Quantitative computed tomography of the lungs and airways in healthy nonsmoking adults

Pulmonary volumes and signs of chronic airflow limitation in quantitative computed tomography

BACKGROUND

Computed tomography (CT) offers pulmonary volumetric quantification but is not commonly used in healthy individuals due to radiation concerns. Chronic airflow limitation (CAL) is one of the diagnostic criteria for chronic obstructive pulmonary disease (COPD), where early diagnosis is important. Our aim was to present reference values for chest CT volumetric and radiodensity measurements and explore their potential in detecting early signs of CAL.

METHODS

From the population-based Swedish CArdioPulmonarybioImage Study (SCAPIS), 294 participants aged 50-64, were categorized into non-CAL (n = 258) and CAL (n = 36) groups based on spirometry. From inspiratory and expiratory CT images we compared lung volumes, mean lung density (MLD), percentage of low attenuation volume (LAV%) and LAV cluster volume between groups, and against reference values from static pulmonary function test (PFT).

RESULTS

The CAL group exhibited larger lung volumes, higher LAV%, increased LAV cluster volume and lower MLD compared to the non-CAL group. Lung volumes significantly deviated from PFT values. Expiratory measurements yielded more reliable results for identifying CAL compared to inspiratory. Using a cut-off value of 0.6 for expiratory LAV%, we achieved sensitivity, specificity and positive/negative predictive values of 72%, 85% and 40%/96%, respectively.

CONCLUSION

We present volumetric reference values from inspiratory and expiratory chest CT images for a middle-aged healthy cohort. These results are not directly comparable to those from PFTs. Measures of MLD and LAV can be valuable in the evaluation of suspected CAL. Further validation and refinement are necessary to demonstrate its potential as a decision support tool for early detection of COPD.

Computed tomography (CT) quantitative assessment of single lobe emphysema correlates with chronic obstructive pulmonary disease (COPD) severity: a cross-sectional study with retrospective data collection

Background

In the past, many researchers have studied the correlation between quantitative parameters of computed tomography (CT) and parameters of pulmonary function test (PFT) in patients with chronic obstructive pulmonary disease (COPD) with good results. Most of these studies have focused on the whole-lung level. In this study, we analyzed the biphasic CT lung volume parameters and the percentage of emphysema volume in different lobes of the lungs of patients with different grades of COPD and assessed their relationship with different lung function indices.

Methods

We retrospectively collected patients who underwent PFTs at The First Affiliated Hospital of Guangzhou Medical University from 1 July 2019 to 27 January 2020, and underwent chest respiratory dual-phase CT scans within 1 week, including 112 non-COPD patients and 297 COPD patients. We quantified the biphasic CT lung volume parameters and the percentage of emphysema volume in different lobes using a pulmonary image analysis tool. One-way analysis of variance (ANOVA) and Kruskal-Wallis H method were used to compare the quantitative CT parameters of each lung lobe in different groups. The correlation between quantitative CT parameters of different lung lobes and lung function indices was assessed using multiple linear regression.

Results

Among the 3 biphasic CT lung volume parameters, only volume change/inspiratory lung volume (∆LV/LVin) in the non-COPD control, mildly to moderately severe, and severe to extremely severe groups had statistical differences in each lobe level (all P<0.05). Correlation was significant between LVin and different lung function indices and between low attenuation areas percent below the threshold of -950 in the inspiratory phase [low attenuation area below -950 in the inspiratory phase (%LAA-950in)] and lung function indices in the left lower lobe (all P<0.05). There was statistically significant correlation between expiratory lung volume and ∆LV/LVin and lung function indices in the right lower lung (all P≤0.001). In the remaining lobes, LVin, expiratory lung volume, ∆LV/LVin, and %LAA-950in correlated with only some of the lung function indices.

Conclusions

The percentage of emphysema volume did not differ between lobes in the non-COPD control and severe to extremely severe COPD populations. LVin and %LAA-950in in the left upper lobe, expiratory lung volume and ∆LV/LVin in the right lower lobe were more reflective of the changes in lung function indices of the patients, whereas the correlation of the 3 biphasic CT lung volume parameters and the percentage of emphysema volume in the upper lobes of both lungs and the right middle lung with lung function indices was unclear.

Computed tomography mucus plugs and airway tree structure in patients with chronic obstructive pulmonary disease: Associations with airflow limitation, health-related independence and mortality

BACKGROUND AND OBJECTIVE

Mucus plugs and underlying airway tree structure can affect airflow limitation and prognosis in patients with chronic obstructive pulmonary disease (COPD), but their relative roles are unclear. This study used two COPD cohorts to examine whether mucus plugs on computed tomography (CT) were associated with airflow limitation and clinical outcomes independent of other airway structural changes and emphysema.

METHODS

Based on visual CT assessment, patients with mucus plugs in 0, 1-2 and ≥3 lung segments were assigned to no-, low- and high-mucus groups. Loss of health-related independence and mortality were prospectively recorded for 3 and 10 years in the Kyoto-Himeji and Hokkaido cohorts, respectively. The percentages of the wall area of the central airways (WA%), total airway count (TAC) and emphysema were quantified on CT.

RESULTS

Of 199 and 96 patients in the Kyoto-Himeji and Hokkaido cohorts, 34% and 30%, respectively, had high mucus scores. In both cohorts, TAC was lower in the high-mucus group than in the no-mucus group, whereas their emphysema severity did not differ. High mucus score and low TAC were independently associated with airflow limitation after adjustment for WA% and emphysema. In multivariable models adjusted for WA% and emphysema, TAC, rather than mucus score, was associated with a greater rate of loss of independence, whereas high mucus score, rather than TAC, was associated with increased mortality.

CONCLUSION

Mucus plugs and lower airway branch count on CT had distinct roles in airflow limitation, health-related independence and mortality in patients with COPD.

Race-Specific Spirometry Equations Do Not Improve Models of Dyspnea and Quantitative Chest CT Phenotypes

BACKGROUND

Race-specific spirometry reference equations are used globally to interpret lung function for clinical, research, and occupational purposes, but inclusion of race is under scrutiny.

RESEARCH QUESTION

Does including self-identified race in spirometry reference equation formation improve the ability of predicted FEV1 values to explain quantitative chest CT abnormalities, dyspnea, or Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification?

STUDY DESIGN AND METHODS

Using data from healthy adults who have never smoked in both the National Health and Nutrition Survey (2007-2012) and COPDGene study cohorts, race-neutral, race-free, and race-specific prediction equations were generated for FEV1. Using sensitivity/specificity, multivariable logistic regression, and random forest models, these equations were applied in a cross-sectional analysis to populations of individuals who currently smoke and individuals who formerly smoked to determine how they affected GOLD classification and the fit of models predicting quantitative chest CT phenotypes or dyspnea.

RESULTS

Race-specific equations showed no advantage relative to race-neutral or race-free equations in models of quantitative chest CT phenotypes or dyspnea. Race-neutral reference equations reclassified up to 19% of Black participants into more severe GOLD classes, while race-neutral/race-free equations may improve model fit for dyspnea symptoms relative to race-specific equations.

INTERPRETATION

Race-specific equations offered no advantage over race-neutral/race-free equations in three distinct explanatory models of dyspnea and chest CT scan abnormalities. Race-neutral/race-free reference equations may improve pulmonary disease diagnoses and treatment in populations highly vulnerable to lung disease.

Heterogeneity and Progression of Chronic Obstructive Pulmonary Disease: Emphysema-Predominant and Non-Emphysema-Predominant Disease

While variation in emphysema severity between patients with chronic obstructive pulmonary disease (COPD) is well-recognized, clinically applicable definitions of the emphysema-predominant disease (EPD) and non-emphysema-predominant disease (NEPD) subtypes have not been established. To study the clinical relevance of the EPD and NEPD subtypes, we tested the association of these subtypes with prospective decline in forced expiratory volume in 1 second (FEV1) and mortality among 3,427 subjects with Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometric grade 2-4 COPD at baseline in the Genetic Epidemiology of COPD (COPDGene) Study, an ongoing national multicenter study that started in 2007. NEPD was defined as airflow obstruction with less than 5% computed tomography (CT) quantitative densitometric emphysema at -950 Hounsfield units, and EPD was defined as airflow obstruction with 10% or greater CT emphysema. Mixed-effects models for FEV1 demonstrated larger average annual FEV1 loss in EPD subjects than in NEPD subjects (-10.2 mL/year; P < 0.001), and subtype-specific associations with FEV1 decline were identified. Cox proportional hazards models showed higher risk of mortality among EPD patients versus NEPD patients (hazard ratio = 1.46, 95% confidence interval: 1.34, 1.60; P < 0.001). To determine whether the NEPD/EPD dichotomy is captured by previously described COPDGene subtypes, we used logistic regression and receiver operating characteristic (ROC) curve analysis to predict NEPD/EPD membership using these previous subtype definitions. The analysis generally showed excellent discrimination, with areas under the ROC curve greater than 0.9. The NEPD and EPD COPD subtypes capture important aspects of COPD heterogeneity and are associated with different rates of disease progression and mortality.

Quantitative Analysis for Lung Disease on Thin-Section CT

Thin-section computed tomography (CT) is widely employed not only for assessing morphology but also for evaluating respiratory function. Three-dimensional images obtained from thin-section CT provide precise measurements of lung, airway, and vessel volumes. These volumetric indices are correlated with traditional pulmonary function tests (PFT). CT also generates lung histograms. The volume ratio of areas with low and high attenuation correlates with PFT results. These quantitative image analyses have been utilized to investigate the early stages and disease progression of diffuse lung diseases, leading to the development of novel concepts such as pre-chronic obstructive pulmonary disease (pre-COPD) and interstitial lung abnormalities. Quantitative analysis proved particularly valuable during the COVID-19 pandemic when clinical evaluations were limited. In this review, we introduce CT analysis methods and explore their clinical applications in the context of various lung diseases. We also highlight technological advances, including images with matrices of 1024 × 1024 and slice thicknesses of 0.25 mm, which enhance the accuracy of these analyses.

