Quantitative computed tomography measurements to evaluate airway disease in chronic obstructive pulmonary disease: Relationship to physiological measurements, clinical index and visual assessment of airway disease

Advances in COPD imaging using CT and MRI: linkage with lung physiology and clinical outcomes

Recent years have witnessed major advances in lung imaging in patients with COPD. These include significant refinements in images obtained by computed tomography (CT) scans together with the introduction of new techniques and software that aim for obtaining the best image whilst using the lowest possible radiation dose. Magnetic resonance imaging (MRI) has also emerged as a useful radiation-free tool in assessing structural and more importantly functional derangements in patients with well-established COPD and smokers without COPD, even before the existence of overt changes in resting physiological lung function tests. Together, CT and MRI now allow objective quantification and assessment of structural changes within the airways, lung parenchyma and pulmonary vessels. Furthermore, CT and MRI can now provide objective assessments of regional lung ventilation and perfusion, and multinuclear MRI provides further insight into gas exchange; this can help in structured decisions regarding treatment plans. These advances in chest imaging techniques have brought new insights into our understanding of disease pathophysiology and characterising different disease phenotypes. The present review discusses, in detail, the advances in lung imaging in patients with COPD and how structural and functional imaging are linked with common resting physiological tests and important clinical outcomes.

Correlation Between HIF1-A Expression and Airway Remodeling in COPD

Background

Airway remodeling is a significant pathological characteristic of chronic obstructive pulmonary disease (COPD). In recent years, hypoxia-inducible factor 1-α (HIF-1α), a member of the hypoxia-inducible factor protein family, has gained attention. However, the potential correlation between HIF-1α and COPD airway remodeling remains unclear.

Objective

This study explored the expression patterns of HIF-1α in patients with COPD and its association with airway remodelling. This investigation aims to furnish novel insights for the clinical identification of prospective therapeutic targets for ameliorating COPD-related airway remodelling.

Patients and Methods

A total of 88 subjects were included, consisting of 28 controls and 60 COPD patients. Various staining methods were employed to observe the pathological changes in airway tissues. Immunohistochemistry was utilized to detect the expression of HIF-1α and MMP9 (matrix metalloproteinase 9) in airway tissues. Enzyme-linked immunosorbent assay (ELISA) was used to measure the concentration in serum of HIF-1α and MMP9. Computed tomography (CT) airway parameters were measured in all participants to assess airway remodeling. The relationship between serum HIF-1α and MMP9 concentrations and airway parameters was analyzed.

Results

Staining of airway structures in COPD patients revealed significant pathological changes associated with airway remodelling, including mixed cilia and subepithelial fibrosis. The expression of HIF-1α and MMP9 was significantly higher in both human airway tissue and serum compared to controls. Chest CT scans exhibited typical imaging features of airway remodeling and increased airway parameters.

Conclusion

The findings suggest a correlation between increased HIF-1α expression and COPD airway remodelling. This study provides novel evidence that HIF-1α may be a potential biomarker for airway remodelling in COPD patients.

Clinical evaluation of pulmonary quantitative computed tomography parameters for diagnosing eosinophilic chronic obstructive pulmonary disease: Characteristics and diagnostic performance

Aims

To investigate the characteristics and diagnostic performance of quantitative computed tomography (QCT) parameters in eosinophilic chronic obstructive pulmonary disease (COPD) patients.

Methods

High-resolution CT scans of COPD patients were retrospectively analyzed, and various emphysematous parenchyma measurements, including lung volume (LC), lung mean density (LMD), lung standard deviation (LSD), full-width half maximum (FWHM), and lung relative voxel number (LRVN) were performed. The QCT parameters were compared between eosinophilic and noneosinophilic COPD patients, using a definition of eosinophilic COPD as blood eosinophil values ≥ 300 cells·µL-1 on at least three times. Receiver operating characteristic curves and area under the curve (ROC-AUC) and python were used to evaluate discriminative efficacy of QCT.

Results

Noneosinophilic COPD patients had a significantly lower TLMD (-846.3 ± 47.9 Hounsfield Unit [HU]) and TFWHM(162.5 ± 30.6 HU) compared to eosinophilic COPD patients (-817.8 ± 54.4, 177.3 ± 33.1 HU, respectively) (p = 0.018, 0.03, respectively). Moreover, the total LC (TLC) and TLSD were significantly lower in eosinophilic COPD group (3234.4 ± 1145.8, 183.8 ± 33.9 HU, respectively) than the noneosinophilic COPD group (5600.2 ± 1248.4, 203.5 ± 20.4 HU, respectively) (p = 0.009, 0.002, respectively). The ROC-AUC values for TLC, TLMD, TLSD, and TFWHM were 0.91 (95% confidence interval [CI], 0.828-0.936), 0.66 (95% CI, 0.546-0.761), 0.64 (95% CI, 0.524-0.742), and 0.63 (95% CI, 0.511-0.731), respectively. When the TLC value was 4110 mL, the sensitivity was 90.7% (95% CI, 79.7-96.9), specificity was 77.8% (95% CI, 57.7-91.4) and accuracy was 86.4%. Notably, TLC demonstrated the highest discriminative efficiency with an F1 Score of 0.79, diagnostic Odds Ratio of 34.3 and Matthews Correlation Coefficient of 0.69, surpassing TLMD (0.55, 3.66, 0.25), TLSD (0.56, 3.95, 0.26), and TFWHM (0.56, 4.16, 0.33).

