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Poorbahrami K, Allshouse MR, Oakes JM. Dosimetry Sensitivity in a Lower Dimensional Model of Patient-Specific Asthma Subjects. IEEE Trans Biomed Eng 2023; 70:2581-2591. [PMID: 37030850 DOI: 10.1109/tbme.2023.3255784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2023]
Abstract
OBJECTIVE Experimental uncertainty will impact in silico model calculations of aerosol delivery and deposition. Patient-specific dosimetry models are often parameterized based on medical imaging data, which contain inherent experimental variability. METHODS Here, we created and parameterized 1D models of three subject-specific asthmatic subjects and randomly assigned perturbations of up to 15 % on airway diameter, segmental volume, and defected volume. Sensitivity of imaging data experimental variability on dosimetry metrics were quantified. RESULTS Lobar particle delivery primarily depended on the distal segmental volumes; 15 % range of noise resulted in delivery to the upper right lobe to vary at most from 15.2 and 18.2 % for one of the severe subjects. Particle deposition was most sensitive to airway diameter; 95 % confidence intervals spanned from 8 to 10.6 % in the mild/moderate subject for 15 % variation on input metrics for 5 [Formula: see text] diameter particles. While these results provide possible ranges of dosimetry calculations for a specific subject, the perturbations were not sufficient to model the large observed inter-subject variability (8.9, 19, and 14.5 % deposition, subjects 1--3, respectively, 5 [Formula: see text] diameter particles). CONCLUSION This study highlights that in silico model predictions are robust in the presence of experimental uncertainty and that it continues to be necessary to perform subject-specific simulations, especially within the presence of heterogeneous airway disease. SIGNIFICANCE Sensitivity analysis provides confidence in calculating deposition in the airways of asthmatic subjects within the presence of experimental uncertainty.
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2
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Polak AG. Algebraic approximation of the distributed model for the pressure drop in the respiratory airways. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2022; 38:e3632. [PMID: 35648086 DOI: 10.1002/cnm.3632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/06/2022] [Accepted: 05/28/2022] [Indexed: 06/15/2023]
Abstract
The complexity of the human respiratory system causes that one of the main methods of analyzing the dynamic pulmonary phenomena and interpreting experimental results are simulations of its computational models. Among the most compound elements of these models, apart from the bronchial tree structure, is the phenomenon of flow limitation in flexible bronchi, which causes them to collapse with increasing flow, thus their properties, such as resistance, compliance and inertance, are highly nonlinear and time-varying. Commonly, this phenomenon is ignored, or a distributed model for the airway pressure drop is applied, simulated with a modified numerical solver of this differential equation (ODE). The disadvantages of this solution are the problems with taking into account the inherent singularity of the model and the long computation time due to iterative nature of the ODE procedure. The aim of the work was to derive an algebraic approximation of this distributed model, suitable for implementation in continuous dynamic models, to validate it by comparing the results of simulations with the respiratory system model including approximate and original (ODE solver) numerical procedures, as well as to evaluate possible acceleration of calculations. All simulations, including spontaneous breathing, mechanical ventilation with the optimal ventilatory waveform and forced expiration, proved that algebraic approximation yielded results negligibly differing from the ODE solution, and shortened the computation time by an order. The proposed approach is an attractive alternative in the case of computer implementations of pulmonary models, where simulations of flows and pressures in the complex respiratory system are of primary importance.
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Affiliation(s)
- Adam G Polak
- Department of Electronic and Photonic Metrology, Faculty of Electronics, Photonics and Microsystems, Wrocław University of Science and Technology, Wrocław, Poland
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3
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Inui S, Yoon SH, Doganay O, Gleeson FV, Kim M. Impaired pulmonary ventilation beyond pneumonia in COVID-19: A preliminary observation. PLoS One 2022; 17:e0263158. [PMID: 35077496 PMCID: PMC8789183 DOI: 10.1371/journal.pone.0263158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 01/12/2022] [Indexed: 01/08/2023] Open
Abstract
Background Coronavirus disease 2019 (COVID-19) may severely impair pulmonary function and cause hypoxia. However, the association of COVID-19 pneumonia on CT with impaired ventilation remains unexplained. This pilot study aims to demonstrate the relationship between the radiological findings on COVID-19 CT images and ventilation abnormalities simulated in a computational model linked to the patients’ symptoms. Methods Twenty-five patients with COVID-19 and four test-negative healthy controls who underwent a baseline non-enhanced CT scan: 7 dyspneic patients, 9 symptomatic patients without dyspnea, and 9 asymptomatic patients were included. A 2D U-Net-based CT segmentation software was used to quantify radiological futures of COVID-19 pneumonia. The CT image-based full-scale airway network (FAN) flow model was employed to assess regional lung ventilation. Functional and radiological features were compared across groups and correlated with the clinical symptoms. Heterogeneity in ventilation distribution and ventilation defects associated with the pneumonia and the patients’ symptoms were assessed. Results Median percentage ventilation defects were 0.2% for healthy controls, 0.7% for asymptomatic patients, 1.2% for symptomatic patients without dyspnea, and 11.3% for dyspneic patients. The median of percentage pneumonia was 13.2% for dyspneic patients and 0% for the other groups. Ventilation defects preferentially affected the posterior lung and worsened with increasing pneumonia linearly (y = 0.91x + 0.99, R2 = 0.73) except for one of the nine dyspneic patients who had disproportionally large ventilation defects (7.8% of the entire lung) despite mild pneumonia (1.2%). The symptomatic and dyspneic patients showed significantly right-skewed ventilation distributions (symptomatic without dyspnea: 0.86 ± 0.61, dyspnea 0.91 ± 0.79) compared to the patients without symptom (0.45 ± 0.35). The ventilation defect analysis with the FAN model provided a comparable diagnostic accuracy to the percentage pneumonia in identifying dyspneic patients (area under the receiver operating characteristic curve, 0.94 versus 0.96). Conclusions COVID-19 pneumonia segmentations from CT scans are accompanied by impaired pulmonary ventilation preferentially in dyspneic patients. Ventilation analysis with CT image-based computational modelling shows it is able to assess functional impairment in COVID-19 and potentially identify one of the aetiologies of hypoxia in patients with COVID-19 pneumonia.