Association of age with computed tomography airway tree morphology in male and female never smokers without lung disease history

BACKGROUND

Sex and aging may affect the airway tree structure in patients with airway diseases and even healthy subjects. Using chest computed tomography (CT), this study sought to determine whether age is associated with airway morphological features differently in healthy males and females.

METHODS

This retrospective cross-sectional study consecutively incorporated lung cancer screening CT data of asymptomatic never smokers (n = 431) without lung disease history. Luminal areas were measured at the trachea, main bronchi, bronchus intermedius, segmental and subsegmental bronchus, and the ratio of their geometric mean to total lung volume (airway-to-lung size ratio, ALR) was determined. Airway fractal dimension (AFD) and total airway count (TAC) were calculated for the segmented airway tree resolved on CT.

RESULTS

The lumen areas of the trachea, main bronchi, segmental and subsegmental airways, AFD and TAC visible on CT were smaller in females (n = 220) than in males (n = 211) after adjusting for age, height, and body mass index, while ALR or count of the 1st to 5th generation airways did not differ. Furthermore, in males but not in females, older age was associated with larger lumen sizes of the main bronchi, segmental and subsegmental airways, and ALR. In contrast, neither male nor female had any associations between age and AFD or TAC on CT.

CONCLUSION

Older age was associated with larger lumen size of the relatively central airways and ALR exclusively in males. Aging may have a more profound effect on airway lumen tree caliber in males than in females.

Undersampled Diffusion-Weighted 129Xe MRI Morphometry of Airspace Enlargement: Feasibility in Chronic Obstructive Pulmonary Disease

Multi-b diffusion-weighted hyperpolarized gas MRI measures pulmonary airspace enlargement using apparent diffusion coefficients (ADC) and mean linear intercepts (L_m). Rapid single-breath acquisitions may facilitate clinical translation, and, hence, we aimed to develop single-breath three-dimensional multi-b diffusion-weighted ¹²⁹Xe MRI using k-space undersampling. We evaluated multi-b (0, 12, 20, 30 s/cm²) diffusion-weighted ¹²⁹Xe ADC/morphometry estimates using a fully sampled and retrospectively undersampled k-space with two acceleration-factors (AF = 2 and 3) in never-smokers and ex-smokers with chronic obstructive pulmonary disease (COPD) or alpha-one anti-trypsin deficiency (AATD). For the three sampling cases, mean ADC/L_m values were not significantly different (all p > 0.5); ADC/L_m values were significantly different for the COPD subgroup (0.08 cm²s^-1/580 µm, AF = 3; all p < 0.001) as compared to never-smokers (0.05 cm²s^-1/300 µm, AF = 3). For never-smokers, mean differences of 7%/7% and 10%/7% were observed between fully sampled and retrospectively undersampled (AF = 2/AF = 3) ADC and L_m values, respectively. For the COPD subgroup, mean differences of 3%/4% and 11%/10% were observed between fully sampled and retrospectively undersampled (AF = 2/AF = 3) ADC and L_m, respectively. There was no relationship between acceleration factor with ADC or L_m (p = 0.9); voxel-wise ADC/L_m measured using AF = 2 and AF = 3 were significantly and strongly related to fully-sampled values (all p < 0.0001). Multi-b diffusion-weighted ¹²⁹Xe MRI is feasible using two different acceleration methods to measure pulmonary airspace enlargement using L_m and ADC in COPD participants and never-smokers.

Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report

Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.

Sex Differences in Airways at Chest CT: Results from the COPDGene Cohort

Background The prevalence of chronic obstructive pulmonary disease (COPD) in women is fast approaching that in men, and women experience greater symptom burden. Although sex differences in emphysema have been reported, differences in airways have not been systematically characterized. Purpose To evaluate whether structural differences in airways may underlie some of the sex differences in COPD prevalence and clinical outcomes. Materials and Methods In a secondary analyses of a multicenter study of never-, current-, and former-smokers enrolled from January 2008 to June 2011 and followed up longitudinally until November 2020, airway disease on CT images was quantified using seven metrics: airway wall thickness, wall area percent, and square root of the wall thickness of a hypothetical airway with internal perimeter of 10 mm (referred to as Pi10) for airway wall; and lumen diameter, airway volume, total airway count, and airway fractal dimension for airway lumen. Least-squares mean values for each airway metric were calculated and adjusted for age, height, ethnicity, body mass index, pack-years of smoking, current smoking status, total lung capacity, display field of view, and scanner type. In ever-smokers, associations were tested between each airway metric and postbronchodilator forced expiratory volume in 1 second (FEV1)-to-forced vital capacity (FVC) ratio, modified Medical Research Council dyspnea scale, St George's Respiratory Questionnaire score, and 6-minute walk distance. Multivariable Cox proportional hazards models were created to evaluate the sex-specific association between each airway metric and mortality. Results In never-smokers (n = 420), men had thicker airway walls than women as quantified on CT images for segmental airway wall area percentage (least-squares mean, 47.68 ± 0.61 [standard error] vs 45.78 ± 0.55; difference, -1.90; P = .02), whereas airway lumen dimensions were lower in women than men after accounting for height and total lung capacity (segmental lumen diameter, 8.05 mm ± 0.14 vs 9.05 mm ± 0.16; difference, -1.00 mm; P < .001). In ever-smokers (n = 9363), men had greater segmental airway wall area percentage (least-squares mean, 52.19 ± 0.16 vs 48.89 ± 0.18; difference, -3.30; P < .001), whereas women had narrower segmental lumen diameter (7.80 mm ± 0.05 vs 8.69 mm ± 0.04; difference, -0.89; P < .001). A unit change in each of the airway metrics (higher wall or lower lumen measure) resulted in lower FEV1-to-FVC ratio, more dyspnea, poorer respiratory quality of life, lower 6-minute walk distance, and worse survival in women compared with men (all P < .01). Conclusion Airway lumen sizes quantified at chest CT were smaller in women than in men after accounting for height and lung size, and these lower baseline values in women conferred lower reserves against respiratory morbidity and mortality for equivalent changes compared with men. © RSNA, 2022 Online supplemental material is available for this article.

Luminal mucus plugs are spatially associated with airway wall thickening in severe COPD and asthma: A single-centered, retrospective, observational study

BACKGROUND

Airway wall thickening and excess airway mucus occur in asthma and chronic obstructive pulmonary disease (COPD), but few studies have investigated the relationship between them. Our objective was to determine the association between computed tomography (CT) airway wall thickening in segmental airways proximal to airways with or without mucus plugging in patients with asthma and COPD.

METHODS

Mucus plugging was scored using a CT bronchopulmonary segment-based scoring system in asthma and COPD patients. For each of the 19 segmental airways, a mucus plug was defined as complete occlusion of one or more of the daughter branches (sub-segmental airways) by mucus. CT airway measurements were generated for each of the 19 segmental airways: wall-area-percentage (WA%), lumen area (LA), and total airway count (TAC) (VIDA Diagnostics Inc.). Multivariable logistic regression models were constructed for the presence of mucus plugs with corresponding CT measurement and adjusted by covariates; each of the 19 segments was treated as a nested variable.

RESULTS

A total of 33 participants were evaluated. Participants had a mean age of 60 ± 15yrs and there were n = 14 (42%) males. There were 16 (48%) participants with a diagnosis of asthma and 17 (52%) with a COPD diagnosis. The mean FEV₁ was 53 ± 21%pred and FEV₁/FVC was 54 ± 15%. The mean mucus score in all participants was 15 ± 4 (min = 0, max = 19). Multivariable logistic regression analysis showed the presence of airway mucus was significantly associated with increased CT WA% (β = 7.30, p = 0.004) and reduced TAC (β = -0.06, p = 0.045).

CONCLUSIONS

There was increased airway wall thickness and reduced airway counts on CT in segments where there was a distal mucus plug compared to segments without mucus plugs in asthma and COPD.

COVID-19 CT Scan Lung Segmentation: How We Do It

The National Health Systems have been severely stressed out by the COVID-19 pandemic because 14% of patients require hospitalization and oxygen support, and 5% require admission to an Intensive Care Unit (ICU). Relationship between COVID-19 prognosis and the extent of alterations on chest CT obtained by both visual and software-based quantification that expresses objective evaluations of the percentage of ventilated lung parenchyma compared to the affected one has been proven. While commercial applications for automatic medical image computing and visualization are expensive and limited in their spread, the open-source systems are characterized by not enough standardization and time-consuming troubles. We analyzed chest CT exams on 246 patients suspected of COVID-19 performed in the Emergency Department CT room. The lung parenchyma segmentation was obtained by a threshold-based method using the open-source 3D Slicer software and software tools called "Segment Editor" and "Segment Quantification." For the three main characteristics analyzed on lungs affected by COVID-19 pneumonia, a specifical densitometry value range was defined: from - 950 to - 700 HU for well-aerated parenchyma; from - 700 to - 250 HU for interstitial lung disease; from - 250 to 250 HU for parenchymal consolidation. For the well-aerated parenchyma and the interstitial alterations, the procedure was semi-automatic with low time consumption, whereas consolidations' analysis needed manual interventions by the operator. After the chest CT, 13% of the sample was admitted to intensive care, while 34% of them to the sub-intensive care. In patients moved to intensive care, the parenchyma analysis reported a higher crazy paving presentation. The quantitative analysis of the alterations affecting the lung parenchyma of patients with COVID-19 pneumonia can be performed by threshold method segmentation on 3D Slicer. The segmentation could have an important role in the quantification in different COVID-19 pneumonia presentations, allowing to help the clinician in the correct management of patients.

Radiopaque Recreations of Lung Pathologies From Clinical Computed Tomography Images Using Potassium Iodide Inkjet 3-dimensional Printing: Proof of Concept

PURPOSE

The purpose of this study was to develop a 3-dimensional (3D) printing method to create computed tomography (CT) realistic phantoms of lung cancer nodules and lung parenchymal disease from clinical CT images.