Conclusion

Eosinophilic COPD patients exhibit lower levels of emphysema and a more uniform density distribution throughout the lungs compared to noneosinophilic COPD patients. Furthermore, TLC demonstrated the highest diagnostic efficiency and may serve as a valuable diagnostic marker for distinguishing between the two groups.

COPD: pulmonary vascular volume associated with cardiac structure and function

BACKGROUND

Early recognition of cardiac dysfunction in patients with chronic obstructive pulmonary disease (COPD) may prevent future cardiac impairment and improve prognosis. Quantitative assessment of subsegmental and segmental vessel volume by Computed Tomographic (CT) imaging can provide a surrogate of pulmonary vascular remodeling. We aimed to examine the relationship between lung segmental- and subsegmental vessel volume, and echocardiographic measures of cardiac structure and function in patients with COPD.

METHODS

We studied 205 participants with COPD, included in a large cohort study of cardiovascular disease in COPD patients. Participants had an available CT scan and echocardiogram. Artificial intelligence (AI) algorithms calculated the subsegmental vessel fraction as the vascular volume in vessels below 10 mm2 in cross-sectional area, indexed to total intrapulmonary vessel volume. Linear regressions were conducted, and standardized ß-coefficients were calculated. Scatterplots were created to visualize the continuous correlations between the vessel fractions and echocardiographic parameters.

RESULTS

We found that lower subsegmental vessel fraction and higher segmental vessel volume were correlated with higher left ventricular (LV) mass, LV diastolic dysfunction, and inferior vena cava (IVC) dilatation. Subsegmental vessel fraction was correlated with right ventricular (RV) remodeling, while segmental vessel fraction was correlated with higher pulmonary pressure. Measures of LV mass and right atrial pressure displayed the strongest correlations with pulmonary vasculature measures.

CONCLUSION

Pulmonary vascular remodeling in patients with COPD, may negatively affect cardiac structure and function. AI-identified remodeling in pulmonary vasculature may provide a tool for early identification of COPD patients at higher risk for cardiac impairment.

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.

Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction

OBJECTIVES

Quantitative CT imaging is an important emphysema biomarker, especially in smoking cohorts, but does not always correlate to radiologists' visual CT assessments. The objectives were to develop and validate a neural network-based slice-wise whole-lung emphysema score (SWES) for chest CT, to validate SWES on unseen CT data, and to compare SWES with a conventional quantitative CT method.

MATERIALS AND METHODS

Separate cohorts were used for algorithm development and validation. For validation, thin-slice CT stacks from 474 participants in the prospective cross-sectional Swedish CArdioPulmonary bioImage Study (SCAPIS) were included, 395 randomly selected and 79 from an emphysema cohort. Spirometry (FEV1/FVC) and radiologists' visual emphysema scores (sum-visual) obtained at inclusion in SCAPIS were used as reference tests. SWES was compared with a commercially available quantitative emphysema scoring method (LAV950) using Pearson's correlation coefficients and receiver operating characteristics (ROC) analysis.

RESULTS

SWES correlated more strongly with the visual scores than LAV950 (r = 0.78 vs. r = 0.41, p < 0.001). The area under the ROC curve for the prediction of airway obstruction was larger for SWES than for LAV950 (0.76 vs. 0.61, p = 0.007). SWES correlated more strongly with FEV1/FVC than either LAV950 or sum-visual in the full cohort (r =  - 0.69 vs. r =  - 0.49/r =  - 0.64, p < 0.001/p = 0.007), in the emphysema cohort (r =  - 0.77 vs. r =  - 0.69/r =  - 0.65, p = 0.03/p = 0.002), and in the random sample (r =  - 0.39 vs. r =  - 0.26/r =  - 0.25, p = 0.001/p = 0.007).

CONCLUSION

The slice-wise whole-lung emphysema score (SWES) correlates better than LAV950 with radiologists' visual emphysema scores and correlates better with airway obstruction than do LAV950 and radiologists' visual scores.

CLINICAL RELEVANCE STATEMENT

The slice-wise whole-lung emphysema score provides quantitative emphysema information for CT imaging that avoids the disadvantages of threshold-based scores and is correlated more strongly with reference tests than LAV950 and reader visual scores.

KEY POINTS

• A slice-wise whole-lung emphysema score (SWES) was developed to quantify emphysema in chest CT images. • SWES identified visual emphysema and spirometric airflow limitation significantly better than threshold-based score (LAV950). • SWES improved emphysema quantification in CT images, which is especially useful in large-scale research.

Early Diagnosis of High-Risk Chronic Obstructive Pulmonary Disease Based on Quantitative High-Resolution Computed Tomography Measurements

Purpose

Quantitative computed tomography (QCT) techniques, focusing on airway anatomy and emphysema, may help to detect early structural changes of COPD disease. This retrospective study aims to identify high-risk COPD participants by using QCT measurements.