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Affiliation(s)
- Shohei Inui
- Departments of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Departments of Radiology, Japan Self- Defense Forces Central Hospital, Tokyo, Japan
| | - Soon Ho Yoon
- Department of Radiology, UMass Memorial Medical Center, Worcester, MA, United States of America
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Ozkan Doganay
- Healthy Science Institute, Ege University, Izmir, Turkey
| | - Fergus V. Gleeson
- Department of Oncology, University of Oxford, Oxford, United Kingdom
- Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, United Kingdom
| | - Minsuok Kim
- Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, United Kingdom
- * E-mail:
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Parraga G, Eddy RL. Measuring Regional Pulmonary Function Using Noncontrast CT: More Reasons to Join the FAN Bandwagon. Radiology 2020; 298:210-211. [PMID: 33236961 DOI: 10.1148/radiol.2020203983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Grace Parraga
- From the Robarts Research Institute, Department of Medical Biophysics, and Division of Respirology, Department of Medicine, Western University, 1151 Richmond St N, London, ON, Canada N6A 5B7 (G.P.); Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, Canada (R.L.E.); and Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, Canada (R.L.E.)
| | - Rachel L Eddy
- From the Robarts Research Institute, Department of Medical Biophysics, and Division of Respirology, Department of Medicine, Western University, 1151 Richmond St N, London, ON, Canada N6A 5B7 (G.P.); Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, Canada (R.L.E.); and Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, Canada (R.L.E.)
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5
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Kim M, Doganay O, Hwang HJ, Seo JB, Gleeson FV. Lobar Ventilation in Patients with COPD Assessed with the Full-Scale Airway Network Flow Model and Xenon-enhanced Dual-Energy CT. Radiology 2020; 298:201-209. [PMID: 33231530 DOI: 10.1148/radiol.2020202485] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Background The full-scale airway network (FAN) flow model shows excellent agreement with limited functional imaging data but requires further validation prior to clinical use. Purpose To validate the ventilation distributions computed with the FAN flow model with xenon ventilation from xenon-enhanced dual-energy (DE) CT in participants with chronic obstructive pulmonary disease (COPD). Materials and Methods In this prospective study, the FAN model extracted structural data from xenon-enhanced DE CT images of men with COPD scanned between June 2012 and July 2013 to compute gas ventilation dynamics. The ventilation distributions on the middle cross-section plane, percentage lobar ventilation, and ventilation heterogeneity quantified by the coefficient of variation (CV) were compared between xenon-enhanced DE CT imaging and the FAN model. The relationship between the ventilation parameters with the densitometry and pulmonary function test results was demonstrated. The agreements and correlations between the parameters were measured using the concordance correlation coefficient and the Pearson correlation coefficient. Results Twenty-two men with COPD (mean age, 67 years ± 7 [standard deviation]) were evaluated. The percentage lobar ventilation computed with FAN showed a strong positive correlation with xenon-enhanced DE CT data (r = 0.7, P < .001). Ninety-five percent of lobar ventilation CV differences lay within 95% confidence intervals. Correlations of the percentage lobar ventilation were negative for percentage emphysema (xenon-enhanced DE CT: r = -0.38, P < .001; FAN: r = -0.23, P = .02) but were positive for percentage normal tissue volume (xenon-enhanced DE CT: r = 0.78, P < .001; FAN: r = 0.45, P < .001). Lung CVs of FAN revealed negative correlations with the spirometry results (CVFAN vs percentage predicted forced expiratory volume in 1 second: r = -0.75, P < .001; CVFAN vs ratio of forced expiratory volume in 1 second to forced vital capacity: r = -0.67, P < .001). Conclusion The full-scale airway network modeled lobar ventilation in patients with chronic obstructive pulmonary disease correlated with the xenon-enhanced dual-energy CT imaging data. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Parraga and Eddy in this issue.
