) and a relative value expressed as a fraction of that in a simulated ventilation image were calculated. All parameters were compared with the true value used in the simulation, and the errors were assessed. An iterative method was used to correct for the partial volume effect, and its effectiveness in improving errors was evaluated. The errors were compared with those of planar imaging. The precision of measurements was significantly better for SPECT than planar imaging (2.8 vs 6.3% for total lung activity, 6 vs 20% for PI, and 3 vs 6% for relative PI). The method of correcting for the influence of the partial volume effect significantly improved the accuracy of PI evaluation without affecting precision. SPECT is capable of accurate and precise measurements of aerosol distribution in the lung, which are improved compared with those measured by conventional planar imaging. A technique for correcting the SPECT data for the influence of the partial volume effect has been described. Simulation is demonstrated as a valuable method of technique evaluation and comparison.

Computer simulations of particle deposition in the developing human lung.

An age-dependent theoretical model has been developed to predict PM dosimetry in children's lungs. Computer codes have been written that describe the dimensions of individual airways and the geometry of branching airway networks within developing lungs. Breathing parameters have also been formulated as functions of subject age. Our computer simulations suggest that particle size, age, and activity level markedly affect deposition patterns of inhaled air pollutants. For example, the predicted lung deposition fraction is 38% in an adult but is nearly twice as high (73%) in a 7-month-old for 2-micron particles inhaled during heavy breathing. Tracheobronchial (TB) and pulmonary (or alveolated airways, P) deposition patterns may also be calculated using the model. Due to different clearance processes in the TB and P airways (i.e., mucociliary transport and macrophage action, respectively), the determination of compartmental dose is important for PM risk assessment analyses. Furthermore, the results of such simulations may aid in the setting of regulatory standards for air pollutants, as the data provide a scientific basis for estimating dose delivered to a designated sensitive subpopulation (children).

Comparison of computer simulations of total lung deposition to human subject data in healthy test subjects.

A mathematical model was used to predict the deposition fractions (DF) of PM within human lungs. Simulations using this computer model were previously validated with human subject data and were used as a control case. Human intersubject variation was accounted for by scaling the base lung morphology dimensions based on measured functional residual capacity (FRC) values. Simulations were performed for both controlled breathing (tidal volumes [VT] of 500 and 1000 mL, respiratory times [T] from 2 to 8 sec) and spontaneous breathing conditions. Particle sizes ranged from 1 to 5 microns. The deposition predicted from the computer model compared favorably with the experimental data. For example, when VT = 1000 mL and T = 2 sec, the error was 1.5%. The errors were slightly higher for smaller tidal volumes. Because the computer model is deterministic (i.e., derived from first principles of physics), the model can be used to predict deposition fractions for a range of situations (i.e., for different ventilatory parameters and particle sizes) for which data are not available. Now that the model has been validated, it may be applied to risk assessment efforts to estimate the inhalation hazards of airborne pollutants.

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.

Importance of cloud motion on cigarette smoke deposition in lung airways.

Deposition patterns of mainstream cigarette smoke were studied in casts of human extrathoracic and lung airways. The laboratory tests were designed to simulate smoking (i.e., the behavior of undiluted cigarette smoke in smokers' lungs), not secondary exposures to non-smokers. The experimental data revealed concentrated deposits at well-defined sites, particularly at bifurcations (most notably at inclusive carinal ridges) and certain segments of tubular airways. The measurements suggest the occurrence of cloud motion wherein particles are not deposited by their individual characteristics but behave as an entity. The observed behavior is consistent with the theory of Martonen (1992), where it was predicted that cigarette smoke could behave aerodynamically as a large cloud (e.g., 20 microns diameter) rather than as submicrometer constituent particles. The effects of cloud motion on deposition are pronounced. For example, an aerosol with a mass median aerodynamic diameter (MMAD) of 0.443 micron and geometric standard deviation (GSD) of 1.44 (i.e., published cigarette smoke values) will have the following deposition fractions: lung (TB + P) = 0.14, tracheobronchial (TB) = 0.03, and pulmonary (P) = 0.11. When cloud motion is simulated, total deposition increases to 0.99 and is concentrated in the TB compartment, especially the upper bronchi; pulmonary deposition is negligible. Cloud motion produces heterogeneous deposition resulting in increased exposures of underlying airway cells to toxic and carcinogenic substances. The deposition sites correlated with incidence of cancers in vivo. At present, cloud motion concentration effects per se are not addressed in federal regulatory standards. The experimental and theoretical data suggest that concentrations of particulate matter may be an important factor to be integrated into U.S. Environmental Protection Agency (EPA) risk assessment protocols.