Patients and Methods

We enrolled 140 participants from the Second Affiliated Hospital of Shenyang Medical College who completed inspiratory high-resolution CT scans, pulmonary function tests (PFTs), and clinical characteristics recorded. They were diagnosed Non-COPD by PFT value of FEV1/FVC >70% and divided into two groups according percentage predicted FEV1 (FEV1%), low-risk COPD group: FEV1% ≥ 95%, high-risk group: 80% < FEV1% < 95%. The QCT measurements were analyzed by the Student's t-test (or Mann-Whitney U-test) method. Then, feature candidates were identified using the LASSO method. Meanwhile, the correlation between QCT measurements and PFTs was assessed by the Spearman rank correlation test. Furthermore, support vector machine (SVM) was performed to identify high-risk COPD participants. The performance of the models was evaluated in terms of accuracy (ACC), sensitivity (SEN), specificity (SPE), F1-score, and area under the ROC curve (AUC), with p <0.05 considered statistically significant.

Results

The SVM based on QCT measurements achieved good performance in identifying high-risk COPD patients with 85.71% of ACC, 88.34% of SEN, 84.00% of SPE, 83.33% of F1-score, and 0.93 of AUC. Further, QCT measurements integration of clinical data improved the performance with an ACC of 90.48%. The emphysema index (%LAA-950) of left lower lung was negatively correlated with PFTs (P < 0.001). The airway anatomy indexes of lumen diameter (LD) were correlated with PFTs.

Conclusion

QCT measurements combined with clinical information could provide an effective tool for an early diagnosis of high-risk COPD. The QCT indexes can be used to assess the pulmonary function status of high-risk COPD.

The utility of quantitative computed tomography in cohort studies of chronic obstructive pulmonary disease: a narrative review

Background and Objective

Chronic obstructive pulmonary disease (COPD) is a significant contributor to global morbidity and mortality. Quantitative computed tomography (QCT), a non-invasive imaging modality, offers the potential to assess lung structure and function in COPD patients. Amidst the coronavirus disease 2019 (COVID-19) pandemic, chest computed tomography (CT) scans have emerged as a viable alternative for assessing pulmonary function (e.g., spirometry), minimizing the risk of aerosolized virus transmission. However, the clinical application of QCT measurements is not yet widespread enough, necessitating broader validation to determine its usefulness in COPD management.

Methods

We conducted a search in the PubMed database in English from January 1, 2013 to April 20, 2023, using keywords and controlled vocabulary related to QCT, COPD, and cohort studies.

Key Content and Findings

Existing studies have demonstrated the potential of QCT in providing valuable information on lung volume, airway geometry, airway wall thickness, emphysema, and lung tissue density in COPD patients. Moreover, QCT values have shown robust correlations with pulmonary function tests, and can predict exacerbation risk and mortality in patients with COPD. QCT can even discern COPD subtypes based on phenotypic characteristics such as emphysema predominance, supporting targeted management and interventions.

Conclusions

QCT has shown promise in cohort studies related to COPD, since it can provide critical insights into the pathogenesis and progression of the disease. Further research is necessary to determine the clinical significance of QCT measurements for COPD management.

Quantitative analyzes of the variability in airways via four-dimensional dynamic ventilation CT in patients with chronic obstructive pulmonary disease: correlation with spirometry data and severity of airflow limitation

Background

In chronic obstructive pulmonary disease (COPD) patients, the diagnosis and assessment of disease severity are mainly based on spirometry, which may lead to misjudgments due to poor patient compliance. Thoracic four-dimensional dynamic ventilation computed tomography (4D-CT) provides more airway data approximating true physiological function than conventional CT. We aimed to determine dynamic changes in airways to elucidate the pathological mechanism underlying COPD and predict the severity of airflow limitation in patients.

Methods

Forty-two COPD patients underwent 4D-CT and spirometry. The minimum lumen diameter changed with the breathing cycle in 4th-generation airways and was continuously measured in the apical (RB1), lateral (RB4) and posterior basal segments (RB10) of the right lung. The minimum lumen diameter in the peak inspiration and peak expiration as well as the peak expiratory/peak inspiratory ratio (E/I ratio), and dynamic coefficient of variance (CV) were calculated.

Results

Correlations of FEV1% with the CV of minimum lumen diameter in RB1 (ρ=-0.473, P=0.002) and in RB10 (ρ=-0.480, P=0.005) were observed, suggesting that the dynamic variability in 4th-generation airways was associated with airflow limitation in COPD patients. The CV of the minimum lumen diameter in RB1 significantly differed between the GOLD I + II and GOLD III + IV groups {8.59 [interquartile range (IQR), 6.63-14.86] vs. 14.64 (10.65-25.88), respectively; P=0.016}, suggesting that the dynamic CV in RB1 increased significantly in the GOLD III + IV group, which had worse pulmonary ventilation function. Based on the receiver operating characteristic (ROC) curve analysis, CV-RB1 predicted FEV1% <50% with an optimal cut-off of 9.43% [sensitivity 85.7%, specificity 57.1%, area under the curve (AUC) 0.717].

Conclusions

4D-CT might be an available method to help diagnose and evaluate the severity of COPD.

Area-Detector Computed Tomography for Pulmonary Functional Imaging

An area-detector CT (ADCT) has a 320-detector row and can obtain isotropic volume data without helical scanning within an area of nearly 160 mm. The actual-perfusion CT data within this area can, thus, be obtained by means of continuous dynamic scanning for the qualitative or quantitative evaluation of regional perfusion within nodules, lymph nodes, or tumors. Moreover, this system can obtain CT data with not only helical but also step-and-shoot or wide-volume scanning for body CT imaging. ADCT also has the potential to use dual-energy CT and subtraction CT to enable contrast-enhanced visualization by means of not only iodine but also xenon or krypton for functional evaluations. Therefore, systems using ADCT may be able to function as a pulmonary functional imaging tool. This review is intended to help the reader understand, with study results published during the last a few decades, the basic or clinical evidence about (1) newly applied reconstruction methods for radiation dose reduction for functional ADCT, (2) morphology-based pulmonary functional imaging, (3) pulmonary perfusion evaluation, (4) ventilation assessment, and (5) biomechanical evaluation.

