Maximizing quantitative accuracy of lung airway lumen and wall measures obtained from X-ray CT imaging

Origins of and lessons from quantitative functional X-ray computed tomography of the lung

Functional CT of the lung has emerged from quantitative CT (qCT). Structural details extracted at multiple lung volumes offer indices of function. Additionally, single volumetric images, if acquired at standardized lung volumes and body posture, can be used to model function by employing such engineering techniques as computational fluid dynamics. With the emergence of multispectral CT imaging including dual energy from energy integrating CT scanners and multienergy binning using the newly released photon counting CT technology, function is tagged via use of contrast agents. Lung disease phenotypes have previously been lumped together by the limitations of spirometry and plethysmography. QCT and its functional embodiment have been imbedded into studies seeking to characterize chronic obstructive pulmonary disease, severe asthma, interstitial lung disease and more. Reductions in radiation dose by an order of magnitude or more have been achieved. At the same time, we have seen significant increases in spatial and density resolution along with methodologic validations of extracted metrics. Together, these have allowed attention to turn towards more mild forms of disease and younger populations. In early applications, clinical CT offered anatomic details of the lung. Functional CT offers regional measures of lung mechanics, the assessment of functional small airways disease, as well as regional ventilation-perfusion matching (V/Q) and more. This paper will focus on the use of quantitative/functional CT for the non-invasive exploration of dynamic three-dimensional functioning of the breathing lung and beating heart within the unique negative pressure intrathoracic environment of the closed chest.

Quantification of Airway Dimensions using a High-Resolution CT Scanner: A Phantom Study

PURPOSE

Small airways with inner diameters less than 2 mm are sites of major airflow limitations in patients with chronic obstructive pulmonary disease (COPD) and asthma. The purpose of this study is to investigate the limitations for accurate assessment of small airway dimensions using both high-resolution CT (HRCT) and conventional normal-resolution CT at low dose levels.

METHODS

To model the normal human airways from the 3^rd to 20^th generations, a cylindrical polyurethane phantom with 14 airway tubes of inner diameters (ID) ranging from 0.3 to 3.4 mm and wall thicknesses (WT) ranging from 0.15 to 1.6 mm was placed within an Anthropomorphic QRM-Thorax phantom. The Aquilion Precision (Canon Medical Systems Corporation) HRCT scanner was used to acquire images at 80, 100 and 120 kV using high resolution mode (HR, 0.25 mm x 160 detector configuration) and normal resolution mode (NR, 0.5 mm x 80 detector configuration). The HR data were reconstructed using 1024 x 1024 matrix (0.22 x 0.22 x 0.25 mm voxel size) and the NR data were reconstructed using a 512 x 512 matrix (0.43 x 0.43 x 0.50 mm). Two reconstruction algorithms (filtered back projection; FBP and an adaptive iterative dose reduction 3D algorithm; AIDR 3D) and three reconstruction kernels (FC30, FC52 and FC56) were investigated. The CTDI_vol dose values ranged from 0.2 to 6.2 mGy. A refined automated full-width half-maximum (FWHM) method was used for the measurement of airway dimensions, where the density profiles were computed by radial oversampling using a polar coordinate system. Both ID and WT were compared to the known dimensions using a regression model, and the root-mean-squared-error (RMSE) and average error were computed across all 14 airway tubes.

RESULTS

The results indicate that the ID can be measured within a 15% error down to approximately 0.8 mm and 2.0 mm using the HR and NR modes, respectively. The overall RMSE (and average error) of ID measurements for HR and NR were 0.10 mm (-0.70%) and 0.31 mm (-2.63%), respectively. The RMSE (and average error) of WT measurements using HR and NR were 0.10 mm (23.27%) and 0.27 mm (53.56%), respectively. The WT measurement using HR yielded a factor of two improvement in accuracy as compared to NR.

CONCLUSIONS

High-resolution CT can provide more accurate measurements of airway dimensions as compared with normal resolution CT, potentially improving quantitative assessment of pathologies such as COPD and asthma. The high resolution mode acquired and reconstructed with AIDR3D and the FC52 kernel provides most accurate measurement of airway dimensions. Low-dose high resolution measurements at dose level above 0.9 mGy can provide improved accuracy on both inner diameters and wall thicknesses compared to full dose normal resolution airway phantom measurements.

Subvoxel vessel wall thickness measurements of the intracranial arteries using a convolutional neural network

Vessel wall thickening of the intracranial arteries has been associated with cerebrovascular disease and atherosclerotic plaque development. Visualization of the vessel wall has been enabled by recent advancements in vessel wall MRI. However, quantifying early wall thickening from these MR images is difficult and prone to severe overestimation, because the voxel size of clinically used acquisitions exceeds the wall thickness of the intracranial arteries. In this study, we aimed for accurate and precise subvoxel vessel wall thickness measurements. A convolutional neural network was trained on MR images of 34 ex vivo circle of Willis specimens, acquired with a clinically used protocol (isotropic acquired voxel size: 0.8 mm). Ground truth measurements were performed on images acquired with an ultra-high-resolution protocol (isotropic acquired voxel size: 0.11 mm) and were used for evaluation. Additionally, we determined the robustness of our method by applying Monte Carlo dropout and test time augmentation. Lastly, we applied our method on in vivo images of three intracranial aneurysms to measure their wall thickness. Our method shows resolvability of different vessel wall thicknesses, well below the acquired voxel size. The method described may facilitate quantitative measurements on MRI data for a wider range of clinical applications.

LOCALLY ADAPTIVE HALF-MAX METHODS FOR AIRWAY LUMEN-AREA AND WALL-THICKNESS AND THEIR REPEAT CT SCAN REPRODUCIBILITY

Quantitative computed tomography (CT)-based characterization of bronchial metrics is increasingly being used to investigate chronic obstructive pulmonary disease (COPD)-related phenotypes. Automated methods for airway measurements benefit large multi-site studies by reducing cost and subjectivity errors. Critical challenges for CT-based analysis of airway morphology are related to location of lumen and wall transitions in the presence of varying scales and intensity-contrasts from proximal to distal sites. This paper introduces locally adaptive half-max methods to locate airway lumen and wall transitions and compute cross-sectional lumen area and wall-thickness. Also, the method uses a consistency analysis of wall-thickness to avoid adjoining-structure-artifacts. Experimental results show that computed bronchial measures at individual anatomic airway tree locations are repeat CT scan reproducible with intra-class correlation coefficient (ICC) values exceeding 0.9 and 0.8 for lumen-area and wall-thickness, respectively. Observed ICC values for derived morphologic measures, e.g., lumen-area compactness (ICC>0.67) and tapering (ICC>0.47) are relatively lower.