MATERIALS AND METHODS

Low-density paper was used as substrate material for inkjet printing with potassium iodide solution to reproduce phantoms that mimic the CT attenuation of lung parenchyma. The relationship between grayscale values and the corresponding CT numbers of prints was first established through the derivation of exponential fitted equation from scanning data. Next, chest CTs from patients with early-stage lung cancer and coronavirus disease 2019 (COVID-19) pneumonia were chosen for 3D printing. CT images of original lung nodule and the 3D-printed nodule phantom were compared based on pixel-to-pixel correlation and radiomic features.

RESULTS

CT images of part-solid lung cancer and 3D-printed nodule phantom showed both high visual similarity and quantitative correlation. R2 values from linear regressions of pixel-to-pixel correlations between 5 sets of patient and 3D-printed image pairs were 0.92, 0.94, 0.86, 0.85, and 0.83, respectively. Comparison of radiomic measures between clinical CT and printed models demonstrated 6.1% median difference, with 25th and 75th percentile range at 2.4% and 15.2% absolute difference, respectively. The densities and parenchymal morphologies from COVID-19 pneumonia CT images were well reproduced in the 3D-printed phantom scans.

CONCLUSION

The 3D printing method presented in this work facilitates creation of CT-realistic reproductions of lung cancer and parenchymal disease from individual patient scans with microbiological and pathology confirmation.

Computed tomography on lung cancer screening is useful for adjuvant comorbidity diagnosis in developing countries

Purpose

The aim of this study was to analyse and quantify the prevalence of six comorbidities from lung cancer screening (LCS) on computed tomography (CT) scans of patients from developing countries.

Methods

For this retrospective study, low-dose CT scans (n=775) were examined from patients who underwent LCS in a tertiary hospital between 2016 and 2020. An age- and sex-matched control group was obtained for comparison (n=370). Using the software, coronary artery calcification (CAC), the skeletal muscle area, interstitial lung abnormalities, emphysema, osteoporosis and hepatic steatosis were accessed. Clinical characteristics of each participant were identified. A t-test and Chi-squared test were used to examine differences between these values. Interclass correlation coefficients (ICCs) and interobserver agreement (assessed by calculating kappa coefficients) were calculated to assess the correlation of measures interpreted by two observers. p-values <0.05 were considered significant.

Results

One or more comorbidities were identified in 86.6% of the patients and in 40% of the controls. The most prevalent comorbidity was osteoporosis, present in 44.2% of patients and in 24.8% of controls. New diagnoses of cardiovascular disease, emphysema and osteoporosis were made in 25%, 7% and 46% of cases, respectively. The kappa coefficient for CAC was 0.906 (p<0.001). ICCs for measures of liver, spleen and bone density were 0.88, 0.93 and 0.96, respectively (p<0.001).

Conclusions

CT data acquired during LCS led to the identification of previously undiagnosed comorbidities. The LCS is useful to facilitate comorbidity diagnosis in developing countries, providing opportunities for its prevention and treatment.

Lung cancer screening is useful to facilitate comorbidity diagnosis in developing countries, providing opportunities for its prevention and treatmenthttps://bit.ly/3KEdGuW

Impact of pixel value truncation on image quality of low dose chest CT

PURPOSE

In some noisy low-dose CT lung cancer screening images, we noticed that the CT density values of air were increased and the visibility of emphysema was distinctly decreased. By examining histograms of these images, we found that the CT density values were truncated at -1,024 HU. The purpose of this study was to investigate the effect of pixel value truncation on the visibility of emphysema using mathematical models.

METHODS AND MATERIALS

Assuming CT noise follows a normal distribution, we derived the relationship between the mean CT density value and the standard deviation (SD) when the pixel values below -1,024 HU are truncated and replaced by -1,024 HU. To validate our mathematical model, 20 untruncated phantom CT images were truncated by simulation, and the mean CT density values and SD of air in the images were measured and compared with the theoretical values. In addition, the mean CT density values and SD of air were measured in 100 cases of real clinical images obtained by GE, Siemens, and Philips scanners, respectively, and the agreement with the theoretical values was examined. Next, the contrast-to-noise ratio (CNR) between air (-1,000 HU) and lung parenchyma (-850 HU) was derived from the mathematical model in the presence and absence of truncation as a measure of the visibility of emphysema. In addition, the radiation dose ratios required to obtain the same CNR in the case with and without truncation were also calculated.

RESULTS

The mathematical model revealed that when the pixel values are truncated, the mean CT density values are proportional to the noise magnitude when the magnitude exceeds a certain level. The mean CT density values and SD measured in the images with pixel values truncated by simulation and in the real clinical images acquired by GE and Philips scanners agreed well with the theoretical values from our mathematical model. In the Siemens images, the measured and theoretical values agreed well when a portion of the truncated values were replaced by random values instead of simply replacing by -1,024 HU. The CNR of air and lung parenchyma was lowered by truncating CT density values compared to that of no truncation. Furthermore, it was found that higher radiation dose was required to obtain the same CNR with truncation as without. As an example, when the noise SD was 60 HU, the radiation dose required for the GE and Philips truncation method was about 1.2 times higher than that without truncation, and that for the Siemens truncation method was about 1.4 times higher.

CONCLUSIONS

It was demonstrated mathematically that pixel value truncation causes a brightening of the mean CT density value and decreases the CNR of emphysema. Our results indicate that it is advisable to turn off truncation at -1,024 HU, especially when scanning at low and ultra-low radiation doses in the thorax. This article is protected by copyright. All rights reserved.

Cluster activation mapping with application to computed tomography scans of the lung

Purpose: An open question in deep clustering is how to explain what in the image is driving the cluster assignments. This is especially important for applications in medical imaging when the derived cluster assignments may inform decision-making or create new disease subtypes. We develop cluster activation mapping (CLAM), which is methodology to create localization maps highlighting the image regions important for cluster assignment. Approach: Our approach uses a linear combination of the activation channels from the last layer of the encoder within a pretrained autoencoder. The activation channels are weighted by a channelwise confidence measure, which is a modification of score-CAM. Results: Our approach performs well under medical imaging-based simulation experiments, when the image clusters differ based on size, location, and intensity of abnormalities. Under simulation, the cluster assignments were predicted with 100% accuracy when the number of clusters was set at the true value. In addition, applied to computed tomography scans from a sarcoidosis population, CLAM identified two subtypes of sarcoidosis based purely on CT scan presentation, which were significantly associated with pulmonary function tests and visual assessment scores, such as ground-glass, fibrosis, and honeycombing. Conclusions: CLAM is a transparent methodology for identifying explainable groupings of medical imaging data. As deep learning networks are often criticized and not trusted due to their lack of interpretability, our contribution of CLAM to deep clustering architectures is critical to our understanding of cluster assignments, which can ultimately lead to new subtypes of diseases.

Differentiating COPD and Asthma using Quantitative CT Imaging and Machine Learning

There are similarities and differences between chronic obstructive pulmonary disease (COPD) and asthma patients in terms of computed tomography (CT) disease-related features. Our objective was to determine the optimal subset of CT imaging features for differentiating COPD and asthma using machine learning.COPD and asthma patients were recruited from Heidelberg University Hospital. CT was acquired and 93 features were extracted (VIDA Diagnostics): percentage of low-attenuating-areas below -950HU (LAA₉₅₀), LAA₉₅₀ hole count, estimated airway-wall-thickness for a 10 mm internal perimeter airway (Pi10), total-airway-count (TAC), as well as inner/outer perimeter/areas and wall thickness for each of five segmental airways, and the average of those five airways. Hybrid feature selection was used to select the optimum number of features, and support vector machine was used to classify COPD and asthma.Ninety-five participants were included (n=48 COPD; n=47 asthma); there were no differences between COPD and asthma for age (p=0.25) or FEV₁ (p=0.31). In a model including all CT features, the accuracy and F1-score was 80% and 81%, respectively. The top features were: LAA_950, LAA₉₅₀ hole count, average outer and inner airway perimeter, outer and inner airway area RB1, and TAC. In the model with only airway features, the accuracy and F1-score were 66% and 68%, respectively. The top features were: inner area RB1, wall thickness RB1, outer area LB1, TAC LB10, average outer/inner perimeter, Pi10, and TAC.In conclusions, COPD and asthma can be differentiated using machine learning with moderate-high accuracy by a subset of only 7 CT features.

Bronchial wall parameters on CT in healthy never-smoking, smoking, COPD, and asthma populations: a systematic review and meta-analysis

Objective

Research on computed tomography (CT) bronchial parameter measurements shows that there are conflicting results on the values for bronchial parameters in the never-smoking, smoking, asthma, and chronic obstructive pulmonary disease (COPD) populations. This review assesses the current CT methods for obtaining bronchial wall parameters and their comparison between populations.

Methods

A systematic review of MEDLINE and Embase was conducted following PRISMA guidelines (last search date 25th October 2021). Methodology data was collected and summarised. Values of percentage wall area (WA%), wall thickness (WT), summary airway measure (Pi10), and luminal area (Ai) were pooled and compared between populations.

Results

A total of 169 articles were included for methodologic review; 66 of these were included for meta-analysis. Most measurements were obtained from multiplanar reconstructions of segmented airways (93 of 169 articles), using various tools and algorithms; third generation airways in the upper and lower lobes were most frequently studied. COPD (12,746) and smoking (15,092) populations were largest across studies and mostly consisted of men (median 64.4%, IQR 61.5 – 66.1%). There were significant differences between populations; the largest WA% was found in COPD (mean SD 62.93 ± 7.41%, n = 6,045), and the asthma population had the largest Pi10 (4.03 ± 0.27 mm, n = 442). Ai normalised to body surface area (Ai/BSA) (12.46 ± 4 mm², n = 134) was largest in the never-smoking population.

Conclusions

Studies on CT-derived bronchial parameter measurements are heterogenous in methodology and population, resulting in challenges to compare outcomes between studies. Significant differences between populations exist for several parameters, most notably in the wall area percentage; however, there is a large overlap in their ranges.