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Affiliation(s)
- Minsuok Kim
- From the School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, England (M.K.); Healthy Science Institute, Ege University, Izmir, Turkey (O.D.); Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea (H.J.H., J.B.S.); Department of Oncology, University of Oxford, Oxford, England (F.V.G.); and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (F.V.G.)
| | - Ozkan Doganay
- From the School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, England (M.K.); Healthy Science Institute, Ege University, Izmir, Turkey (O.D.); Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea (H.J.H., J.B.S.); Department of Oncology, University of Oxford, Oxford, England (F.V.G.); and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (F.V.G.)
| | - Hye Jeon Hwang
- From the School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, England (M.K.); Healthy Science Institute, Ege University, Izmir, Turkey (O.D.); Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea (H.J.H., J.B.S.); Department of Oncology, University of Oxford, Oxford, England (F.V.G.); and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (F.V.G.)
| | - Joon Beom Seo
- From the School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, England (M.K.); Healthy Science Institute, Ege University, Izmir, Turkey (O.D.); Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea (H.J.H., J.B.S.); Department of Oncology, University of Oxford, Oxford, England (F.V.G.); and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (F.V.G.)
| | - Fergus V Gleeson
- From the School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, England (M.K.); Healthy Science Institute, Ege University, Izmir, Turkey (O.D.); Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea (H.J.H., J.B.S.); Department of Oncology, University of Oxford, Oxford, England (F.V.G.); and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (F.V.G.)
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Yoon S, Tam TM, Rajaraman PK, Lin CL, Tawhai M, Hoffman EA, Choi S. An integrated 1D breathing lung simulation with relative hysteresis of airway structure and regional pressure for healthy and asthmatic human lungs. J Appl Physiol (1985) 2020; 129:732-747. [PMID: 32758040 DOI: 10.1152/japplphysiol.00176.2020] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
This study aims to develop a one-dimensional (1D) computational fluid dynamics (CFD) model with dynamic airway geometry that considers airway wall compliance and acinar dynamics. The proposed 1D model evaluates the pressure distribution and the hysteresis between the pressure and tidal volume (Vtidal) in the central and terminal airways for healthy and asthmatic subjects. Four-dimensional CT images were captured at 11-14 time points during the breathing cycle. The airway diameter and length were reconstructed using a volume-filling method and a stochastic model at respective time points. The obtained values for the airway diameter and length were interpolated via the Akima spline to avoid unboundedness. A 1D energy balance equation considering the effects of wall compliance and parenchymal inertance was solved using the efficient aggregation-based algebraic multigrid solver, a sparse matrix solver, reducing the computational costs by around 90% when compared with the generalized minimal residual solver. In the Vtidal versus displacement in the basal direction (z-coordinate), the inspiration curve was lower than the expiration curve, leading to relative hysteresis. The dynamic deformation model was the major factor influencing the difference in the workload in the central and terminal airways. In contrast, wall compliance and parenchymal inertance appeared only marginally to affect the pressure and workload. The integrated 1D model mimicked dynamic deformation by predicting airway diameter and length at each time point, describing the effects of wall compliance and parenchymal inertance. This computationally efficient model could be utilized to assess breathing mechanism as an alternative to pulmonary function tests.NEW & NOTEWORTHY This study introduces a one-dimensional (1D) computational fluid dynamics (CFD) model mimicking the realistic changes in diameter and length in whole airways and reveals differences in lung deformation between healthy and asthmatic subjects. Utilizing computational models, the effects of parenchymal inertance and airway wall compliance are investigated by changing ventilation frequency and airway wall elastance, respectively.
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Affiliation(s)
- Sujin Yoon
- School of Mechanical Engineering, Kyungpook National University, Daegu, South Korea
| | - Tran Minh Tam
- School of Mechanical Engineering, Kyungpook National University, Daegu, South Korea
| | - Prathish K Rajaraman
- IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, Iowa.,Department of Mechanical Engineering, University of Iowa, Iowa City, Iowa
| | - Ching-Long Lin
- IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, Iowa.,Department of Mechanical Engineering, University of Iowa, Iowa City, Iowa.,Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa.,Department of Radiology, University of Iowa, Iowa City, Iowa
| | - Merryn Tawhai
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Eric A Hoffman
- Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa.,Department of Radiology, University of Iowa, Iowa City, Iowa.,Department of Internal Medicine, University of Iowa, Iowa City, Iowa
| | - Sanghun Choi
- School of Mechanical Engineering, Kyungpook National University, Daegu, South Korea
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Nousias S, Zacharaki EI, Moustakas K. AVATREE: An open-source computational modelling framework modelling Anatomically Valid Airway TREE conformations. PLoS One 2020; 15:e0230259. [PMID: 32243444 PMCID: PMC7122715 DOI: 10.1371/journal.pone.0230259] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 02/25/2020] [Indexed: 11/18/2022] Open
Abstract
This paper presents AVATREE, a computational modelling framework that generates Anatomically Valid Airway tree conformations and provides capabilities for simulation of broncho-constriction apparent in obstructive pulmonary conditions. Such conformations are obtained from the personalized 3D geometry generated from computed tomography (CT) data through image segmentation. The patient-specific representation of the bronchial tree structure is extended beyond the visible airway generation depth using a knowledge-based technique built from morphometric studies. Additional functionalities of AVATREE include visualization of spatial probability maps for the airway generations projected on the CT imaging data, and visualization of the airway tree based on local structure properties. Furthermore, the proposed toolbox supports the simulation of broncho-constriction apparent in pulmonary diseases, such as chronic obstructive pulmonary disease (COPD) and asthma. AVATREE is provided as an open-source toolbox in C++ and is supported by a graphical user interface integrating the modelling functionalities. It can be exploited in studies of gas flow, gas mixing, ventilation patterns and particle deposition in the pulmonary system, with the aim to improve clinical decision making.