Advances for Pulmonary Functional Imaging: Dual-Energy Computed Tomography for Pulmonary Functional Imaging

Dual-energy computed tomography (DECT) can improve the differentiation of material by using two different X-ray energy spectra, and may provide new imaging techniques to diagnostic radiology to overcome the limitations of conventional CT in characterizing tissue. Some techniques have used dual-energy imaging, which mainly includes dual-sourced, rapid kVp switching, dual-layer detectors, and split-filter imaging. In iodine images, images of the lung's perfused blood volume (PBV) based on DECT have been applied in patients with pulmonary embolism to obtain both images of the PE occluding the pulmonary artery and the consequent perfusion defects in the lung's parenchyma. PBV images of the lung also have the potential to indicate the severity of PE, including chronic thromboembolic pulmonary hypertension. Virtual monochromatic imaging can improve the accuracy of diagnosing pulmonary vascular diseases by optimizing kiloelectronvolt settings for various purposes. Iodine images also could provide a new approach in the area of thoracic oncology, for example, for the characterization of pulmonary nodules and mediastinal lymph nodes. DECT-based lung ventilation imaging is also available with noble gases with high atomic numbers, such as xenon, which is similar to iodine. A ventilation map of the lung can be used to image various pulmonary diseases such as chronic obstructive pulmonary disease.

Detection of Small Airway Dysfunction in Asthmatic Patients by Spirometry and Impulse Oscillometry System

BACKGROUND

There is no gold standard in diagnosing SAD. Indicators of SAD are considered: (a) a value <65% of predicted values of two of three measures, FEF25-75, FEF50 e FEF75 (FEF+); (b) a value of FEV3/FEV6 < LLN (FEV3/FEV6+); (c) an IOS value of R5-R20 >0.07 kPa·s·L-1 (R5-R20+).

AIM AND OBJECTIVES

The aim of the study was to ascertain, in asthmatic patients, whether spirometry and IOS indicators agree in detecting SAD. We also assessed the relationship between spirometry and IOS indicators and clinical features of asthma.

METHODS

We prospectively recruited adult asthmatic patients. Anthropometric and clinical characteristics were recorded. All patients performed spirometry and IOS tests.

RESULTS

We enrolled 301 asthmatic patients (179 females; mean age 50 ± 16 years) with normal to moderately severe degree of airway obstruction; 91% were non-smokers, 74% were atopic, 28% had an exacerbation in the previous year, and 18% had a poor asthma control by ACT. SAD was diagnosed in 62% of patients through FEF+, in 40% through FEV3/FEV6+ and in 41% through R5-R20+. κ values were 0.49 between FEF+ and FEV3/FEV6+, 0.20 between FEF+ and R5-R20+, 0.07 between FEV3/FEV6+ and R5-R20+. R5-R20+ but not FEF+ and FEV3/FEV6+ was significantly associated with ACT score (p < 0.05).

CONCLUSIONS

Our study shows that in mild to moderately severe asthmatic patients, spirometry and IOS indicators are complementary in diagnosing SAD. Additionally, IOS indicator, but not spirometry ones, was related to asthma control.

Structural features on quantitative chest computed tomography of patients with maximal mid-expiratory flow impairment in a normal lung function population

BACKGROUND

Maximal mid-expiratory flow (MMEF) is an earlier predictor of chronic obstructive pulmonary disease (COPD) development than forced expiratory volume in 1 s (FEV₁). Changes of lung structure in patients with MMEF impairment only is still not clear. Therefore, this study aimed to investigate the structural features of patients with decreased MMEF by quantitative computed tomography (QCT) and develop a predictive model for predicting patients with reduced MMEF in normal lung function population.

METHODS

In this study, 131 patients with normal spirometry results and available volumetric chest CT images were enrolled and divided into the reduced MMEF group (FEV₁/forced expiratory vital capacity (FEV₁/FVC) > 0.7, FEV₁% predictive values (FEV₁%pred) > 80%, MMEF%pred < 80%, n = 52) and the normal MMEF group (FEV₁/FVC > 0.7, FEV₁%pred > 80%, MMEF%pred ≥ 80%, n = 79). The emphysema, small airway disease and medium-size airway parameters were measured by a commercial software. The differences were investigated in clinical features, spirometrical parameters and QCT parameters between the two groups. A nomogram model was constructed based on the results of the multivariable logistic regression model. Spearman's correlation coefficients were calculated between QCT measurements and spirometrical parameters.