Development of a CT imaging phantom of anthromorphic lung using fused deposition modeling 3D printing

Development of patient-specific CT imaging phantoms with randomly incorporated lesions of various shapes and sizes for calibrating image intensity and validating quantitative measurement software is very challenging. In this investigation, a physical phantom that accurately represents a patient's specific anatomy and the intensity of lung CT images at the voxel level will be fabricated using fused deposition modeling (FDM) 3D printing. Segmentation and modeling of a patient's CT data were performed by an expert and the results were confirmed by a thoracic radiologist with more than 20 years of experience. This facilitated the extraction of the details of the patient's anatomy; various kinds of nodules with different shapes and sizes were randomly added to the modeled lung for evaluating the size-accuracy of the quantification software. To achieve these Hounsfield Units (HU) ranges for the corresponding voxels in acquired CT scans, the infill ratios of FDM 3D printing were controlled. Based on CT scans of the 3D printed phantoms, the measured HU for normal pulmonary parenchyma, ground glass opacity (GGO), and solid nodules were determined to be within target HU ranges. The accuracy of the mean absolute difference and the mean relative difference of nodules were less than 0.55 ± 0.30 mm and 3.72 ± 1.64% (mean difference ± 95 CI), respectively. Patient-specific CT imaging phantoms were designed and manufactured using an FDM printer, which could be applied for the precise calibration of CT intensity and the validation of image quantification software.

The Association Between Bronchial Wall CT Attenuation and Spirometry in Patients with Bronchial Asthma

RATIONALE AND OBJECTIVE

The purpose of this study was to evaluate the correlation between generation-based bronchial wall attenuation on thin-section computed tomography (CT) scans and airflow limitation in patients with bronchial asthma.

MATERIALS AND METHODS

This study included 28 bronchial asthma patients (13 men, 15 women; age range, 23-89 years) who underwent both chest CT and spirometry. On CT, the mean values of peak wall attenuation, wall area percentage, and luminal area were measured in the segmental, subsegmental, and sub-subsegmental bronchi of the right B1 and B10 bronchi. Correlations of the CT measurements with forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC), percent predicted forced expiratory flow at 25%-75% of the FVC (%pred forced expiratory flow25-75), and percent predicted peak flow rate were evaluated with Spearman's rank correlation test.

RESULTS

The peak wall attenuation of each generation of segmental bronchi significantly correlated with the forced expiratory volume in 1 second/FVC (B1 segmental, ρ = -0.683, p < 0.0001; B1 subsegmental, ρ = -0.875, p < 0.0001; B1 sub-subsegmental, ρ = -0.926, p < 0.0001; B10 segmental, ρ = -0.811, p < 0.0001; B10 subsegmental, ρ = -0.903, p < 0.0001; B10 sub-subsegmental ρ = -0.950, p < 0.0001). Similar correlations were found between the peak wall attenuation and %pred forced expiratory flow 25-75 or percent predicted peak flow rate. Overall, the correlation coefficients were relatively high in the more peripheral bronchial generations. In all measurements, the coefficients of the peak wall attenuations were higher than those of the wall area percentage and luminal area.

CONCLUSION

Peak attenuation of the bronchial wall, particularly in the peripheral bronchi, measured on CT is a good biomarker for the severity of bronchial asthma.

Reproducibility of an airway tapering measurement in computed tomography with application to bronchiectasis

We propose a pipeline to acquire a scalar tapering measurement from the carina to the most distal point of an individual airway visible on computed tomography (CT). We show the applicability of using tapering measurements on clinically acquired data by quantifying the reproducibility of the tapering measure. We generate a spline from the centerline of an airway to measure the area and arclength at contiguous intervals. The tapering measurement is the gradient of the linear regression between area in log space and arclength. The reproducibility of the measure was assessed by analyzing different radiation doses, voxel sizes, and reconstruction kernel on single timepoint and longitudinal CT scans and by evaluating the effect of airway bifurcations. Using 74 airways from 10 CT scans, we show a statistical difference, p = 3.4 × 10 - 4 , in tapering between healthy airways ( n = 35 ) and those affected by bronchiectasis ( n = 39 ). The difference between the mean of the two populations is 0.011    mm - 1 , and the difference between the medians of the two populations was 0.006    mm - 1 . The tapering measurement retained a 95% confidence interval of ± 0.005    mm - 1 in a simulated 25 mAs scan and retained a 95% confidence of ± 0.005    mm - 1 on simulated CTs up to 1.5 times the original voxel size. We have established an estimate of the precision of the tapering measurement and estimated the effect on precision of the simulated voxel size and CT scan dose. We recommend that the scanner calibration be undertaken with the phantoms as described, on the specific CT scanner, radiation dose, and reconstruction algorithm that are to be used in any quantitative studies.

Attenuation profile matching: An accurate and scan parameter-robust measurement method for small airway dimensions in low-dose CT scans

PURPOSE

The dimensions of small airways with an internal diameter of less than 2-3 mm are important biomarkers for the evaluation of pulmonary diseases, such as asthma and chronic obstructive pulmonary disease (COPD). The resolution limitations of CT systems, however, have remained a barrier to be of use for determining the small airway dimensions. We present a novel approach, called the attenuation profile matching (APM) method, which allows for the accurate determination of the small airway dimension while being robust to varying CT scan parameters.

METHOD

For generating the synthetic attenuation profiles of an airway, we acquired and employed the point spread functions of a CT system by calculating its convolution with numerical airway models with varying wall thicknesses. The dimensions of a given airway were determined as per the numerical model yielding minimum error between the measured and the synthetic attenuation profiles across the airway.

RESULTS

In a phantom study with airway tubes, the APM method proved to be highly accurate in determining airway wall dimensions. The measurement error for the smallest tube (0.6 mm thickness, 3 mm diameter) was merely 0.02 mm (3.3%) in wall thickness and 0.17 mm (5.6%) in lumen diameter. In a pilot clinical test, the APM method was able to distinguish the airway wall thicknesses of COPD cases (1.16 ± 0.23 mm) from those of normal subjects (0.6 ± 0.18 mm), while the measurements using the full width at half maximum method substantially overlapped (1.45 ± 0.32 mm vs. 1.28 ± 0.30 mm, respectively) and were barely distinguishable from each other.

CONCLUSION

Our proposed APM method has the potential to overcome the resolution limitations of current CT systems and accurately determine the small airway dimensions in COPD patients.

Prognostic Significance of Large Airway Dimensions on Computed Tomography in the General Population. The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study

RATIONALE

Large airway dimensions on computed tomography (CT) have been associated with lung function, symptoms, and exacerbations in chronic obstructive pulmonary disease (COPD), as well as with symptoms in smokers with preserved spirometry. Their prognostic significance in persons without lung disease remains undefined.

