Fully automatic quantitative assessment of emphysema in computed tomography: comparison with pulmonary function testing and normal values

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.

Predicting Postoperative Lung Function in Patients with Lung Cancer Using Imaging Biomarkers

There have been previous studies conducted to predict postoperative lung function with pulmonary function tests (PFTs). Computing tomography (CT) can quantitatively measure small airway walls' thickness, lung volume, pulmonary vessel volume, and emphysema area, which reflect the severity of respiratory diseases. These measurements are considered imaging biomarkers. This study aimed to predict postoperative lung function with imaging biomarkers. A retrospective analysis of 79 patients with lung cancer who had undergone lung surgery was completed. Postoperative lung function measured by forced expiratory volume in one second (FEV1) was defined as an outcome. Preoperative clinico-pathological parameters and imaging biomarkers representing airway walls' thickness, severity of emphysema, total lung volume, and pulmonary vessel volume were measured quantitatively in chest CT by an automated segmentation software, AVIEW COPD. Pi1 was defined as the first percentile along the histogram of lung attenuation that represents the degree of emphysema. Wafw was defined as the airway thickness, which was calculated by the full-width at half-maximum method. Logistic and linear regressions were used to assess these variables. If the actual postoperative FEV1 was higher than the postoperative FEV1 projected by a formula, the group was considered to be preserved. Among the 79 patients, 16 of the patients were grouped as a non-preserved group, and 63 of them were grouped as a preserved group. The patients in the preserved FEV1 group had a higher vessel volume than the non-preserved group. Pi1 and Wafw were independent predictors of postoperative lung function. Imaging biomarkers can be considered significant variables in predicting postoperative lung function in patients with lung cancer.

Comparison of Virtual Non-Contrast and True Non-Contrast CT Images Obtained by Dual-Layer Spectral CT in COPD Patients

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death. Recent studies have underlined the importance of non-contrast-enhanced chest CT scans not only for emphysema progression quantification, but for correlation with clinical outcomes as well. As about 40 percent of the 300 million CT scans per year are contrast-enhanced, no proper emphysema quantification is available in a one-stop-shop approach for patients with known or newly diagnosed COPD. Since the introduction of spectral imaging (e.g., dual-energy CT scanners), it has been possible to create virtual non-contrast-enhanced images (VNC) from contrast-enhanced images, making it theoretically possible to offer proper COPD imaging despite contrast enhancing. This study is aimed towards investigating whether these VNC images are comparable to true non-contrast-enhanced images (TNC), thereby reducing the radiation exposure of patients and usage of resources in hospitals. In total, 100 COPD patients with two scans, one with (VNC) and one without contrast media (TNC), within 8 weeks or less obtained by a spectral CT using dual-layer technology, were included in this retrospective study. TNC and VNC were compared according to their voxel-density histograms. While the comparison showed significant differences in the low attenuated volumes (LAVs) of TNC and VNC regarding the emphysema threshold of -950 Houndsfield Units (HU), the 15th and 10th percentiles of the LAVs used as a proxy for pre-emphysema were comparable. Upon further investigation, the threshold-based LAVs (-950 HU) of TNC and VNC were comparable in patients with a water equivalent diameter (DW) below 270 mm. The study concludes that VNC imaging may be a viable option for assessing emphysema progression in COPD patients, particularly those with a normal body mass index (BMI). Further, pre-emphysema was generally comparable between TNC and VNC. This approach could potentially reduce radiation exposure and hospital resources by making additional TNC scans obsolete.

Evaluation of retrieval accuracy and visual similarity in content-based image retrieval of chest CT for obstructive lung disease

The aim of our study was to assess the performance of content-based image retrieval (CBIR) for similar chest computed tomography (CT) in obstructive lung disease. This retrospective study included patients with obstructive lung disease who underwent volumetric chest CT scans. The CBIR database included 600 chest CT scans from 541 patients. To assess the system performance, follow-up chest CT scans of 50 patients were evaluated as query cases, which showed the stability of the CT findings between baseline and follow-up chest CT, as confirmed by thoracic radiologists. The CBIR system retrieved the top five similar CT scans for each query case from the database by quantifying and comparing emphysema extent and size, airway wall thickness, and peripheral pulmonary vasculatures in descending order from the database. The rates of retrieval of the same pairs of query CT scans in the top 1-5 retrievals were assessed. Two expert chest radiologists evaluated the visual similarities between the query and retrieved CT scans using a five-point scale grading system. The rates of retrieving the same pairs of query CTs were 60.0% (30/50) and 68.0% (34/50) for top-three and top-five retrievals. Radiologists rated 64.8% (95% confidence interval 58.8-70.4) of the retrieved CT scans with a visual similarity score of four or five and at least one case scored five points in 74% (74/100) of all query cases. The proposed CBIR system for obstructive lung disease integrating quantitative CT measures demonstrated potential for retrieving chest CT scans with similar imaging phenotypes. Further refinement and validation in this field would be valuable.

Prediction of disease severity in COPD: a deep learning approach for anomaly-based quantitative assessment of chest CT

OBJECTIVES

To quantify regional manifestations related to COPD as anomalies from a modeled distribution of normal-appearing lung on chest CT using a deep learning (DL) approach, and to assess its potential to predict disease severity.

MATERIALS AND METHODS

Paired inspiratory/expiratory CT and clinical data from COPDGene and COSYCONET cohort studies were included. COPDGene data served as training/validation/test data sets (N = 3144/786/1310) and COSYCONET as external test set (N = 446). To differentiate low-risk (healthy/minimal disease, [GOLD 0]) from COPD patients (GOLD 1-4), the self-supervised DL model learned semantic information from 50 × 50 × 50 voxel samples from segmented intact lungs. An anomaly detection approach was trained to quantify lung abnormalities related to COPD, as regional deviations. Four supervised DL models were run for comparison. The clinical and radiological predictive power of the proposed anomaly score was assessed using linear mixed effects models (LMM).

RESULTS

The proposed approach achieved an area under the curve of 84.3 ± 0.3 (p < 0.001) for COPDGene and 76.3 ± 0.6 (p < 0.001) for COSYCONET, outperforming supervised models even when including only inspiratory CT. Anomaly scores significantly improved fitting of LMM for predicting lung function, health status, and quantitative CT features (emphysema/air trapping; p < 0.001). Higher anomaly scores were significantly associated with exacerbations for both cohorts (p < 0.001) and greater dyspnea scores for COPDGene (p < 0.001).

CONCLUSION

Quantifying heterogeneous COPD manifestations as anomaly offers advantages over supervised methods and was found to be predictive for lung function impairment and morphology deterioration.

CLINICAL RELEVANCE STATEMENT

Using deep learning, lung manifestations of COPD can be identified as deviations from normal-appearing chest CT and attributed an anomaly score which is consistent with decreased pulmonary function, emphysema, and air trapping.

KEY POINTS

• A self-supervised DL anomaly detection method discriminated low-risk individuals and COPD subjects, outperforming classic DL methods on two datasets (COPDGene AUC = 84.3%, COSYCONET AUC = 76.3%). • Our contrastive task exhibits robust performance even without the inclusion of expiratory images, while voxel-based methods demonstrate significant performance enhancement when incorporating expiratory images, in the COPDGene dataset. • Anomaly scores improved the fitting of linear mixed effects models in predicting clinical parameters and imaging alterations (p < 0.001) and were directly associated with clinical outcomes (p < 0.001).

Quantitative CT parameters correlate with lung function in chronic obstructive pulmonary disease: A systematic review and meta-analysis

Objective

This study aimed to analyze the correlation between quantitative computed tomography (CT) parameters and airflow obstruction in patients with COPD.

Methods

PubMed, Embase, Cochrane and Web of Knowledge were searched by two investigators from inception to July 2022, using a combination of pertinent items to discover articles that investigated the relationship between CT measurements and lung function parameters in patients with COPD. Five reviewers independently extracted data, and evaluated it for quality and bias. The correlation coefficient was calculated, and heterogeneity was explored. The following CT measurements were extracted: percentage of lung attenuation area <-950 Hounsfield Units (HU), mean lung density, percentage of airway wall area, air trapping index, and airway wall thickness. Two airflow obstruction parameters were extracted: forced expiratory volume in the first second as a percentage of prediction (FEV₁%pred) and FEV₁ divided by forced expiratory volume lung capacity.

Results

A total of 141 studies (25,214 participants) were identified, which 64 (6,341 participants) were suitable for our meta-analysis. Results from our analysis demonstrated that there was a significant correlation between quantitative CT parameters and lung function. The absolute pooled correlation coefficients ranged from 0.26 (95% CI, 0.18 to 0.33) to 0.70 (95% CI, 0.65 to 0.75) for inspiratory CT and 0.56 (95% CI, 0.51 to 0.60) to 0.74 (95% CI, 0.68 to 0.80) for expiratory CT.

