Segmentation and quantitative analysis of intrathoracic airway trees from computed tomography images

Chest CT Airway and Vascular Measurements in Females with COPD or Long-COVID

Chest CT provides a way to quantify pulmonary airway and vascular tree measurements. In patients with COPD, CT airway measurement differences in females are concomitant with worse quality-of-life and other outcomes. CT total airway count (TAC), airway lumen area (LA), and wall thickness (WT) also differ in females with long-COVID. Our objective was to evaluate CT airway and pulmonary vascular and quality-of-life measurements in females with COPD as compared to ex-smokers and patients with long-COVID. Chest CT was acquired 3-months post-COVID-19 infection in females with long-COVID for comparison with the same inspiratory CT in female ex-smokers and COPD patients. TAC, LA, WT, and pulmonary vascular measurements were quantified. Linear regression models were adjusted for confounders including age, height, body-mass-index, lung volume, pack-years and asthma diagnosis. Twenty-one females (53 ± 14 years) with long-COVID, 17 female ex-smokers (69 ± 9 years) and 13 female COPD (67 ± 6 years) patients were evaluated. In the absence of differences in quality-of-life scores, females with long-COVID reported significantly different LA (p = 0.006) compared to ex-smokers but not COPD (p = 0.7); WT% was also different compared to COPD (p = 0.009) but not ex-smokers (p = 0.5). In addition, there was significantly greater pulmonary small vessel volume (BV5) in long-COVID as compared to female ex-smokers (p = 0.045) and COPD (p = 0.003) patients and different large (BV10) vessel volume as compared to COPD (p = 0.03). In females with long-COVID and highly abnormal quality-of-life scores, there was CT evidence of airway remodelling, similar to ex-smokers and patients with COPD, but there was no evidence of pulmonary vascular remodelling.Clinical Trial Registration: www.clinicaltrials.gov NCT05014516 and NCT02279329.

A Precise Pulmonary Airway Tree Segmentation Method Using Quasi-Spherical Region Constraint and Tracheal Wall Gap Sealing

Accurate segmentation of the pulmonary airway tree is crucial for diagnosing lung diseases. To tackle the issues of low segmentation accuracy and frequent leaks in existing methods, this paper proposes a precise segmentation method using quasi-spherical region-constrained wavefront propagation with tracheal wall gap sealing. Based on the characteristic that the surface formed by seed points approximates the airway cross-section, the width of the unsegmented airway is calculated, determining the initial quasi-spherical constraint region. Using the wavefront propagation method, seed points are continuously propagated and segmented along the tracheal wall within the quasi-spherical constraint region, thus overcoming the need to determine complex segmentation directions. To seal tracheal wall gaps, a morphological closing operation is utilized to extract the characteristics of small holes and locate low-brightness tracheal wall gaps. By filling the CT values at these gaps, the method seals the tracheal wall gaps. Extensive experiments on the EXACT09 dataset demonstrate that our algorithm ranks third in segmentation completeness. Moreover, its performance in preventing airway leaks is significantly better than the top-two algorithms, effectively preventing large-scale leak-induced spread.

COPD phenotypes by computed tomography and ventilatory response to exercise

INTRODUCTION

Computed tomographic (CT) phenotypic patterns of chronic obstructive pulmonary disease (COPD) identify different clinical features of disease. The impact of these variables on the physiological response to exercise has been the focus of a great deal of research as it allows more individualized clinical approaches. The aim of our study was to evaluate the relationships between CT phenotyping of subjects with COPD and the ventilatory response during cardiopulmonary exercise testing (CPET).

METHODS

Subjects with COPD were classified into four phenotypes based on CT metrics of emphysema (low attenuation area less than a threshold of -950 Hounsfield [%LAA-950]) and airwall thickness (bronchial wall area percentage [%WA]).

RESULTS

Eighty COPD patients (78.8% males, median age 65±11.3 years) were enrolled in the study. Based on CT phenotype, 25 (31.3%) patients were classified as normal, 27 (33.8%) air dominant, 17 (21.3%) emphysema dominant and 11 (13.8%) mixed type. The emphysema and mixed phenotypes showed the highest ventilatory equivalent for carbon dioxide (VE/VCO2) and VE/VCO2 slope (p<0,05). In all phenotypes, %LAA was positive correlated with VE/VCO2 and VE/VCO2 slope (r = 0.437, p = 0.006 and r = 0.503, p<0.001, respectively). %WA also showed a positive correlation with VE/VCO2 and VE/VCO2 slope (r = 0.541, p<0.001 and r = 0.299, p = 0.033, respectively). In multivariate regression models, after adjustment for age, BMI, sex and FEV1, %LAA was the only independent predictor of VE/VCO2 and VE/VCO2 slope (β 0.343, SE 0.147, 95% CI 0.009/0.610, p = 0.044 and β 0.496, SE 0.081, 95% CI 0.130/0.455, p = 0.001, respectively).

CONCLUSION

Emphysema (%LAA) and airways metrics (%WA) had strong relationships with the different characteristics of ventilatory response to exercise in subjects with mild to moderate COPD. In particular, %LAA seemed to play an important role as an independent predictor of VE/VCO2 and VE/VCO2 slope. These results suggested that CT phenotyping may help predicting ventilatory response to exercise in subjects with COPD.

Quantitative CT Scan Imaging of the Airways for Diagnosis and Management of Lung Disease

CT scan imaging provides high-resolution images of the lungs in patients with chronic respiratory diseases. Extensive research over the last several decades has focused on developing novel quantitative CT scan airway measurements that reflect abnormal airway structure. Despite many observational studies demonstrating that associations between CT scan airway measurements and clinically important outcomes such as morbidity, mortality, and lung function decline, few quantitative CT scan measurements are applied in clinical practice. This article provides an overview of the relevant methodologic considerations for implementing quantitative CT scan airway analyses and provides a review of the scientific literature involving quantitative CT scan airway measurements used in clinical or randomized trials and observational studies of humans. We also discuss emerging evidence for the clinical usefulness of quantitative CT scan imaging of the airways and discuss what is required to bridge the gap between research and clinical application. CT scan airway measurements continue to improve our understanding of disease pathophysiologic features, diagnosis, and outcomes. However, a literature review revealed a need for studies evaluating clinical benefit when quantitative CT scan imaging is applied in the clinical setting. Technical standards for quantitative CT scan imaging of the airways and high-quality evidence of clinical benefit from management guided by quantitative CT scan imaging of the airways are required.

Two-stage contextual transformer-based convolutional neural network for airway extraction from CT images

Accurate airway segmentation from computed tomography (CT) images is critical for planning navigation bronchoscopy and realizing a quantitative assessment of airway-related chronic obstructive pulmonary disease (COPD). Existing methods face difficulty in airway segmentation, particularly for the small branches of the airway. These difficulties arise due to the constraints of limited labeling and failure to meet clinical use requirements in COPD. We propose a two-stage framework with a novel 3D contextual transformer for segmenting the overall airway and small airway branches using CT images. The method consists of two training stages sharing the same modified 3D U-Net network. The novel 3D contextual transformer block is integrated into both the encoder and decoder path of the network to effectively capture contextual and long-range information. In the first training stage, the proposed network segments the overall airway with the overall airway mask. To improve the performance of the segmentation result, we generate the intrapulmonary airway branch label, and train the network to focus on producing small airway branches in the second training stage. Extensive experiments were performed on in-house and multiple public datasets. Quantitative and qualitative analyses demonstrate that our proposed method extracts significantly more branches and longer lengths of the airway tree while accomplishing state-of-the-art airway segmentation performance. The code is available at https://github.com/zhaozsq/airway_segmentation.