OBJECTIVES

To examine associations between large airway dimensions on CT and respiratory outcomes in a population-based cohort of adults without prevalent lung disease.

METHODS

The Multi-Ethnic Study of Atherosclerosis recruited participants ages 45-84 years without cardiovascular disease in 2000-2002; we excluded participants with prevalent chronic lower respiratory disease (CLRD). Spirometry was measured in 2004-2006 and 2010-2012. CLRD hospitalizations and deaths were classified by validated criteria through 2014. The average wall thickness for a hypothetical airway of 10-mm lumen perimeter on CT (Pi10) was calculated using measures of airway wall thickness and lumen diameter. Models were adjusted for age, sex, principal components of ancestry, body mass index, smoking, pack-years, scanner, percent emphysema, genetic risk score, and initial forced expiratory volume in 1 second (FEV1) percent predicted.

RESULTS

Greater Pi10 was associated with 9% faster FEV1 decline (95% confidence interval [CI], 2 to 15%; P = 0.012) and increased incident COPD (odds ratio, 2.22; 95% CI, 1.43-3.45; P = 0.0004) per standard deviation among 1,830 participants. Over 78,147 person-years, higher Pi10 was associated with a 57% higher risk of first CLRD hospitalization or mortality (P = 0.0496) per standard deviation. Of Pi10's component measures, both greater airway wall thickness and narrower lumen predicted incident COPD and CLRD clinical events.

CONCLUSIONS

In adults without CLRD, large airway dimensions on CT were prospectively associated with accelerated lung function decline and increased risks of COPD and CLRD hospitalization and mortality.

Semi-automatic Methods for Airway and Adjacent Vessel Measurement in Bronchiectasis Patterns in Lung HRCT Images of Cystic Fibrosis Patients

Airway and vessel characterization of bronchiectasis patterns in lung high-resolution computed tomography (HRCT) images of cystic fibrosis (CF) patients is very important to compute the score of disease severity. We propose a hybrid and evolutionary optimized threshold and model-based method for characterization of airway and vessel in lung HRCT images of CF patients. First, the initial model of airway and vessel is obtained using the enhanced threshold-based method. Then, the model is fitted to the actual image by optimizing its parameters using particle swarm optimization (PSO) evolutionary algorithm. The experimental results demonstrated the outperformance of the proposed method over its counterpart in R-squared, mean and variance of error, and run time. Moreover, the proposed method outperformed its counterpart for airway inner diameter/vessel diameter (AID/VD) and airway wall thickness/vessel diameter (AWT/VD) biomarkers in R-squared and slope of regression analysis.

Management of COPD: Is there a role for quantitative imaging?

While the recent development of quantitative imaging methods have led to their increased use in the diagnosis and management of many chronic diseases, medical imaging still plays a limited role in the management of chronic obstructive pulmonary disease (COPD). In this review we highlight three pulmonary imaging modalities: computed tomography (CT), magnetic resonance imaging (MRI) and optical coherence tomography (OCT) imaging and the COPD biomarkers that may be helpful for managing COPD patients. We discussed the current role imaging plays in COPD management as well as the potential role quantitative imaging will play by identifying imaging phenotypes to enable more effective COPD management and improved outcomes.

Influence of Coronary Artery Diameter on Intracoronary Transluminal Attenuation Gradient During CT Angiography

OBJECTIVES

The goal of this study was to assess the effect of coronary artery diameter on luminal attenuation and the correlation between the transluminal attenuation gradient (TAG) and transluminal diameter gradient (TDG) on computed tomography (CT) coronary angiography.

BACKGROUND

Recent studies have reported promising results of TAG in detecting significant stenosis. However, because of the intrinsic nature of CT reconstruction algorithms, luminal attenuation may be affected by vessel diameter.

METHODS

In this 3-part study, phantom simulating vessels of various diameters immersed in different contrast mixtures were scanned, and intraluminal attenuations were measured. In addition, dynamic volume CT scanning was performed in 3 mongrel dogs (untreated, a stenosis model, and an occlusion model) using 320-row area detector computed tomography and intraluminal attenuations, and TAGs were calculated at each temporal scan and compared. In a separate clinical study, TAGs and TDGs of 152 coronary arteries from 62 patients who underwent 320-row area detector computed tomography coronary angiography and invasive angiography were measured and compared.

RESULTS

Intraluminal attenuation of phantom vessels gradually decreased along with a decrease in diameter. Animal studies revealed that the peak attenuation of distal smaller coronary arteries did not reach that of proximal larger coronary arteries: 55.2% to 78.1% peak attenuation of proximal coronary arteries. No differences in TAG were found between stenotic and normal left circumflex arteries at temporal scans (all, p > 0.05). The clinical study demonstrated significant correlation between TAG and TDG (r = 0.580; p < 0.0001).

CONCLUSIONS

Intraluminal attenuation was shown to decrease with diminution of vessel diameters. In addition, TAG exhibited a significant correlation with TDG, implying that TAG may be a secondary result because of differences in diameters.

Automated detection and quantitative assessment of pulmonary airways depicted on CT images

We developed and tested a fully automated computerized scheme that identifies pulmonary airway sections depicted on computed tomography (CT) images and computes their sizes including the lumen and airway wall areas. The scheme includes four processing modules that (1) segment left and right lung areas, (2) identify airway locations, (3) segment airway walls from neighboring pixels, and (4) compute airway sizes. The scheme uses both a raster scanning and a labeling algorithm complemented by simple classification rules for region size and circularity to automatically search for and identify airway sections of interest. A profile tracking method is used to segment airway walls from neighboring pixels including those associated with dense tissue (i.e., pulmonary arteries) along scanning radial rays. A partial pixel membership method is used to compute airway size. The scheme was tested on ten randomly selected CT studies that included 26 sets of CT images acquired using both low and conventional dose CT examinations with one of four reconstruction algorithms (namely, "bone," "lung," "soft," and "standard" convolution kernels). Three image section thicknesses (1.25, 2.5, and 5 mm) were evaluated. The scheme detected a large number of quantifiable airway sections when the CT images were reconstructed using high spatial frequency convolution kernels. The detection results demonstrated a consistent trend for all test image sets in that as airway lumen size increases, on average the airway wall area increases as well and the wall area percentage decreases. The study suggested that CT images reconstructed using high spatial frequency convolution kernels and thin-section thickness were most amenable to automated detection, reasonable segmentation, and quantified assessment when the airways are close to being perpendicular to the CT image plane.

Effect of Reducing Field of View on Multidetector Quantitative Computed Tomography Parameters of Airway Wall Thickness in Asthma

OBJECTIVE

We reduced the computed tomography (CT)-reconstructed field of view (FOV), increasing pixel density across airway structures and reducing partial volume effects, to determine whether this would improve accuracy of airway wall thickness quantification.