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Affiliation(s)
- Stavros Nousias
- Department of Electrical and Computer Engineering, University of Patras, Patras, Greece
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8
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Kim M, Doganay O, Matin TN, Povey T, Gleeson FV. CT-based Airway Flow Model to Assess Ventilation in Chronic Obstructive Pulmonary Disease: A Pilot Study. Radiology 2019; 293:666-673. [PMID: 31617794 DOI: 10.1148/radiol.2019190395] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background The lack of functional information in thoracic CT remains a limitation of its use in the clinical management of chronic obstructive pulmonary disease (COPD). Purpose To compare the distribution of pulmonary ventilation assessed by a CT-based full-scale airway network (FAN) flow model with hyperpolarized xenon 129 (129Xe) MRI (hereafter, 129Xe MRI) and technetium 99m-diethylenetriaminepentaacetic acid aerosol SPECT ventilation imaging (hereafter, V-SPECT) in participants with COPD. Materials and Methods In this prospective study performed between May and August 2017, pulmonary ventilation in participants with COPD was computed by using the FAN flow model. The modeled pulmonary ventilation was compared with functional imaging data from breath-hold time-series 129Xe MRI and V-SPECT. FAN-derived ventilation images on the coronal plane and volumes of interest were compared with functional lung images. Percentage lobar ventilation estimated by the FAN model was compared with that measured at 129Xe MRI and V-SPECT. The statistical significance of ventilation distribution between FAN and functional images was demonstrated with the Spearman correlation coefficient and χ2 distance. Results For this study, nine participants (seven men [mean age, 65 years ± 5 {standard deviation}] and two women [mean age, 63 years ± 7]) with COPD that was Global Initiative for Chronic Obstructive Lung Disease stage II-IV were enrolled. FAN-modeled ventilation profile showed strong positive correlation with images from 129Xe MRI (ρ = 0.67; P < .001) and V-SPECT (ρ = 0.65; P < .001). The χ2 distances of the ventilation histograms in the volumes of interest between the FAN and 129Xe MRI and FAN and V-SPECT were 0.16 ± 0.08 and 0.28 ± 0.14, respectively. The ratios of lobar ventilations in the models were linearly correlated to images from 129Xe MRI (ρ = 0.67; P < .001) and V-SPECT (ρ = 0.59; P < .001). Conclusion A CT-based full-scale airway network flow model provided regional pulmonary ventilation information for chronic obstructive pulmonary disease and correlates with hyperpolarized xenon 129 MRI and technetium 99m-diethylenetriaminepentaacetic acid aerosol SPECT ventilation imaging. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Schiebler and Parraga in this issue.
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Affiliation(s)
- Minsuok Kim
- From the Departments of Engineering Science (M.K., T.P.) and Oncology (O.D., F.V.G.), University of Oxford, Parks Road, Oxford OX1 3PJ, England; and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (O.D., T.N.M., F.V.G.)
| | - Ozkan Doganay
- From the Departments of Engineering Science (M.K., T.P.) and Oncology (O.D., F.V.G.), University of Oxford, Parks Road, Oxford OX1 3PJ, England; and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (O.D., T.N.M., F.V.G.)
| | - Tahreema N Matin
- From the Departments of Engineering Science (M.K., T.P.) and Oncology (O.D., F.V.G.), University of Oxford, Parks Road, Oxford OX1 3PJ, England; and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (O.D., T.N.M., F.V.G.)
| | - Thomas Povey
- From the Departments of Engineering Science (M.K., T.P.) and Oncology (O.D., F.V.G.), University of Oxford, Parks Road, Oxford OX1 3PJ, England; and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (O.D., T.N.M., F.V.G.)
| | - Fergus V Gleeson
- From the Departments of Engineering Science (M.K., T.P.) and Oncology (O.D., F.V.G.), University of Oxford, Parks Road, Oxford OX1 3PJ, England; and Department of Radiology, The Churchill Hospital, Oxford University Hospitals NHS Trust, Headington, England (O.D., T.N.M., F.V.G.)
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Poorbahrami K, Mummy DG, Fain SB, Oakes JM. Patient-specific modeling of aerosol delivery in healthy and asthmatic adults. J Appl Physiol (1985) 2019; 127:1720-1732. [PMID: 31513445 DOI: 10.1152/japplphysiol.00221.2019] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The magnitude and regional heterogeneity of airway obstructions in severe asthmatics is likely linked to insufficient drug delivery, as evidenced by the inability to mitigate exacerbations with inhaled aerosol medications. To understand the correlation between morphometric features, airflow distribution, and inhaled dosimetry, we perform dynamic computational simulations in two healthy and four asthmatic subjects. Models incorporate computed tomography-based and patient-specific central airway geometries and hyperpolarized 3He MRI-measured segmental ventilation defect percentages (SVDPs), implemented as resistance boundary conditions. Particles [diameters (dp) = 1, 3, and 5 μm] are simulated throughout inhalation, and we record their initial conditions, both spatially and temporally, with their fate in the lung. Predictions highlight that total central airway deposition is the same between the healthy subjects (26.6%, dp = 3 μm) but variable among the asthmatic subjects (ranging from 5.9% to 59.3%, dp = 3 μm). We found that by preferentially releasing the particles during times of fast or slow inhalation rates we enhance either central airway deposition percentages or peripheral particle delivery, respectively. These predictions highlight the potential to identify with simulations patients who may not receive adequate therapeutic dosages with inhaled aerosol medication and therefore identify patients who may benefit from alternative treatment strategies. Furthermore, by improving regional dose levels, we may be able to preferentially deliver drugs to the airways in need, reducing associated adverse side effects.NEW & NOTEWORTHY Although it is evident that exacerbation mitigation is unsuccessful in some asthmatics, it remains unclear whether or not these patients receive adequate dosages of inhaled therapeutics. By coupling MRI and computed tomography data with patient-specific computational models, our predictions highlight the large intersubject variability, specifically in severe asthma.