Conclusions

Results from this analysis demonstrated that quantitative CT parameters are significantly correlated with lung function in patients with COPD. With recent advances in chest CT, we can evaluate morphological features in the lungs that cannot be obtained by other clinical indices, such as pulmonary function tests. Therefore, CT can provide a quantitative method to advance the development and testing of new interventions and therapies for patients with COPD.

Semi-automated micro-computed tomography lung segmentation and analysis in mouse models

Computed Tomography (CT) is a standard clinical tool utilized to diagnose known lung pathologies based on established grading methods. However, for preclinical trials and toxicity investigations in animal models, more comprehensive datasets are typically needed to determine discriminative features between experimental treatments, which oftentimes require analysis of multiple images and their associated differential quantification using manual segmentation methods. Furthermore, for manual segmentation of image data, three or more readers is the gold standard of analysis, but this requirement can be time-consuming and inefficient, depending on variability due to reader bias. In previous papers, microCT image manual segmentation was a valuable tool for assessment of lung pathology in several animal models; however, the manual segmentation approach and the commercial software used was typically a major rate-limiting step. To improve the efficiency, the semi-manual segmentation method was streamlined, and a semi-automated segmentation process was developed to produce:•Quantifiable segmentations: using manual and semi-automated analysis methods for assessing experimental injury and toxicity models,•Deterministic results and efficiency through automation in an unbiased and parameter free process, thereby reducing reader variance, user time, and increases throughput in data analysis,•Cost-Effectiveness: portable with low computational resource demand, based on a cross-platform open-source ImageJ program.

Quantitative CT analysis of lung parenchyma to improve malignancy risk estimation in incidental pulmonary nodules

Objectives

To assess the value of quantitative computed tomography (QCT) of the whole lung and nodule-bearing lobe regarding pulmonary nodule malignancy risk estimation.

Methods

A total of 251 subjects (median [IQR] age, 65 (57–73) years; 37% females) with pulmonary nodules on non-enhanced thin-section CT were retrospectively included. Twenty percent of the nodules were malignant, the remainder benign either histologically or at least 1-year follow-up. CT scans were subjected to in-house software, computing parameters such as mean lung density (MLD) or peripheral emphysema index (pEI). QCT variable selection was performed using logistic regression; selected variables were integrated into the Mayo Clinic and the parsimonious Brock Model.

Results

Whole-lung analysis revealed differences between benign vs. malignant nodule groups in several parameters, e.g. the MLD (−766 vs. −790 HU) or the pEI (40.1 vs. 44.7 %). The proposed QCT model had an area-under-the-curve (AUC) of 0.69 (95%-CI, 0.62−0.76) based on all available data. After integrating MLD and pEI into the Mayo Clinic and Brock Model, the AUC of both clinical models improved (AUC, 0.91 to 0.93 and 0.88 to 0.91, respectively). The lobe-specific analysis revealed that the nodule-bearing lobes had less emphysema than the rest of the lung regarding benign (EI, 0.5 vs. 0.7 %; p < 0.001) and malignant nodules (EI, 1.2 vs. 1.7 %; p = 0.001).

Conclusions

Nodules in subjects with higher whole-lung metrics of emphysema and less fibrosis are more likely to be malignant; hereby the nodule-bearing lobes have less emphysema. QCT variables could improve the risk assessment of incidental pulmonary nodules.

Key Points

• Nodules in subjects with higher whole-lung metrics of emphysema and less fibrosis are more likely to be malignant.

• The nodule-bearing lobes have less emphysema compared to the rest of the lung.

• QCT variables could improve the risk assessment of incidental pulmonary nodules.

Artificial Intelligence in Lung Imaging

Recently, interest and advances in artificial intelligence (AI) including deep learning for medical images have surged. As imaging plays a major role in the assessment of pulmonary diseases, various AI algorithms have been developed for chest imaging. Some of these have been approved by governments and are now commercially available in the marketplace. In the field of chest radiology, there are various tasks and purposes that are suitable for AI: initial evaluation/triage of certain diseases, detection and diagnosis, quantitative assessment of disease severity and monitoring, and prediction for decision support. While AI is a powerful technology that can be applied to medical imaging and is expected to improve our current clinical practice, some obstacles must be addressed for the successful implementation of AI in workflows. Understanding and becoming familiar with the current status and potential clinical applications of AI in chest imaging, as well as remaining challenges, would be essential for radiologists and clinicians in the era of AI. This review introduces the potential clinical applications of AI in chest imaging and also discusses the challenges for the implementation of AI in daily clinical practice and future directions in chest imaging.

AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine

Automated image analysis plays an increasing role in radiology in detecting and quantifying image features outside of the perception of human eyes. Common AI-based approaches address a single medical problem, although patients often present with multiple interacting, frequently subclinical medical conditions. A holistic imaging diagnostics tool based on artificial intelligence (AI) has the potential of providing an overview of multi-system comorbidities within a single workflow. An interdisciplinary, multicentric team of medical experts and computer scientists designed a pipeline, comprising AI-based tools for the automated detection, quantification and characterization of the most common pulmonary, metabolic, cardiovascular and musculoskeletal comorbidities in chest computed tomography (CT). To provide a comprehensive evaluation of each patient, a multidimensional workflow was established with algorithms operating synchronously on a decentralized Joined Imaging Platform (JIP). The results of each patient are transferred to a dedicated database and summarized as a structured report with reference to available reference values and annotated sample images of detected pathologies. Hence, this tool allows for the comprehensive, large-scale analysis of imaging-biomarkers of comorbidities in chest CT, first in science and then in clinical routine. Moreover, this tool accommodates the quantitative analysis and classification of each pathology, providing integral diagnostic and prognostic value, and subsequently leading to improved preventive patient care and further possibilities for future studies.

A Preliminary Study on the Relationship Between High-Resolution Computed Tomography and Pulmonary Function in People at Risk of Developing Chronic Obstructive Pulmonary Disease

Objectives

Patients with chronic obstructive pulmonary disease (COPD) have high morbidity and mortality, the opportunity to carry out a thoracic high-resolution CT (HRCT) scan may increase the possibility to identify the group at risk of disease. The aim of our study was to explore the differences in HRCT emphysema parameters, air trapping parameters, and lung density parameters between high and low-risk patients of COPD and evaluate their correlation with pulmonary function parameters.

Methods

In this retrospective, single-center cohort study, we enrolled outpatients from the Physical Examination Center and Respiratory Medicine of The First Affiliated Hospital of Wenzhou Medical University. The patients who were ≥ 40 years-old, had chronic cough or sputum production, and/or had exposure to risk factors for the disease and had not reached the diagnostic criteria is considered people at risk of COPD. They were divided into low-risk group and high-risk group according to FEV₁/FVC ≥ 80% and 80%>FEV₁/FVC ≥ 70%. Data on clinical characteristics, clinical symptom score, pulmonary function, and HRCT were recorded.

Results

72 COPD high-risk patients and 86 COPD low-risk patients were enrolled in the study, and the air trapping index of left, right, and bilateral lungs of the high-risk group were higher than those of the low-risk group. However, the result of mean expiratory lung density was opposite. The emphysema index of left, right, and bilateral lungs were negatively correlated with FEV₁/FVC (correlation coefficients were -0.33, -0.22, -0.26). Consistently, the air trapping index of left and right lungs and bilateral lungs were negatively correlated with FEV₁/FVC (correlation coefficients were -0.33, -0.23, -0.28). Additionally, the mean expiratory lung density of left and right lungs and bilateral lungs were positively correlated with FEV₁/FVC (correlation coefficients were 0.31, 0.25, 0.29).

Conclusion

The emphysema index, air trapping index and the mean expiratory lung density shows significantly positive correlation with FEV₁/FVC which can be used to assess the pulmonary function status of people at risk of COPD and provide a useful supplement for the early and comprehensive assessment of the disease.