METHODS

We performed CT imaging on a lung phantom and 29 participants. Images were reconstructed at 30-, 15-, and 10-cm FOV using a medium-smooth kernel. Cross-sectional airway dimensions were compared at each FOV with repeated-measures analysis of variance.

RESULTS

Phantom measurements were more accurate when FOV decreased from 30 to 15 cm (P < 0.05). Decreasing FOV further to 10 cm did not significantly improve accuracy. Human airway measurements similarly decreased by decreasing FOV (P < 0.001). Percent changes in all measurements when reducing FOV from 30 to 15 cm were less than 3%.

CONCLUSIONS

Airway measurements at 30-cm FOV are near the limits of CT resolution using a medium-smooth kernel. Reducing reconstructed FOV would minimally increase sensitivity to detect differences in airway dimensions.

A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT

Inflammatory and infectious lung diseases commonly involve bronchial airway structures and morphology, and these abnormalities are often analyzed non-invasively through high resolution computed tomography (CT) scans. Assessing airway wall surfaces and the lumen are of great importance for diagnosing pulmonary diseases. However, obtaining high accuracy from a complete 3-D airway tree structure can be quite challenging. The airway tree structure has spiculated shapes with multiple branches and bifurcation points as opposed to solid single organ or tumor segmentation tasks in other applications, hence, it is complex for manual segmentation as compared with other tasks. For computerized methods, a fundamental challenge in airway tree segmentation is the highly variable intensity levels in the lumen area, which often causes a segmentation method to leak into adjacent lung parenchyma through blurred airway walls or soft boundaries. Moreover, outer wall definition can be difficult due to similar intensities of the airway walls and nearby structures such as vessels. In this paper, we propose a computational framework to accurately quantify airways through (i) a novel hybrid approach for precise segmentation of the lumen, and (ii) two novel methods (a spatially constrained Markov random walk method (pseudo 3-D) and a relative fuzzy connectedness method (3-D)) to estimate the airway wall thickness. We evaluate the performance of our proposed methods in comparison with mostly used algorithms using human chest CT images. Our results demonstrate that, on publicly available data sets and using standard evaluation criteria, the proposed airway segmentation method is accurate and efficient as compared with the state-of-the-art methods, and the airway wall estimation algorithms identified the inner and outer airway surfaces more accurately than the most widely applied methods, namely full width at half maximum and phase congruency.

Clinical correlations of computed tomography imaging in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease is a complex disease with heterogeneous presentation, progression, and structural abnormality that is currently graded solely on clinical and physiologic parameters. Thoracic computed tomography imaging holds promise for phenotyping in chronic obstructive pulmonary disease, but despite increasing availability, this methodology has yet to be incorporated into clinical guidelines or routine clinical practice. However, the unique clinical implications of emphysema and airways disease are becoming clearer. Emphysema has a strong association with more rapid disease progression and mortality. Airways disease has a strong relationship with symptoms and health status. It is hoped that future refinement of emphysema assessment allowing for quantitative subtyping will also increase our ability to define clinically meaningful subgroups, as will development of methodologies to assess airways disease and, in particular, small airways through inspiratory/expiratory image registration techniques. Most important, however, is the need for longitudinal data, in not only observational but also therapeutic settings, such that the impact of interventions on radiographically defined phenotypes can be assessed.

Computerized detection of noncalcified plaques in coronary CT angiography: evaluation of topological soft gradient prescreening method and luminal analysis

PURPOSE

The buildup of noncalcified plaques (NCPs) that are vulnerable to rupture in coronary arteries is a risk for myocardial infarction. Interpretation of coronary CT angiography (cCTA) to search for NCP is a challenging task for radiologists due to the low CT number of NCP, the large number of coronary arteries, and multiple phase CT acquisition. The authors conducted a preliminary study to develop machine learning method for automated detection of NCPs in cCTA.

METHODS

With IRB approval, a data set of 83 ECG-gated contrast enhanced cCTA scans with 120 NCPs was collected retrospectively from patient files. A multiscale coronary artery response and rolling balloon region growing (MSCAR-RBG) method was applied to each cCTA volume to extract the coronary arterial trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for NCP candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. The NCP candidates were then characterized by a luminal analysis that used 3D geometric features to quantify the shape information and gray-level features to evaluate the density of the NCP candidates. With machine learning techniques, useful features were identified and combined into an NCP score to differentiate true NCPs from false positives (FPs). To evaluate the effectiveness of the image analysis methods, the authors performed tenfold cross-validation with the available data set. Receiver operating characteristic (ROC) analysis was used to assess the classification performance of individual features and the NCP score. The overall detection performance was estimated by free response ROC (FROC) analysis.

RESULTS

With our TSG prescreening method, a prescreening sensitivity of 92.5% (111/120) was achieved with a total of 1181 FPs (14.2 FPs/scan). On average, six features were selected during the tenfold cross-validation training. The average area under the ROC curve (AUC) value for training was 0.87 ± 0.01 and the AUC value for validation was 0.85 ± 0.01. Using the NCP score, FROC analysis of the validation set showed that the FP rates were reduced to 3.16, 1.90, and 1.39 FPs/scan at sensitivities of 90%, 80%, and 70%, respectively.

CONCLUSIONS

The topological soft-gradient prescreening method in combination with the luminal analysis for FP reduction was effective for detection of NCPs in cCTA, including NCPs causing positive or negative vessel remodeling. The accuracy of vessel segmentation, tracking, and centerline identification has a strong impact on NCP detection. Studies are underway to further improve these techniques and reduce the FPs of the CADe system.

Volumetric quantification of airway wall in CT via collision-free active surface model: application to asthma assessment

Emerging idea in asthma phenotyping, incorporating local morphometric information on the airway wall thickness would be able to better account for the process of airway remodeling as indicator of pathology or therapeutic impact. It is thus important that such information be provided uniformly along the airway tree, not on a sparse (cross-section) sampling basis. The volumetric segmentation of the airway wall from CT data is the issue addressed in this paper by exploiting a patient-specific surface active model. An original aspect taken into account in the proposed deformable model is the management of auto-collisions for this complex morphology. The analysis of several solutions ended up with the design of a motion vector field specific to the patient geometry to guide the deformation. The segmentation result, presented as two embedded inner/outer surfaces of the wall, allows the quantification of the tissue thickness based on a locally-defined measure sensitive to even small surface irregularities. The method is validated with respect to several ground truth simulations of pulmonary CT data with different airway geometries and acquisition protocols showing accuracy within the CT resolution range. Results from an ongoing clinical study on moderate and severe asthma are presented and discussed.