Quantitative CT Characteristics of Cluster Phenotypes in the Severe Asthma Research Program Cohorts

Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led to the identification of novel asthma phenotypes. Purpose To determine whether quantitative CT (qCT) could help distinguish between clinical asthma phenotypes. Materials and Methods A retrospective cross-sectional analysis was conducted with the use of qCT images (maximal bronchodilation at total lung capacity [TLC], or inspiration, and functional residual capacity [FRC], or expiration) from the cluster phenotypes of SARP participants (cluster 1: minimal disease; cluster 2: mild, reversible; cluster 3: obese asthma; cluster 4: severe, reversible; cluster 5: severe, irreversible) enrolled between September 2001 and December 2015. Airway morphometry was performed along standard paths (RB1, RB4, RB10, LB1, and LB10). Corresponding voxels from TLC and FRC images were mapped with use of deformable image registration to characterize disease probability maps (DPMs) of functional small airway disease (fSAD), voxel-level volume changes (Jacobian), and isotropy (anisotropic deformation index [ADI]). The association between cluster assignment and qCT measures was evaluated using linear mixed models. Results A total of 455 participants were evaluated with cluster assignments and CT (mean age ± SD, 42.1 years ± 14.7; 270 women). Airway morphometry had limited ability to help discern between clusters. DPM fSAD was highest in cluster 5 (cluster 1 in SARP III: 19.0% ± 20.6; cluster 2: 18.9% ± 13.3; cluster 3: 24.9% ± 13.1; cluster 4: 24.1% ± 8.4; cluster 5: 38.8% ± 14.4; P < .001). Lower whole-lung Jacobian and ADI values were associated with greater cluster severity. Compared to cluster 1, cluster 5 lung expansion was 31% smaller (Jacobian in SARP III cohort: 2.31 ± 0.6 vs 1.61 ± 0.3, respectively, P < .001) and 34% more isotropic (ADI in SARP III cohort: 0.40 ± 0.1 vs 0.61 ± 0.2, P < .001). Within-lung Jacobian and ADI SDs decreased as severity worsened (Jacobian SD in SARP III cohort: 0.90 ± 0.4 for cluster 1; 0.79 ± 0.3 for cluster 2; 0.62 ± 0.2 for cluster 3; 0.63 ± 0.2 for cluster 4; and 0.41 ± 0.2 for cluster 5; P < .001). Conclusion Quantitative CT assessments of the degree and intraindividual regional variability of lung expansion distinguished between well-established clinical phenotypes among participants with asthma from the Severe Asthma Research Program study. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Verschakelen in this issue.

Lung resistance and elastance are different in ex vivo sheep lungs ventilated by positive and negative pressures

Lung resistance (R_L) and elastance (E_L) can be measured during positive or negative pressure ventilation. Whether the different modes of ventilation produce different R_L and E_L is still being debated. Although negative pressure ventilation (NPV) is more physiological, positive pressure ventilation (PPV) is more commonly used for treating respiratory failure. In the present study we measured lung volume, airway diameter and airway volume, as well as R_L and E_L with PPV and NPV in explanted sheep lungs. We found that lung volume under a static pressure, either positive or negative, was not different. However, R_L and E_L were significantly higher in NPV at high inflation pressures. Interestingly, diameters of smaller airways (diameters < 3.5 mm) and total airway volume were significantly greater at high negative inflation pressures compared with those at high positive inflation pressures. This suggests that NPV is more effective in distending the peripheral airways, likely due to the fact that negative pressure is applied through the pleural membrane and reaches the central airways via the peripheral airways, whereas positive pressure is applied in the opposite direction. More distension of lung periphery could explain why R_L is higher in NPV (vs. PPV), because the peripheral parenchyma is a major source of tissue resistance, which is a part of the R_L that increases with pressure. This explanation is consistent with the finding that during high frequency ventilation (>1 Hz, where R_L reflects airway resistance more than tissue resistance), the difference in R_L between NPV and PPV disappeared.

Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique

BACKGROUND AND OBJECTIVE

Cement dust exposure is likely to affect the structural and functional alterations in segmental airways and parenchymal lungs. This study develops an artificial neural network (ANN) model for identifying cement dust-exposed (CDE) subjects using quantitative computed tomography-based airway structural and functional features.

METHODS

We obtained the airway features in five central and five sub-grouped segmental regions and the lung features in five lobar regions and one total lung region from 311 CDE and 298 non-CDE (NCDE) subjects. The five-fold cross-validation method was adopted to train the following classification models:ANN, support vector machine (SVM), logistic regression (LR), and decision tree (DT). For all the classification models, linear discriminant analysis (LDA) and genetic algorithm (GA) were applied for dimensional reduction and hyperparameterization, respectively. The ANN model without LDA was also optimized by the GA method to observe the effect of the dimensional reduction.

RESULTS

The genetically optimized ANN model without the LDA method was the best in terms of the classification accuracy. The accuracy, sensitivity, and specificity of the GA-ANN model with four layers were greater than those of the other classification models (i.e., ANN, SVM, LR, and DT using LDA and GA methods) in the five-fold cross-validation. The average values of accuracy, sensitivity, and specificity for the five-fold cross-validation were 97.0%, 98.7%, and 98.6%, respectively.

CONCLUSIONS

We demonstrated herein that a quantitative computed tomography-based ANN model could more effectively detect CDE subjects when compared to their counterpart models. By employing the model, the CDE subjects may be identified early for therapeutic intervention.

Quantitative CT Analysis of Diffuse Lung Disease

Quantitative analysis of thin-section CT of the chest has a growing role in the clinical evaluation and management of diffuse lung diseases. This heterogeneous group includes diseases with markedly different prognoses and treatment options. Quantitative tools can assist in both accurate diagnosis and longitudinal management by improving characterization and quantification of disease and increasing the reproducibility of disease severity assessment. Furthermore, a quantitative index of disease severity may serve as a useful tool or surrogate endpoint in evaluating treatment efficacy. The authors explore the role of quantitative imaging tools in the evaluation and management of diffuse lung diseases. Lung parenchymal features can be classified with threshold, histogram, morphologic, and texture-analysis-based methods. Quantitative CT analysis has been applied in obstructive, infiltrative, and restrictive pulmonary diseases including emphysema, cystic fibrosis, asthma, idiopathic pulmonary fibrosis, hypersensitivity pneumonitis, connective tissue-related interstitial lung disease, and combined pulmonary fibrosis and emphysema. Some challenges limiting the development and practical application of current quantitative analysis tools include the quality of training data, lack of standard criteria to validate the accuracy of the results, and lack of real-world assessments of the impact on outcomes. Artifacts such as patient motion or metallic beam hardening, variation in inspiratory effort, differences in image acquisition and reconstruction techniques, or inaccurate preprocessing steps such as segmentation of anatomic structures may lead to inaccurate classification. Despite these challenges, as new techniques emerge, quantitative analysis is developing into a viable tool to supplement the traditional visual assessment of diffuse lung diseases and to provide decision support regarding diagnosis, prognosis, and longitudinal evaluation of disease. ^©RSNA, 2019.

Performance of quantitative CT parameters in assessment of disease severity in COPD: A prospective study

BACKGROUND

Both emphysematous destruction of lung parenchyma and airway remodeling is thought to contribute to airflow limitation in cases of chronic obstructive pulmonary disease (COPD).

OBJECTIVE

To evaluate the value of quantitative computed tomography (QCT) parameters of emphysema and airway disease with disease severity in patients with COPD.

MATERIALS AND METHODS

We prospectively studied 50 patients with COPD, which included nonsmokers and patients with different degrees of cumulative smoking exposure. Three QCT parameters namely LAA% (low attenuation area percentage), WA% (Wall area percentage), and pi10 were calculated as per the standard technique. Forced expiratory volume in 1 s (FEV1), BODE score, and MMRC dyspnea scale were used as measures of disease severity.

