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A computational fluid dynamics technique is applied to understand the relative importance of the upper and intra-thoracic airways and their role in determining central airflow patterns with particular attention paid to the importance of turbulence. The geometry of the human upper respiratory tract is derived from volumetric scans of a volunteer imaged via multidetector-row computed tomography. Geometry 1 consists of a mouth piece, the mouth, the oropharynx, the larynx, and the intra-thoracic airways of up to 6 generations. Geometry 2 comprises only the intra-thoracic airways. The results show that a curved sheet-like turbulent laryngeal jet is observed only in geometry 1 with turbulence intensity in the trachea varying from 10% to 20%, whereas the turbulence in geometry 2 is negligible. The presence of turbulence is found to increase the maximum localised wall shear stress by three folds. The proper orthogonal decomposition analysis reveals that the regions of high turbulence intensity are associated with Taylor-Görtler-like vortices. We conclude that turbulence induced by the laryngeal jet could significantly affect airway flow patterns as well as tracheal wall shear stress. Thus airflow modeling, particularly subject specific evaluations, should consider upper as well as intra-thoracic airway geometry.

The authors propose a nonrigid image registration approach to align two computed-tomography (CT)-derived lung datasets acquired during breath-holds at two inspiratory levels when the image distortion between the two volumes is large. The goal is to derive a three-dimensional warping function that can be used in association with computational fluid dynamics studies. In contrast to the sum of squared intensity difference (SSD), a new similarity criterion, the sum of squared tissue volume difference (SSTVD), is introduced to take into account changes in reconstructed Hounsfield units (scaled attenuation coefficient, HU) with inflation. This new criterion aims to minimize the local tissue volume difference within the lungs between matched regions, thus preserving the tissue mass of the lungs if the tissue density is assumed to be relatively constant. The local tissue volume difference is contributed by two factors: Change in the regional volume due to the deformation and change in the fractional tissue content in a region due to inflation. The change in the regional volume is calculated from the Jacobian value derived from the warping function and the change in the fractional tissue content is estimated from reconstructed HU based on quantitative CT measures. A composite of multilevel B-spline is adopted to deform images and a sufficient condition is imposed to ensure a one-to-one mapping even for a registration pair with large volume difference. Parameters of the transformation model are optimized by a limited-memory quasi-Newton minimization approach in a multiresolution framework. To evaluate the effectiveness of the new similarity measure, the authors performed registrations for six lung volume pairs. Over 100 annotated landmarks located at vessel bifurcations were generated using a semiautomatic system. The results show that the SSTVD method yields smaller average landmark errors than the SSD method across all six registration pairs.

Tawhai MH, Nash MP, Lin C, Hoffman EA. Supine and prone differences in regional lung density and pleural pressure gradients in the human lung with constant shape. J Appl Physiol 107: 912-920, 2009. First published July 9, 2009 doi:10.1152/japplphysiol.00324.2009The explanation for prone and supine differences in tissue density and pleural pressure gradients in the healthy lung has been inferred from several studies as compression of dependent tissue by the heart in the supine posture; however, this hypothesis has not been directly confirmed. Differences could also arise from change in shape of the chest wall and diaphragm, and because of shape with respect to gravity. The contribution of this third mechanism is explored here. Tissue density and static elastic recoil were estimated in the supine and prone left human lung at functional residual capacity using a finite-element analysis. Supine model geometries were derived from multidetector row computed tomography imaging of two subjects: one normal (subject 1), and one with small airway disease (subject 2). For each subject, the prone model was the supine lung shape with gravity reversed; therefore, the prone model was isolated from the influence of displacement of the diaphragm, chest wall, or heart. Model estimates were validated against multidetector row computed tomography measurement of regional density for each subject supine and an independent study of the prone and supine lung. The magnitude of the gradient in density supine (Ϫ4.33%/cm for subject 1, and Ϫ4.96%/cm for subject 2) was nearly twice as large as for the prone lung (Ϫ2.72%/cm for subject 1, and Ϫ2.51%/cm for subject 2), consistent with measurements in dogs. The corresponding pleural pressure gradients were 0.54 cmH2O/cm (subject 1) and 0.56 cmH2O/cm (subject 2) for supine, and 0.29 cmH2O/cm (subject 1) and 0.27 cmH2O/cm (subject 2) for prone. A smaller prone gradient was predicted without shape change of the "container" or support of the heart by the lung. The influence of the heart was to constrain the shape in which the lung deformed.pleural pressure gradient; lung orientation; acute lung injury; acute respiratory distress syndrome PRONE POSTURE HAS BEEN ADVOCATED for patients with acute lung injury or the acute respiratory distress syndrome because of observed improvement in gas exchange in several studies. Acute lung injury and acute respiratory distress syndrome involve acute pulmonary edema and inflammation, and they also typically involve reduced lung compliance, surfactant deficiency, and airway collapse. The improvement to gas exchange in the prone posture is not completely understood; however, several factors have been suggested to be involved: turning prone expands the tissue in the dorsal region (7), thereby improving local ventilation and drainage of secretions while reducing shunt; improved ventilation-perfusion matching; and reduced compression of lung tissue by the heart (1, 2, 14). It is likely that the beneficial effect on gas exchange arises from a combination of mechanisms;...

We present a novel image-based technique to estimate a subject-specific boundary condition (BC) for computational fluid dynamics (CFD) simulation of pulmonary air flow. The information of regional ventilation for an individual is derived by registering two computed tomography (CT) lung datasets and then passed to the CT-resolved airways as the flow BC. The CFD simulations show that the proposed method predicts lobar volume changes consistent with direct imagemeasured metrics, whereas the other two traditional BCs (uniform velocity or uniform pressure) yield lobar volume changes and regional pressure differences inconsistent with observed physiology.