Limitations of airway dimension measurement on images obtained using multi-detector row computed tomography

Objectives

(a) To assess the effects of computed tomography (CT) scanners, scanning conditions, airway size, and phantom composition on airway dimension measurement and (b) to investigate the limitations of accurate quantitative assessment of small airways using CT images.

Methods

An airway phantom, which was constructed using various types of material and with various tube sizes, was scanned using four CT scanner types under different conditions to calculate airway dimensions, luminal area (Ai), and the wall area percentage (WA%). To investigate the limitations of accurate airway dimension measurement, we then developed a second airway phantom with a thinner tube wall, and compared the clinical CT images of healthy subjects with the phantom images scanned using the same CT scanner. The study using clinical CT images was approved by the local ethics committee, and written informed consent was obtained from all subjects. Data were statistically analyzed using one-way ANOVA.

Results

Errors noted in airway dimension measurement were greater in the tube of small inner radius made of material with a high CT density and on images reconstructed by body algorithm (p<0.001), and there was some variation in error among CT scanners under different fields of view. Airway wall thickness had the maximum effect on the accuracy of measurements with all CT scanners under all scanning conditions, and the magnitude of errors for WA% and Ai varied depending on wall thickness when airways of <1.0-mm wall thickness were measured.

Conclusions

The parameters of airway dimensions measured were affected by airway size, reconstruction algorithm, composition of the airway phantom, and CT scanner types. In dimension measurement of small airways with wall thickness of <1.0 mm, the accuracy of measurement according to quantitative CT parameters can decrease as the walls become thinner.

Optimal graph search based segmentation of airway tree double surfaces across bifurcations

Identification of both the luminal and the wall areas of the bronchial tree structure from volumetric X-ray computed tomography (CT) data sets is of critical importance in distinguishing important phenotypes within numerous major lung diseases including chronic obstructive pulmonary diseases (COPD) and asthma. However, accurate assessment of the inner and outer airway wall surfaces of a complete 3-D tree structure is difficult due to their complex nature, particularly around the branch areas. In this paper, we extend a graph search based technique (LOGISMOS) to simultaneously identify multiple inter-related surfaces of branching airway trees. We first perform a presegmentation of the input 3-D image to obtain basic information about the tree topology. The presegmented image is resampled along judiciously determined paths to produce a set of vectors of voxels (called voxel columns). The resampling process utilizes medial axes to ensure that voxel columns of appropriate lengths and directions are used to capture the object surfaces without interference. A geometric graph is constructed whose edges connect voxels in the resampled voxel columns and enforce validity of the smoothness and separation constraints on the sought surfaces. Cost functions with directional information are employed to distinguish inner and outer walls. The assessment of wall thickness measurement on a CT-scanned double-wall physical phantom (patterned after an in vivo imaged human airway tree) achieved highly accurate results on the entire 3-D tree. The observed mean signed error of wall thickness ranged from -0.09 ±0.24 mm to 0.07 ±0.23 mm in bifurcating/nonbifurcating areas. The mean unsigned errors were 0.16±0.12 mm to 0.20±0.11 mm. When the airway wall surface was partitioned into meaningful subregions, the airway wall thickness accuracy was the same in most tested bifurcation/nonbifurcation and carina/noncarina regions (p=NS). Once validated on phantoms, our method was applied to human in vivo volumetric CT data to demonstrate relationships of airway wall thickness as a function of luminal dimension and airway tree generation. Wall thickness differences between the bifurcation/nonbifurcation regions were statistically significant (p < 0.05) for tree generations 6, 7, 8, and 9. In carina/noncarina regions, the wall thickness was statistically different in generations 1, 4, 5, 6, 7, and 8.

Sputum mediator profiling and relationship to airway wall geometry imaging in severe asthma

Background

Severe asthma is a heterogeneous disease and the relationship between airway inflammation and airway remodelling is poorly understood. We sought to define sputum mediator profiles in severe asthmatics categorised by CT-determined airway geometry and sputum differential cell counts.

Methods

In a single centre cross-sectional observational study we recruited 59 subjects with severe asthma that underwent sputum induction and thoracic CT. Quantitative CT analysis of the apical segment of the right upper lobe (RB1) was performed. Forty-one mediators in sputum samples were measured of which 21 mediators that were assessable in >50% of samples were included in the analyses.

Results

Independent of airway geometry, sputum MMP9 and IL-1β were elevated in those groups with a high sputum neutrophil count while sputum ICAM was elevated in those subjects with a low sputum neutrophil count. In contrast, sputum CCL11, IL-1α and fibrinogen were different in groups stratified by both sputum neutrophil count and airway geometry. Sputum CCL11 concentration was elevated in subjects with a low sputum neutrophil count and high luminal and total RB1 area, whereas sputum IL1α was increased in subjects with a high sputum neutrophil count and low total RB1 area. Sputum fibrinogen was elevated in those subjects with RB1 luminal narrowing and in those subjects with neutrophilic inflammation without luminal narrowing.

Conclusions

We have demonstrated that sputum mediator profiling reveals a number of associations with airway geometry. Whether these findings reflect important biological phenotypes that might inform stratified medicine approaches requires further investigation.

Image analysis for cystic fibrosis: computer-assisted airway wall and vessel measurements from low-dose, limited scan lung CT images

Cystic fibrosis (CF) is a life-limiting genetic disease that affects approximately 30,000 Americans. When compared to those of normal children, airways of infants and young children with CF have thicker walls and are more dilated in high-resolution computed tomographic (CT) imaging. In this study, we develop computer-assisted methods for assessment of airway and vessel dimensions from axial, limited scan CT lung images acquired at low pediatric radiation doses. Two methods (threshold- and model-based) were developed to automatically measure airway and vessel sizes for pairs identified by a user. These methods were evaluated on chest CT images from 16 pediatric patients (eight infants and eight children) with different stages of mild CF related lung disease. Results of threshold-based, corrected with regression analysis, and model-based approaches correlated well with both electronic caliper measurements made by experienced observers and spirometric measurements of lung function. While the model-based approach results correlated slightly better with the human measurements than those of the threshold method, a hybrid method, combining these two methods, resulted in the best results.

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.

Cigarette smoking and airway wall thickness on CT scan in a multi-ethnic cohort: the MESA Lung Study

BACKGROUND

Autopsy studies show that smoking contributes to airway wall hyperplasia and narrowing of the airway lumen. Studies of smoking and airway measures on computed tomography (CT) scan are limited to case-control studies of measures that combine airway lumen and wall thickness.

OBJECTIVES

We hypothesized that cumulative cigarette smoking would be associated with increased airway wall thickness in a large, population-based cohort.