Key Points

• Diverse methodology in measuring airways contributes to overlap in ranges of bronchial parameters among the never-smoking, smoking, COPD, and asthma populations.

• The combined number of never-smoking participants in studies is low, limiting insight into this population and the impact of participant characteristics on bronchial parameters.

• Wall area percent of the right upper lobe apical segment is the most studied (87 articles) and differentiates all except smoking vs asthma populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-08600-1.

Pixel-based analysis of pulmonary changes on CT lung images due to COVID-19 pneumonia

Objectives: Computed tomography (CT) plays a complementary role in the diagnosis of the pneumonia-burden of COVID-19 disease. However, the low contrast of areas of inflammation on CT images, areas of infection are difficult to identify. The purpose of this study is to develop a post-image-processing method for quantitative analysis of COVID-19 pneumonia-related changes in CT attenuation values using a pixel-based analysis rather than more commonly used clustered focal pneumonia volumes. The COVID-19 pneumonia burden is determined by experienced radiologists in the clinic. Previous AI software was developed for the measurement of COVID-19 lesions based on the extraction of local pneumonia features. In this respect, changes in the pixel levels beyond the clusters may be overlooked by deep learning algorithms. The proposed technique focuses on the quantitative measurement of COVID-19 related pneumonia over the entire lung in pixel-by-pixel fashion rather than only clustered focal pneumonia volumes.

Material and Methods: Fifty COVID-19 and 50 age-matched negative control patients were analyzed using the proposed technique and commercially available artificial intelligence (AI) software. The %pneumonia was calculated using the relative volume of parenchymal pixels within an empirically defined CT density range, excluding pulmonary airways, vessels, and fissures. One-way ANOVA analysis was used to investigate the statistical difference between lobar and whole lung %pneumonia in the negative control and COVID-19 cohorts.

Results: The threshold of high-and-low CT attenuation values related to pneumonia caused by COVID-19 were found to be between ₋642.4 HU and 143 HU. The %pneumonia of the whole lung, left upper, and lower lobes were 8.1 ± 4.4%, 6.1 ± 4.5, and 11.3 ± 7.3% for the COVID-19 cohort, respectively, and statistically different (P < 0.01). Additionally, the pixel-based methods correlate well with existing AI methods and are approximately four times more sensitive to pneumonia particularly at the upper lobes compared with commercial software in COVID-19 patients (P < 0.01).

Conclusion: Pixel-by-pixel analysis can accurately assess pneumonia in COVID-19 patients with CT. Pixel-based techniques produce more sensitive results than AI techniques. Using the proposed novel technique, %pneumonia could be quantitatively calculated not only in the clusters but also in the whole lung with an improved sensitivity by a factor of four compared to AI-based analysis. More significantly, pixel-by-pixel analysis was more sensitive to the upper lobe pneumonia, while AI-based analysis overlooked the upper lung pneumonia region. In the future, this technique can be used to investigate the efficiency of vaccines and drugs and post COVID-19 effects.

Deriving Regionally Specific Biomarkers of Emphysema and Small Airways Disease Using Variable Threshold Parametric Response Mapping on Volumetric Lung CT Images

PURPOSE

This study aims to develop and validate a parametric response mapping (PRM) methodology to accurately identify diseased regions of the lung by using variable thresholds to account for alterations in regional lung function between the gravitationally-independent (anterior) and gravitationally-dependent (posterior) lung in CT images acquired in the supine position.

METHODS

34 male Sprague-Dawley rats (260-540 g) were imaged, 4 of which received elastase injection (100 units/kg) as a model for emphysema (EMPH). Gated volumetric CT was performed at end-inspiration (EI) and end-expiration (EE) on separate groups of free-breathing (n = 20) and ventilated (n = 10) rats in the supine position. To derive variable thresholds for the new PRM methodology, voxels were first grouped into 100 bins based on the fractional distance along the anterior-to-posterior direction. Lower limits of normal (LLN) for x-ray attenuation in each bin were set by determining the smallest region that enclosed 98% of voxels from healthy, ventilated animals.

RESULTS

When utilizing fixed thresholds in the conventional PRM methodology, a distinct posterior-anterior gradient was seen, in which nearly the entire posterior region of the lung was identified as HEALTHY, while the anterior lung was labeled as significantly less so (t(29) = -3.27, p = 0.003). In both cohorts, %SAD progressively increased from posterior to anterior, while %HEALTHY lung decreased in the same direction. After applying our PRM methodology with variable thresholds to the same rat images, the posterior-anterior trend in %SAD quantification was removed from all rats and the significant increase of diseased lung in the anterior was removed.

CONCLUSIONS

The PRM methodology using variable thresholds provides regionally specific markers of %SAD and %EMPH by correcting for alterations in regional lung function associated with the naturally occurring vertical gradient of dependent vs. non-dependent lung density and compliance.

Computed tomography total airway count predicts progression to COPD in at-risk smokers

There is limited understanding of how to identify people at high risk of developing COPD. Our objective was to investigate the association between computed tomography (CT) total airway count (TAC) and incident COPD over 3 years among ever-smokers from the population-based Canadian Cohort Obstructive Lung Disease (CanCOLD) study.

CT and spirometry were acquired in ever-smokers at baseline; spirometry was repeated at 3-year follow-up. CT TAC was generated by summing all airway segments in the segmented airway tree (VIDA Diagnostics, Inc.). CT airway wall area, wall thickness for a theoretical airway with 10 mm perimeter (Pi10), and low attenuation areas below −856 HU (LAA₈₅₆) were also measured. Logistic and mixed effects regression models were constructed to determine the association for CT measurements with development of COPD and forced expiratory volume in 1 s/forced vital capacity (FEV₁/FVC) decline, respectively.

Among 316 at-risk participants evaluated at baseline (65±9 years, 40% female, 18±19 pack-years), incident COPD was detected in 56 participants (18%) over a median 3.1±0.6 years of follow-up. Among CT measurements, only TAC was associated with incident COPD (p=0.03), where a 1-sd decrement in TAC increased the odds ratio for incident COPD by a factor of two. In a multivariable linear regression model, reduced TAC was significantly associated with greater longitudinal FEV₁/FVC decline (p=0.03), but no other measurements were significant.

CT TAC predicts incident COPD in at-risk smokers, indicating that smokers exhibit early structural changes associated with COPD prior to abnormal spirometry.

Computed tomography (CT) total airway count (TAC) predicts incident COPD in at-risk smokers, indicating that smokers exhibit early airway remodelling prior to abnormal spirometry and that CT TAC is a potential tool to help identify smokers at increased risk of COPDhttps://bit.ly/2UTw3I4

Total Lung and Lobar Quantitative Assessment Based on Paired Inspiratory-Expiratory Chest CT in Healthy Adults: Correlation with Pulmonary Ventilatory Function

Objective: To provide the quantitative volumetric data of the total lung and lobes in inspiration and expiration from healthy adults, and to explore the value of paired inspiratory–expiratory chest CT scan in pulmonary ventilatory function and further explore the influence of each lobe on ventilation. Methods: A total of 65 adults (29 males and 36 females) with normal clinical pulmonary function test (PFT) and paired inspiratory–expiratory chest CT scan were retrospectively enrolled. The inspiratory and expiratory volumetric indexes of the total lung (TL) and 5 lobes (left upper lobe [LUL], left lower lobe [LLL], right upper lobe [RUL], right middle lobe [RML], and right lower lobe [RLL]) were obtained by Philips IntelliSpace Portal image postprocessing workstation, including inspiratory lung volume (LV_in), expiratory lung volume (LV_ex), volume change (∆LV), and well-aerated lung volume (WAL, lung tissue with CT threshold between −950 and −750 HU in inspiratory scan). Spearman correlation analysis was used to explore the correlation between CT quantitative indexes of the total lung and ventilatory function indexes (including total lung capacity [TLC], residual volume [RV], and force vital capacity [FVC]). Multiple stepwise regression analysis was used to explore the influence of each lobe on ventilation. Results: At end-inspiratory phase, the LV_in-TL was 4664.6 (4282.7, 5916.2) mL, the WAL_TL was 4173 (3639.6, 5250.9) mL; both showed excellent correlation with TLC (LV_in-TL: r = 0.890, p < 0.001; WAL_TL: r = 0.879, p < 0.001). From multiple linear regression analysis with lobar CT indexes as variables, the LV_in and WAL of these two lobes, LLL and RUL, showed a significant relationship with TLC. At end-expiratory phase, the LV_ex-TL was 2325.2 (1969.7, 2722.5) mL with good correlation with RV (r = 0.811, p < 0.001), of which the LV_ex of RUL and RML had a significant relationship with RV. For the volumetric change within breathing, the ∆LV_TL was 2485.6 (2169.8, 3078.1) mL with good correlation with FVC (r = 0.719, p < 0.001), moreover, WAL_TL showed a better correlation with FVC (r = 0.817, p < 0.001) than that of ∆LV_TL. Likewise, there was also a strong association between ∆LV, WAL of these two lobes (LLL and RUL), and FVC. Conclusions: The quantitative indexes derived from paired inspiratory–expiratory chest CT could reflect the clinical pulmonary ventilatory function, LLL, and RUL give greater impact on ventilation. Thus, the pulmonary functional evaluation needs to be more precise and not limited to the total lung level.