Correlations between Volumetric Capnography and Automated Quantitative Computed Tomography Analysis in Patients with Severe COPD

Background: In chronic obstructive pulmonary disease (COPD), morphological analysis made by computed tomography (CT) is usually correlated with spirometry as the main functional tool. In this study, quantitative CT analysis (QCT) was compared with volumetric capnography (VCap), alongside spirometry and the 6-min walk test (6MWT). Methods: Twenty-seven patients with severe/very severe COPD were included, compared with nineteen control subjects. All participants performed spirometry and chest high resolution CT scans that were analyzed with fully-automated software. The COPD group was also submitted to VCap and 6MWT. Results: COPD patients (65.07 ± 8.25 years) showed an average FEV1 of 1.2 L (44% of the predicted) and the control group (34.36 ± 8.78 years). VCap × QCT: positive correlations were observed with bronchial wall thickening and negative correlations with diameter and area of the bronchial lumen. Spirometry × QCT: positive correlations were observed between post-BD FVC, FEV1 and FEF 25–75% and diameter and luminal area of the airways and FVC and lung and vascular volumes (emphysema). Negative correlation was observed between post-BD FVC and FEV1 when compared with Pi10 (internal perimeter of 10 mm). 6MWT vs. QCT: negative correlations were observed between the distance covered with relative wall thickness (airways) and vascular volume and peripheral vascular volume (vasculature). Conclusion: Relevant correlations between QCT and pulmonary function variables were found, including the VCap, highlighting the importance of structural analysis in conjunction with a multidimensional functional assessment. This is the first study to correlate airway and parenchyma QCT with VCap.

Spatial Dependence of CT Emphysema in Chronic Obstructive Pulmonary Disease Quantified by Using Join-Count Statistics

Background Existing CT emphysema measurements quantify the extent or clustering of emphysema voxels in chronic obstructive pulmonary disease (COPD); however, these measurements do not quantify how those voxels are clustered. Purpose To develop a CT measurement to quantify the "compactness" of emphysema voxels, called the normalized join count (NJC), and to determine whether the NJC measurement differentiates COPD disease severity and correlates with lung function and visual emphysema scores. Materials and Methods In this secondary analysis of a prospective study, lung function and CT images were obtained from the Canadian Cohort Obstructive Lung Disease study visit 1 from 2009 to 2013. Participants were categorized as never-smokers, at risk, mild COPD, or moderate-severe COPD. Diffusion capacity for carbon monoxide/alveolar volume was measured. CT emphysema was scored visually by radiologists. CT measurements included the percentage low-attenuation area with attenuation less than -950 HU (%LAA_-950insp), low-attenuation cluster (LAC), and lowest 15th percentile point of the CT lung density histogram. NJC was developed to measure compactness of CT emphysema voxels. An analysis of variance determined differences between groups. Multivariable ridge regression determined association between CT measurements with lung function and radiologist scores. Results A total of 1294 participants (750 men; mean age, 67 years ± 10) were analyzed (277 never-smokers, 306 at risk, 427 mild COPD, and 284 moderate-severe COPD). NJC, %LAA_-950insp, and LAC measurements were higher in moderate-severe COPD than in never-smokers and at-risk participants (P < .05 for all comparisons), but only NJC was different between mild and ;moderate-severe COPD (mean, 1.98% ± 3.61 vs 1.44% ± 2.14; P < .05). In multivariable regression analysis, among all CT measurements NJC had the greatest relative contribution to diffusion capacity for carbon monoxide/alveolar volume (P = .002) and visual emphysema score (P < .001). Conclusion The relationship of normalized join count with severity of chronic obstructive pulmonary disease may indicate that the assessment of this disease is dependent on the number of low attenuating voxels or the size of clusters and the spatial arrangement of such voxels. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Grenier in this issue.

[Pulmonary Emphysema: Visual Interpretation and Quantitative Analysis]

Pulmonary emphysema is a cause of chronic obstructive pulmonary disease. Emphysema can be accurately diagnosed via CT. The severity of emphysema can be assessed using visual interpretation or quantitative analysis. Various studies on emphysema using deep learning have also been conducted. Although the classification of emphysema has proven clinically useful, there is a need to improve the reliability of the measurement.

The impact of lung parenchyma attenuation on nodule volumetry in lung cancer screening

Background

Recent recommendations for lung nodule management include volumetric analysis using tools that present intrinsic measurement variability, with possible impacts on clinical decisions and patient safety. This study was conducted to evaluate whether changes in the attenuation of the lung parenchyma adjacent to a nodule affect the performance of nodule segmentation using computed tomography (CT) studies and volumetric tools.

Methods

Two radiologists retrospectively applied two commercially available volumetric tools for the assessment of lung nodules with diameters of 5–8 mm detected by low-dose chest CT during a lung cancer screening program. The radiologists recorded the success and adequacy of nodule segmentation, nodule volume, manually and automatically (or semi-automatically) obtained long- and short-axis measurements, mean attenuation of adjacent lung parenchyma, and presence of interstitial lung abnormalities or disease, emphysema, pleural plaques, and linear atelectasis. Regression analysis was performed to identify predictors of good nodule segmentation using the volumetric tools. Interobserver and intersoftware agreement on good nodule segmentation was assessed using the intraclass correlation coefficient.

Results

In total, data on 1265 nodules (mean patient age, 68.3 ± 5.1 years; 70.2% male) were included in the study. In the regression model, attenuation of the adjacent lung parenchyma was highly significant (odds ratio 0.987, p < 0.001), with a large effect size. Interobserver and intersoftware agreement on good segmentation was good, although one software package performed better and measurements differed consistently between software packages.

Conclusion

For lung nodules with diameters of 5–8 mm, the likelihood of good segmentation declines with increasing attenuation of the adjacent parenchyma.

Radiomics approach for survival prediction in chronic obstructive pulmonary disease

OBJECTIVES

To apply radiomics analysis for overall survival prediction in chronic obstructive pulmonary disease (COPD), and evaluate the performance of the radiomics signature (RS).

METHODS

This study included 344 patients from the Korean Obstructive Lung Disease (KOLD) cohort. External validation was performed on a cohort of 112 patients. In total, 525 chest CT-based radiomics features were semi-automatically extracted. The five most useful features for survival prediction were selected by least absolute shrinkage and selection operation (LASSO) Cox regression analysis and used to generate a RS. The ability of the RS for classifying COPD patients into high or low mortality risk groups was evaluated with the Kaplan-Meier survival analysis and Cox proportional hazards regression analysis.

RESULTS

The five features remaining after the LASSO analysis were %LAA_-950, AWT_Pi10_6^th, AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA_18mm. The RS demonstrated a C-index of 0.774 in the discovery group and 0.805 in the validation group. Patients with a RS greater than 1.053 were classified into the high-risk group and demonstrated worse overall survival than those in the low-risk group in both the discovery (log-rank test, < 0.001; hazard ratio [HR], 5.265) and validation groups (log-rank test, < 0.001; HR, 5.223). For both groups, RS was significantly associated with overall survival after adjustments for patient age and body mass index.

CONCLUSIONS

A radiomics approach for survival prediction and risk stratification in COPD patients is feasible, and the constructed radiomics model demonstrated acceptable performance. The RS derived from chest CT data of COPD patients was able to effectively identify those at increased risk of mortality.

KEY POINTS

• A total of 525 chest CT-based radiomics features were extracted and the five radiomics features of %LAA_-950, AWT_Pi10_6^th, AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA_18mm were selected to generate a radiomics model. • A radiomics model for predicting survival of COPD patients demonstrated reliable performance with a C-index of 0.774 in the discovery group and 0.805 in the validation group. • Radiomics approach was able to effectively identify COPD patients with an increased risk of mortality, and patients assigned to the high-risk group demonstrated worse overall survival in both the discovery and validation groups.

Automated CT Staging of Chronic Obstructive Pulmonary Disease Severity for Predicting Disease Progression and Mortality with a Deep Learning Convolutional Neural Network

Purpose

To develop a deep learning-based algorithm to stage the severity of chronic obstructive pulmonary disease (COPD) through quantification of emphysema and air trapping on CT images and to assess the ability of the proposed stages to prognosticate 5-year progression and mortality.

Materials and Methods

In this retrospective study, an algorithm using co-registration and lung segmentation was developed in-house to automate quantification of emphysema and air trapping from inspiratory and expiratory CT images. The algorithm was then tested in a separate group of 8951 patients from the COPD Genetic Epidemiology study (date range, 2007-2017). With measurements of emphysema and air trapping, bivariable thresholds were determined to define CT stages of severity (mild, moderate, severe, and very severe) and were evaluated for their ability to prognosticate disease progression and mortality using logistic regression and Cox regression.

Results

On the basis of CT stages, the odds of disease progression were greatest among patients with very severe disease (odds ratio [OR], 2.67; 95% CI: 2.02, 3.53; P < .001) and were elevated in patients with moderate disease (OR, 1.50; 95% CI: 1.22, 1.84; P = .001). The hazard ratio of mortality for very severe disease at CT was 2.23 times the normal ratio (95% CI: 1.93, 2.58; P < .001). When combined with Global Initiative for Chronic Obstructive Lung Disease (GOLD) staging, patients with GOLD stage 2 disease had the greatest odds of disease progression when the CT stage was severe (OR, 4.48; 95% CI: 3.18, 6.31; P < .001) or very severe (OR, 4.72; 95% CI: 3.13, 7.13; P < .001).