RESULTS

FEV1 was inversely and significantly associated with all three QCT parameters. Receiver operated characteristic curves in prediction of GOLD class 3 COPD yielded cut-off values of 12.2, 61.45, and 3.5 for LAA%, WA%, and pi10, respectively, with high sensitivities and specificities. In multiple linear regression model, however, only LAA% proved to be significantly associated with FEV1, BODE, and dyspnea.

CONCLUSION

QCT indices of both emphysema and airway disease influence FEV1, dyspnea, and BODE score in patients with COPD. Emphysema, however, appears to be more closely related to disease severity.

CT Radiomics in Thoracic Oncology: Technique and Clinical Applications

Precision medicine offers better treatment options and improved survival for cancer patients based on individual variability. As the success of precision medicine depends on robust biomarkers, the requirement for improved imaging biomarkers that reflect tumor biology has grown exponentially. Radiomics, the field of study in which high-throughput data are generated and large amounts of advanced quantitative features are extracted from medical images, has shown great potential as a source of quantitative biomarkers in the field of oncology. Radiomics provides quantitative information about the morphology, texture, and intratumoral heterogeneity of the tumor itself as well as features related to pulmonary function. Hence, radiomics data can be used to build descriptive and predictive clinical models that relate imaging characteristics to tumor biology phenotypes. In this review, we describe the workflow of CT radiomics, types of CT radiomics, and its clinical application in thoracic oncology.

Differentiation of quantitative CT imaging phenotypes in asthma versus COPD

Introduction

Quantitative CT (QCT) imaging-based metrics have quantified disease alterations in asthma and chronic obstructive pulmonary disease (COPD), respectively. We seek to characterise the similarity and disparity between these groups using QCT-derived airway and parenchymal metrics.

Methods

Asthma and COPD subjects (former-smoker status) were selected with a criterion of post-bronchodilator FEV₁ <80%. Healthy non-smokers were included as a control group. Inspiratory and expiratory QCT images of 75 asthmatic, 215 COPD and 94 healthy subjects were evaluated. We compared three segmental variables: airway circularity, normalised wall thickness and normalised hydraulic diameter, indicating heterogeneous airway shape, wall thickening and luminal narrowing, respectively. Using an image registration, we also computed six lobar variables including per cent functional small-airway disease, per cent emphysema, tissue fraction at inspiration, fractional-air-volume change, Jacobian and functional metric characterising anisotropic deformation.

Results

Compared with healthy subjects, both asthma and COPD subjects demonstrated a decreased airway circularity especially in large and upper lobar airways, and a decreased normalised hydraulic diameter in segmental airways. Besides, COPD subjects had more severe emphysema and small-airway disease, as well as smaller regional tissue fraction and lung deformation, compared with asthmatic subjects. The difference of emphysema, small-airway disease and tissue fraction between asthma and COPD was more prominent in upper and middle lobes.

Conclusions

Patients with asthma and COPD, with a persistent FEV₁ <80%, demonstrated similar alterations in airway geometry compared with controls, but different degrees of alterations in parenchymal regions. Density-based metrics measured at upper and middle lobes were found to be discriminant variables between patients with asthma and COPD.

CT Quantification of Lungs and Airways in Normal Korean Subjects

Objective

To measure and compare the quantitative parameters of the lungs and airways in Korean never-smokers and current or former smokers (“ever-smokers”).

Materials and Methods

Never-smokers (n = 119) and ever-smokers (n = 45) who had normal spirometry and visually normal chest computed tomography (CT) results were retrospectively enrolled in this study. For quantitative CT analyses, the low attenuation area (LAA) of LAA_I-950, LAA_E-856, CT attenuation value at the 15th percentile, mean lung attenuation (MLA), bronchial wall thickness of inner perimeter of a 10 mm diameter airway (Pi10), total lung capacity (TLC_CT), and functional residual capacity (FRC_CT) were calculated based on inspiratory and expiratory CT images. To compare the results between groups according to age, sex, and smoking history, independent t test, one way ANOVA, correlation test, and simple and multiple regression analyses were performed.

Results

The values of attenuation parameters and volume on inspiratory and expiratory quantitative computed tomography (QCT) were significantly different between males and females (p < 0.001). The MLA and the 15th percentile value on inspiratory QCT were significantly lower in the ever-smoker group than in the never-smoker group (p < 0.05). On expiratory QCT, all lung attenuation parameters were significantly different according to the age range (p < 0.05). Pi10 in ever-smokers was significantly correlated with forced expiratory volume in 1 second/forced vital capacity (r = −0.455, p = 0.003). In simple and multivariate regression analyses, TLC_CT, FRC_CT, and age showed significant associations with lung attenuation (p < 0.05), and only TLC_CT was significantly associated with inspiratory Pi10.

Conclusion

In Korean subjects with normal spirometry and visually normal chest CT, there may be significant differences in QCT parameters according to sex, age, and smoking history.

LINKING LUNG AIRWAY STRUCTURE TO PULMONARY FUNCTION VIA COMPOSITE BRIDGE REGRESSION

The human lung airway is a complex inverted tree-like structure. Detailed airway measurements can be extracted from MDCT-scanned lung images, such as segmental wall thickness, airway diameter, parent-child branch angles, etc. The wealth of lung airway data provides a unique opportunity for advancing our understanding of the fundamental structure-function relationships within the lung. An important problem is to construct and identify important lung airway features in normal subjects and connect these to standardized pulmonary function test results such as FEV1%. Among other things, the problem is complicated by the fact that a particular airway feature may be an important (relevant) predictor only when it pertains to segments of certain generations. Thus, the key is an efficient, consistent method for simultaneously conducting group selection (lung airway feature types) and within-group variable selection (airway generations), i.e., bi-level selection. Here we streamline a comprehensive procedure to process the lung airway data via imputation, normalization, transformation and groupwise principal component analysis, and then adopt a new composite penalized regression approach for conducting bi-level feature selection. As a prototype of composite penalization, the proposed composite bridge regression method is shown to admit an efficient algorithm, enjoy bi-level oracle properties, and outperform several existing methods. We analyze the MDCT lung image data from a cohort of 132 subjects with normal lung function. Our results show that, lung function in terms of FEV1% is promoted by having a less dense and more homogeneous lung comprising an airway whose segments enjoy more heterogeneity in wall thicknesses, larger mean diameters, lumen areas and branch angles. These data hold the potential of defining more accurately the "normal" subject population with borderline atypical lung functions that are clearly influenced by many genetic and environmental factors.

Quantitative computed tomography imaging of airway remodeling in severe asthma

Asthma is a heterogeneous condition and approximately 5-10% of asthmatic subjects have severe disease associated with structure changes of the airways (airway remodeling) that may develop over time or shortly after onset of disease. Quantitative computed tomography (QCT) imaging of the tracheobronchial tree and lung parenchyma has improved during the last 10 years, and has enabled investigators to study the large airway architecture in detail and assess indirectly the small airway structure. In severe asthmatics, morphologic changes in large airways, quantitatively assessed using 2D-3D airway registration and recent algorithms, are characterized by airway wall thickening, luminal narrowing and bronchial stenoses. Extent of expiratory gas trapping, quantitatively assessed using lung densitometry, may be used to assess indirectly small airway remodeling. Investigators have used these quantitative imaging techniques in order to attempt severity grading of asthma, and to identify clusters of asthmatic patients that differ in morphologic and functional characteristics. Although standardization of image analysis procedures needs to be improved, the identification of remodeling pattern in various phenotypes of severe asthma and the ability to relate airway structures to important clinical outcomes should help target treatment more effectively.