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Affiliation(s)
- Kamran Poorbahrami
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts
| | - David G Mummy
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin
| | - Sean B Fain
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Jessica M Oakes
- Department of Bioengineering, Northeastern University, Boston, Massachusetts
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Choi S, Yoon S, Jeon J, Zou C, Choi J, Tawhai MH, Hoffman EA, Delvadia R, Babiskin A, Walenga R, Lin CL. 1D network simulations for evaluating regional flow and pressure distributions in healthy and asthmatic human lungs. J Appl Physiol (1985) 2019; 127:122-133. [PMID: 31095459 DOI: 10.1152/japplphysiol.00016.2019] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
This study aimed to introduce a one-dimensional (1D) computational fluid dynamics (CFD) model for airway resistance and lung compliance to examine the relationship between airway resistance, pressure, and regional flow distribution. We employed five healthy and five asthmatic subjects who had dynamic computed tomography (CT) scans (4D CT) along with two static scans at total lung capacity and functional residual capacity. Fractional air-volume change ( ΔVairf ) from 4D CT was used for a validation of the 1D CFD model. We extracted the diameter ratio from existing data sets of 61 healthy subjects for computing mean and standard deviation (SD) of airway constriction/dilation in CT-resolved airways. The lobar mean (SD) of airway constriction/dilation was used to determine diameters of CT-unresolved airways. A 1D isothermal energy balance equation was solved, and pressure boundary conditions were imposed at the acinar region (model A) or at the pleural region (model B). A static compliance model was only applied for model B to link acinar and pleural regions. The values of 1D CFD-derived ΔVairf for model B demonstrated better correlation with 4D CT-derived ΔVairf than model A. In both inspiration and expiration, asthmatic subjects with airway constriction show much greater pressure drop than healthy subjects without airway constriction. This increased transpulmonary pressures in the asthmatic subjects, leading to an increased workload (hysteresis). The 1D CFD model was found to be useful in investigating flow structure, lung hysteresis, and pressure distribution for healthy and asthmatic subjects. The derived flow distribution could be used for imposing boundary conditions of 3D CFD. NEW & NOTEWORTHY A one-dimensional (1D) computational fluid dynamics (CFD) model for airway resistance and lung compliance was introduced to examine the relationship between airway resistance, pressure, and regional flow distribution. The 1D CFD model investigated differences of flow structure, lung hysteresis, and pressure distribution for healthy and asthmatic subjects. The derived flow distribution could be used for imposing boundary conditions of three-dimensional CFD.
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Affiliation(s)
- Sanghun Choi
- School of Mechanical Engineering, Kyungpook National University , Daegu , Republic of Korea
| | - Sujin Yoon
- School of Mechanical Engineering, Kyungpook National University , Daegu , Republic of Korea
| | - Jichan Jeon
- School of Mechanical Engineering, Kyungpook National University , Daegu , Republic of Korea
| | - Chunrui Zou
- Department of Mechanical Engineering, University of Iowa , Iowa City, Iowa.,IIHR-Hydroscience and Engineering, University of Iowa , Iowa City, Iowa
| | - Jiwoong Choi
- IIHR-Hydroscience and Engineering, University of Iowa , Iowa City, Iowa
| | - Merryn H Tawhai
- Auckland Bioengineering Institute, University of Auckland , Auckland , New Zealand
| | - Eric A Hoffman
- Department of Biomedical Engineering, University of Iowa , Iowa City, Iowa.,Department of Radiology, University of Iowa , Iowa City, Iowa.,Department of Internal Medicine, University of Iowa , Iowa City, Iowa
| | - Renishkumar Delvadia
- Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration , Silver Spring, Maryland
| | - Andrew Babiskin
- Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration , Silver Spring, Maryland
| | - Ross Walenga
- Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration , Silver Spring, Maryland
| | - Ching-Long Lin
- Department of Mechanical Engineering, University of Iowa , Iowa City, Iowa.,Department of Biomedical Engineering, University of Iowa , Iowa City, Iowa.,Department of Radiology, University of Iowa , Iowa City, Iowa.,IIHR-Hydroscience and Engineering, University of Iowa , Iowa City, Iowa
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Whitfield CA, Horsley A, Jensen OE. Modelling structural determinants of ventilation heterogeneity: A perturbative approach. PLoS One 2018; 13:e0208049. [PMID: 30496317 PMCID: PMC6264152 DOI: 10.1371/journal.pone.0208049] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 11/09/2018] [Indexed: 01/19/2023] Open
Abstract
We have developed a computational model of gas mixing and ventilation in the human lung represented as a bifurcating network. We have simulated multiple-breath washout (MBW), a clinical test for measuring ventilation heterogeneity (VH) in patients with obstructive lung conditions. By applying airway constrictions inter-regionally, we have predicted the response of MBW indices to obstructions and found that they detect a narrow range of severe constrictions that reduce airway radius to 10%–30% of healthy values. These results help to explain the success of the MBW test to distinguish obstructive lung conditions from healthy controls. Further, we have used a perturbative approach to account for intra-regional airway heterogeneity that avoids modelling each airway individually. We have found, for random airway heterogeneity, that the variance in MBW indices is greater when indices are already elevated due to constrictions. By quantifying this effect, we have shown that variability in lung structure and mechanical properties alone can lead to clinically significant variability in MBW indices (specifically the Lung Clearance Index—LCI, and the gradient of phase-III slopes—Scond), but only in cases simulating obstructive lung conditions. This method is a computationally efficient way to probe the lung’s sensitivity to structural changes, and to quantify uncertainty in predictions due to random variations in lung mechanical and structural properties.