RESULTS

There were more males in reduced MMEF group than normal group (P < 0.05). Lung parenchyma parameter (PRM^Emph) and airway-related parameters (functional small airway disease (PRM^fSAD), luminal area of fifth- and sixth- generation airway (LA₅, LA₆) were significantly different between the reduced MMEF group and the normal group (20.2 ± 17.4 vs 9.4 ± 6.7, 3.4 ± 3.5 vs 1.9 ± 2.0, 12.2 ± 2.5 vs 13.7 ± 3.4, 7.7 ± 2.4 vs 8.9 ± 2.8, respectively, all P < 0.01). After multivariable logistical regression, only sex (odds ratio [OR]: 2.777; 95% confidence interval [CI]:1.123-3.867), PRM^fSAD (OR:1.102, 95%CI:1.045-1.162) and LA₆ (OR:0.650, 95%CI:0.528-0.799) had significant differences between the two groups (P < 0.05) and a model incorporating with the three indicators was constructed (area under curve, 0.836). Correlation analysis showed MMEF%pred had mild to moderate correlation with airway-related measurements.

CONCLUSION

In normal lung function population, patients with reduced MMEF have potential medium-size and small airway changes, and MMEF%pred is significantly associated with airway-related CT parameters. The nomogram incorporating with sex, PRM^fSAD and LA₆ has good predictive value and offers more objective evidences in a group with reduced MMEF.

A Computer-based Analysis for Identification and Quantification of Small Airway Disease in Lung Computed Tomography Images: A Comprehensive Review for Radiologists

Computed tomography (CT) imaging is being increasingly used in clinical practice for detailed characterization of lung diseases. Respiratory diseases involve various components of the lung, including the small airways. Evaluation of small airway disease on CT images is challenging as the airways cannot be visualized directly by a CT scanner. Small airway disease can manifest as pulmonary air trapping (AT). Although AT may be sometimes seen as mosaic attenuation on expiratory CT images, it is difficult to identify diffuse AT visually. Computer technology advances over the past decades have provided methods for objective quantification of small airway disease on CT images. Quantitative CT (QCT) methods are being rapidly developed to quantify underlying lung diseases with greater precision than subjective visual assessment of CT images. A growing body of evidence suggests that QCT methods can be practical tools in the clinical setting to identify and quantify abnormal regions of the lung accurately and reproducibly. This review aimed to describe the available methods for the identification and quantification of small airway disease on CT images and to discuss the challenges of implementing QCT metrics in clinical care for patients with small airway disease.

Quantitative CT lung densitometry as an obstructive marker for the diagnosis of bronchiolitis obliterans in children

The purpose of this study is to evaluate the quantitative diagnostic performance of computed tomography (CT) densitometry in pediatric patients with bronchiolitis obliterans (BO). We measured the mean lung density (MLD) and represented the difference of MLD in inspiratory and expiratory phases (MLDD), the ratio of the MLD (E/I MLD), and the relative volume percentage of lung density at 50-Hounsfield unit (HU) interval threshold (E600 to E950). We calculated the sensitivity, specificity, and diagnostic accuracy of the lung density indices for the diagnosis of BO. A total of 81 patients, including 51 patients with BO and 30 controls, were included in this study. In the BO patients, expiratory (EXP) MLD and MLDD were significantly lower, and E/I MLD and expiratory low attenuation areas below the threshold of −850 HU to −950 HU (E850, E900, and E950) were statistically significantly higher than controls. Multivariate logistic regression analysis showed that MLDD (odds ratio [OR] = 0.98, p < .001), E/I MLD (OR = 1.39, p < .001), and E850 to E950 were significant densitometry parameters for BO diagnosis. In a receiver-operating characteristic analysis, E900 (cutoff, 1.4%; AUC = 0.920), E/I MLD (cutoff, 0.87; AUC = 0.887), and MLDD (cutoff, 109 HU; AUC = 0.867) showed high accuracy for the diagnosis of BO. In conclusion, the lung CT densitometry can serve as a quantitative marker providing additional indications of expiratory airflow limitation in pediatric patients with BO.

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.

Quantitative imaging analysis detects subtle airway abnormalities in symptomatic military deployers

Background

Exposure to inhalational hazards during post-9/11 deployment to Southwest Asia and Afghanistan puts military personnel at risk for respiratory symptoms and disease. Pulmonary function and qualitative chest high resolution computed tomography (HRCT) are often normal in “deployers” with persistent respiratory symptoms. We explored the utility of quantitative HRCT imaging markers of large and small airways abnormalities, including airway wall thickness, emphysema, and air trapping, in symptomatic deployers with clinically-confirmed lung disease compared to controls.

Methods

Chest HRCT images from 45 healthy controls and 82 symptomatic deployers with asthma, distal lung disease or both were analyzed using Thirona Lung quantification software to calculate airway wall thickness (by Pi10), emphysema (by percentage of lung volume with attenuation < -950 Hounsfield units [LAA%-950]), and three parameters of air trapping (expiratory/inspiratory total lung volume and mean lung density ratios, and LAA%-856). SAS v.9.4 was used to compare demographic and clinical characteristics between deployers and controls using Chi-Square, Fisher Exact or t-tests. Linear regression was used to assess relationships between pulmonary function and quantitative imaging findings.

Results

Gender and smoking status were not statistically significantly different between groups, but deployers were significantly younger than controls (42 vs 58 years, p < 0.0001), had higher body mass index (31 vs 28 kg/m², p = 0.01), and had fewer total smoking pack-years (8 vs. 26, p = 0.007). Spirometric measures were not statistically significantly different between groups. Pi10 and LAA%-950 were significantly elevated in deployers compared to controls in unadjusted analyses, with the emphysema measure remaining significantly higher in deployers after adjustment for age, sex, smoking, BMI, and expiratory total lung volume. Air trapping parameters were more common in control images, likely due to differences in age and smoking between groups. Among deployers, LAA%-950 and Pi10 were significantly correlated with spirometric markers of obstruction based on ratio of forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) and/or percent predicted FEV1.