Ultra-short echo-time magnetic resonance imaging lung segmentation with under-Annotations and domain shift

Ultra-short echo-time (UTE) magnetic resonance imaging (MRI) provides enhanced visualization of pulmonary structural and functional abnormalities and has shown promise in phenotyping lung disease. Here, we describe the development and evaluation of a lung segmentation approach to facilitate UTE MRI methods for patient-based imaging. The proposed approach employs a k-means algorithm in kernel space for pair-wise feature clustering and imposes image domain continuous regularization, coined as continuous kernel k-means (CKKM). The high-order CKKM algorithm was simplified through upper bound relaxation and solved within an iterative continuous max-flow framework. We combined the CKKM with U-net and atlas-based approaches and comprehensively evaluated the performance on 100 images from 25 patients with asthma and bronchial pulmonary dysplasia enrolled at Robarts Research Institute (Western University, London, Canada) and Centre Hospitalier Universitaire (Sainte-Justine, Montreal, Canada). For U-net, we trained the network five times on a mixture of five different images with under-annotations and applied the model to 64 images from the two centres. We also trained a U-net on five images with full and brush annotations from one centre, and tested the model on 32 images from the other centre. For an atlas-based approach, we employed three atlas images to segment 64 target images from the two centres through straightforward atlas registration and label fusion. We applied the CKKM algorithm to the baseline U-net and atlas outputs and refined the initial segmentation through multi-volume image fusion. The integration of CKKM substantially improved baseline results and yielded, with minimal computational cost, segmentation accuracy, and precision that were greater than some state-of-the-art deep learning models and similar to experienced observer manual segmentation. This suggests that deep learning and atlas-based approaches may be utilized to segment UTE MRI datasets using relatively small training datasets with under-annotations.

Computed tomography semi-automated lung volume quantification in SARS-CoV-2-related pneumonia

OBJECTIVES

To evaluate a semi-automated segmentation and ventilated lung quantification on chest computed tomography (CT) to assess lung involvement in patients affected by SARS-CoV-2. Results were compared with clinical and functional parameters and outcomes.

METHODS

All images underwent quantitative analyses with a dedicated workstation using a semi-automatic lung segmentation software to compute ventilated lung volume (VLV), Ground-glass opacity (GGO) volume (GGO-V), and consolidation volume (CONS-V) as absolute volume and as a percentage of total lung volume (TLV). The ratio between CONS-V, GGO-V, and VLV (CONS-V/VLV and GGO-V/VLV, respectively), TLV (CONS-V/TLV, GGO-V/TLV, and GGO-V + CONS-V/TLV respectively), and the ratio between VLV and TLV (VLV/TLV) were calculated.

RESULTS

A total of 108 patients were enrolled. GGO-V/TLV significantly correlated with WBC (r = 0.369), neutrophils (r = 0.446), platelets (r = 0.182), CRP (r = 0.190), PaCO2 (r = 0.176), HCO3- (r = 0.284), and PaO2/FiO2 (P/F) values (r = - 0.344). CONS-V/TLV significantly correlated with WBC (r = 0.294), neutrophils (r = 0.300), lymphocytes (r = -0.225), CRP (r = 0.306), PaCO2 (r = 0.227), pH (r = 0.162), HCO3- (r = 0.394), and P/F (r = - 0.419) values. Statistically significant differences between CONS-V, GGO-V, GGO-V/TLV, CONS-V/TLV, GGO-V/VLV, CONS-V/VLV, GGO-V + CONS-V/TLV, VLV/TLV, CT score, and invasive ventilation by ET were found (all p < 0.05).

CONCLUSION

The use of quantitative semi-automated algorithm for lung CT elaboration effectively correlates the severity of SARS-CoV-2-related pneumonia with laboratory parameters and the need for invasive ventilation.

KEY POINTS

• Pathological lung volumes, expressed both as GGO-V and as CONS-V, can be considered a useful tool in SARS-CoV-2-related pneumonia. • All lung volumes, expressed themselves and as ratio with TLV and VLV, correlate with laboratory data, in particular C-reactive protein and white blood cell count. • All lung volumes correlate with patient's outcome, in particular concerning invasive ventilation.

Quantitative inspiratory-expiratory chest CT to evaluate pulmonary involvement in pediatric hematopoietic stem-cell transplantation patients

Pulmonary complications following allogeneic hematopoietic stem-cell transplantation (HSCT) are a significant source of morbidity and complications may arise from a myriad of infectious and noninfectious sources. These complications may occur soon or many months post-transplantation and can have a broad range of outcomes. Surveillance for pulmonary involvement in the pediatric HSCT population can be challenging due to poor compliance with clinical pulmonary function testing, primarily spirometry, and there may be a role for clinical imaging to provide an additional means of monitoring, particularly in the era of clinical low-dose computed tomography (CT) protocols. In this single-site, retrospective study, a review of our institution's radiological and HSCT databases was conducted to assess the utility of a quantitative CT algorithm to describe ventilation abnormalities on high-resolution chest CT scans of pediatric HSCT patients. Thirteen non-contrast enhanced chest CT examinations acquired both in inspiration and expiration, from 12 deceased HSCT patients (median age at HSCT 10.4 years, median days of CT 162) were selected for the analysis. Also, seven age-matched healthy controls (median age 15.5) with non-contrast-enhanced inspiration-expiration chest CT were selected for comparison. We report that, compared to healthy age-matched controls, HSCT patients had larger percentages of poorly ventilated (median, 13.5% vs. 2.3%, p < .001) and air trapped (median 12.3% vs. 0%, p < .001) regions of lung tissue, suggesting its utility as a potential screening tool. Furthermore, there was wide variation within individual HSCT patients, supporting the use of multivolume CT and quantitative analysis to describe and phenotype post-transplantation lung involvement.

Progression of Emphysema and Small Airways Disease in Cigarette Smokers

BACKGROUND

Little is known about factors associated with emphysema progression in cigarette smokers. We evaluated factors associated with change in emphysema and forced expiratory volume in 1 second (FEV1) in participants with and without chronic obstructive pulmonary disease (COPD).

METHODS

This retrospective study included individuals participating in the COPD Genetic Epidemiology study who completed the 5-year follow-up, including inspiratory and expiratory computed tomography (CT) and spirometry. All paired CT scans were analyzed using micro-mapping, which classifies individual voxels as emphysema or functional small airway disease (fSAD). Presence and progression of emphysema and FEV1 were determined based on comparison to nonsmoker values. Logistic regression analyses were used to identify clinical parameters associated with disease progression.

RESULTS

A total of 3088 participants were included with a mean ± SD age of 60.7±8.9 years, including 72 nonsmokers. In all Global initiative for chronic Obstructive Lung Disease (GOLD) stages, the presence of emphysema at baseline was associated with emphysema progression (odds ratio [OR]: GOLD 0: 4.32; preserved ratio-impaired spirometry [PRISm]; 5.73; GOLD 1: 5.16; GOLD 2: 5.69; GOLD 3/4: 5.55; all p ≤0.01). If there was no emphysema at baseline, the amount of fSAD at baseline was associated with emphysema progression (OR for 1% increase: GOLD 0: 1.06; PRISm: 1.20; GOLD 1: 1.7; GOLD 3/4: 1.08; all p ≤ 0.03).In 1735 participants without spirometric COPD, progression in emphysema occurred in 105 (6.1%) participants and only 21 (1.2%) had progression in both emphysema and FEV1.

CONCLUSIONS

The presence of emphysema is an important predictor of emphysema progression. In patients without emphysema, fSAD is associated with the development of emphysema. In participants without spirometric COPD, emphysema progression occurred independently of FEV1 decline.

Central airway and peripheral lung structures in airway disease-dominant COPD

The concept that the small airway is a primary pathological site for all COPD phenotypes has been challenged by recent findings that the disease starts from the central airways in COPD subgroups and that a smaller central airway tree increases COPD risk. This study aimed to examine whether the computed tomography (CT)-based airway disease-dominant (AD) subtype, defined using the central airway dimension, was less associated with small airway dysfunction (SAD) on CT, compared to the emphysema-dominant (ED) subtype.

COPD patients were categorised into mild, AD, ED and mixed groups based on wall area per cent (WA%) of the segmental airways and low attenuation volume per cent in the Kyoto–Himeji (n=189) and Hokkaido COPD cohorts (n=93). The volume per cent of SAD regions (SAD%) was obtained by nonrigidly registering inspiratory and expiratory CT.

The AD group had a lower SAD% than the ED group and similar SAD% to the mild group. The AD group had a smaller lumen size of airways proximal to the segmental airways and more frequent asthma history before age 40 years than the ED group. In multivariable analyses, while the AD and ED groups were similarly associated with greater airflow limitation, the ED, but not the AD, group was associated with greater SAD%, whereas the AD, but not the ED, group was associated with a smaller central airway size.

The CT-based AD COPD subtype might be associated with a smaller central airway tree and asthma history, but not with peripheral lung pathologies including small airway disease, unlike the ED subtype.

This study shows that airway disease-dominant COPD, defined using central airway dimension on CT, is associated with a smaller central airway tree, less small airway dysfunction and slower lung function decline than the emphysema-dominant COPDhttps://bit.ly/3nNwxIC

Generation-based study of airway remodeling in smokers with normal-looking CT with normalization to control inter-subject variability

PURPOSE

With the help of quantitative computed tomography (QCT), it is possible to identify smoking-associated airway remodeling. However, there is currently little information on whether QCT-based airway metrics are sensitive to early airway wall remodeling in subclinical phases of smoking-associated airway disease. This study aimed to evaluate a predictive model that normalized airway parameters and investigate structural airway alterations in smokers with normal-looking CT using the normalization scheme.

METHODS

In this retrospective analysis, 222 non-smokers (male 97, female 125) and 69 smokers (male 66, female 3) from January 2014 to December 2016 were included, and airway parameters were quantitatively analyzed. To control inter-subject variability, multiple linear regressions of tracheal wall thickness (WT), diameter (D), and luminal area (LA) were performed, adjusted for age, sex, and height. Using this normalization scheme, airway parameters with matched generation were compared between smokers and non-smokers.

RESULTS

Using the normalization scheme, it was possible to assess generation-based structural alterations of the airways in subclinical smokers. Smokers showed diffuse luminal narrowing of airways for most generations (P < 0.05, except 3rd generation), no change in wall thickness of the proximal bronchi (1st-3rd generation), and a thinning of distal airways (P <0.05, ≥4th generation).

CONCLUSION

QCT assessment for subclinical smokers can help identify minimal structural changes in airways induced by smoking.

Template Creation for High-Resolution Computed Tomography Scans of the Lung in R Software

Rationale and Objectives.

