Airflow modeling of steady inspiration in two realistic proximal airway trees reconstructed from human thoracic tomodensitometric images

Abstract

Detailed description of the flow field in human airways is highly important to better understand human breathing and provide a patient's customized diagnosis. An integrated numerical simulation platform is presently proposed in order to incorporate medical images into a numerical software to calculate flow field and to analyze it in terms of fluid dynamics. The platform was set up to compute steady inspiratory airflow in realistic human airways reconstructed from tomodensitometric medical images at resting breathing conditions. This morpho-functional simulation platform has been tested retrospectively with two CT-scanned patient airway morphological models: (i) a normal airway model (subject A) with no evidence of morphological alteration and (ii) a highly altered airway model (subject B) exhibiting a severe stenosis in the right main bronchus. First, various morphological aspects proper to each airway model are provided to show the performance and interest of the reconstruction method. Second, we describe the three-dimensional flow patterns associated to the global morphological features, which are mainly shared by the present realistic models and previous idealistic airway models. Finally, the flow characteristics associated to local morphological features specific to realistic airway models are discussed. The results demonstrate that the morpho-functional simulation platform is able to capture the main features of airway velocity patterns but also more specific airflow patterns which are related to customized patient morphological features such as laminar vortex formation. The present results suggest that the proposed airway functional imaging platform is adequate to provide most of functional information related to airflow and enable a patient to patient diagnosis.

Categorization of Lung Morphology Based on FRC and Height: Computer Simulations of Aerosol Deposition

“…Some specifics regarding this complex structure are not described in the Soong model, for instance, its asymmetric structure, the occurrence of trifurcations (Cohen et al 1990), the tracheal shape (Mehta and Myat 1984), and the differences in the main bifurcation angle (Karabulut 2005). In order to build a specific lung model for an individual, it may be necessary to use detailed characteristics of the subject's lung morphology-coming from medical images-to better represent his/her lung morphology (Vial et al 2005). The prediction of aerosolized drug transport and deposition would be realized in this patient-specific morphology and would help to adapt and optimize the treatment and lead to customized aerosol therapy regimens.…”

“…As such, aerosol deposition has been thoroughly investigated using 3-dimensional (3D) computational fluid dynamics (CFD) simulations of flow patterns and particle transport and deposition (Katz and Martonen 1996;Martonen et al 2005b;Vial et al 2005;Longest and Vinchurkar 2007;Farkas and Balashazy 2008;Xi et al 2008). Analytical modeling is an alternative to these 3D CFD methods.…”

Computational Modeling of Airway and Pulmonary Vascular Structure and Function: Development of a "Lung Physiome"

“…37,38 Medical imaging (typically CT, computed tomography) is now used routinely to construct geometric models of the upper-to-central airway. Recognizing the importance of anatomical geometry in the prediction of airflow, several groups have constructed models based on in vivo volumetric imaging, 8,39–42 and 3D CFD is beginning to be used to understand intersubject variability in inhaled fluid transport, 43 and response to clinical interventions. 44 A limitation of 3D CFD is that it is usually restricted to analysis of relatively small portions of the airway (or vascular) tree.…”

The lung physiome: merging imaging‐based measures with predictive computational models

“…Modern imaging provides a high‐resolution tool with which to measure and define the lung. Early imaging‐based studies measured the geometry of the airway tree;19 later work used imaging to derive models of the airway‐tree geometry and connectivity 4, 20–23. These anatomically based models are specific to an imaged individual rather than seeking to be representative of a population.…”