Conclusions

Quantitative chest HRCT imaging analysis identifies emphysema in deployers with asthma and distal lung disease, and may be useful in detecting and monitoring deployment-related lung disease in a population where spirometry is typically normal.

Quantitative Assessment of Airway Changes in Fibrotic Interstitial Lung Abnormality Patients by Chest CT According to Cumulative Cigarette Smoking

Purpose: The aim of this study was to evaluate the role of Pi10 in patients with fibrotic interstitial lung abnormality (fibrotic ILA) in a chest CT, according to cumulative cigarette smoking. Methods: We retrospectively assessed 54 fibrotic ILA patients and 18 healthy non-smokers (control) who underwent non-enhanced CT and pulmonary function tests. We quantitatively analyzed airway changes (the inner luminal area, airway inner parameter, airway wall thickness, Pi10, skewness, and kurtosis) in the chest CT of fibrotic ILA patients, and the fibrotic ILA patients were categorized into groups based on pack-years: light, moderate, heavy. Airway change data and pulmonary function tests among the three groups of fibrotic ILA patients were compared with those of the control group by one-way ANOVA. Results: Mean skewness (2.58 ± 0.36) and kurtosis (7.64 ± 2.36) in the control group were significantly different from those of the fibrotic ILA patients (1.89 ± 0.37 and 3.62 ± 1.70, respectively, p < 0.001). In fibrotic ILA group, only heavy smokers had significantly increased Pi10 (mean increase 0.04, p = 0.013), increased airway wall thickness of the segmental bronchi (mean increase 0.06 mm, p = 0.005), and decreased lung diffusing capacity for carbon monoxide (p = 0.023). Conclusion: Pi10, as a biomaker of quantitative CT in fibrotic ILA patients, can reveal that smoking affects airway remodeling.

Determinants of blood eosinophil levels in the general population and patients with COPD: a population-based, epidemiological study

Background

Blood eosinophils are considered a biomarker for the treatment of chronic obstructive pulmonary disease (COPD). Population-based studies are needed to better understand the determinants of the blood eosinophil count (BEC) in individuals with and without COPD.

Methods

EPISCAN II is a multicentre, cross-sectional, population-based epidemiological study aimed at investigating the prevalence and determinants of COPD in Spain. Study subjects were randomly selected from the general population, and COPD was defined by a post-bronchodilator FEV₁/FVC < 0.7. For the pre-specified outcomes related to BEC, the first 35 COPD and 35 non-COPD subjects were consecutively recruited in 12 of the participating centres with the objective of analysing 400 individuals in each group. Baseline BEC and its association with demographic, clinical and functional variables were analysed.

Results

A total of 326 COPD and 399 non-COPD subjects were included in the analysis. The mean age (standard deviation [SD]) was 63.2 years (11.0), 46.3% were male, and 27.6% were active smokers. BEC was significantly higher in individuals with COPD [192 cells/μL (SD: 125) vs. 160 cells/μL (SD: 114); p = 0.0003]. In a stepwise multivariate model, being male, active smoker and having a previous diagnosis of asthma were independently associated with having a higher BEC.

Conclusions

This population-based study estimated the distribution of eosinophils in the healthy adult population and concluded that COPD patients have a significantly higher BEC. Male sex, active smoking and concomitant asthma were significantly associated with a higher BEC.

Pre-chronic obstructive pulmonary disease: a pathophysiologic process or an opinion term?

PURPOSE OF REVIEW

Current guidelines does not include current or former smokers who do not have spirometric airflow limitation in their diagnostic or therapeutic algorithms for chronic obstructive pulmonary disease (COPD). The purpose of this review is to outline the burden of respiratory morbidity in this population and to discuss the potential utility of their classification as pre-COPD.

RECENT FINDINGS

It is increasingly clear that patients with a history of exposure to cigarette smoke or other environmental pollutants may have substantial lung pathology and respiratory impairment even in the absence of airflow limitation, as detected by spirometry. Not all of these patients will develop airflow limitation, but many will have considerable respiratory morbidity and a comparable prognosis to those with classical, spirometrically defined COPD. The use of the term pre-COPD may allow for the identification of these individuals in order to target preventive and earlier therapeutic strategies.

SUMMARY

Spirometry is not adequately sensitive to identify many current and former smokers and other exposed populations with significant lung pathology and respiratory symptoms. Though the pathologic processes present in these patients differ, the earlier identification of this pre-COPD population may foster the development of more effective and disease-modifying treatments.

Detection and staging of chronic obstructive pulmonary disease using a computed tomography-based weakly supervised deep learning approach

OBJECTIVES

Chronic obstructive pulmonary disease (COPD) is underdiagnosed globally. The present study aimed to develop weakly supervised deep learning (DL) models that utilize computed tomography (CT) image data for the automated detection and staging of spirometry-defined COPD.