CT-Definable Subtypes of Chronic Obstructive Pulmonary Disease: A Statement of the Fleischner Society

The purpose of this statement is to describe and define the phenotypic abnormalities that can be identified on visual and quantitative evaluation of computed tomographic (CT) images in subjects with chronic obstructive pulmonary disease (COPD), with the goal of contributing to a personalized approach to the treatment of patients with COPD. Quantitative CT is useful for identifying and sequentially evaluating the extent of emphysematous lung destruction, changes in airway walls, and expiratory air trapping. However, visual assessment of CT scans remains important to describe patterns of altered lung structure in COPD. The classification system proposed and illustrated in this article provides a structured approach to visual and quantitative assessment of COPD. Emphysema is classified as centrilobular (subclassified as trace, mild, moderate, confluent, and advanced destructive emphysema), panlobular, and paraseptal (subclassified as mild or substantial). Additional important visual features include airway wall thickening, inflammatory small airways disease, tracheal abnormalities, interstitial lung abnormalities, pulmonary arterial enlargement, and bronchiectasis.

Review of automatic pulmonary lobe segmentation methods from CT

The computational detection of pulmonary lobes from CT images is a challenging segmentation problem with important respiratory health care applications, including surgical planning and regional image analysis. Several authors have proposed automated algorithms and we present a methodological review. These algorithms share a number of common stages and we consider each stage in turn, comparing the methods applied by each author and discussing their relative strengths. No standard method has yet emerged and none of the published methods have been demonstrated across a full range of clinical pathologies and imaging protocols. We discuss how improved methods could be developed by combining different approaches, and we use this to propose a workflow for the development of new algorithms.

Longitudinal changes in airway remodeling and air trapping in severe asthma

RATIONALE AND OBJECTIVES

Previous cross-sectional studies have demonstrated that airway wall thickness and air trapping are greater in subjects with severe asthma than in those with mild-to-moderate asthma. However, a better understanding of how airway remodeling and lung density change over time is needed. This study aimed to evaluate predictors of airway wall remodeling and change in lung function and lung density over time in severe asthma.

MATERIALS AND METHODS

Phenotypic characterization and quantitative multidetector-row computed tomography (MDCT) of the chest were performed at baseline and ∼2.6 years later in 38 participants with asthma (severe n = 24 and mild-to-moderate n = 14) and nine normal controls from the Severe Asthma Research Program.

RESULTS

Subjects with severe asthma had a significant decline in postbronchodilator forced expiratory volume in 1 second percent (FEV1%) predicted over time (P < .001). Airway wall thickness measured by MDCT was increased at multiple airway generations in severe asthma compared to mild-to-moderate asthma (wall area percent [WA%]: P < .05) and normals (P < .05) at baseline and year 2. Over time, there was an increase in WA% and wall thickness percent (WT%) in all subjects (P = .030 and .009, respectively) with no change in emphysema-like lung or air trapping. Baseline prebronchodilator FEV1% inversely correlated with WA% and WT% (both P < .05). In a multivariable regression model, baseline WA%, race, and health care utilization were predictors of subsequent airway remodeling.

CONCLUSIONS

Severe asthma subjects have a greater decline in lung function over time than normal subjects or those with mild-to-moderate asthma. MDCT provides a noninvasive measure of airway wall thickness that may predict subsequent airway remodeling.

Disproportionate contribution of right middle lobe to emphysema and gas trapping on computed tomography

RATIONALE

Given that the diagnosis of chronic obstructive pulmonary disease (COPD) relies on demonstrating airflow limitation by spirometry, which is known to be poorly sensitive to early disease, and to regional differences in emphysema, we sought to evaluate individual lobar contributions to global spirometric measures.

METHODS

Subjects with COPD were compared with smokers without airflow obstruction, and non-smokers. Emphysema (% low attenuation area, LAAinsp<-950 HU, at end-inspiration) and gas trapping (%LAAexp<-856 HU at end-expiration) on CT were quantified using density mask analyses for the whole lung and for individual lobes, and distribution across lobes and strength of correlation with spirometry were compared.

RESULTS

The right middle lobe had the highest %LAAinsp<-950 HU in smokers and controls, and the highest %LAAexp<-856 HU in all three groups. While RML contributed to emphysema and gas trapping disproportionately to its relatively small size, it also showed the least correlation with spirometry. There was no change in correlation of whole lung CT metrics with spirometry when the middle lobe was excluded from analyses. Similarly, RML had the highest %LAAexp<-856 HU while having the least correlation with spirometry.

CONCLUSIONS

Because of the right middle lobe's disproportionate contribution to CT-based emphysema measurements, and low contribution to spirometry, longitudinal studies of emphysema progression may benefit from independent analysis of the middle lobe in whole lung quantitative CT assessments. Our findings may also have implications for heterogeneity assessments and target lobe selection for lung volume reduction.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT00608764.

Visual Assessment of CT Findings in Smokers With Nonobstructed Spirometric Abnormalities in The COPDGene® Study

Within the COPD Genetic Epidemiology (COPDGene^®) study population of cigarette smokers, 9% were found to be unclassifiable by the Global Initiative for chronic Obstructive Lung Disease (GOLD) criteria. This study was to identify the differences in computed tomography (CT) findings between this nonobstructed (GOLDU) group and a control group of smokers with normal lung function. This research was approved by the institutional review board of each institution. CT images of 400 participants in the COPDGene^® study (200 GOLDU, 200 smokers with normal lung function) were retrospectively evaluated in a blinded fashion. Visual CT assessment included lobar analysis of emphysema (type, extent), presence of paraseptal emphysema, airway wall thickening, expiratory air trapping, centrilobular nodules, atelectasis, non-fibrotic and fibrotic interstitial lung disease (ILD), pleural thickening, diaphragmatic eventration, vertebral body changes and internal thoracic diameters (in mm). Univariate comparisons of groups for each CT parameter and multiple logistic regression were performed to determine the imaging features associated with GOLDU. When compared with the control group, GOLDU participants had a significantly higher prevalence of unilateral diaphragm eventration (30% vs. 16%), airway wall thickening, centrilobular nodules, reticular abnormality, paraseptal emphysema (33% vs. 17%), linear atelectasis (60% vs. 35.6%), kyphosis (12% vs. 4%), and a smaller internal transverse thoracic diameter (255 ± 22.5 [standard deviation] vs. 264.8 ± 22.4, mm) (all p<0.05). With multiple logistic regression, all of these CT parameters, except non-fibrotic ILD and kyphosis, remained significantly associated with GOLDU status (p<0.05). In cigarette smokers, chest wall abnormalities and parenchymal lung disease, which contribute to restrictive physiologic impairment, are associated with GOLD-nonobstructed status.

Relationships between airflow obstruction and quantitative CT measurements of emphysema, air trapping, and airways in subjects with and without chronic obstructive pulmonary disease

OBJECTIVE

This study evaluates the relationships between quantitative CT (QCT) and spirometric measurements of disease severity in cigarette smokers with and without chronic obstructive pulmonary disease (COPD).

MATERIALS AND METHODS

Inspiratory and expiratory CT scans of 4062 subjects in the Genetic Epidemiology of COPD (COPDGene) Study were evaluated. Measures examined included emphysema, defined as the percentage of low-attenuation areas≤-950 HU on inspiratory CT, which we refer to as "LAA-950I"; air trapping, defined as the percentage of low-attenuation areas≤-856 HU on expiratory CT, which we refer to as "LAA-856E"; and the inner diameter, inner and outer areas, wall area, airway wall thickness, and square root of the wall area of a hypothetical airway of 10-mm internal perimeter of segmental and subsegmental airways. Correlations were determined between spirometry and several QCT measures using statistics software (SAS, version 9.2).