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Affiliation(s)
- Carl A. Whitfield
- Division of Infection, Immunity and Respiratory Medicine, University of Manchester, Southmoor Road, Manchester, United Kingdom, M23 9LT
- School of Mathematics, University of Manchester, Oxford Road, Manchester, United Kingdom, M13 9PL
- * E-mail:
| | - Alex Horsley
- Division of Infection, Immunity and Respiratory Medicine, University of Manchester, Southmoor Road, Manchester, United Kingdom, M23 9LT
| | - Oliver E. Jensen
- School of Mathematics, University of Manchester, Oxford Road, Manchester, United Kingdom, M13 9PL
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12
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Oakes JM, Mummy D, Poorbahrami K, Zha W, Fain SB. Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects. IEEE Trans Biomed Eng 2018; 66:1318-1327. [PMID: 30281426 DOI: 10.1109/tbme.2018.2872845] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Combined, medical imaging data and respiratory computer simulations may facilitate novel insight into pulmonary disease phenotypes, including the structure/function relationships within the airways. This integration may ultimately enable improved classification and treatment of asthma. Severe asthma (15% of asthmatics) is particularly challenging to treat, as these patients do not respond well to inhaled therapeutics. METHODS This study combines medical image data with patient-specific computational models to predict gas distributions and airway mechanics in healthy and asthmatic subjects. We achieve this by integrating segmental volume defect percent (SVDP), measured from hyperpolarized 3He MRI and CT images, to create models of patient-specific gas flow within the conducting airways. Predicted and measured SVDP distributions are achieved when the prescribed resistances are increased systematically. RESULTS Because of differences in airway morphology and regional function, airway resistances and flow structures varied between the asthmatic subjects. Specifically, while mean SVDP was similar between the severe asthmatics (4.30±5.22 versus 3.54±5.98%), one subject exhibited abnormal flow structures, high near wall flow gradients, and enhanced conducting airway resistances (17.3E-3versus 1.1E-3 cmH2O-s/mL) in comparison to the other severe asthmatic subject. CONCLUSION By coupling medical imaging data with computer simulations, we provide detailed insight into pathological flow characteristics and airway mechanics in asthmatics, beyond what could be inferred independently.
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13
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Kim M, Collier GJ, Wild JM, Chung YM. Effect of upper airway on tracheobronchial fluid dynamics. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2018; 34:e3112. [PMID: 29856119 DOI: 10.1002/cnm.3112] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 05/24/2018] [Accepted: 05/27/2018] [Indexed: 05/17/2023]
Abstract
The upper airways play a significant role in the tracheal flow dynamics. Despite many previous studies, however, the effect of the upper airways on the ventilation distribution in distal airways has remained a challenge. The aim of this study is to experimentally and computationally investigate the dynamic behaviour in the intratracheal flow induced by the upper respiratory tract and to assess its influence on the subsequent tributaries. Patient-specific images from 2 different modalities (magnetic resonance imaging of the upper airways and computed tomography of the lower airways) were segmented and combined. An experimental phantom of patient-specific airways (including the oral cavity, larynx, trachea, down to generations 6-8) was generated using 3D printing. The flow velocities in this phantom model were measured by the flow-sensitised phase contrast magnetic resonance imaging technique and compared with the computational fluid dynamics simulations. Both experimental and computational results show a good agreement in the time-averaged velocity fields as well as fluctuating velocity. The flows in the proximal trachea were complex and unsteady under both lower- and higher-flow rate conditions. Computational fluid dynamics simulations were also performed with an airways model without the upper airways. Although the flow near the carina remained unstable only when the inflow rate was high, the influence of the upper airways caused notable changes in distal flow distributions when the 2 airways models were compared with and without the upper airways. The results suggest that the influence of the upper airways should be included in the respiratory flow assessment as the upper airways extensively affect the flows in distal airways and consequent ventilation distribution in the lungs.