A standard lung template could improve population-level analyses for computed tomography (CT) scans of the lung. We develop a fully-automated pre-processing pipeline for image analysis of the lungs using updated methodologies and R software that results in the creation of a standard lung template. We apply this pipeline to CT scans from a sarcoidosis population, exploring the influence of registration on radiomic analyses.

Materials and Methods.

Using 65 high-resolution CT scans from healthy adults, we create a standard lung template by segmenting the left and right lungs, non-linearly registering lung masks to an initial template mask, and using an unbiased, iterative procedure to converge to a standard lung shape (Dice similarity coefficient ≥0.99). We compare three-dimensional radiomic features between control and sarcoidosis patients, before and after registration to a study-specific lung template.

Results.

The final lung template had a right lung volume of 2967 cm³ and left lung volume of 2623 cm³, with a median HU = −862. Registration significantly affected radiomic features, shifting the HU distribution to the left, decreasing variability, and increasing smoothness (p<0.0001). The registration improved detective ability of radiomics; for contrast, autocorrelation, energy and homogeneity, the group effect was significant post-registration (p<0.05), but was not significant pre-registration.

Conclusion.

The final lung template and software used for its creation are publicly available via the lungct R package to facilitate its use in practice. This study advances lung imaging by developing tools to improve population-level analyses for various lung diseases.

The Performance of Chest CT in Evaluating the Clinical Severity of COVID-19 Pneumonia: Identifying Critical Cases Based on CT Characteristics

Objectives

To assess the clinical severity of COVID-19 pneumonia using qualitative and/or quantitative chest CT indicators and identify the CT characteristics of critical cases.

Materials and Methods

Fifty-one patients with COVID-19 pneumonia including ordinary cases (group A, n=12), severe cases(group B, n=15) and critical cases (group C, n=24) were retrospectively enrolled. The qualitative and quantitative indicators from chest CT were recorded and compared using Fisher's exact test, one-way ANOVA, Kruskal-Wallis H test and receiver operating characteristic analysis.

Results

Depending on the severity of the disease, the number of involved lung segments and lobes, the frequencies of consolidation, crazy-paving pattern and air bronchogram increased in more severe cases. Qualitative indicators including total severity score for the whole lung and total score for crazy-paving and consolidation could distinguish groups B and C from A(69% sensitivity, 83% specificity and 73% accuracy) but were similar between group B and group C. Combined qualitative and quantitative indicators could distinguish these three groups with high sensitivity(B+C vs. A, 90%; C vs. B, 92%), specificity(100%, 87%) and accuracy(92%, 90%). Critical cases had higher total severity score(>10) and higher total score for crazy-paving and consolidation(>4) than ordinary cases, and had higher mean lung density(>-779HU) and full width at half maximum(>128HU) but lower relative volume of normal lung density(≦50%) than ordinary/severe cases. In our critical cases, eight patients with relative volume of normal lung density smaller than 40% received mechanical ventilation for supportive treatment, and two of them had died.

Conclusion

A rapid, accurate severity assessment of COVID-19 pneumonia based on chest CT would be feasible and could provide help for making management decisions, especially for the critical cases.

From infancy to adulthood-Developmental changes in pulmonary quantitative computed tomography parameters

Purpose

Quantified computed tomography (qCT) is known for correlations with airflow obstruction and fibrotic changes of the lung. However, as qCT studies often focus on diseased and elderly subjects, current literature lacks physiological qCT values during body development. We evaluated chest CT examinations of a healthy cohort, reaching from infancy to adulthood, to determine physiological qCT values and changes during body development.

Method

Dose-optimized chest CT examinations performed over the last 3 years using a dual-source CT were retrospectively analysed. Exclusion criteria were age >30 years and any known or newly diagnosed lung pathology. Lung volume, mean lung density, full-width-at-half-maximum and low attenuated volume (LAV) were semi-automated quantified in 151 patients. qCT values between different age groups as well as unenhanced (Group 1) and contrast-enhanced (Group 2) protocols were compared. Models for projection of age-dependant changes in qCT values were fitted.

Results

Significant differences in qCT parameters were found between the age groups from 0 to 15 years (p < 0.05). All parameters except LAV merge into a plateau level above this age as shown by polynomial models (r2 between 0.85 and 0.67). In group 2, this plateau phase is shifted back around five years. Except for the volume, significant differences in all qCT values were found between group 1 and 2 (p < 0.01).

Conclusion

qCT parameters underly a specific age-dependant dynamic. Except for LAV, qCT parameters reach a plateau around adolescence. Contrast-enhanced protocols seem to shift this plateau backwards.

Comprehensive stereological assessment of the human lung using multiresolution computed tomography

The application of stereology to lung casts and two-dimensional microscopy images is the gold standard for quantification of the human lung anatomy. However, these techniques are labor intensive, involving fixation, embedding, and histological sectioning of samples and thus have prevented comprehensive studies. Our objective was to demonstrate the application of stereology to volumetric multiresolution computed tomography (CT) to efficiently and extensively quantify the human lung anatomy. Nontransplantable donor lungs from individuals with no evidence of respiratory disease (n = 13) were air inflated, frozen at 10 cmH₂O, and scanned using CT. Systematic uniform random samples were taken, scanned using micro-CT, and assessed using stereology. The application of stereology to volumetric CT imaging enabled comprehensive quantification of total lung volume, volume fractions of alveolar, alveolar duct, and tissue, mean linear intercept, alveolar surface area, alveolar surface area density, septal wall thickness, alveolar number, number-weighted mean alveolar volume, and the number and morphometry of terminal and transitional bronchioles. With the use of this data set, we found that women and men have the same number of terminal bronchioles (last generation of conducting airways), but men have longer terminal bronchioles, a smaller wall area percentage, and larger lungs due to a greater number of alveoli per acinus. The application of stereology to multiresolution CT imaging enables comprehensive analysis of the human lung parenchyma that identifies differences between men and women. The reported data set of normal donor lungs aged 25-77 yr provides reference data for future studies of chronic lung disease to determine exact changes in tissue pathology.NEW & NOTEWORTHY Stereology has been the gold standard to quantify the three-dimensional lung anatomy using two-dimensional microscopy images. However, such techniques are labor intensive. This study provides a method that applies stereology to volumetric computed tomography images of frozen whole human lungs and systematic uniform random samples. The method yielded a comprehensive data set on the small airways and parenchymal lung structures, highlighting morphometric sex differences and providing a reference data set for future pathological studies.

Chronic Obstructive Pulmonary Disease in Women: A Biologically Focused Review with a Systematic Search Strategy

Purpose

Evidence suggests that chronic obstructive pulmonary disease (COPD) symptoms and progression may differ between men and women. However, limited information is currently available on the pathophysiological and biological factors that may underlie these sex-related differences. The objective of this review is to systematically evaluate reports of potential sex-related differences, including genetic, pathophysiological, structural, and other biological factors, that may influence COPD development, manifestation, and progression in women.

Patients and Methods

A PubMed literature search was conducted from inception until January 2020. Original reports of genetic, hormonal, and physiological differences, and biological influences that could contribute to COPD development, manifestation, and progression in women were included.

Results

Overall, 491 articles were screened; 29 articles met the inclusion criteria. Results from this analysis demonstrated between-sex differences in inflammatory, immune, genetic, structural, and physiological factors in patients with COPD.

Conclusion

Various biological differences are observed between men and women with COPD including differences in inflammatory and metabolic pathways related to obesity and fat distribution, immune cell function and autophagy, extent and distribution of emphysema and airway wall remodeling. An enhanced understanding of these differences has the potential to broaden our understanding of how COPD develops and progresses, thereby providing an opportunity to ultimately improve diagnosis, treatment, and monitoring of COPD in both men and women.

Lobar distribution of non-emphysematous gas trapping and lung hyperinflation in chronic obstructive pulmonary disease

BACKGROUND

Lung hyperinflation in chronic obstructive pulmonary disease (COPD) is closely associated with emphysema and non-emphysematous gas trapping, termed functional small airway disease (fSAD), on inspiratory and expiratory computed tomography (CT). Because the cranial-caudal emphysema distribution affects pulmonary function and fSAD may precede emphysema on CT, we tested the hypothesis that lobar fSAD distribution would affect lung hyperinflation differently in COPD with minimal and established emphysema.

METHODS

The volume percentages of fSAD and emphysema (fSAD% and Emph%) over the upper and lower lobes were measured using inspiratory and expiratory CT in 70 subjects with COPD. Subjects were divided into those with minimal and established emphysema (n = 36 and 34) using a threshold of 10% Emph% in the whole lung.

RESULTS

In the minimal emphysema group, fSAD% in the upper and lower lobes was positively correlated with functional residual capacity (FRC) and residual volume to total lung capacity ratio (RV/TLC), and the correlation of fSAD% with RV/TLC was greater in the lower lobes. Conversely, in the established emphysema group, fSAD% in the upper and lower lobes was correlated with RV/TLC, but not with FRC. In multivariate analysis, fSAD% in the lower lobes, but not in the upper lobes, was associated with RV/TLC in subjects with minimal emphysema after adjusting for age, smoking status, and bronchodilator use.

CONCLUSION

Non-emphysematous gas trapping in the upper and lower lobes has a distinct physiological effect, especially in COPD with minimal emphysema. This local evaluation might allow sensitive detection of changes in lung hyperinflation in COPD.

Quantitative CT detects progression in COPD patients with severe emphysema in a 3-month interval

OBJECTIVES

Chronic obstructive pulmonary disease (COPD) is characterized by variable contributions of emphysema and airway disease on computed tomography (CT), and still little is known on their temporal evolution. We hypothesized that quantitative CT (QCT) is able to detect short-time changes in a cohort of patients with very severe COPD.

METHODS

Two paired in- and expiratory CT each from 70 patients with avg. GOLD stage of 3.6 (mean age = 66 ± 7.5, mean FEV1/FVC = 35.28 ± 7.75) were taken 3 months apart and analyzed by fully automatic software computing emphysema (emphysema index (EI), mean lung density (MLD)), air-trapping (ratio expiration to inspiration of mean lung attenuation (E/I MLA), relative volume change between - 856 HU and - 950 HU (RVC_856-950)), and parametric response mapping (PRM) parameters for each lobe separately and the whole lung. Airway metrics measured were wall thickness (WT) and lumen area (LA) for each airway generation and the whole lung.