Conclusion

Automated CT algorithms can facilitate staging of COPD severity, have diagnostic performance comparable with that of spirometric GOLD staging, and provide further prognostic value when used in conjunction with GOLD staging.Supplemental material is available for this article.© RSNA, 2021See also commentary by Kalra and Ebrahimian in this issue.

Computed tomography based measurements to evaluate lung density and lung growth after congenital diaphragmatic hernia

Emphysema-like-change of lung is one aspect of lung morbidity in children after congenital diaphragmatic hernia (CDH). This study aims to evaluate if the extent of reduced lung density can be quantified through pediatric chest CT examinations, if side differences are present and if emphysema-like tissue is more prominent after CDH than in controls. Thirty-seven chest CT scans of CDH patients (mean age 4.5 ± 4.0 years) were analyzed semi-automatically and compared to an age-matched control group. Emphysema-like-change was defined as areas of lung density lower than - 950 HU in percentage (low attenuating volume, LAV). A p-value lower than 0.05 was regarded as statistically significant. Hypoattenuating lung tissue was more frequently present in the ipsilateral lung than the contralateral side (LAV 12.6% vs. 5.7%; p < 0.0001). While neither ipsilateral nor contralateral lung volume differed between CDH and control (p > 0.05), LAV in ipsilateral (p = 0.0002), but not in contralateral lung (p = 0.54), was higher in CDH than control. It is feasible to quantify emphysema-like-change in pediatric patients after CDH. In the ipsilateral lung, low-density areas are much more frequently present both in comparison to contralateral and to controls. Especially the ratio of LAV ipsilateral/contralateral seems promising as a quantitative parameter in the follow-up after CDH.

Joint Statement of the German Respiratory Society and German Society of Thoracic Surgery in Cooperation with the German Radiological Society: Structural Prerequisites of Centres for Interventional Treatment of Emphysema

Interventional treatment of emphysema offers a wide range of surgical and endoscopic options for patients with advanced disease. Multidisciplinary collaboration of pulmonology, thoracic surgery, and imaging disciplines in patient selection, therapy, and follow-up ensures treatment quality. The present joint statement describes the required structural and quality prerequisites of treatment centres. This is a translation of the German article "Positionspapier der Deutschen Gesellschaft für Pneumologie und Beatmungsmedizin und der Deutschen Gesellschaft für Thoraxchirurgie in Kooperation mit der Deutschen Röntgengesellschaft: Strukturvoraussetzungen von Zentren für die interventionelle Emphysemtherapie" Pneumologie. 2020;74:17-23.

Pulmonary Vascular Volume Estimated by Automated Software is a Mortality Predictor after Acute Pulmonary Embolism

Fundamento:

A embolia pulmonar aguda (EPA) tem desfecho clínico variável. A angiotomografia computadorizada (angio-CT) é considerada o padrão-ouro para o diagnóstico.

Objetivo:

Avaliar se o volume vascular pulmonar (VVP) quantificado por software automatizado é um preditor de mortalidade após EPA.

Métodos:

Estudo de coorte retrospectivo no qual a imagem da angio-CT de 61 pacientes com EPA foi reanalisada. O VVP e o volume pulmonar (VP) foram estimados automaticamente pelo software Yacta. Calculamos o VVP ajustado pela razão: VVP(cm³)/VP(litros). Parâmetros prognósticos clássicos da angio-CT (carga embólica; razão do diâmetro do ventrículo direito/ventrículo esquerdo; razão do diâmetro da artéria pulmonar/aorta; desvio do septo interventricular; infarto pulmonar e refluxo de contraste na veia hepática) foram avaliados. A mortalidade em 1 mês foi o desfecho analisado. Consideramos um valor de p <0,05 como estatisticamente significativo.

Resultados:

Sete mortes (11%) ocorreram entre os 61 pacientes durante 1 mês de seguimento. O VVP ajustado <23cm³/L foi um preditor independente de mortalidade na análise univariada (odds ratio [OR]: 26; intervalo de confiança de 95% [IC95%]: 3-244; p=0,004) e na análise multivariada (OR ajustado: 19 [IC95%: 1,3-270]; p=0,03). Os parâmetros clássicos da angio-CT não foram associados à mortalidade em 1 mês nesta amostra. O VVP ajustado <23cm³/L apresentou sensibilidade de 86%, especificidade de 82%, valor preditivo negativo de 94% e valor preditivo positivo de 64% para identificação dos pacientes que morreram.

Conclusão:

VVP ajustado <23cm³/L foi um preditor independente de mortalidade após EPA. Esse parâmetro mostrou melhor desempenho prognóstico do que os outros achados clássicos da angio-CT. (Arq Bras Cardiol. 2020; 115(5):809-818)

Correlation between quantitative multi-detector computed tomography lung analysis and pulmonary function tests in chronic obstructive pulmonary disease patients

Background

Chronic obstructive pulmonary disease [COPD] is a very common disease in developing as well as in developed countries. Using CT has a growing interest to give a phenotypic classification helping the clinical characterization of COPD patients. So, the aim of the present study was to evaluate whether there was a significant correlation between quantitative computed tomography lung analysis and pulmonary function tests in chronic obstructive pulmonary disease patients.

Results

The study included 50 male patients with a mean age of 62.82 years ± 8.65 years standard deviation [SD]. Significant correlation was found between the pulmonary function tests [FEV1 and FEV1/FVC ratio], and all parameters of quantitative assessment with – 950 HU [the percentage of low-attenuation areas (% LAA)]. Pulmonary function tests according to GOLD [Global Initiative for Chronic Obstructive Lung Disease] guidelines revealed that 4% had normal pulmonary function, 8% had mild obstructive defect, 32% had moderate obstructive defect, 26% had severe obstructive defect, and 30% had very severe obstructive defect.

Conclusion

Automated CT densitometry defining the emphysema severity was significantly correlated with the parameters of pulmonary function tests and providing an alternative, quick, simple, non-invasive study for evaluation of emphysema severity. Its main importance was the determination of the extent and distribution of affected emphysematous parts of the lungs especially for selecting the patients suitable for the lung volume reduction surgery.

Consolidating Lung Volume Reduction Surgery After Endoscopic Lung Volume Reduction Failure

BACKGROUND

Bronchoscopic valve placement constitutes an effective endoscopic lung volume reduction (ELVR) therapy in patients with severe emphysema and low collateral ventilation. After the most destroyed lobe is occluded with valves, significant target lobe volume reduction leads to improvements in lung function, exercise capacity, and quality of life. The effects are not consistent in some patients, leading to long-term therapy failure. We hypothesized that surgical lung volume reduction (LVRS) would reestablish ELVR short-term clinical improvements after ELVR long-term failure.

METHODS

This retrospective single-center analysis included all patients who underwent consolidating LVRS by lobectomy after long-term failure of valve therapy between 2010 and 2015. Changes in forced expiratory volume in 1 second, residual volume, 6-minute walking distance, and Modified Medical Research Council dyspnea score 90 days after ELVR and LVRS were analyzed, and the outcomes of both procedures were compared.

RESULTS

LVRS was performed in 20 patients after ELVR failure. A lower lobectomy was performed in 90%. The 30-day mortality of the cohort was 0% and 90-day mortality was 5% (1 of 20). The remaining 19 patients showed a significant increase in forced expiratory volume in 1 second (+27.5% ± 19.4%) and a reduction in residual volume (-21.0% ± 17.4%) and total lung capacity (-11.1% ± 11.1%). This resulted in significant improvements in exercise tolerance (6-minute walking distance: +56 ± 60 m) and relief of dyspnea (ΔModified Medical Research Council: -1.8 ± 1.4 points.).

CONCLUSIONS

Consolidating LVRS by lobectomy after failure of a previously successful ELVR is feasible and results in significant symptom relief and improvement of lung function.

Long-term exposure to PM10 and NO2 in relation to lung function and imaging phenotypes in a COPD cohort

BACKGROUND

Ambient air pollution can contribute to the development and exacerbation of COPD. However, the influence of air pollution on objective COPD phenotypes, especially from imaging, is not well studied. We investigated the influence of long-term exposure to air pollution on lung function and quantitative imaging measurements in a Korean cohort of participants with and without COPD diagnosis.