RESULTS

QCT measurements of low-attenuation areas correlate strongly and significantly (p<0.0001) with spirometry. The correlation between LAA-856E and forced expiratory volume in 1 second (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) (r=-0.77 and -0.84, respectively) is stronger than the correlation between LAA-950I and FEV1 and FEV1/FVC (r=-0.67 and r=-0.76). Inspiratory and expiratory volume changes decreased with increasing disease severity, as measured by the Global Initiative for Chronic Obstructive Pulmonary Disease (GOLD) staging system (p<0.0001). When airway variables were included with low-attenuation area measures in a multiple regression model, the model accounted for a statistically greater proportion of variation in FEV1 and FEV1/FVC (R2=0.72 and 0.77, respectively). Airway measurements alone are less correlated with spirometric measures of FEV1 (r=0.15 to -0.44) and FEV1/FVC (r=0.19 to -0.34).

CONCLUSION

QCT measurements are strongly associated with spirometric results showing impairment in smokers. LAA-856E strongly correlates with physiologic measurements of airway obstruction. Airway measurements can be used concurrently with QCT measures of low-attenuation areas to accurately predict lung function.

Quantitative computed tomography-derived clusters: redefining airway remodeling in asthmatic patients

BACKGROUND

Asthma heterogeneity is multidimensional and requires additional tools to unravel its complexity. Computed tomography (CT)-assessed proximal airway remodeling and air trapping in asthmatic patients might provide new insights into underlying disease mechanisms.

OBJECTIVES

The aim of this study was to explore novel, quantitative, CT-determined asthma phenotypes.

METHODS

Sixty-five asthmatic patients and 30 healthy subjects underwent detailed clinical, physiologic characterization and quantitative CT analysis. Factor and cluster analysis techniques were used to determine 3 novel, quantitative, CT-based asthma phenotypes.

RESULTS

Patients with severe and mild-to-moderate asthma demonstrated smaller mean right upper lobe apical segmental bronchus (RB1) lumen volume (LV) in comparison with healthy control subjects (272.3 mm(3) [SD, 112.6 mm(3)], 259.0 mm(3) [SD, 53.3 mm(3)], 366.4 mm(3) [SD, 195.3 mm(3)], respectively; P = .007) but no difference in RB1 wall volume (WV). Air trapping measured based on mean lung density expiratory/inspiratory ratio was greater in patients with severe and mild-to-moderate asthma compared with that seen in healthy control subjects (0.861 [SD, 0.05)], 0.866 [SD, 0.07], and 0.830 [SD, 0.06], respectively; P = .04). The fractal dimension of the segmented airway tree was less in asthmatic patients compared with that seen in control subjects (P = .007). Three novel, quantitative, CT-based asthma clusters were identified, all of which demonstrated air trapping. Cluster 1 demonstrates increased RB1 WV and RB1 LV but decreased RB1 percentage WV. On the contrary, cluster 3 subjects have the smallest RB1 WV and LV values but the highest RB1 percentage WV values. There is a lack of proximal airway remodeling in cluster 2 subjects.

CONCLUSIONS

Quantitative CT analysis provides a new perspective in asthma phenotyping, which might prove useful in patient selection for novel therapies.

Airway and pulmonary vascular measurements using contrast-enhanced micro-CT in rodents

Preclinical imaging allows pulmonary researchers to study lung disease and pulmonary drug delivery noninvasively and longitudinally in small animals. However, anatomically localizing a pathology or drug deposition to a particular lung region is not easily done. Thus, a detailed knowledge of the anatomical structure of small animal lungs is necessary for understanding disease progression and in addition would facilitate the analysis of the imaging data, mapping drug deposition and relating function to structure. In this study, contrast-enhanced micro-computed tomography (CT) of the lung produced high-resolution images that allowed for the characterization of the rodent airway and pulmonary vasculature. Contrast-enhanced micro-CT was used to visualize the airways and pulmonary vasculature in Sprague-Dawley rats (200–225 g) and BALB/c mice (20–25 g) postmortem. Segmented volumes from these images were processed to yield automated measurements of the airways and pulmonary vasculature. The diameters, lengths, and branching angles of the airway, arterial, and venous trees were measured and analyzed as a function of generation number and vessel diameter to establish rules that could be applied at all levels of tree hierarchy. In the rat, airway, arterial, and venous tress were measured down to the 20th, 16th, and 14th generation, respectively. In the mouse, airway, arterial, and venous trees were measured down to the 16th, 8th, and 7th generation, respectively. This structural information, catalogued in a rodent database, will increase our understanding of lung structure and will aid in future studies of the relationship between structure and function in animal models of disease.

Airway distensibility by HRCT in asthmatics and COPD with comparable airway obstruction

INTRODUCTION

Decreased airway distensibility (AD) in response to deep inspirations, as assessed by HRCT, has been associated with the severity of asthma and COPD.

AIMS

The current study was designed to compare the magnitude of AD by HRCT in individuals with asthma and COPD with comparable degrees of bronchial obstruction, and to explore factors that may influence it.

RESULTS

We enrolled a total of 12 asthmatics (M/F:7/5) and 8 COPD (7/1) with comparable degree of bronchial obstruction (FEV1% predicted mean ± SEM: 69.1 ± 5.2% and 61.2 ± 5.0%, respectively; p = 0.31). Each subject underwent chest HRCT at FRC and at TLC. A total of 701 airways (range 20 to 38 airway per subject; 2.0 to 23.1 mm in diameter) were analyzed. AD did not differ between asthmatics and COPD (mean ± SEM: 14 ± 3.5% and 17 ± 4.3%, respectively; p = 0.58). In asthmatics, AD was significantly associated with FEV1% predicted (r(2) = 0.45, p = 0.018). We found a significant correlation between the change in lung volume and the change in AD by HRCT (r(2) = 0.64, p = 0.002). In COPD, we found significant correlations between AD and the RV% predicted (r(2) = 0.51, p = 0.046) and the RV/TLC (r(2) = 0.68, p = 0.01).

CONCLUSIONS

AD was primarily affected by the dynamic ability to change lung volumes in asthmatics, and by static lung volumes in COPD.

Forced expiratory capnography and chronic obstructive pulmonary disease (COPD)

This report proposes a potentially sensitive and simple physiological method to detect early changes and to follow disease progression in obstructive pulmonary disease (COPD) based upon the usual pulmonary function test. Pulmonary function testing is a simple, although relatively insensitive, method to detect and follow COPD. As a proof-of-concept, we have examined the slope of the plateau for carbon dioxide during forced expiratory capnography in healthy (n = 10) and COPD subjects (n = 10). We compared the change in the rate of exhalation of carbon dioxide over time as a marker of heterogeneous ventilation of the lung. All subjects underwent pulmonary function testing, body-plethysmography, and forced exhalation capnography. The subjects with COPD also underwent high-resolution computed tomography of the chest. Regression lines were fitted to the slopes of the forced exhalation capnogram curves. There was no difference in the mean levels of exhaled carbon dioxide between the COPD and the healthy groups (p > 0.48). We found a significant difference in the mean slope of the forced exhalation capnogram for the COPD subjects compared to the healthy subjects (p = 0.01). Most important, for the COPD subjects, there was a significant positive correlation between the slope of the forced exhaled capnogram and a defined radiodensity measurement of the lung by high-resolution computed tomography (r(2) = 0.49, p = 0.02). The slope of the forced exhalation capnogram may be a simple way to determine physiological changes in the lungs in patients with COPD that are not obtainable with standard pulmonary function tests. Forced exhalation capnography would be of great clinical benefit if it can identify early disease changes and at-risk individuals.