METHODS

The Multi-Ethnic Study of Atherosclerosis enrolled participants age 45-84 years from the general population. Smoking history was assessed via standardized questionnaire items; current smoking was confirmed in half the cohort with cotinine. Airway lumen and wall thickness were measured in two dimensions in posterior basal segmental bronchi on cardiac-gated CT scans. Analyses were adjusted for age, gender, genetic ancestry, education, height, weight, asthma history, particulate matter, scanner type, and scanner current.

RESULTS

Half of the 7898 participants had smoked and 14% were current smokers. Pack-years of smoking were associated with thicker airway walls (mean increase 0.002 mm per ten pack-years [95% CI: 0.00002, 0.004] p = 0.03). Current smoking was associated with narrower airway lumens (mean decrease -0.11 mm [95% CI: -0.2, -0.02] p = 0.02). There was no evidence that either association was modified by genetic ancestry, and findings persisted among participants without clinical disease.

CONCLUSIONS

Long-term cigarette smoking was associated with subclinical increases in wall thickness of sub-segmental airways whereas current smoking was associated with narrower airway lumen diameters. Smoking may contribute to airway wall thickening prior to the development of overt chronic obstructive pulmonary disease.

Optical coherence tomography in conjunction with bronchoscopy

OBJECTIVE

To evaluate the feasibility of and the potential for using optical coherence tomography in conjunction with conventional bronchoscopy in the evaluation of the airways.

METHODS

This was a pilot study based on an ex vivo experimental model involving three animals: one adult New Zealand rabbit and two Landrace pigs. An optical coherence tomography imaging catheter was inserted through the working channel of a flexible bronchoscope in order to reach the distal trachea of the animals. Images of the walls of the trachea were systematically taken along its entire length, from the distal to the proximal portion.

RESULTS

The imaging catheter was easily adapted to the working channel of the bronchoscope. High-resolution images of cross sections of the trachea were taken in real time, precisely delineating microstructures, such as the epithelium, submucosa, and cartilage, as well as the adventitia of the anterior and lateral tracheal walls. The corresponding layers of the epithelium, mucosa, and cartilage were clearly differentiated. The mucosa, submucosa, and trachealis muscle were clearly identified in the posterior wall.

CONCLUSIONS

It is feasible to use an optical coherence tomography imaging catheter in combination with a flexible bronchoscope. Optical coherence tomography produces high-resolution images that reveal the microanatomy of the trachea, including structures that are typically seen only on images produced by conventional histology.

Computerized identification of airway wall in CT examinations using a 3D active surface evolution approach

Airway diseases (e.g., asthma, emphysema, and chronic bronchitis) are extremely common worldwide. Any morphological variations (abnormalities) of airways may physically change airflow and ultimately affect the ability of the lungs in gas exchange. In this study, we describe a novel algorithm aimed to automatically identify airway walls depicted on CT images. The underlying idea is to place a three-dimensional (3D) surface model within airway regions and thereafter allow this model to evolve (deform) under predefined external and internal forces automatically to the location where these forces reach a state of balance. By taking advantage of the geometric and the density characteristics of airway walls, the evolution procedure is performed in a distance gradient field and ultimately stops at regions with the highest contrast. The performance of this scheme was quantitatively evaluated from several perspectives. First, we assessed the accuracy of the developed scheme using a dedicated lung phantom in airway wall estimation and compared it with the traditional full-width at half maximum (FWHM) method. The phantom study shows that the developed scheme has an error ranging from 0.04 mm to 0.36 mm, which is much smaller than the FWHM method with an error ranging from 0.16 mm to 0.84 mm. Second, we compared the results obtained by the developed scheme with those manually delineated by an experienced (>30 years) radiologist on clinical chest CT examinations, showing a mean difference of 0.084 mm. In particular, the sensitivity of the scheme to different reconstruction kernels was evaluated on real chest CT examinations. For the 'lung', 'bone' and 'standard' kernels, the average airway wall thicknesses computed by the developed scheme were 1.302 mm, 1.333 mm and 1.339 mm, respectively. Our preliminary experiments showed that the scheme had a reasonable accuracy in airway wall estimation. For a clinical chest CT examination, it took around 4 min for this scheme to identify the inner and outer airway walls on a modern PC.

Accuracy limits for the thickness measurement of the hip joint cartilage in 3-D MR images: simulation and validation

This paper describes a theoretical simulation method for ascertaining the inherent limits on the accuracy of thickness measurement of hip joint cartilage in 3-D MR images. This method can specify where and how thickness can be measured with sufficient accuracy under the certain MR imaging conditions. In the numerical simulation, we present a mathematical model for two adjacent sheet structures separated by a small distance, which simulated the femoral and acetabular cartilage and the joint space width in the hip joint; moreover, we perform the numerical simulation of MR imaging and postprocessing for thickness measurement. We especially focused on the effects of voxel anisotropy in MR imaging with variable orientation of cartilage surface and different joint space width. Also, thickness measurement is performed in MR imaging with isotropic voxel. The results from MR data with isotropic voxels show that accurate measurement of cartilage thickness at location of measured values of the hip joint space width and the cartilage thickness being two times as large as the voxel size or above should be possible. The simulation method is validated by comparison with the actual results obtained from the experiments using three phantoms, five normal cadaver hip specimens, and nine patients with osteoarthritis.

Recent findings in chronic obstructive pulmonary disease by using quantitative computed tomography

Chronic obstructive pulmonary disease (COPD) is characterized by an incompletely reversible airflow limitation that results from a combination of airway wall remodeling and emphysematous lung destruction. Forced expiratory volume in 1s (FEV(1)) has been considered the gold standard for diagnosis, classification, and follow-up in patients with COPD, but it has certain limitations and it is still necessary to find other noninvasive modalities to complement FEV(1) to evaluate the effect of therapeutic interventions and the pathogenesis of COPD. Quantitative computed tomography (CT) has partly met this demand. The extent of emphysema and airway dimensions measured using quantitative CT are associated with morphological and functional changes and clinical symptoms in patients with COPD. Phenotyping COPD based on quantitative CT has facilitated interventional and genotypic studies. Recent advances in COPD findings with quantitative CT are discussed in this review.

Airway imaging in disease: gimmick or useful tool?

Airway remodeling is an important pathophysiological mechanism in a variety of chronic airway diseases. Historically investigators have had to use invasive techniques such as histological examination of excised tissue to study airway wall structure. The last several years has seen a proliferation of relatively noninvasive techniques to assess the airway branching pattern, wall thickness, and more recently, airway wall tissue components. These methods include computed tomography, magnetic resonance imaging, and optical coherence tomography. These new imaging technologies have become popular because to understand the physiology of lung disease it is important we understand the underlying anatomy. However, these new approaches are not standardized or available in all centers so a review of their validity and clinical utility is appropriate. This review documents how investigators are working hard to correct for inconsistencies between techniques so that they become more accepted and utilized in clinical settings. These new imaging techniques are very likely to play a frontline role in the study of lung disease and will, hopefully, allow clinicians and investigators to better understand disease pathogenesis and to design and assess new therapeutic interventions.