RESULTS

The average of the emphysema parameters (EI, MLD) increased significantly by 1.5% (p < 0.001) for the whole lung, whereas air-trapping parameters (E/I MLA, RVC_856-950) were stable. PRM_Emph increased from 34.3 to 35.7% (p < 0.001), whereas PRM_Normal decrased from 23.6% to 22.8% (p = 0.012). WT decreased significantly from 1.17 ± 0.18 to 1.14 ± 0.19 mm (p = 0.036) and LA increased significantly from 25.08 ± 4.49 to 25.84 ± 4.87 mm² (p = 0.041) for the whole lung. The generation-based analysis showed heterogeneous results.

CONCLUSION

QCT detects short-time progression of emphysema in severe COPD. The changes were partly different among lung lobes and airway generations, indicating that QCT is useful to address the heterogeneity of COPD progression.

KEY POINTS

• QCT detects short-time progression of emphysema in severe COPD in a 3-month period. • QCT is able to quantify even slight parenchymal changes, which were not detected by spirometry. • QCT is able to address the heterogeneity of COPD, revealing inconsistent changes individual lung lobes and airway generations.

Age-Related Structural and Functional Changes in the Mouse Lung

Lung function declines with advancing age. To improve our understanding of the structure-function relationships leading to this decline, we investigated structural alterations in the lung and their impact on micromechanics and lung function in the aging mouse. Lung function analysis was performed in 3, 6, 12, 18, and 24 months old C57BL/6 mice (n = 7-8/age), followed by lung fixation and stereological sample preparation. Lung parenchymal volume, total, ductal and alveolar airspace volume, alveolar volume and number, septal volume, septal surface area and thickness were quantified by stereology as well as surfactant producing alveolar epithelial type II (ATII) cell volume and number. Parenchymal volume, total and ductal airspace volume increased in old (18 and 24 months) compared with middle-aged (6 and 12 months) and young (3 months) mice. While the alveolar number decreased from young (7.5 × 10⁶) to middle-aged (6 × 10⁶) and increased again in old (9 × 10⁶) mice, the mean alveolar volume and mean septal surface area per alveolus conversely first increased in middle-aged and then declined in old mice. The ATII cell number increased from middle-aged (8.8 × 10⁶) to old (11.8 × 10⁶) mice, along with the alveolar number, resulting in a constant ratio of ATII cells per alveolus in all age groups (1.4 ATII cells per alveolus). Lung compliance and inspiratory capacity increased, whereas tissue elastance and tissue resistance decreased with age, showing greatest changes between young and middle-aged mice. In conclusion, alveolar size declined significantly in old mice concomitant with a widening of alveolar ducts and late alveolarization. These changes may partly explain the functional alterations during aging. Interestingly, despite age-related lung remodeling, the number of ATII cells per alveolus showed a tightly controlled relation in all age groups.

Computed Tomography Imaging for Novel Therapies of Chronic Obstructive Pulmonary Disease

Novel therapeutic options in chronic obstructive pulmonary disease (COPD) require delicate patient selection and thus demand for expert radiologists visually and quantitatively evaluating high-resolution computed tomography (CT) with additional functional acquisitions such as paired inspiratory-expiratory scans or dynamic airway CT. The differentiation between emphysema-dominant and airway-dominant COPD phenotypes by imaging has immediate clinical value for patient management. Assessment of emphysema severity, distribution patterns, and fissure integrity are essential for stratifying patients for different surgical and endoscopic lung volume reduction procedures. This is supported by quantitative software-based postprocessing of CT data sets, which delivers objective emphysema and airway remodelling metrics. However, the significant impact of scanning and reconstruction parameters, as well as intersoftware variability still hamper comparability between sites and studies. In earlier stage COPD imaging, it is less clear as to what extent quantitative CT might impact decision making and therapy follow-up, as emphysema progression is too slow to realistically be useful as a mid-term outcome measure in an individual, and longitudinal data on airway remodelling are still very limited.

A New Bronchodilator Response Grading Strategy Identifies Distinct Patient Populations

Rationale: A positive bronchodilator response (BDR) according to American Thoracic Society/European Respiratory Society (ATS/ERS) guidelines require both 200 ml and 12% increase in forced expiratory volume in 1 second (FEV1) or forced vital capacity (FVC) after bronchodilator inhalation. This dual criterion is insensitive in those with high or low FEV1.Objectives: To establish BDR criteria with volume or percentage FEV1 change.Methods: The largest FEV1 and FVC were identified from three pre- and three post-bronchodilator maneuvers in COPDGene (Genetic Epidemiology of COPD) participants. A total of 7,741 individuals with coefficient of variation less than 15% for both FEV1 and FVC formed bronchodilator categories of FEV1 response: negative (≤0.00% or ≤0.00 L), minimal (>0.00% to ≤9.00% or >0.00 L to ≤0.09 L), mild (>9.00% to ≤16.00% or >0.09 L to ≤0.16 L), moderate (>16.00% to ≤26.00% or >0.16 L to ≤0.26 L), and marked (>26.00% or >0.26 L). These response size categories are based on empirical limits considering average FEV1 increase of approximately 160 ml and the clinically important difference for FEV1. To compare flow and volume response characteristics, BDR-FEV1 category assignments were applied for the BDR-FVC response.Results: Twenty percent met mild and 31% met moderate or marked BDR-FEV1 criteria, whereas 12% met mild and 33% met moderate or marked BDR-FVC criteria. In contrast, only 20.6% met ATS/ERS positive criteria. Compared with the negative BDR-FEV1 category, the minimal, mild, moderate, and marked BDR-FEV1 categories were associated with greater 6-minute-walk distance and lower St. George's Respiratory Questionnaire and modified Medical Research Council dyspnea scale scores. Compared with negative BDR, moderate and marked BDR-FEV1 categories were associated with fewer exacerbations, and minimal BDR was associated with lower computed tomography airway wall thickness. Compared with the negative category, all BDR-FVC categories were associated with increasing emphysema percentage and gas trapping percentage. Moderate and marked BDR-FVC categories were associated with higher St. George's Respiratory Questionnaire scores but fewer exacerbations and lower dyspnea scores.Conclusions: BDR grading by FEV1 volume or percentage response identified subjects otherwise missed by ATS/ERS criteria. BDR grades were associated with functional exercise performance, quality of life, exacerbation frequency, dyspnea, and radiological airway measures. BDR grades in FEV1 and FVC indicate different clinical and radiological characteristics.

MUC5B variant is associated with visually and quantitatively detected preclinical pulmonary fibrosis

BACKGROUND

Relatives of patients with familial interstitial pneumonia (FIP) are at increased risk for pulmonary fibrosis. We assessed the prevalence and risk factors for preclinical pulmonary fibrosis (PrePF) in first-degree relatives of patients with FIP and determined the utility of deep learning in detecting PrePF on CT.

METHODS

First-degree relatives of patients with FIP over 40 years of age who believed themselves to be unaffected by pulmonary fibrosis underwent CT scans of the chest. Images were visually reviewed, and a deep learning algorithm was used to quantify lung fibrosis. Genotyping for common idiopathic pulmonary fibrosis risk variants in MUC5B and TERT was performed.

FINDINGS

In 494 relatives of patients with FIP from 263 families of patients with FIP, the prevalence of PrePF on visual CT evaluation was 15.6% (95% CI 12.6 to 19.0). Compared with visual CT evaluation, deep learning quantitative CT analysis had 84% sensitivity (95% CI 0.72 to 0.89) and 86% sensitivity (95% CI 0.83 to 0.89) for discriminating subjects with visual PrePF diagnosis. Subjects with PrePF were older (65.9, SD 10.1 years) than subjects without fibrosis (55.8 SD 8.7 years), more likely to be male (49% vs 37%), more likely to have smoked (44% vs 27%) and more likely to have the MUC5B promoter variant rs35705950 (minor allele frequency 0.29 vs 0.21). MUC5B variant carriers had higher quantitative CT fibrosis scores (mean difference of 0.36%), a difference that remains significant when controlling for age and sex.

INTERPRETATION

PrePF is common in relatives of patients with FIP. Its prevalence increases with age and the presence of a common MUC5B promoter variant. Quantitative CT analysis can detect these imaging abnormalities.

Radiomic measures from chest high-resolution computed tomography associated with lung function in sarcoidosis

INTRODUCTION

Pulmonary sarcoidosis is a rare heterogeneous lung disease of unknown aetiology, with limited treatment options. Phenotyping relies on clinical testing including visual scoring of chest radiographs. Objective radiomic measures from high-resolution computed tomography (HRCT) may provide additional information to assess disease status. As the first radiomics analysis in sarcoidosis, we investigate the potential of radiomic measures as biomarkers for sarcoidosis, by assessing 1) differences in HRCT between sarcoidosis subjects and healthy controls, 2) associations between radiomic measures and spirometry, and 3) trends between Scadding stages.

METHODS

Radiomic features were computed on HRCT in three anatomical planes. Linear regression compared global radiomic features between sarcoidosis subjects (n=73) and healthy controls (n=78), and identified associations with spirometry. Spatial differences in associations across the lung were investigated using functional data analysis. A subanalysis compared radiomic features between Scadding stages.

RESULTS

Global radiomic measures differed significantly between sarcoidosis subjects and controls (p<0.001 for skewness, kurtosis, fractal dimension and Geary's C), with differences in spatial radiomics most apparent in superior and lateral regions. In sarcoidosis subjects, there were significant associations between radiomic measures and spirometry, with a large association found between Geary's C and forced vital capacity (FVC) (p=0.008). Global radiomic measures differed significantly between Scadding stages (p<0.032), albeit nonlinearly, with stage IV having more extreme radiomic values. Radiomics explained 71.1% of the variability in FVC compared with 51.4% by Scadding staging alone.