METHODS

Study participants (N = 457 including 296 COPD cases) were obtained from the COPD in Dusty Areas (CODA) cohort. Annual average concentrations of particulate matter less than or equal to 10 μm in diameter (PM10) and nitrogen dioxide (NO2) were estimated at the participants' residential addresses using a spatial air pollution prediction model. All the participants underwent volumetric computerized tomography (CT) and spirometry measurements and completed survey questionnaires. We examined the associations of PM10 and NO2 with FVC, FEV1, emphysema index, and wall area percent, using linear regression models adjusting for age, gender, education, smoking, height, weight, and COPD medication.

RESULTS

The age of study participants averaged 71.7 years. An interquartile range difference in annual PM10 exposure of 4.4 μg/m3 was associated with 0.13 L lower FVC (95% confidence interval (CI), - 0.22- -0.05, p = 0.003). Emphysema index (mean = 6.36) was higher by 1.13 (95% CI, 0.25-2.02, p = 0.012) and wall area percent (mean = 68.8) was higher by 1.04 (95% CI, 0.27-1.80, p = 0.008). Associations with imaging phenotypes  were not observed with NO2.

CONCLUSIONS

Long-term exposure to PM10 correlated with both lung function and COPD-relevant imaging phenotypes in a Korean cohort.

Influence of acquisition settings and radiation exposure on CT lung densitometry-An anthropomorphic ex vivo phantom study

Objectives

To systematically evaluate the influence of acquisition settings in conjunction with raw-data based iterative image reconstruction (IR) on lung densitometry based on multi-row detector computed tomography (CT) in an anthropomorphic chest phantom.

Materials and methods

Ten porcine heart-lung explants were mounted in an ex vivo chest phantom shell, six with highly and four with low attenuating chest wall. CT (Somatom Definition Flash, Siemens Healthineers) was performed at 120kV_p and 80kV_p, each combined with current-time products of 120, 60, 30, and 12mAs, and was reconstructed with filtered back projection (FBP) and IR (Safire, Siemens Healthineers). Mean lung density (LD), air density (AD) and noise were measured by semi-automated region-of interest (ROI) analysis, with 120kV_p/120 mAs serving as the standard of reference.

Results

Using IR, noise in lung parenchyma was reduced by ~ 31% at high attenuating chest wall and by ~ 22% at low attenuating chest wall compared to FBP, respectively (p<0.05). IR induced changes in the order of ±1 HU to mean absolute LD and AD compared to corresponding FBP reconstructions which were statistically significant (p<0.05).

Conclusions

Densitometry is influenced by acquisition parameters and reconstruction algorithms to a degree that may be clinically negligible. However, in longitudinal studies and clinical research identical protocols and potentially other measures for calibration may be required.

Quantitative CT Analysis in Patients with Pulmonary Emphysema: Do Calculated Differences Between Full Inspiration and Expiration Correlate with Lung Function?

Purpose

The aim of this retrospective study was to evaluate correlations between parameters of quantitative computed tomography (QCT) analysis, especially the 15th percentile of lung attenuation (P15), and parameters of clinical tests in a large group of patients with pulmonary emphysema.

Patients and Methods

One hundred and seventy-two patients with pulmonary emphysema and chronic obstructive pulmonary disease (COPD) global initiative for chronic obstructive lung disease (GOLD) stage 3 or 4 were assessed by nonenhanced thin-section CT scans in full inspiratory and expiratory breath-hold, pulmonary function test (PFT), a 6-minute walk test (6MWT), and quality of life questionnaires (SGRQ and CAT). QCT parameters included total lung volume (TLV), total emphysema score (TES), and P15, all measured at inspiration (IN) and expiration (EX). Differences between inspiration and expiration were calculated for TLV (TLV_Diff), TES (TES_Diff), and P15 (P15_Diff). Spearman correlation analysis was performed.

Results

CT-measured lung volume in inspiration (TLV_IN) correlated strongly with spirometry-measured total lung capacity (TLC) (r=0.81, p<0.001) and moderately to strongly with residual volume (RV), forced vital capacity (FVC), and forced expiratory volume in 1 second (FEV₁)/FVC (r=0.60, 0.56, and −0.49, each p<0.001). Lung volume in expiration (TLV_EX) correlated moderately to strongly with TLC, RV and FEV₁/FVC ratio (r=0.75, 0.66, and −0.43, each p<0.001). TES and P15 showed stronger correlations with the carbon monoxide transfer coefficient (KCO%) (r= −0.42, 0.44, both p<0.001), when measured during expiration. P15_Diff correlated moderately with KCO% and carbon monoxide diffusing capacity (DLCO%) (r= 0.41, 0.40, both p<0.001). The 6MWT and most QCT parameters showed significant differences between COPD GOLD 3 and 4 groups.

Conclusion

Our results suggest that QCT can help predict the severity of lung function decrease in patients with pulmonary emphysema and COPD GOLD 3 or 4. Some QCT parameters, including P15_EX and P15_Diff, correlated moderately to strongly with parameters of pulmonary function tests.

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.

Automatic Quantitative Computed Tomography Evaluation of the Lungs in Patients With Systemic Sclerosis Treated With Autologous Stem Cell Transplantation

BACKGROUND/OBJECTIVE

Interstitial lung disease stands among the leading causes of death in systemic sclerosis (SSc) patients. Autologous hematopoietic stem cell transplantation (AHSCT) has been proven superior to conventional immunosuppressive therapy in severe and progressive SSc. Here, pulmonary quantitative measurements were obtained in high-resolution computed tomography (HRCT) scans of patients with SSc before and after AHSCT.

METHODS

The medical records of thirthy-three patients who underwent AHSCT between 2011 and 2017 were evaluated for clinical and tomographic features at baseline (pre-AHCST) and 18 months after the procedure. Quantitative analysis of HRCT images by a fully automated program calculated lung volumes, densities, attenuation percentiles, and vascular volume. Patients were divided into 2 groups, according to changes in forced vital capacity (FVC). The "best response" group included patients that had an increased FVC of 10% or greater, and the "stable response" group included those who had a decreased or an increased FVC of less than 10%.

RESULTS

In the best response group (15 patients), there was reduction (p < 0.05) of mean lung density and density percentile values after AHSCT. In the stable response group (18 patients), there were no significant changes in lung volumes and pulmonary densities after AHSCT. Pulmonary HRCT densities showed moderate/strong correlation with function.

CONCLUSIONS

Quantitative HRCT analysis identified significant reduction in pulmonary densities in patients with improved pulmonary function after AHSCT. Lung density, as evaluated by the quantitative HRCT analysis tool, has potential to become a biomarker in the evaluation of interstitial lung disease treatment in patients with SSc.

Workflow-centred open-source fully automated lung volumetry in chest CT

AIM

To develop a robust open-source method for fully automated extraction of total lung capacity (TLC) from computed tomography (CT) images and to demonstrate its integration into the clinical workflow.

MATERIALS AND METHODS

Using only open-source software, an algorithm was developed based on a region-growing method that does not require manual interaction. Lung volumes calculated from reconstructions with different kernels (TLC_CT) were assessed. To validate the algorithm calculations, the results were correlated to TLC measured by pulmonary function testing (TLC_PFT) in a subgroup of patients for which this information was available within 3 days of the CT examination.

RESULTS

A total of 288 patients were analysed retrospectively. Manual review revealed poor segmentation results in 13 (4.5%) patients. In the validation subgroup, the correlation between TLC_CT and TLC_PFT was r=0.87 (p<0.001). Measurements showed excellent agreement between the two reconstruction kernels with an intraclass correlation coefficient (ICC) of 0.99. Calculation of the volumes took an average of 5 seconds (standard deviation: 3.72 seconds). Integration of the algorithm into the departments of the PACS environment was successful. A DICOM-encapsulated PDF document with measurements and an overlay of the segmentation results was sent to the PACS to allow the radiologists to detect false measurements.

CONCLUSIONS

The algorithm developed allows fast and fully automated calculation of lung volume without any additional input from the radiologist. The algorithm delivers excellent segmentation in >95% of cases with significant positive correlations between lung volume on CT and TLC on PFT.

Interventional therapy in patients with severe emphysema: evaluation of contraindications and their incidence

Background:

Endoscopic and surgical interventions may be beneficial for selected patients with emphysema. Rates of treatment failure decrease when the predictors for successful therapy are known. The aim of the study was to evaluate the number of patients with severe emphysema who were not eligible for any intervention, and the reasons for their exclusion.

Methods:

The study was a retrospective analysis of 231 consecutive patients with advanced emphysema who were considered for interventional therapy in 2016 at the Thoraxklinik, Heidelberg, Germany. The reasons for not receiving valve or coil therapy were assessed for all patients who did not receive any therapy.