CT based computerized identification and analysis of human airways: a review

As one of the most prevalent chronic disorders, airway disease is a major cause of morbidity and mortality worldwide. In order to understand its underlying mechanisms and to enable assessment of therapeutic efficacy of a variety of possible interventions, noninvasive investigation of the airways in a large number of subjects is of great research interest. Due to its high resolution in temporal and spatial domains, computed tomography (CT) has been widely used in clinical practices for studying the normal and abnormal manifestations of lung diseases, albeit there is a need to clearly demonstrate the benefits in light of the cost and radiation dose associated with CT examinations performed for the purpose of airway analysis. Whereas a single CT examination consists of a large number of images, manually identifying airway morphological characteristics and computing features to enable thorough investigations of airway and other lung diseases is very time-consuming and susceptible to errors. Hence, automated and semiautomated computerized analysis of human airways is becoming an important research area in medical imaging. A number of computerized techniques have been developed to date for the analysis of lung airways. In this review, we present a summary of the primary methods developed for computerized analysis of human airways, including airway segmentation, airway labeling, and airway morphometry, as well as a number of computer-aided clinical applications, such as virtual bronchoscopy. Both successes and underlying limitations of these approaches are discussed, while highlighting areas that may require additional work.

Computed tomographic imaging of the airways in COPD and asthma

Computed tomography (CT) is the modality of choice for imaging the airways. Volumetric data sets with isotropic spatial resolution based on multidetector thin-section CT with overlapping reconstruction should be used. Chronic obstructive pulmonary disease and asthma are the 2 most common disease entities that are defined by airflow obstruction. The morphologic correlates of airway changes are dilation of the lumen, thickening of the wall, visibility of small airways due to mucus or edema, air trapping, hypoxic vasoconstriction, and collapsibility. To assess air trapping, additional expiratory low-dose scans are recommended. In clinical routine, these findings are visually assessed and should be routinely reported. However, the interobserver variability is high, and there is a clear need for objective software-based measurements. The development of such tools is challenging, and they are just becoming available on a broader scale. Novel techniques based on dual-energy CT aim to measure iodine distribution maps to assess pulmonary perfusion as well as the distribution of inhaled xenon gas to assess the distribution and time course of pulmonary ventilation. However, these techniques are still being investigated in clinical studies. This review will provide an overview of CT for the diagnosis of chronic obstructive pulmonary disease and asthma, its role in phenotyping these diseases, and the measurement of disease severity and functional compromise.

Quantitative computed tomography in COPD: possibilities and limitations

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that is characterized by chronic airflow limitation. Unraveling of this heterogeneity is challenging but important, because it might enable more accurate diagnosis and treatment. Because spirometry cannot distinguish between the different contributing pathways of airflow limitation, and visual scoring is time-consuming and prone to observer variability, other techniques are sought to start this phenotyping process. Quantitative computed tomography (CT) is a promising technique, because current CT technology is able to quantify emphysema, air trapping, and large airway wall dimensions. This review focuses on CT quantification techniques of COPD disease components and their current status and role in phenotyping COPD.

Imaging of lung function using hyperpolarized helium-3 magnetic resonance imaging: Review of current and emerging translational methods and applications

During the past several years there has been extensive development and application of hyperpolarized helium-3 (HP (3)He) magnetic resonance imaging (MRI) in clinical respiratory indications such as asthma, chronic obstructive pulmonary disease, cystic fibrosis, radiation-induced lung injury, and transplantation. This review focuses on the state-of-the-art of HP (3)He MRI and its application to clinical pulmonary research. This is not an overview of the physics of the method, as this topic has been covered previously. We focus here on the potential of this imaging method and its challenges in demonstrating new types of information that has the potential to influence clinical research and decision making in pulmonary medicine. Particular attention is given to functional imaging approaches related to ventilation and diffusion-weighted imaging with applications in chronic obstructive pulmonary disease, cystic fibrosis, asthma, and radiation-induced lung injury. The strengths and challenges of the application of (3)He MRI in these indications are discussed along with a comparison to established and emerging imaging techniques.

Quantitative bronchial luminal volumetric assessment of pulmonary function loss by thin-section MDCT in pulmonary emphysema patients

OBJECTIVES

To determine the capability of quantitative bronchial luminal volume to assess pulmonary function loss and disease severity in pulmonary emphysema patients.

METHODS

Thirty-seven smokers (mean age, 68.1 years) underwent CT examinations and pulmonary function tests. For the quantitative assessment, luminal voxels of trachea and bronchi were computationally counted and the ratio of the following luminal voxels to all luminal voxels was obtained: (1) the lobe bronchi and the peripheral bronchi (Ratio(lobe)), and (2) the main bronchi and the peripheral bronchi (Ratio(main)). To determine the capability of these assessments to predict pulmonary function loss, these ratios were correlated with pulmonary function tests. To determine the capability for predicting disease severity, these ratios were compared between clinical groups.

RESULTS

These ratios were no significant correlated with vital capacity and forced vital capacity (FVC) (p > 0.05), however significantly correlated with forced expiratory volume in 1s (FEV1) (Ratio(lobe): r = 0.61, p < 0.0001, Ratio(main): r = 0.58, p < 0.0005) and FEV1/FVC (Ratio(lobe): r = 0.36, p < 0.05, Ratio(main): r = 0.33, p < 0.05). The Ratio(lobe) of smokers without COPD was significantly different from those of moderate COPD and severe or very severe COPD (p < 0.05), while that of mild COPD was significantly different from that of severe or very severe COPD (p < 0.01). The Ratio(main) of severe or very severe COPD patients was significantly different from those of other groups (p < 0.05).

CONCLUSIONS

Quantitative bronchial luminal volumes were reflected the airflow limitation parameters and was corresponded to clinical groups in emphysema patients.

Measuring small airways in transverse CT images correction for partial volume averaging and airway tilt

RATIONALE AND OBJECTIVES

Airway wall dimensions can be determined in vivo using transverse computed tomographic (CT) images, but the measurement of airway phantoms shows that the wall thickness is consistently overestimated for small airways. This phantom study was performed to derive and test corrections to the measurements on the basis of consideration of partial volume averaging and tilt effects.

MATERIALS AND METHODS

A lung phantom with six polycarbonate tubes embedded in foam was scanned, and the cross-sectional dimensions of the tubes were determined using the full width at half maximum, zero crossing, and phase congruency edge detection methods. Equations were derived using the reported wall intensity to correct for partial volume averaging. Corrections for the overestimation of the wall thickness due to the tilt of the tube with respect to the CT z-axis were also derived.

