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.

Rationale: Smoking-related microvascular loss causes end-organ damage in the kidneys, heart, and brain. Basic research suggests a similar process in the lungs, but no large studies have assessed pulmonary microvascular blood flow (PMBF) in early chronic lung disease.Objectives: To investigate whether PMBF is reduced in mild as well as more severe chronic obstructive pulmonary disease (COPD) and emphysema.Methods: PMBF was measured using gadolinium-enhanced magnetic resonance imaging (MRI) among smokers with COPD and control subjects age 50 to 79 years without clinical cardiovascular disease. COPD severity was defined by standard criteria. Emphysema on computed tomography (CT) was defined by the percentage of lung regions below 2950 Hounsfield units (2950 HU) and by radiologists using a standard protocol. We adjusted for potential confounders, including smoking, oxygenation, and left ventricular cardiac output.Measurements and Main Results: Among 144 participants, PMBF was reduced by 30% in mild COPD, by 29% in moderate COPD, and by 52% in severe COPD (all P , 0.01 vs. control subjects). PMBF was reduced with greater percentage emphysema 2950HU and radiologist-defined emphysema, particularly panlobular and centrilobular emphysema (all P < 0.01). Registration of MRI and CT images revealed that PMBF was reduced in mild COPD in both nonemphysematous and emphysematous lung regions. Associations for PMBF were independent of measures of small airways disease on CT and gas trapping largely because emphysema and small airways disease occurred in different smokers.Conclusions: PMBF was reduced in mild COPD, including in regions of lung without frank emphysema, and may represent a distinct pathological process from small airways disease. PMBF may provide an imaging biomarker for therapeutic strategies targeting the pulmonary microvasculature.

The effects of intra- and intersubject variabilities in airway geometry on airflow in the human lungs are investigated by large eddy simulation. The airway models of two human subjects consisting of extra- and intrathoracic airways are reconstructed from CT images. For intrasubject study, airflows at two inspiratory flow rates are simulated on the airway geometries of the same subject with four different levels of truncation. These airway models are the original complete geometry and three geometries obtained by truncating the original one at the subglottis, the supraglottis, and the laryngopharynx, respectively. A comparison of the airflows in the complete geometry model shows that the characteristics of the turbulent laryngeal jet in the trachea are similar regardless of Reynolds number in terms of mean velocities, turbulence statistics, coherent structures, and pressure distribution. The truncated airway models, however, do not produce the similar flow structures observed in the complete geometry. An improved inlet boundary condition is then proposed for the airway model truncated at the laryngopharynx to improve the accuracy of solution. The new boundary condition significantly improves the mean flow. The spectral analysis shows that turbulent characteristics are captured downstream away from the glottis. For intersubject study, although the overall flow characteristics are similar, two morphological factors are found to significantly affect the flows between subjects. These are the constriction ratio of the glottis with respect to the trachea and the curvature and shape of the airways.

A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.

High frequency oscillatory ventilation (HFOV) is considered an efficient and safe respiratory technique to ventilate neonates and patients with acute respiratory distress syndrome. HFOV has very different characteristics from normal breathing physiology, with a much smaller tidal volume and a higher breathing frequency. In this work, the high frequency oscillatory flow is studied using a computational fluid dynamics (CFD) analysis in three different geometrical models with increasing complexity: a straight tube, a single-bifurcation tube model, and a computedtomography (CT)-based human airway model of up to seven generations. We aim to understand the counter-flow phenomenon at flow reversal and its role in convective mixing in these models using sinusoidal waveforms of different frequencies and Reynolds numbers. Mixing is quantified by the stretch rate analysis. In the straight-tube model, coaxial counter flow with opposing fluid streams is formed around flow reversal, agreeing with an analytical Womersley solution. However, counter flow yields no net convective mixing at end cycle. In the single-bifurcation model, counter flow at high Re is intervened with secondary vortices in the parent (child) branch at end expiration (inspiration), resulting in an irreversible mixing process. For the CT-based airway model three cases are considered, consisting of the normal breathing case, the highfrequency-normal-Re case, and the HFOV case. The counter-flow structure is more evident in the high-frequency-normal-Re case than the HFOV case. The instantaneous and time-averaged stretch rates at the end of two breathing cycles and in the vicinity of flow reversal are computed. It is found that counter flow contributes about 20% to mixing in HFOV.