Results:

Of the 231 patients, 50% received an interventional therapy for lung volume reduction (LVR) (82% valve therapy, 6% coil therapy, 4.3% polymeric LVR or bronchial thermal vapour ablation, 4.3% total lung denervation, and 3.4% lung volume reduction surgery [LVRS]). A total of 115 patients did not undergo LVR. Out of these, valve or coil therapy was not performed due to one or more of the following reasons: incomplete fissure in 37% and 0%; missing target lobe in 31% and 30%; personal decision in 18% and 28%; pulmonary function test results in 8% and 15%; ventilatory failure in 4% and 4%; missing optimal standard medical care and/or continued nicotine abuse in 4% and 3%; general condition too good in less than 1% and 3%; cardiovascular comorbidities in 0% and 3%; age of patient in 0% and less than 1%. Both techniques were not performed due to one or more of the following reasons: solitary pulmonary nodule(s)/consolidation in 27%; bronchopathy in 7%; neoplasia in 2%; destroyed lung in 2%; prior LVRS in less than 1%.

Conclusions:

The main reason for not placing valves was an incomplete fissure and for coils a missing target lobe. Numerous additional contraindications that may exclude a patient from interventional emphysema therapy should be respected.

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.

Quantitative CT analysis in patients with pulmonary emphysema: is lung function influenced by concomitant unspecific pulmonary fibrosis?

Purpose

Quantitative analysis of CT scans has proven to be a reproducible technique, which might help to understand the pathophysiology of chronic obstructive pulmonary disease (COPD) and combined pulmonary fibrosis and emphysema. The aim of this retrospective study was to find out if the lung function of patients with COPD with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages III or IV and pulmonary emphysema is measurably influenced by high attenuation areas as a correlate of concomitant unspecific fibrotic changes of lung parenchyma.

Patients and methods

Eighty-eight patients with COPD GOLD stage III or IV underwent CT and pulmonary function tests. Quantitative CT analysis was performed to determine low attenuation volume (LAV) and high attenuation volume (HAV), which are considered to be equivalents of fibrotic (HAV) and emphysematous (LAV) changes of lung parenchyma. Both parameters were determined for the whole lung, as well as peripheral and central lung areas only. Multivariate regression analysis was used to correlate HAV with different parameters of lung function.

Results

Unlike LAV, HAV did not show significant correlation with parameters of lung function. Even in patients with a relatively high HAV of more than 10%, in contrast to HAV (p=0.786) only LAV showed a significantly negative correlation with forced expiratory volume in 1 second (r=−0.309, R²=0.096, p=0.003). A severe decrease of DLCO% was associated with both larger HAV (p=0.045) and larger LAV (p=0.001). Residual volume and FVC were not influenced by LAV or HAV.

Conclusion

In patients with COPD GOLD stage III-IV, emphysematous changes of lung parenchyma seem to have such a strong influence on lung function, which is a possible effect of concomitant unspecific fibrosis is overwhelmed.

Role of Quantitative Computed Tomographic Scan Analysis in Lung Volume Reduction for Emphysema

Recent advances in bronchoscopic lung volume reduction (BLVR) offer new therapeutic alternatives for patients with emphysema and hyperinflation. Endobronchial valves and coils are 2 potential BLVR techniques which have been shown to improve pulmonary function and the quality of life in patients with emphysema. Current patient selection for LVR procedures relies on 3 main inclusion criteria: low attenuation area (in %), also known as emphysema score, heterogeneity score, and fissure integrity score. Volumetric analysis in combination with densitometric analysis of the affected lung lobe or segment with quantitative CT to determine emphysema severity play an important role in treatment planning and post-operative assessment. Due to the variations in lung anatomy, manual corrections are often required to ensure successful and accurate lobe segmentation for pathological and post-treatment CT scan analysis. The advanced development and utilisation of quantitative CT do not simply represent regional changes in pulmonary function but aids in analysis for better patient selection with severe emphysema who are most likely to benefit from BLVR.

Regional lung densities in alpha-1 antitrypsin deficiency compared to predicted values

Background

We developed a method to calculate a standard score for lung tissue mass derived from CT scan images from a control group without respiratory disease. We applied the method to images from subjects with emphysema associated with alpha-1 antitrypsin deficiency (AATD) and used it to study regional patterns of differential tissue mass.

Methods

We explored different covariates in 76 controls. Standardization was applied to facilitate comparability between different CT scanners and a standard Z-score (Standard Mass Score, SMS) was developed, representing lung tissue loss compared to normal lung mass. This normative data was defined for the entire lungs and for delineated apical, central and basal regions. The agreement with D_LCO%pred was explored in a data set of 180 patients with emphysema who participated in a trial of alpha-1-antitrypsin augmentation treatment (RAPID).

Results

Large differences between emphysematous and normal tissue of more than 10 standard deviations were found. There was reasonable agreement between SMS and D_LCO%pred for the global densitometry (κ = 0.252, p < 0.001), varying from κ = 0.138 to κ = 0.219 and 0.264 (p < 0.001), in the apical, central and basal region, respectively. SMS and D_LCO%pred correlated consistently across apical, central and basal regions. The SMS distribution over the different lung regions showed a distinct pattern suggesting that emphysema due to severe AATD develops from basal to central and ultimately apical regions.

Conclusions

Standardization and normalization of lung densitometry is feasible and the adoption of the developed principles helps to characterize the distribution of emphysema, required for clinical decision making.

Electronic supplementary material

The online version of this article (10.1186/s12931-019-1012-3) contains supplementary material, which is available to authorized users.

Advanced pulmonary MRI to quantify alveolar and acinar duct abnormalities: Current status and future clinical applications

There are serious clinical gaps in our understanding of chronic lung disease that require novel, sensitive, and noninvasive in vivo measurements of the lung parenchyma to measure disease pathogenesis and progressive changes over time as well as response to treatment. Until recently, our knowledge and appreciation of the tissue changes that accompany lung disease has depended on ex vivo biopsy and concomitant histological and stereological measurements. These measurements have revealed the underlying pathologies that drive lung disease and have provided important observations about airway occlusion, obliteration of the terminal bronchioles and airspace enlargement, or fibrosis and their roles in disease initiation and progression. ex vivo tissue stereology and histology are the established gold standards and, more recently, micro-computed tomography (CT) measurements of ex vivo tissue samples has also been employed to reveal new mechanistic findings about the progression of obstructive lung disease in patients. While these approaches have provided important understandings using ex vivo analysis of excised samples, recently developed hyperpolarized noble gas MRI methods provide an opportunity to noninvasively measure acinar duct and terminal airway dimensions and geometry in vivo, and, without radiation burden. Therefore, in this review we summarize emerging pulmonary MRI morphometry methods that provide noninvasive in vivo measurements of the lung in patients with bronchopulmonary dysplasia and chronic obstructive pulmonary disease, among others. We discuss new findings, future research directions, as well as clinical opportunities to address current gaps in patient care and for testing of new therapies. Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;50:28-40.

Longitudinal airway remodeling in active and past smokers in a lung cancer screening population

OBJECTIVES

To longitudinally investigate smoking cessation-related changes of quantitative computed tomography (QCT)-based airway metrics in a group of heavy smokers.

METHODS

CT scans were acquired in a lung cancer screening population over 4 years at 12-month intervals in 284 long-term ex-smokers (ES), 405 continuously active smokers (CS), and 31 subjects who quitted smoking within 2 years after baseline CT (recent quitters, RQ). Total diameter (TD), lumen area (LA), and wall percentage (WP) of 1st-8th generation airways were computed using airway analysis software. Inter-group comparison was performed using Mann-Whitney U test or Student's t test (two groups), and ANOVA or ANOVA on ranks with Dunn's multiple comparison test (more than two groups), while Fisher's exact test or chi-squared test was used for categorical data. Multiple linear regression was used for multivariable analysis.

RESULTS

At any time, TD and LA were significantly higher in ES than CS, for example, in 5th-8th generation airways at baseline with 6.24 mm vs. 5.93 mm (p < 0.001) and 15.23 mm² vs. 13.51 mm² (p < 0.001), respectively. RQ showed higher TD (6.15 mm vs. 5.93 mm, n.s.) and significantly higher LA (14.77 mm² vs. 13.51 mm², p < 0.001) than CS after 3 years, and after 4 years. In multivariate analyses, smoking status independently predicted TD, LA, and WP at baseline, at 3 years and 4 years (p < 0.01-0.001), with stronger impact than pack years.

CONCLUSIONS

Bronchial dimensions depend on the smoking status. Smoking-induced airway remodeling can be partially reversible after smoking cessation even in long-term heavy smokers. Therefore, QCT-based airway metrics in clinical trials should consider the current smoking status besides pack years.