MODELING AIRWAY PROBABILITY

We present a probability model for lung airways in computed tomography (CT) images. Lung airways are tubular structures that display specific features, such as low intensity and proximity to vessels and bronchial walls. From these features, the posterior probability for the airway feature space was computed using a Bayesian model based on 20 CT images from subjects with different degrees of Chronic Obstructive Pulmonary Disease (COPD). The likelihood probability was modeled using both a Gaussian distribution and a nonparametric kernel density estimation method. After exhaustive feature selection, good specificity and sensitivity were achieved in a cross-validation study for both the Gaussian (0.83, 0.87) and the nonparametric method (0.79, 0.89). The model generalizes well when trained using images from a late stage COPD group. This probability model may facilitate airway extraction and quantitative assessment of lung diseases, which is useful in many clinical and research settings.

Chronic obstructive pulmonary disease: lobe-based visual assessment of volumetric CT by Using standard images--comparison with quantitative CT and pulmonary function test in the COPDGene study

PURPOSE

To provide a new detailed visual assessment scheme of computed tomography (CT) for chronic obstructive pulmonary disease (COPD) by using standard reference images and to compare this visual assessment method with quantitative CT and several physiologic parameters.

MATERIALS AND METHODS

This research was approved by the institutional review board of each institution. CT images of 200 participants in the COPDGene study were evaluated. Four thoracic radiologists performed independent, lobar analysis of volumetric CT images for type (centrilobular, panlobular, and mixed) and extent (on a six-point scale) of emphysema, the presence of bronchiectasis, airway wall thickening, and tracheal abnormalities. Standard images for each finding, generated by two radiologists, were used for reference. The extent of emphysema, airway wall thickening, and luminal area were quantified at the lobar level by using commercial software. Spearman rank test and simple and multiple regression analyses were performed to compare the results of visual assessment with physiologic and quantitative parameters.

RESULTS

The type of emphysema, determined by four readers, showed good agreement (κ = 0.63). The extent of the emphysema in each lobe showed good agreement (mean weighted κ = 0.70) and correlated with findings at quantitative CT (r = 0.75), forced expiratory volume in 1 second (FEV(1)) (r = -0.68), FEV(1)/forced vital capacity (FVC) ratio (r = -0.74) (P < .001). Agreement for airway wall thickening was fair (mean κ = 0.41), and the number of lobes with thickened bronchial walls correlated with FEV(1) (r = -0.60) and FEV(1)/FVC ratio (r = -0.60) (P < .001).

CONCLUSION

Visual assessment of emphysema and airways disease in individuals with COPD can provide reproducible, physiologically substantial information that may complement that provided by quantitative CT assessment.

Chronic obstructive pulmonary disease: CT quantification of airways disease

Chronic obstructive pulmonary disease (COPD) is an increasing cause of morbidity and mortality worldwide and results in substantial social and economic burdens. COPD is a heterogeneous disease with both extrapulmonary and pulmonary components. The pulmonary component is characterized by an airflow limitation that is not fully reversible. In the authors' opinion, none of the currently available classifications combining airflow limitation measurements with clinical parameters is sufficient to determine the prognosis and treatment of a particular patient with COPD. With regard to the causes of airflow limitation, CT can be used to quantify the two main contributions to COPD: emphysema, and small airways disease (a narrowing of the airways). CT quantification--with subsequent COPD phenotyping--can contribute to improved patient care, assessment of COPD progression, and identification of severe COPD with increasing risk of mortality. Small airways disease can be quantified through measurements reflecting morphology, quantification of obstruction, and changes in airways walls. This article details these three approaches and concludes with perspectives and directions for further research.

The importance of imaging and physiology measurements in assessing the delivery of peripherally targeted aerosolized drugs

Considerable recent effort has been directed towards developing new aerosol formulations and delivery devices that can target drugs to the lung periphery. In order to determine the efficacy of targeted drug therapy, it is essential that the peripheral lung region be adequately assessed. Imaging of the airways structure and pathology has greatly advanced in the last decade and this rate of growth is accelerating as new technologies become available. Lung imaging continues to play an important role in the study of the peripheral airways and, when combined with state-of-the-art lung function measurements and computational modeling, can be a powerful tool for investigating the effects of inhaled medication. This article focuses on recent strategies in imaging and physiological measurements of the lungs that allow the assessment of inhaled medication delivered to the periphery and discusses how these methods may help to further optimize and refine future aerosol delivery technology.

Relationship between quantitative CT metrics and health status and BODE in chronic obstructive pulmonary disease

BACKGROUND

The value of quantitative CT (QCT) to identify chronic obstructive pulmonary disease (COPD) phenotypes is increasingly appreciated. The authors hypothesised that QCT-defined emphysema and airway abnormalities relate to St George's Respiratory Questionnaire (SGRQ) and Body-Mass Index, Airflow Obstruction, Dyspnea and Exercise Capacity Index (BODE).

METHODS

1200 COPDGene subjects meeting Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria for COPD with QCT analysis were included. Total lung emphysema was measured using the density mask technique with a -950 Hounsfield unit threshold. An automated programme measured mean wall thickness (WT), wall area percentage (WA%) and 10 mm lumenal perimeter (pi10) in six segmental bronchi. Separate multivariate analyses examined the relative influence of airway measures and emphysema on SGRQ and BODE.

RESULTS

In separate models predicting SGRQ score, a 1 unit SD increase in each airway measure predicted higher SGRQ scores (for WT, 1.90 points higher, p=0.002; for WA%, 1.52 points higher, p=0.02; for pi10, 2.83 points higher p<0.001). The comparable increase in SGRQ for a 1 unit SD increase in emphysema percentage in these models was relatively weaker, significant only in the pi10 model (for emphysema percentage, 1.45 points higher, p=0.01). In separate models predicting BODE, a 1 unit SD increase in each airway measure predicted higher BODE scores (for WT, 1.07-fold increase, p<0.001; for WA%, 1.20-fold increase, p<0.001; for pi10, 1.16-fold increase, p<0.001). In these models, emphysema more strongly influenced BODE (range 1.24-1.26-fold increase, p<0.001).

CONCLUSION

Emphysema and airway disease both relate to clinically important parameters. The relative influence of airway disease is greater for SGRQ; the relative influence of emphysema is greater for BODE.

Comparison of human lung tissue mass measurements from ex vivo lungs and high resolution CT software analysis

Background

Quantification of lung tissue via analysis of computed tomography (CT) scans is increasingly common for monitoring disease progression and for planning of therapeutic interventions. The current study evaluates the quantification of human lung tissue mass by software analysis of a CT to physical tissue mass measurements.

Methods

Twenty-two ex vivo lungs were scanned by CT and analyzed by commercially available software. The lungs were then dissected into lobes and sublobar segments and weighed. Because sublobar boundaries are not visually apparent, a novel technique of defining sublobar segments in ex vivo tissue was developed. The tissue masses were then compared to measurements by the software analysis.

Results

Both emphysematous (n = 14) and non-emphysematous (n = 8) bilateral lungs were evaluated. Masses (Mean ± SD) as measured by dissection were 651 ± 171 g for en bloc lungs, 126 ± 60 g for lobar segments, and 46 ± 23 g for sublobar segments. Masses as measured by software analysis were 598 ± 159 g for en bloc lungs, 120 ± 58 g for lobar segments, and 45 ± 23 g for sublobar segments. Correlations between measurement methods was above 0.9 for each segmentation level. The Bland-Altman analysis found limits of agreement at the lung, lobe and sublobar levels to be −13.11% to −4.22%, –13.59% to 4.24%, and –45.85% to 44.56%.

Conclusion

The degree of concordance between the software mass quantification to physical mass measurements provides substantial evidence that the software method represents an appropriate non-invasive means to determine lung tissue mass.