RESULTS

All three methods (full width at half maximum, zero crossing, and phase congruency) overestimated the wall thickness of the small polycarbonate tubes. It was verified that two sources of error were partial volume averaging and tilt that was introduced when the phantom was positioned with tube axes at an angle to the CT z-axis. The corrections were applied to the measured tube wall dimensions and substantially reduced the deviation of the CT measurements from the true values.

CONCLUSIONS

Correcting for partial volume effects and airway tilt greatly increases the accuracy of simulated airway wall measurements in transverse CT images.

A theoretical model of the application of RF energy to the airway wall and its experimental validation

Background

Bronchial thermoplasty is a novel technique designed to reduce an airway's ability to contract by reducing the amount of airway smooth muscle through controlled heating of the airway wall. This method has been examined in animal models and as a treatment for asthma in human subjects. At the present time, there has been little research published about how radiofrequency (RF) energy and heat is transferred to the airways of the lung during bronchial thermoplasty procedures. In this manuscript we describe a computational, theoretical model of the delivery of RF energy to the airway wall.

Methods

An electro-thermal finite-element-analysis model was designed to simulate the delivery of temperature controlled RF energy to airway walls of the in vivo lung. The model includes predictions of heat generation due to RF joule heating and transfer of heat within an airway wall due to thermal conduction. To implement the model, we use known physical characteristics and dimensions of the airway and lung tissues. The model predictions were tested with measurements of temperature, impedance, energy, and power in an experimental canine model.

Results

Model predictions of electrode temperature, voltage, and current, along with tissue impedance and delivered energy were compared to experiment measurements and were within ± 5% of experimental averages taken over 157 sample activations.

The experimental results show remarkable agreement with the model predictions, and thus validate the use of this model to predict the heat generation and transfer within the airway wall following bronchial thermoplasty.

Conclusions

The model also demonstrated the importance of evaporation as a loss term that affected both electrical measurements and heat distribution. The model predictions showed excellent agreement with the empirical results, and thus support using the model to develop the next generation of devices for bronchial thermoplasty. Our results suggest that comparing model results to RF generator electrical measurements may be a useful tool in the early evaluation of a model.

Quantitative analysis of high-resolution computed tomography scans in severe asthma subphenotypes

Background

Severe asthma is a heterogeneous condition. Airway remodelling is a feature of severe asthma and can be determined by the assessment of high-resolution computed tomography (HRCT) scans. The aim of this study was to assess whether airway remodelling is restricted to specific subphenotypes of severe asthma.

Methods

A retrospective analysis was performed of HRCT scans from subjects who had attended a single-centre severe asthma clinic between 2003 and 2008. The right upper lobe apical segmental bronchus (RB1) dimensions were measured and the clinical and sputum inflammatory characteristics associated with RB1 geometry were assessed by univariate and multivariate regression analyses. Longitudinal sputum data were available and were described as area under the time curve (AUC). Comparisons were made in RB1 geometry across subjects in four subphenotypes determined by cluster analysis, smokers and non-smokers, and subjects with and without persistent airflow obstruction.

Results

Ninety-nine subjects with severe asthma and 16 healthy controls were recruited. In the subjects with severe asthma the RB1 percentage wall area (%WA) was increased (p=0.009) and lumen area (LA)/body surface area (BSA) was decreased (p=0.008) compared with controls but was not different across the four subphenotypes. Airway geometry was not different between smokers and non-smokers and RB1 %WA was increased in those with persistent airflow obstruction. RB1 %WA in severe asthma was best associated with airflow limitation and persistent neutrophilic airway inflammation (model R²=0.27, p=0.001).

Conclusions

Airway remodelling of proximal airways occurs in severe asthma and is associated with impaired lung function and neutrophilic airway inflammation.

Quantitative assessment of bronchial wall attenuation with thin-section CT: An indicator of airflow limitation in chronic obstructive pulmonary disease

OBJECTIVE

The purpose of this study was to evaluate the relation between bronchial wall attenuation on thin-section CT images and airflow limitation in persons with chronic obstructive pulmonary disease.

SUBJECTS AND METHODS

One hundred fourteen subjects (65 men, 49 women; age range, 56-74 years) enrolled in the National Lung Screening Trial underwent chest CT and prebronchodilation spirometry at a single institution. At CT, mean peak wall attenuation, wall area percentage, and luminal area were measured in the third, fourth, and fifth generations of the right B(1) and B(10) segmental bronchi. Correlations with forced expiratory volume in the first second of expiration (FEV(1)) expressed as percentage of predicted value were evaluated with Spearman's rank correlation test.

RESULTS

The peak wall attenuation of each generation of segmental bronchi correlated significantly with FEV(1) as percentage of predicted value (B(1) third, r = -0.323, p = 0.0005; B(1) fourth, r = -0.406, p < 0.0001; B(1) fifth, r = -0.478, p < 0.0001; B(10) third, r = -0.268, p = 0.004; B(10) fourth, r = -0.476, p < 0.0001; B(10) fifth, r = -0.548, p < 0.0001). The correlation coefficients were higher in peripheral airway generations. Wall area percentage and luminal area had similar significant correlations. In multivariate analysis to predict FEV(1) as percentage of predicted value, the coefficient of determination of the model with the combination of percentage of low-attenuation area (< -950 HU) and peak wall attenuation of the fifth generation of the right B(10) was 0.484; the coefficient of determination with percentage of low-attenuation area and wall area percentage was 0.40.

CONCLUSION

Peak attenuation of the bronchial wall measured at CT correlates significantly with expiratory airflow obstruction in subjects with chronic obstructive pulmonary disease, particularly in the distal airways.

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.

Image analysis for cystic fibrosis: automatic lung airway wall and vessel measurement on CT images

Cystic Fibrosis (CF) is the most common lethal genetic disorder in the Caucasian population, affecting about 30,000 people in the United States. It results in inflammation, hence thickening of airway (AW) walls. It has been demonstrated that AW inflammation begins early in life producing structural AW damage. Because this damage can be present in patients who are relatively asymptomatic, lung disease can progress insidiously. High-resolution computed tomographic imaging has also shown that the AWs of infants and young children with CF have thicker walls and are more dilated than those of normal children. The purpose of this study was to develop computerized methods which allow rapid, efficient and accurate assessment of computed tomographic AW and vessel (V) dimensions from axial CT lung images. For this purpose, a full-width-half-max based automatic AW and V size measurement method was developed. The only user input required is approximate center marking of AW and V by an expert. The method was evaluated on a patient population of 4 infants and 4 children with different stages of mild CF related lung disease. This new automated method for assessing early AW disease in infants and children with CF represents a potentially useful outcome measure for future intervention trials.