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Affiliation(s)
- Minsuok Kim
- School of Engineering, University of Warwick, Coventry, UK
| | - Guilhem J Collier
- Academic Unit of Radiology, Institute for In Silico Medicine, University of Sheffield, Sheffield, UK
| | - Jim M Wild
- Academic Unit of Radiology, Institute for In Silico Medicine, University of Sheffield, Sheffield, UK
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14
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Choi S, Choi J, Lin CL. Contributions of Kinetic Energy and Viscous Dissipation to Airway Resistance in Pulmonary Inspiratory and Expiratory Airflows in Successive Symmetric Airway Models With Various Bifurcation Angles. J Biomech Eng 2018; 140:2657498. [PMID: 29049545 DOI: 10.1115/1.4038163] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Indexed: 11/08/2022]
Abstract
The aim of this study was to investigate and quantify contributions of kinetic energy and viscous dissipation to airway resistance during inspiration and expiration at various flow rates in airway models of different bifurcation angles. We employed symmetric airway models up to the 20th generation with the following five different bifurcation angles at a tracheal flow rate of 20 L/min: 15 deg, 25 deg, 35 deg, 45 deg, and 55 deg. Thus, a total of ten computational fluid dynamics (CFD) simulations for both inspiration and expiration were conducted. Furthermore, we performed additional four simulations with tracheal flow rate values of 10 and 40 L/min for a bifurcation angle of 35 deg to study the effect of flow rate on inspiration and expiration. Using an energy balance equation, we quantified contributions of the pressure drop associated with kinetic energy and viscous dissipation. Kinetic energy was found to be a key variable that explained the differences in airway resistance on inspiration and expiration. The total pressure drop and airway resistance were larger during expiration than inspiration, whereas wall shear stress and viscous dissipation were larger during inspiration than expiration. The dimensional analysis demonstrated that the coefficients of kinetic energy and viscous dissipation were strongly correlated with generation number. In addition, the viscous dissipation coefficient was significantly correlated with bifurcation angle and tracheal flow rate. We performed multiple linear regressions to determine the coefficients of kinetic energy and viscous dissipation, which could be utilized to better estimate the pressure drop in broader ranges of successive bifurcation structures.
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Affiliation(s)
- Sanghun Choi
- Department of Mechanical Engineering, Kyungpook National University, Daegu 41566, South Korea e-mail:
| | - Jiwoong Choi
- IIHR-Hydroscience & Engineering, Iowa City, IA 52242; Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 e-mail:
| | - Ching-Long Lin
- IIHR-Hydroscience & Engineering, Iowa City, IA 52242; Department of Mechanical and Industrial Engineering, 3131 Seamans Center for the Engineering Arts and Sciences Iowa City, The University of Iowa, Iowa City, IA 52242 e-mail:
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15
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Abstract
Biomedical research and clinical practice are struggling to cope with the growing complexity that the progress of health care involves. The most challenging diseases, those with the largest socioeconomic impact (cardiovascular conditions; musculoskeletal conditions; cancer; metabolic, immunity, and neurodegenerative conditions), are all characterized by a complex genotype-phenotype interaction and by a "systemic" nature that poses a challenge to the traditional reductionist approach. In 2005 a small group of researchers discussed how the vision of computational physiology promoted by the Physiome Project could be translated into clinical practice and formally proposed the term Virtual Physiological Human. Our knowledge about these diseases is fragmentary, as it is associated with molecular and cellular processes on the one hand and with tissue and organ phenotype changes (related to clinical symptoms of disease conditions) on the other. The problem could be solved if we could capture all these fragments of knowledge into predictive models and then compose them into hypermodels that help us tame the complexity that such systemic behavior involves. In 2005 this was simply not possible-the necessary methods and technologies were not available. Now, 10 years later, it seems the right time to reflect on the original vision, the results achieved so far, and what remains to be done.
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Affiliation(s)
- Marco Viceconti
- Department of Mechanical Engineering and Insigneo Institute for in silico Medicine, University of Sheffield, Sheffield S1 3JD, United Kingdom;
| | - Peter Hunter
- Auckland Bioengineering Institute, University of Auckland, Auckland 1142, New Zealand
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16
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Donovan GM. Inter-airway structural heterogeneity interacts with dynamic heterogeneity to determine lung function and flow patterns in both asthmatic and control simulated lungs. J Theor Biol 2017; 435:98-105. [PMID: 28867222 DOI: 10.1016/j.jtbi.2017.08.024] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 08/23/2017] [Accepted: 08/28/2017] [Indexed: 01/10/2023]
Abstract
Asthma is a disease involving both airway remodelling (e.g. thickening of the airway wall) and acute, reversible airway narrowing driven by airway smooth muscle contraction. Both of these processes are known to be heterogeneous, and in this study we consider a new theoretical model which considers the interactions of both mechanisms: structural heterogeneity (variation in airway remodelling) and dynamic heterogeneity (emergent variation in airway narrowing and flow). By integrating both types of inter-airway heterogeneity in a full human lung geometry, we are able to draw several insights regarding the mechanisms underlying observed ventilation heterogeneity. We show that: (1) bimodal ventilation distributions are driven by paradoxical contraction/dilation patterns for airways of all sizes; (2) structural heterogeneity differences between asthmatic and control subjects significantly influences resulting lung function, and observed ventilation heterogeneity patterns; and (3) individual airway dilation probabilities are uncorrelated with prior airway remodelling of that airway.
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Affiliation(s)
- G M Donovan
- Department of Mathematics, University of Auckland, New Zealand.