Lung imaging - two dimensional gamma scintigraphy, SPECT, CT and PET

This review will cover the principles of imaging the deposition of inhaled drugs and some of the state-of-the art imaging techniques being used today. Aerosol deposition can be imaged and quantified by the addition of a radiolabel to the aerosol formulation. The subsequent imaging of the inhaled deposition pattern can be acquired by different imaging techniques. Specifically, this review will focus on the use of two-dimensional planar, gamma scintigraphy, SPECT, CT and PET. This review will look at how these imaging techniques are used to investigate the mechanisms of drug delivery in the lung and how the lung anatomy and physiology have the potential to alter therapeutic outcomes.

Chronic obstructive pulmonary disease exacerbations in the COPDGene study: associated radiologic phenotypes

PURPOSE

To test the hypothesis-given the increasing emphasis on quantitative computed tomographic (CT) phenotypes of chronic obstructive pulmonary disease (COPD)-that a relationship exists between COPD exacerbation frequency and quantitative CT measures of emphysema and airway disease.

MATERIALS AND METHODS

This research protocol was approved by the institutional review board of each participating institution, and all participants provided written informed consent. One thousand two subjects who were enrolled in the COPDGene Study and met the GOLD (Global Initiative for Chronic Obstructive Lung Disease) criteria for COPD with quantitative CT analysis were included. Total lung emphysema percentage was measured by using the attenuation mask technique with a -950-HU threshold. An automated program measured the mean wall thickness and mean wall area percentage in six segmental bronchi. The frequency of COPD exacerbation in the prior year was determined by using a questionnaire. Statistical analysis was performed to examine the relationship of exacerbation frequency with lung function and quantitative CT measurements.

RESULTS

In a multivariate analysis adjusted for lung function, bronchial wall thickness and total lung emphysema percentage were associated with COPD exacerbation frequency. Each 1-mm increase in bronchial wall thickness was associated with a 1.84-fold increase in annual exacerbation rate (P = .004). For patients with 35% or greater total emphysema, each 5% increase in emphysema was associated with a 1.18-fold increase in this rate (P = .047).

CONCLUSION

Greater lung emphysema and airway wall thickness were associated with COPD exacerbations, independent of the severity of airflow obstruction. Quantitative CT can help identify subgroups of patients with COPD who experience exacerbations for targeted research and therapy development for individual phenotypes.

Gender differences of airway dimensions in anatomically matched sites on CT in smokers

RATIONALE AND OBJECTIVES

There are limited data on, and controversies regarding gender differences in the airway dimensions of smokers. Multi-detector CT (MDCT) images were analyzed to examine whether gender could explain differences in airway dimensions of anatomically matched airways in smokers.

MATERIALS AND METHODS

We used VIDA imaging software to analyze MDCT scans from 2047 smokers (M:F, 1021:1026) from the COPDGene® cohort. The airway dimensions were analyzed from segmental to subsubsegmental bronchi. We compared the differences of luminal area, inner diameter, wall thickness, wall area percentage (WA%) for each airway between men and women, and multiple linear regression including covariates (age, gender, body sizes, and other relevant confounding factors) was used to determine the predictors of each airway dimensions.

RESULTS

Lumen area, internal diameter and wall thickness were smaller for women than men in all measured airway (18.4 vs 22.5 mm(2) for segmental bronchial lumen area, 10.4 vs 12.5 mm(2) for subsegmental bronchi, 6.5 vs 7.7 mm(2) for subsubsegmental bronchi, respectively p < 0.001). However, women had greater WA% in subsegmental and subsubsegmental bronchi. In multivariate regression, gender remained one of the most significant predictors of WA%, lumen area, inner diameter and wall thickness.

CONCLUSION

Women smokers have higher WA%, but lower luminal area, internal diameter and airway thickness in anatomically matched airways as measured by CT scan than do male smokers. This difference may explain, in part, gender differences in the prevalence of COPD and airflow limitation.

Lung imaging in asthmatic patients: the picture is clearer

Imaging of the lungs in patients with asthma has evolved dramatically over the last decade with sophisticated techniques, such as computed tomography, magnetic resonance imaging, positron emission tomography, and single photon emission computed tomography. New insights into current and future modalities for imaging in asthmatic patients and their application are discussed to potentially shed a clearer picture of the underlying pathophysiology of asthma, especially severe asthma, and the proposed clinical utility of imaging in patients with this common disease.

Individual canine airway response variability to a deep inspiration

In healthy individuals, a DI can reverse (bronchodilation) or prevent (bronchoprotection) induced airway constriction. For individuals with asthma or COPD, these effects may be attenuated or absent. Previous work showed that the size and duration of a DI affected the subsequent response of the airways. Also, increased airway tone lead to increased airway size variability. The present study examined how a DI affected the temporal variability in individual airway baseline size and after methacholine challenge in dogs using High-Resolution Computed Tomography. Dogs were anesthetized and ventilated, and on 4 separate days, HRCT scans were acquired before and after a DI at baseline and during a continuous intravenous infusion of methacholine (Mch) at 3 dose rates (17, 67, and 200 μg/min). The Coefficient of Variation was used as an index of temporal variability in airway size.We found that at baseline and the lowest dose of Mch, variability decreased immediately and 5 minutes after the DI (P < 0.0001). In contrast, with higher doses of Mch, the DI caused a variable response. At a rate of 67 μg/min of Mch, the temporal variability increased after 5 minutes, while at a rate of 200 μg/min of Mch, the temporal variability increased immediately after the DI. Increased airway temporal variability has been shown to be associated with asthma. Although the mechanisms underlying this temporal variability are poorly understood, the beneficial effects of a DI to decrease airway temporal variability was eliminated when airway tone was increased. If this effect is absent in asthmatics, this may suggest a possible mechanism for the loss of bronchoprotective and bronchodilatory effects after a DI in asthma.

Micron particle deposition in a tracheobronchial airway model under different breathing conditions

Effective management of asthma is dependent on achieving adequate delivery of the drugs into the lung. Inhalers come in the form of dry powder inhalers (DPIs) and metered dose inhalers (pMDIs) with the former requiring a deep fast breath for activation while there are no restrictions on inhalation rates for the latter. This study investigates two aerosol medication delivery methods (i) an idealised case for drug particle delivery under a normal breathing cycle (inhalation-exhalation) and (ii) for an increased effort during the inhalation with a breath hold. A computational model of a human tracheobronchial airway was reconstructed from computerised tomography (CT) scans. The model's geometry and lobar flow distribution were compared with experimental and empirical models to verify the current model. Velocity contours and secondary flow vectors showed vortex formation downstream of the bifurcations which enhanced particle deposition. The velocity contour profiles served as a predictive tool for the final deposition patterns. Different spherical aerosol particle sizes (3-10μm, 1.55g/cm(3)) were introduced into the airway for comparison over a range of Stokes number. It was found that a deep inhalation with a breath hold of 2s did not necessarily increase later deposition up to the sixth branch generation, but rather there was an increase in the deposition in the first few airway generations was found. In addition the breath hold allows deposition by sedimentation which assists in locally targeted deposition. Visualisation of particle deposition showed local "hot-spots" where particle deposition was concentrated in the lung airway.

Quantitative imaging of COPD

Computed tomography has facilitated recognition that chronic obstructive pulmonary disease is not a single disease but encompasses several overlapping entities, including emphysema, bronchitis, and small airways disease. Quantitative computed tomography can effectively characterize and quantify the extent of emphysema, airway wall thickening, and air trapping related to small airways disease.

Influence of rapid fluid loading on airway structure and function in healthy humans

BACKGROUND

The present study examined the influence of rapid intravenous fluid loading (RFL) on airway structure and pulmonary vascular volumes using computed tomography imaging and the subsequent impact on pulmonary function in healthy adults (n = 16).