KEY POINTS

• Airway lumen and diameter are decreased in active smokers compared to ex-smokers, and there is a trend towards increased airway wall thickness in active smokers. • Smoking-related airway changes improve within 2 years after smoking cessation. • Smoking status is an independent predictor of airway dimensions.

Time-series hyperpolarized xenon-129 MRI of lobar lung ventilation of COPD in comparison to V/Q-SPECT/CT and CT

Purpose

To derive lobar ventilation in patients with chronic obstructive pulmonary disease (COPD) using a rapid time-series hyperpolarized xenon-129 (HPX) magnetic resonance imaging (MRI) technique and compare this to ventilation/perfusion single-photon emission computed tomography (V/Q-SPECT), correlating the results with high-resolution computed tomography (CT) and pulmonary function tests (PFTs).

Materials and methods

Twelve COPD subjects (GOLD stages I–IV) participated in this study and underwent HPX-MRI, V/Q-SPECT/CT, high-resolution CT, and PFTs. HPX-MRI was performed using a novel time-series spiral k-space sampling approach. Relative percentage ventilations were calculated for individual lobe for comparison to the relative SPECT lobar ventilation and perfusion. The absolute HPX-MRI percentage ventilation in each lobe was compared to the absolute CT percentage emphysema score calculated using a signal threshold method. Pearson’s correlation and linear regression tests were performed to compare each imaging modality.

Results

Strong correlations were found between the relative lobar percentage ventilation with HPX-MRI and percentage ventilation SPECT (r = 0.644; p < 0.001) and percentage perfusion SPECT (r = 0.767; p < 0.001). The absolute CT percentage emphysema and HPX percentage ventilation correlation was also statistically significant (r = 0.695, p < 0.001). The whole lung HPX percentage ventilation correlated with the PFT measurements (FEV₁ with r = − 0.886, p < 0.001*, and FEV₁/FVC with r = − 0.861, p < 0.001*) better than the whole lung CT percentage emphysema score (FEV₁ with r = − 0.635, p = 0.027; and FEV₁/FVC with r = − 0.652, p = 0.021).

Conclusion

Lobar ventilation with HPX-MRI showed a strong correlation with lobar ventilation and perfusion measurements derived from SPECT/CT, and is better than the emphysema score obtained with high-resolution CT.

Key Points

• The ventilation hyperpolarized xenon-129 MRI correlates well with ventilation and perfusion with SPECT/CT with the advantage of higher temporal and spatial resolution.

• The hyperpolarized xenon-129 MRI correlates with the PFT measurements better than the high-resolution CT with the advantage of avoiding the use of ionizing radiation.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5888-y) contains supplementary material, which is available to authorized users.

GOLD stage predicts thoracic aortic calcifications in patients with COPD

Although some of the associations between chronic obstructive pulmonary disease (COPD) and atherosclerosis are based on shared risk factors such as smoking, recent epidemiological evidence suggests that COPD is a risk factor for vascular disease due to systemic inflammation. The present study assessed the hypothesis that disease severity (as expressed by the GOLD stage) independently predicts the extent of vascular calcifications. A total of 160 smokers diagnosed with COPD (GOLD I-IV, 40 subjects of each GOLD stage) and 40 smokers at risk (GOLD 0; median age of 60 years old; Q1:56;Q3:65; 135 males and 65 females) underwent non-contrast, non-electrocardiography synchronized chest computerised tomography. The volume of thoracic aortic calcifications was quantified semi-automatically within a region from T1 through T12. Multiparametric associations with GOLD stage, smoking history, sex, age, body mass index and emphysema index were evaluated using generalized linear regression analysis. Thoracic aortic calcifications were highly prevalent in this cohort (187/200 subjects, 709 (Q1:109;Q3:2163) mm³). Analysis of variance on ranks demonstrated a significant difference in calcium between different GOLD-stages as well as patients at risk of COPD (F=36.8, P<0.001). In the multivariable analysis, GOLD-stages were indicated to be predictive of thoracic aortic calcifications (P≤0.0033) besides age (P<0.0001), while age appeared to be the strongest predictor. Other variables were not statistically linked to thoracic aortic calcifications in the multivariable model. COPD severity, as expressed by the GOLD-stage, is a significant predictor of thoracic aortic calcifications, independent of covariates such as age or tobacco consumption.

Quantitative CT detects changes in airway dimensions and air-trapping after bronchial thermoplasty for severe asthma

OBJECTIVES

Bronchial thermoplasty (BT) can be considered in the treatment of severe asthma to reduce airway smooth muscle mass and bronchoconstriction. We hypothesized that BT may thus have long-term effects on airway dimensions and air-trapping detectable by quantitative computed tomography (QCT).

METHODS

Paired in- and expiratory CT and inspiratory CT were acquired in 17 patients with severe asthma before and up to two years after bronchial thermoplasty and in 11 additional conservatively treated patients with serve asthma, respectively. A fully automatic software calculated the airways metrics for wall thickness (WT), wall percentage (WP), lumen area (LA) and total diameter (TD). Furthermore, lung air-trapping was quantified by determining the quotient of mean lung attenuation in expiration vs. inspiration (E/I MLA) and relative volume change in the Hounsfield interval -950 to -856 in expiration to inspiration (RVC_856-950) in a generation- and lobe-based approach, respectively.

RESULTS

BT reduced WT for the combined analysis of the 2nd-7th airway generation significantly by 0.06 mm (p = 0.026) and WP by 2.05% (p < 0.001), whereas LA and TD did not change significantly (p = 0.147, p = 0.706). No significant changes were found in the control group. Furthermore, E/I MLA and RVC_856-950 decreased significantly after BT by 12.65% and 1.77% (p < 0.001), respectively.

CONCLUSION

BT significantly reduced airway narrowing and air-trapping in patients with severe asthma. This can be interpreted as direct therapeutic effects caused by a reduction in airway-smooth muscle mass and changes in innervation. A reduction in air-trapping indicates an influence on more peripheral airways not directly treated by the BT procedure.

Endoscopic approaches for treating emphysema

INTRODUCTION

Surgical treatment of severe pulmonary emphysema has so far been associated with relatively high perioperative morbidity and mortality. In the past two decades, novel approaches to lung volume reduction and alternative minimally invasive endoscopic techniques have been developed. This review presents the different techniques (blocking and nonblocking) available until present as well as the appropriate patient selection and possible complications. Areas covered: All available randomized controlled trials (RCTs) have been evaluated. The only blocking technique is the reversible valve implantation. It results in lobar volume reduction and clinical benefit in emphysema patients with absent interlobar collateral ventilation and its efficacy has been confirmed in various RCTs. Non-blocking techniques that are independent of collateral ventilation include the partially irreversible coil implantation leading to parenchymal compression, the irreversible bronchoscopic thermal vapor ablation, and the polymeric lung volume reduction both inducing inflammatory reaction. These methods have been up to date examined in a few RCTs only. Finally, the targeted lung denervation aims at sustainable bronchodilation by ablation of parasympathetic pulmonary nerves. Expert commentary: Future studies must address the predictors of clinical outcome as well as the reduction of complications to improve both outcome and safety.

Relationship of spirometric, body plethysmographic, and diffusing capacity parameters to emphysema scores derived from CT scans

Phenotyping of chronic obstructive pulmonary disease (COPD) with computed tomography (CT) is used to distinguish between emphysema- and airway-dominated type. The phenotype is reflected in correlations with lung function measures. Among these, the relative value of body plethysmography has not been quantified. We addressed this question using CT scans retrospectively collected from clinical routine in a large COPD cohort. Three hundred and thirty five patients with baseline data of the German COPD cohort COPD and Systemic Consequences-Comorbidities Network were included. CT scans were primarily evaluated using a qualitative binary emphysema score. The binary score was positive for emphysema in 52.5% of patients, and there were significant differences between the positive/negative groups regarding forced expiratory volume in 1 second (FEV₁), FEV₁/forced vital capacity (FVC), intrathoracic gas volume (ITGV), residual volume (RV), specific airway resistance (sRaw), transfer coefficient (KCO), transfer factor for carbon monoxide (TLCO), age, pack-years, and body mass index (BMI). Stepwise discriminant analyses revealed the combination of FEV₁/FVC, RV, sRaw, and KCO to be significantly related to the binary emphysema score. The additional positive predictive value of body plethysmography, however, was only slightly higher than that of the conventional combination of spirometry and diffusing capacity, which if taken alone also achieved high predictive values, in contrast to body plethysmography. The additional information on the presence of CT-diagnosed emphysema as conferred by body plethysmography appeared to be minor compared to the well-known combination of spirometry and CO diffusing capacity.