CONCLUSIONS

Radiomic HRCT measures objectively differentiate disease abnormalities, associate with lung function and identify trends in Scadding stage, showing promise as quantitative biomarkers for pulmonary sarcoidosis.

The importance of CT quantitative evaluation of emphysema in lung cancer screening cohort with negative findings by visual evaluation

INTRODUCTION

One-stop quantitative evaluation of emphysema and lung nodule in lung cancer screening is very important for patient.

OBJECTIVE

To evaluate the quantitative emphysema in the large-sample low-dose CT lung cancer screening cohort with negative CT findings by subjective visual assessment.

METHODS

One thousand, two hundred and thirty-one participants with negative visual evaluation were included in this retrospective study. The lungs were automatically segmented and the following were calculated: total lung volume (TLV), total emphysema volume (TEV), emphysema index (EI), 15th percentile lung density and mean lung density. EI ≥6% was defined as emphysema. The quantitative parameters were compared between different genders and ages. The quantitative parameters and risk factors were compared between emphysema and non-emphysema groups.

RESULTS

The proportion of smokers, TLV, TEV and EI of men were greater than that of women (P < 0.001). No correlation was found between age and volumes; the TEV and EI of people older than 60 years were greater than those younger than 60 years (P < 0.05) by age categorisation. One hundred and two participants showed emphysema, accounting for 8.29%. The incidence of emphysema in men was greater than that in women in total (P < 0.05). All the CT quantitative parameters were significantly different between emphysema and non-emphysema groups. The ratio of male, secondhand smoke exposure and chronic bronchitis history was greater in emphysema than that in the non-emphysema group (P < 0.05).

CONCLUSION

CT quantitative emphysema evaluation is recommended in people older than 60 years, especially in males, providing more precise information, aiding the early diagnosis of emphysema and informing early intervention.

Normal lung attenuation distribution and lung volume on computed tomography in a Chinese population

Backgroud and objectives: Although lung attenuation distribution and lung volume on computed tomography (CT) have been widely used in evaluating COPD and interstitial lung disease, there are only a few studies regarding the normal range of these indices, especially in Chinese subjects. We aimed to describe the normal range of lung attenuation distribution and lung volume based on CT.

Methods: Subjects with normal lung function and basically normal chest CT findings (derivation group) at Ruijin Hospital, Shanghai (from January 2010 to June 2014) were included according to inclusion and exclusion criteria. The range of the percentage of lung volume occupied by low attenuation areas (LAA%), percentile of the histogram of attenuation values (Perc n), and total lung volume were analyzed. Relationships of these measures with demographic variables were evaluated. Participants who underwent chest CT examination for disease screening and had basically normal CT findings served as an external validation group.

Results: The number of subjects in the derivation group and external validation groups were 564 and 1,787, respectively. Mean total lung volumes were 4,468±1,271 mL and 4,668±1,192 mL, and median LAA%(-950 HU) was 0.19 (0.03–0.43) and 0.17 (0.01–0.41), in the derivation and external validation groups, respectively. Reference equations for lung volume and attenuation distribution (LAA% using -1,000–210 HU, Perc 1 to Perc 98) were generated: Lung volume (mL) = -1.015 *10^4+605.3*Sex (1= male, 0= female)+92.61*Height (cm) –12.99*Weight (kg) ±1766; LAA% (-950 HU)=[0.2027+0.05926*Sex (1= male, 0= female) –4.111*10^-3*Weight (kg) +4.924*10^-3*Height (cm) +8.504*10^-4*Age]^7.341–0.05; Upper limit of normal range: [0.2027+0.05926*Sex-4.111*10^-3*Weight+4.924*10^-3*Height+8.504*10^-4*Age+0.1993]^7.341–0.05.

Conclusion: This large population-based retrospective study demonstrated the normal range of LAA%, Perc n, and total lung volume measured on CT scans among subjects with normal lung function and CT findings. Reference equations are provided.

Association of Obesity with Quantitative Chest CT Measured Airway Wall Thickness in WTC Workers with Lower Airway Disease

BACKGROUND

We previously reported that wall area percent (WAP), a quantitative CT (QCT) indicator of airway wall thickness and, presumably, inflammation, is associated with adverse longitudinal expiratory flow trajectories in WTC workers, but that obesity and weight gain also seemed to be independently predictive of the latter. Previous studies have reported no association between WAP and obesity, so we investigated that association in nonsmoking WTC-exposed individuals and healthy unexposed controls.

METHODS

We assessed WAP using the Chest Imaging Platform QCT system in a segmental bronchus in 118 former WTC workers, and 89 COPDGene® WTC-unexposed and asymptomatic subjects. We used multiple regression to model WAP vs. body mass index (BMI) in the two groups, adjusting for important subject and CT image characteristics.

RESULTS

Unadjusted analyses revealed significant differences between the two groups with regards to WAP, age, gender, scan pixel spacing and slice interval, but not BMI or total lung capacity. In adjusted analysis, there was a significant interaction between BMI and WTC exposure on WAP. BMI was significantly and positively associated with WAP in the WTC group, but not in the COPDGene® group, but stratified analyses revealed that the effect was significant in WTC subjects with clinical evidence of lower airway disease (LAD).

DISCUSSION

Unlike non-diseased subjects, BMI was significantly associated with WAP in WTC workers and, in stratified analyses, the association was significant only among those with LAD. Our findings suggest that this adverse effect of obesity on airway structure and inflammation may be confined to already diseased individuals.

Objectively Measured Chronic Lung Injury on Chest CT

BACKGROUND

Tobacco smoke exposure is associated with emphysema and pulmonary fibrosis, both of which are irreversible. We have developed a new objective CT analysis tool that combines densitometry with machine learning to detect high attenuation changes in visually normal appearing lung (Norm_HA) that may precede these diseases.

METHODS

We trained the classification tool by placing 34,528 training points in chest CT scans from 297 COPDGene participants. The tool was then used to classify lung tissue in 9,038 participants as normal, emphysema, fibrotic/interstitial, or Norm_HA. Associations between the quartile of Norm_HA and plasma-based biomarkers, clinical severity, and mortality were evaluated using Jonckheere-Terpstra, pairwise Wilcoxon rank-sum tests, and multivariable linear and Cox regression.

RESULTS

A higher percentage of lung occupied by Norm_HA was associated with higher C-reactive protein and intercellular adhesion molecule 1 (P for trend for both < .001). In analyses adjusted for multiple covariates, including high and low attenuation area, compared with those in the lowest quartile of Norm_HA, those in the highest quartile had a 6.50 absolute percent lower percent predicted lower FEV₁ (P < .001), an 8.48 absolute percent lower percent predicted forced expiratory volume, a 10.78-meter shorter 6-min walk distance (P = .011), and a 56% higher risk of death (P = .003). These findings were present even in those individuals without visually defined interstitial lung abnormalities.

CONCLUSIONS

A new class of Norm_HA on CT may represent a unique tissue class associated with adverse outcomes, independent of emphysema and fibrosis.

MRI and CT lung biomarkers: Towards an in vivo understanding of lung biomechanics

BACKGROUND

The biomechanical properties of the lung are necessarily dependent on its structure and function, both of which are complex and change over time and space. This makes in vivo evaluation of lung biomechanics and a deep understanding of lung biomarkers, very challenging. In patients and animal models of lung disease, in vivo evaluations of lung structure and function are typically made at the mouth and include spirometry, multiple-breath gas washout tests and the forced oscillation technique. These techniques, and the biomarkers they provide, incorporate the properties of the whole organ system including the parenchyma, large and small airways, mouth, diaphragm and intercostal muscles. Unfortunately, these well-established measurements mask regional differences, limiting their ability to probe the lung's gross and micro-biomechanical properties which vary widely throughout the organ and its subcompartments. Pulmonary imaging has the advantage in providing regional, non-invasive measurements of healthy and diseased lung, in vivo. Here we summarize well-established and emerging lung imaging tools and biomarkers and how they may be used to generate lung biomechanical measurements.

METHODS

We review well-established and emerging lung anatomical, microstructural and functional imaging biomarkers generated using synchrotron x-ray tomographic-microscopy (SRXTM), micro-x-ray computed-tomography (micro-CT), clinical CT as well as magnetic resonance imaging (MRI).

FINDINGS

Pulmonary imaging provides measurements of lung structure, function and biomechanics with high spatial and temporal resolution. Imaging biomarkers that reflect the biomechanical properties of the lung are now being validated to provide a deeper understanding of the lung that cannot be achieved using measurements made at the mouth.

Imaging Advances in Chronic Obstructive Pulmonary Disease. Insights from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) Study

The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.

Airway wall thickening on CT: Relation to smoking status and severity of COPD

Airway wall thickening in cigarette smokers is thought to be a result of inflammatory changes and airway remodeling. This study investigates if CT-derived airway wall thickening associates to disease severity in smokers with and without COPD and if airway wall thickening is reversible by smoking cessation. We examined 2000 smokers and 46 never-smokers who returned for a 5-year follow-up visit in the COPDGene-study. Multivariable regression analyses were performed at visit 1 to associate airway wall thickness (expressed as Pi10) with percent predicted forced expiratory volume in 1 s (FEV1%-predicted), 6-min walking distance (6MWD), and St. George Respiratory Questionnaire (SGRQ). Longitudinal analyses were performed to assess the effect of smoking cessation on Pi10 using linear mixed models. A higher Pi10 was significantly associated with worse FEV1%-predicted, 6MWD, and SGRQ in all GOLD-stages. Longitudinal analyses showed that subjects that quit smoking significantly decreased in Pi10 (ΔPi10 = -0.18 mm, p < 0.001). Subjects that started smoking had a significant increase in Pi10 (ΔPi10 = 0.14 mm, p < 0.001). Pi10 is a clinically relevant biomarker of smoking-related airway injury in smokers with and without COPD. The change in Pi10 with change in smoking status suggests that it can quantify a reversible component of smoking-related airway inflammation.