METHODS AND RESULTS

Total lung capacity (DeltaTLC = -6%), forced vital capacity (DeltaFVC = -14%), and peak expiratory flow (DeltaPEF = -19%) decreased, and residual volume (DeltaRV = +38%) increased post-RFL (P < .05). Airway luminal cross-sectional area (CSA) decreased at the trachea, and at airway generation 3 (P < .05), wall thickness changed minimally with a tendency for increasing in generation five (P = .13). Baseline pulmonary function was positively associated with airway luminal CSA; however, this relationship deteriorated after RFL. Lung tissue volume and pulmonary vascular volumes increased 28% (P < .001) post-RFL, but did not fully account for the decline in TLC.

CONCLUSIONS

These data suggest that RFL results in obstructive/restrictive PF changes that are most likely related to structural changes in smaller airways or changes in extrapulmonary vascular beds.

Automatic lung segmentation in CT images with accurate handling of the hilar region

A fully automated and three-dimensional (3D) segmentation method for the identification of the pulmonary parenchyma in thorax X-ray computed tomography (CT) datasets is proposed. It is meant to be used as pre-processing step in the computer-assisted detection (CAD) system for malignant lung nodule detection that is being developed by the Medical Applications in a Grid Infrastructure Connection (MAGIC-5) Project. In this new approach the segmentation of the external airways (trachea and bronchi), is obtained by 3D region growing with wavefront simulation and suitable stop conditions, thus allowing an accurate handling of the hilar region, notoriously difficult to be segmented. Particular attention was also devoted to checking and solving the problem of the apparent 'fusion' between the lungs, caused by partial-volume effects, while 3D morphology operations ensure the accurate inclusion of all the nodules (internal, pleural, and vascular) in the segmented volume. The new algorithm was initially developed and tested on a dataset of 130 CT scans from the Italung-CT trial, and was then applied to the ANODE09-competition images (55 scans) and to the LIDC database (84 scans), giving very satisfactory results. In particular, the lung contour was adequately located in 96% of the CT scans, with incorrect segmentation of the external airways in the remaining cases. Segmentation metrics were calculated that quantitatively express the consistency between automatic and manual segmentations: the mean overlap degree of the segmentation masks is 0.96 ± 0.02, and the mean and the maximum distance between the mask borders (averaged on the whole dataset) are 0.74 ± 0.05 and 4.5 ± 1.5, respectively, which confirms that the automatic segmentations quite correctly reproduce the borders traced by the radiologist. Moreover, no tissue containing internal and pleural nodules was removed in the segmentation process, so that this method proved to be fit for the use in the framework of a CAD system. Finally, in the comparison with a two-dimensional segmentation procedure, inter-slice smoothness was calculated, showing that the masks created by the 3D algorithm are significantly smoother than those calculated by the 2D-only procedure.

Asthma: an imaging update

Significant advances continue in the subjective and quantifiable imaging features of asthma. Radiologists need to be aware of not only the general features, but also potential asthma mimics as well as complications.

An automated self-similarity analysis of the pulmonary tree of the Sprague-Dawley rat

We present the results of an automated analysis of the morphometry of the pulmonary airway trees of the Sprague-Dawley rat. Our work is motivated by a need to inform lower-dimensional mathematical models to prescribe realistic boundary conditions for multiscale hybrid models of rat lung mechanics. Silicone casts were made from three age-matched, male Sprague-Dawley rats, immersed in a gel containing a contrast agent and subsequently imaged with magnetic resonance (MR). From a segmentation of this data, we extracted a connected graph, representing the airway centerline. Segment statistics (lengths and diameters) were derived from this graph. To validate this MR imaging/digital analysis method, airway segment measurements were compared with nearly 1,000 measurements collected by hand using an optical microscope from one of the rat lung casts. To evaluate the reproducibility of the MR imaging/digital analysis method, two lung casts were each imaged three times with randomized orientations in the MR bore. Diameters and lengths of randomly selected airways were compared among each of the repeated imaging datasets to estimate the variability. Finally, we analyzed the morphometry of the airway tree by assembling individual airway segments into structures that span multiple generations, which we call branches. We show that branches not segments are the fundamental repeating unit in the rat lung and develop simple mathematical relationships describing these structures for the entire lung. Our analysis shows that airway diameters and lengths have both a deterministic and stochastic character.

Automated segmentation and morphometric analysis of the human airway tree from multidetector CT images

Remarkable advances in computed tomography (CT) technology geared our research toward investigating the integrative function of the lung and the development of a database of the airway tree incorporating anatomical and functional data with computational models. As part of this project, we are developing the algorithm to construct an anatomically realistic geometric model of airways from CT images. The basic concept of the algorithm is to segment as many airway trees as possible from CT images and later correct quantified parameters based on CT values. CT images are acquired with a 64-channel multidetector CT, and the airway is then extracted from them by the region-growing method while maintaining connectivity. Using this method, we extracted 428 airways up to the 14th branching generation. Although the airway diameters up to the 4th generation showed good agreement with those reported in an autopsy study, those in later generations were all greater than the reported values because of the limited resolution of the CT images. We corrected the errors in diameters by assessing the relationship between the diameter and median value of Hounsfield unit (HU) intensity of each airway; consequently, the diameters up to generation 8 agreed well with the reported values. Based on these results, we conclude that the use of HU-based correction algorithm combined with rough segmentation can be another way to improve data accuracy in the morphometric analysis of airways from CTs.

Airway remodeling measured by multidetector CT is increased in severe asthma and correlates with pathology

BACKGROUND

To prospectively apply an automated, quantitative three-dimensional approach to imaging and airway analysis to assess airway remodeling in asthma patients.

METHODS

Using quantitative software (Pulmonary Workstation, version 0.139; VIDA Diagnostics; Iowa City, IA) that enables quantitative airway segment measurements of low-dose, thin-section (0.625 to 1.25 mm), multidetector-row CT (MDCT) scans, we compared airway wall thickness (WT) and wall area (WA) in 123 subjects participating in a prospective multicenter cohort study, the National Institutes of Health Severe Asthma Research Program (patients with severe asthma, n = 63; patients with mild-to-moderate asthma, n = 35); and healthy subjects, n = 25). A subset of these subjects underwent fiberoptic bronchoscopy and endobronchial biopsies (n = 32). WT and WA measurements were corrected for total airway diameter and area: WT and WA, respectively.

RESULTS

Subjects with severe asthma had a significantly greater WT% than patients with mild-to-moderate asthma and healthy subjects (17.2 +/- 1.5 vs 16.5 +/- 1.6 [p = 0.014] and 16.3 +/- 1.2 [p = 0.031], respectively) and a greater WA percentage (WA%) compared to patients with mild-to-moderate asthma and healthy subjects (56.6 +/- 2.9 vs 54.7 +/- 3.3 [p = 0.005] and 54.6 +/- 2.4 [p = 0.003], respectively). Both WT% and WA% were inversely correlated with baseline FEV(1) percent predicted (r = -0.39, p < 0.0001 and r = -0.40, p < 0.0001, respectively) and positively correlated with response to a bronchodilator (r = 0.28, p = 0.002 and r = 0.35, p < 0.0001, respectively). The airway epithelial thickness measure on the biopsy sample correlated with WT% (r = 0.47; p = 0.007) and WA% (r = 0.52; p = 0.003). In the same individual, there is considerable regional heterogeneity in airway WT.

CONCLUSION

Patients with severe asthma have thicker airway walls as measured on MDCT scan than do patients with mild asthma or healthy subjects, which correlates with pathologic measures of remodeling and the degree of airflow obstruction. MDCT scanning may be a useful technique for assessing airway remodeling in asthma patients, but overlap among the groups limits the diagnostic value in individual subjects.