Validation of automated lobe segmentation on paired inspiratory-expiratory chest CT in 8-14 year-old children with cystic fibrosis

Objectives

Densitometry on paired inspiratory and expiratory multidetector computed tomography (MDCT) for the quantification of air trapping is an important approach to assess functional changes in airways diseases such as cystic fibrosis (CF). For a regional analysis of functional deficits, an accurate lobe segmentation algorithm applicable to inspiratory and expiratory scans is beneficial.

Materials and methods

We developed a fully automated lobe segmentation algorithm, and subsequently validated automatically generated lobe masks (ALM) against manually corrected lobe masks (MLM). Paired inspiratory and expiratory CTs from 16 children with CF (mean age 11.1±2.4) acquired at 4 time-points (baseline, 3mon, 12mon, 24mon) with 2 kernels (B30f, B60f) were segmented, resulting in 256 ALM. After manual correction spatial overlap (Dice index) and mean differences in lung volume and air trapping were calculated for ALM vs. MLM.

Results

The mean overlap calculated with Dice index between ALM and MLM was 0.98±0.02 on inspiratory, and 0.86±0.07 on expiratory CT. If 6 lobes were segmented (lingula treated as separate lobe), the mean overlap was 0.97±0.02 on inspiratory, and 0.83±0.08 on expiratory CT. The mean differences in lobar volumes calculated in accordance with the approach of Bland and Altman were generally low, ranging on inspiratory CT from 5.7±52.23cm³ for the right upper lobe to 17.41±14.92cm³ for the right lower lobe. Higher differences were noted on expiratory CT. The mean differences for air trapping were even lower, ranging from 0±0.01 for the right upper lobe to 0.03±0.03 for the left lower lobe.

Conclusions

Automatic lobe segmentation delivers excellent results for inspiratory and good results for expiratory CT. It may become an important component for lobe-based quantification of functional deficits in cystic fibrosis lung disease, reducing necessity for user-interaction in CT post-processing.

Use of computed tomography and automated software for quantitative analysis of the vasculature of patients with pulmonary hypertension

Objective

To perform a quantitative analysis of the lung parenchyma and pulmonary vasculature of patients with pulmonary hypertension (PH) on computed tomography angiography (CTA) images, using automated software.

Materials and Methods

We retrospectively analyzed the CTA findings and clinical records of 45 patients with PH (17 males and 28 females), in comparison with a control group of 20 healthy individuals (7 males and 13 females); the mean age differed significantly between the two groups (53 ± 14.7 vs. 35 ± 9.6 years; p = 0.0001).

Results

The automated analysis showed that, in comparison with the controls, the patients with PH showed lower 10th percentile values for lung density, higher vascular volumes in the right upper lung lobe, and higher vascular volume ratios between the upper and lower lobes. In our quantitative analysis, we found no differences among the various PH subgroups. We inferred that a difference in the 10th percentile values indicates areas of hypovolemia in patients with PH and that a difference in pulmonary vascular volumes indicates redistribution of the pulmonary vasculature and an increase in pulmonary vasculature resistance.

Conclusion

Automated analysis of pulmonary vessels on CTA images revealed alterations and could represent an objective diagnostic tool for the evaluation of patients with PH.

Diagnostic Value of Quantitative Chest CT Scan in a Case of Spontaneous Pneumothorax

An 18-year-old woman with no previous medical history presented to an outside hospital facility with acute chest pain. She had mild shortness of breath, particularly with exertion, for the prior 2 months.

Lung densitometry: why, how and when

Lung densitometry assesses with computed tomography (CT) the X-ray attenuation of the pulmonary tissue which reflects both the degree of inflation and the structural lung abnormalities implying decreased attenuation, as in emphysema and cystic diseases, or increased attenuation, as in fibrosis. Five reasons justify replacement with lung densitometry of semi-quantitative visual scales used to measure extent and severity of diffuse lung diseases: (I) improved reproducibility; (II) complete vs. discrete assessment of the lung tissue; (III) shorter computation times; (IV) better correlation with pathology quantification of pulmonary emphysema; (V) better or equal correlation with pulmonary function tests (PFT). Commercially and open platform software are available for lung densitometry. It requires attention to technical and methodological issues including CT scanner calibration, radiation dose, and selection of thickness and filter to be applied to sections reconstructed from whole-lung CT acquisition. Critical is also the lung volume reached by the subject at scanning that can be measured in post-processing and represent valuable information per se. The measurements of lung density include mean and standard deviation, relative area (RA) at -970, -960 or -950 Hounsfield units (HU) and 1st and 15th percentile for emphysema in inspiratory scans, and RA at -856 HU for air trapping in expiratory scans. Kurtosis and skewness are used for evaluating pulmonary fibrosis in inspiratory scans. The main indication for lung densitometry is assessment of emphysema component in the single patient with chronic obstructive pulmonary diseases (COPD). Additional emerging applications include the evaluation of air trapping in COPD patients and in subjects at risk of emphysema and the staging in patients with lymphangioleiomyomatosis (LAM) and with pulmonary fibrosis. It has also been applied to assess prevalence of smoking-related emphysema and to monitor progression of smoking-related emphysema, alpha1 antitrypsin deficiency emphysema, and pulmonary fibrosis. Finally, it is recommended as end-point in pharmacological trials of emphysema and lung fibrosis.

Influence of fissure integrity on quantitative CT and emphysema distribution in emphysema-type COPD using a dedicated COPD software

OBJECTIVES

Fissure integrity (FI) plays a key role in selecting patients for interventional emphysema therapy. We investigated its interference with automated lobar segmentation in quantitative computed tomography (CT) and emphysema distribution.

METHODS

CT was available for 50 patients with chronic obstructive pulmonary disease (COPD). Lobe segmentation was performed fully automated by software and corrected manually. FI was evaluated visually using a %-scale. The influence of FI on emphysema ratio (ER=percentage of lung volume with density values<-950 HU), mean lung density (MLD), emphysema and total volume of adjacent lobes was analyzed. Lobe-based results were compared with respect to FI.

RESULTS

Differences in ER in adjacent lobes for complete vs. incomplete fissures were 12.4% for the right horizontal, 0.2% and 3% for the right oblique and 4.4% for the left oblique fissure (all p>0.05). Results for emphysema comparing automated vs. manually corrected segmentation exceeded clinically acceptable values, but were not significantly affected by FI (p>0.05). The widest limits of agreement for ER and MLD were noted in the right middle lobe ([-14, 17.4%], [-22.4, 32.4 Hounsfield Units]).

CONCLUSIONS

Automated lobe segmentation and emphysema distribution are not significantly affected by FI. Manual correction of automated lobar segmentation is still recommended in severe emphysema.

Texture-based Quantification of Centrilobular Emphysema and Centrilobular Nodularity in Longitudinal CT Scans of Current and Former Smokers

RATIONALE AND OBJECTIVES

The effect of smoking cessation on centrilobular emphysema (CLE) and centrilobular nodularity (CN), two manifestations of smoking-related lung injury on computed tomography (CT) images, has not been clarified. The objective of this study is to leverage texture analysis to investigate differences in extent of CLE and CN between current and former smokers.

MATERIALS AND METHODS

Chest CT scans from 350 current smokers, 401 former smokers, and 25 control subjects were obtained from the multicenter COPDGene Study, a Health Insurance Portability and Accountability Act-compliant study approved by the institutional review board of each participating clinical study center. Additionally, for 215 of these subjects, a follow-up CT scan was obtained approximately 5 years later. For each CT scan, 5000 circular regions of interest (ROIs) of 35-pixel diameter were randomly selected throughout the lungs. The patterns present in each ROI were summarized by 50 computer-extracted texture features. A logistic regression classifier was leveraged to classify each ROI as normal lung, CLE, or CN, and differences in the percentages of normal lung, CLE, and CN by study group were assessed.

RESULTS

Former smokers had significantly more CLE (P <0.01) but less CN (P <0.001) than did current smokers, even after adjustment for important covariates such as patient age, GOLD stage, smoking history, forced expiratory volume in 1 second, gas trapping, and scanner model. Among patients with longitudinal CT scans, continued smoking led to a slight increase in CLE (P = 0.13), whereas sustained abstinence from smoking led to further reduction in CN (P <0.05).

CONCLUSIONS

The proposed texture-based approach quantifies the extent of CN and CLE with high precision. Differences in smoking-related lung disease between longitudinal scans of current smokers and longitudinal scans of former smokers suggest that CN may be reversible on smoking cessation.