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

https://doi.org/10.1016/j.medengphy.2007.11.002Get rights and content

Abstract

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.

Introduction

Computational fluid dynamics (CFD) analyses in the biomedical field are becoming more and more widely used. A lot of work has been done in the cardio-vascular field [8], [26] but also in the respiratory domain the technique is being employed more often, both for upper [6], [12], [27] and lower airway modeling [28], [29]. The application of CFD for studying the flow inside the airways could provide valuable information for the clinical practice (e.g. regional ventilation and resistance) and for the development and evaluation of inhalation treatments. If useful information is to be extracted within these frameworks, it is important to consider the effect of patient-specific geometries and boundary conditions (BC). Especially when dealing with patients with lung diseases, considerable deviations from averaged lung models with homogeneous BC can be found.

Many authors start facing the challenge of simulating flow behaviour inside the lower airways based on theoretical models. These models describe the branching structure of the airways of a normal, averaged human being and vary from the symmetric Weibel model [1], [13], [15], [17], [20] to more complicated asymmetric models [25]. The results provide valuable insight into the flow patterns inside a cascading tubing system, but morphological irregularities, that every respiratory system is prone to, are not taken into account. Consequently an evolution to image-based patient-specific lower airway models is foreseen [10], [20], [24].

Some studies have already considered patient-specific geometries, resulting in more realistic flow behaviour [5], [7], [16], [21]. However, the absence of patient-specific BC still limits the reliability of CFD results for application in clinical practice.

The aim of this project is to demonstrate a method to obtain an accurate patient-specific geometrical model with corresponding BC, then to perform an accurate flow simulation and validate the results with a widely used clinical method. This should improve and demonstrate the reliability of the method and allow the use of CFD for cases of interest within clinical practise, analysing the flow within (severely) diseased lung.

Section snippets

Methods

Performing patient-specific analysis introduces a number of complexities. Foremost, cooperation with the clinical practice is required to obtain high-resolution computed tomography (CT) or magnetic resonance imaging (MRI) images. Equally important as those images are the data relating to the lung level at which the image has been taken, the clinical condition of the patient, results of dynamic and static lung volumes such as forced expiratory volume in 1 s (FEV1), total lung capacity (TLC) and

Results

The gamma scintigraphy results are presented in Fig. 2. The top figures present the projections of the particles on an anterior and posterior plane respectively. The bottom two figures show the projection of particles from a 45° angle from left and right to determine the amount of peripheral deposition.

The results showed an asymmetrical distribution of the technetium particles inside the lower airways; more particles are observed in the right lung compared to the left lung. A quantitative

Discussion

The aim of the study was to determine a patient-specific approach to perform a numerical flow analysis of the air inside the lower airways. Emphasis has been put on obtaining detailed patient-specific models and on the determination of correct BC.

Based on CT images, information was extracted with respect to the airway morphology and the BC that need to be used. It was shown that a minimal invasive test can provide enough information to determine the internal flow distribution. A comparison with

Conclusion

This study has outlined a method for performing a patient-specific analysis of the respiratory system and validated the approach by comparing the outcome with the results of a clinical test. It has been illustrated that the distinct characteristics of pathological lungs not only raise the need to construct a model specifically for that patient but also the need to incorporate clinical data as a basis for accurate BC in the CFD workflow. A vast amount of information can be obtained through

Conflict of interest

This paper has been prepared according to all ethical and scientific standards. There are no conflicts of interest. Each of the authors has been involved in the design of the study, interpretation of the data, and writing of the manuscript and that each of the authors has read and concurs with the content in the manuscript. The material within has not been and will not be submitted for publication elsewhere except as an abstract.

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