METHODS

A large, highly heterogeneous dataset was established, consisting of 1393 participants retrospectively recruited from outpatient, inpatient, and physical examination center settings of four large public hospitals in China. All participants underwent both inspiratory chest CT scans and pulmonary function tests. CT images, spirometry data, demographic information, and clinical information of each participant were collected. An attention-based multi-instance learning (MIL) model for COPD detection was trained using CT scans from 837 participants. External validation of the COPD detection was performed with 620 low-dose CT (LDCT) scans acquired from the National Lung Screening Trial (NLST) cohort. A multi-channel 3D residual network was further developed to categorize GOLD stages among confirmed COPD patients.

RESULTS

The attention-based MIL model used for COPD detection achieved an area under the receiver operating characteristic curve (AUC) of 0.934 (95% CI: 0.903, 0.961) on the internal test set and 0.866 (95% CI: 0.805, 0.928) on the LDCT subset acquired from the NLST. The multi-channel 3D residual network was able to correctly grade 76.4% of COPD patients in the test set (423/553) using the GOLD scale.

CONCLUSIONS

The proposed chest CT-DL approach can automatically identify spirometry-defined COPD and categorize patients according to the GOLD scale. As such, this approach may be an effective case-finding tool for COPD diagnosis and staging.

KEY POINTS

• Chronic obstructive pulmonary disease is underdiagnosed globally, particularly in developing countries. • The proposed chest computed tomography (CT)-based deep learning (DL) approaches could accurately identify spirometry-defined COPD and categorize patients according to the GOLD scale. • The chest CT-DL approach may be an alternative case-finding tool for COPD identification and evaluation.

Applications of artificial intelligence in the thorax: a narrative review focusing on thoracic radiology

Objective

This review will focus on how AI—and, specifically, deep learning—can be applied to complement aspects of the current healthcare system. We describe how AI-based tools can augment existing clinical workflows by discussing the applications of AI to worklist prioritization and patient triage, the performance-boosting effects of AI as a second reader, and the use of AI to facilitate complex quantifications. We also introduce prominent examples of recent AI applications, such as tuberculosis screening in resource-constrained environments, the detection of lung cancer with screening CT, and the diagnosis of COVID-19. We also provide examples of prognostic predictions and new discoveries beyond existing clinical practices.

Background

Artificial intelligence (AI) has shown promising performance for thoracic diseases, particularly in the field of thoracic radiology. However, it has not yet been established how AI-based image analysis systems can help physicians in clinical practice.

Methods

This review included peer-reviewed research articles on AI in the thorax published in English between 2015 and 2021.

Conclusions

With advances in technology and appropriate preparation of physicians, AI could address various clinical problems that have not been solved due to a lack of clinical resources or technological limitations.

Keywords

Artificial intelligence (AI); deep learning (DL); computer aided diagnosis (CAD); thoracic radiology; pulmonary medicine

Subtyping preserved ratio impaired spirometry (PRISm) by using quantitative HRCT imaging characteristics

BACKGROUND

Preserved Ratio Impaired Spirometry (PRISm) is defined as FEV1/FVC ≥ 70% and FEV1 < 80%pred by pulmonary function test (PFT). It has highly prevalence and is associated with increased respiratory symptoms, systemic inflammation, and mortality. However, there are few radiological studies related to PRISm. The purpose of this study was to investigate the quantitative high-resolution computed tomography (HRCT) characteristics of PRISm and to evaluate the correlation between quantitative HRCT parameters and pulmonary function parameters, with the goal of establishing a nomogram model for predicting PRISm based on quantitative HRCT.

METHODS

A prospective and continuous study was performed in 488 respiratory outpatients from February 2020 to February 2021. All patients underwent both deep inspiratory and expiratory CT examinations, and received pulmonary function test (PFT) within 1 month. According to the exclusion criteria and Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification standard, 94 cases of normal pulmonary function, 51 cases of PRISm and 48 cases of mild to moderate chronic obstructive lung disease (COPD) were included in the study. The lung parenchyma, parametric response mapping (PRM), airway and vessel parameters were measured by automatic segmentation software (Aview). One-way analysis of variance (ANOVA) was used to compare the differences in clinical features, pulmonary function parameters and quantitative CT parameters. Spearman rank correlation analysis was used to evaluate the correlation between CT quantitative index and pulmonary function parameters. The predictors were obtained by binary logistics regression analysis respectively in normal and PRISm as well as PRISm and mild to moderate COPD, and the nomogram model was established.

RESULTS

There were significant differences in pulmonary function parameters among the three groups (P < 0.001). The differences in pulmonary parenchyma parameters such as emphysema index (EI), pixel indices-1 (PI-1) and PI-15 were mainly between mild to moderate COPD and the other two groups. The differences of airway parameters and pulmonary vascular parameters were mainly between normal and the other two groups, but were not found between PRISm and mild to moderate COPD. Especially there were significant differences in mean lung density (MLD) and the percent of normal in PRM (PRM^Normal) among the three groups. Most of the pulmonary quantitative CT parameters had mild to moderate correlation with pulmonary function parameters. The predictors of the nomogram model using binary logistics regression analysis to distinguish normal from PRISm were smoking, MLD, the percent of functional small airways disease (fSAD) in PRM (PRM^fSAD) and Lumen area. It had a good goodness of fit (χ² = 0.31, P < 0.001) with the area under curve (AUC) value of 0.786. The predictor of distinguishing PRISm from mild to moderate COPD were PRM^Emph (P < 0.001, AUC = 0.852).