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17
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Montesantos S, Katz I, Venegas J, Pichelin M, Caillibotte G. The effect of disease and respiration on airway shape in patients with moderate persistent asthma. PLoS One 2017; 12:e0182052. [PMID: 28759656 PMCID: PMC5536319 DOI: 10.1371/journal.pone.0182052] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Accepted: 07/11/2017] [Indexed: 12/03/2022] Open
Abstract
Computational models of gas transport and aerosol deposition frequently utilize idealized models of bronchial tree structure, where airways are considered a network of bifurcating cylinders. However, changes in the shape of the lung during respiration affect the geometry of the airways, especially in disease conditions. In this study, the internal airway geometry was examined, concentrating on comparisons between mean lung volume (MLV) and total lung capacity (TLC). A set of High Resolution CT images were acquired during breath hold on a group of moderate persistent asthmatics at MLV and TLC after challenge with a broncho-constrictor (methacholine) and the airway trees were segmented and measured. The airway hydraulic diameter (Dh) was calculated through the use of average lumen area (Ai) and average internal perimeter (Pi) at both lung volumes and was found to be systematically higher at TLC by 13.5±9% on average, with the lower lobes displaying higher percent change in comparison to the lower lobes. The average internal diameter (Din) was evaluated to be 12.4±6.8% (MLV) and 10.8±6.3% (TLC) lower than the Dh, for all the examined bronchi, a result displaying statistical significance. Finally, the airway distensibility per bronchial segment and per generation was calculated to have an average value of 0.45±0.28, exhibiting high variability both between and within lung regions and generations. Mixed constriction/dilation patterns were recorded between the lung volumes, where a number of airways either failed to dilate or even constricted when observed at TLC. We conclude that the Dh is higher than Din, a fact that may have considerable effects on bronchial resistance or airway loss at proximal regions. Differences in caliber changes between lung regions are indicative of asthma-expression variability in the lung. However, airway distensibility at generation 3 seems to predict distensibility more distally.
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Affiliation(s)
| | - Ira Katz
- Medical R&D, Air Liquide Santé International, Paris Saclay, France.,Department of Mechanical Engineering, Lafayette College, Easton, PA, United States of America
| | - Jose Venegas
- Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Marine Pichelin
- Medical R&D, Air Liquide Santé International, Paris Saclay, France
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18
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Montesantos S, Katz I, Pichelin M, Caillibotte G. The Creation and Statistical Evaluation of a Deterministic Model of the Human Bronchial Tree from HRCT Images. PLoS One 2016; 11:e0168026. [PMID: 27977730 PMCID: PMC5157997 DOI: 10.1371/journal.pone.0168026] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2016] [Accepted: 11/25/2016] [Indexed: 02/03/2023] Open
Abstract
A quantitative description of the morphology of lung structure is essential prior to any form of predictive modeling of ventilation or aerosol deposition implemented within the lung. The human lung is a very complex organ, with airway structures that span two orders of magnitude and having a multitude of interfaces between air, tissue and blood. As such, current medical imaging protocols cannot provide medical practitioners and researchers with in-vivo knowledge of deeper lung structures. In this work a detailed algorithm for the generation of an individualized 3D deterministic model of the conducting part of the human tracheo-bronchial tree is described. Distinct initial conditions were obtained from the high-resolution computed tomography (HRCT) images of seven healthy volunteers. The algorithm developed is fractal in nature and is implemented as a self-similar space sub-division procedure. The expansion process utilizes physiologically realistic relationships and thresholds to produce an anatomically consistent human airway tree. The model was validated through extensive statistical analysis of the results and comparison of the most common morphological features with previously published morphometric studies and other equivalent models. The resulting trees were shown to be in good agreement with published human lung geometric characteristics and can be used to study, among other things, structure-function relationships in simulation studies.
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Affiliation(s)
| | - Ira Katz
- Medical R&D, Air Liquide Santé International, Paris Saclay, France
- Department of Mechanical Engineering, Lafayette College, Easton, PA, United States of America
| | - Marine Pichelin
- Medical R&D, Air Liquide Santé International, Paris Saclay, France
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19
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Development and Analysis of Patient-Based Complete Conducting Airways Models. PLoS One 2015; 10:e0144105. [PMID: 26656288 PMCID: PMC4684353 DOI: 10.1371/journal.pone.0144105] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2014] [Accepted: 11/13/2015] [Indexed: 11/19/2022] Open
Abstract
The analysis of high-resolution computed tomography (CT) images of the lung is dependent on inter-subject differences in airway geometry. The application of computational models in understanding the significance of these differences has previously been shown to be a useful tool in biomedical research. Studies using image-based geometries alone are limited to the analysis of the central airways, down to generation 6-10, as other airways are not visible on high-resolution CT. However, airways distal to this, often termed the small airways, are known to play a crucial role in common airway diseases such as asthma and chronic obstructive pulmonary disease (COPD). Other studies have incorporated an algorithmic approach to extrapolate CT segmented airways in order to obtain a complete conducting airway tree down to the level of the acinus. These models have typically been used for mechanistic studies, but also have the potential to be used in a patient-specific setting. In the current study, an image analysis and modelling pipeline was developed and applied to a number of healthy (n = 11) and asthmatic (n = 24) CT patient scans to produce complete patient-based airway models to the acinar level (mean terminal generation 15.8 ± 0.47). The resulting models are analysed in terms of morphometric properties and seen to be consistent with previous work. A number of global clinical lung function measures are compared to resistance predictions in the models to assess their suitability for use in a patient-specific setting. We show a significant difference (p < 0.01) in airways resistance at all tested flow rates in complete airway trees built using CT data from severe asthmatics (GINA 3-5) versus healthy subjects. Further, model predictions of airways resistance at all flow rates are shown to correlate with patient forced expiratory volume in one second (FEV1) (Spearman ρ = -0.65, p < 0.001) and, at low flow rates (0.00017 L/s), FEV1 over forced vital capacity (FEV1/FVC) (ρ = -0.58, p < 0.001). We conclude that the pipeline and anatomical models can be used directly in mechanistic modelling studies and can form the basis for future patient-based modelling studies.
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