CONCLUSIONS

PRISm was significantly different from subjects with normal pulmonary function in small airway and vessel lesions, which was more inclined to mild to moderate COPD, but there was no increase in pulmonary parenchymal attenuation. The nomogram based on quantitative HRCT parameters has good predictive value and provide more objective evidence for the early screening of PRISm.

The Value of Impulse Oscillometric Parameters and Quantitative HRCT Parameters in Differentiating Asthma-COPD Overlap from COPD

Purpose

To evaluate the value of impulse oscillometry (IOS) and quantitative HRCT parameters for differentiating asthma-COPD overlap (ACO) in COPD patients.

Patients and Methods

We enrolled 44 controls and 66 COPD patients, divided into the pure COPD group (n=40) and the ACO group (n=26). Spearman correlation analysis was utilized to assess the relationship between the quantitative HRCT and IOS parameters. A binary logistic regression analysis was performed to analyze the associations between the different variables and the risk of ACO. Receiver operating characteristic (ROC) curves were employed to identify the optimal cutoff and assess the diagnostic value of relative volume change -856 HU to -950 HU (RVC_{-856 to -950}), decrease in the resistance from 5 Hz to 20 Hz (R5-R20) and their combination in predicting ACO. Bootstrapping validation was used to evaluate the internal validation. The concordance index (C-index) and calibration plot were calculated to assess the discrimination and calibration of the prediction model.

Results

Binary logistic regression analysis indicated that RVC_{-856 to -950} and the IOS parameters (R5-R20, R5, X5) were independently correlated with a higher risk of developing ACO after adjusting for age, sex, body mass index (BMI), history of smoking, exacerbation and atopy or allergic rhinitis. A correlation analysis showed a good correlation between the pulmonary function parameters and RVC_{-856 to -950}, with a weaker correlation with the % area of low attenuation (LAA%) in ACO patients. Combining RVC_{-856 to -950} and R5-R20 to predict ACO, the AUC was 0.909, and the optimal cutoff value was >-0.62 for RVC_{-856 to -950} and >0.09 for R5-R20. Good calibration and favorable discrimination were displayed with a higher C-index.

Conclusion

More serious small airway impairment exists in ACO patients. The combination of RVC_{-856 to -950} and R5-R20 could be applied to differentiate ACO from COPD patients.

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.

Computed tomography-identified phenotypes of small airway obstructions in chronic obstructive pulmonary disease

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characteristic of small airway inflammation, obstruction, and emphysema. It is well known that spirometry alone cannot differentiate each separate component. Computed tomography (CT) is widely used to determine the extent of emphysema and small airway involvement in COPD. Compared with the pulmonary function test, small airway CT phenotypes can accurately reflect disease severity in patients with COPD, which is conducive to improving the prognosis of this disease. CT measurement of central airway morphology has been applied in clinical, epidemiologic, and genetic investigations as an inference of the presence and severity of small airway disease. This review will focus on presenting the current knowledge and methodologies in chest CT that aid in identifying discrete COPD phenotypes.

Lung density analysis using quantitative computed tomography in children with pectus excavatum

Purpose

To evaluate the mean lung density in children with pectus excavatum (PE) and to assess the correlation between the cardiac rotation angle, Haller index, pulmonary function test, and lung density.

Material and methods

This retrospective study included 33 children with PE and 31 healthy controls. The densities of lung parenchyma were evaluated by quantitative computed tomography (CT). Three lung levels were determined: T4 vertebra level, T10 vertebra level, and the level of the measurement of the cardiac rotation angle. The cardiac rotation angle and the Haller index were calculated. All measurements were done by 2 radiologists, independently. Student’s t-test or the Mann-Whitney U test, intraclass correlation coefficients, Pearson or Spearman’s rank correlation coefficient, and Kruskal-Wallis test were used for statistical analysis. A p-value less than 0.05 was considered as statistically significant.

Results

All the lung levels in the PE group had lower mean densities than healthy children, with statistical significance in the right lung at the T10 vertebra level (−818.60 ± 33.49 HU, −798.45 ± 40.24 HU; p = 0.028). There was a correlation between the cardiac rotation angle and the Haller index (r = 0.593; p < 0.001). There were no correlations between mean lung density and cardiac rotation angle, Haller index, and pulmonary function tests.

Conclusions

The lower mean lung densities were found in PE, especially in the right lower lobe. The parenchymal aeration should be considered independently from the severity of PE.

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.

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.

HRCT characteristics of severe emphysema patients: Interobserver variability among expert readers and comparison with quantitative software

PURPOSE

For a successful bronchoscopic lung volume reduction coil treatment it is important to place the coils in the most emphysematous lobes. Therefore assessment of the lobe with greatest destruction is essential. Our aims were to investigate the level of agreement among expert reviewers of HRCT-scans in emphysema patients and the comparison with QCT (quantitative computed tomography) software.

METHOD

Five experienced CT-assessors, conducted a visual assessment of the baseline HRCT-scans of emphysema patients who participated in the RENEW bronchoscopic lung volume reduction coil study. On the same HRCT-scans, a QCT analysis was performed.

RESULTS

In total 134 HRCT-scans were rated by all 5 experts. All 5 CT-assessors agreed on which was the most destructed lobe in 61 % of the left lungs (ƙ:0.459) and 60 % of the right lungs (ƙ:0.370). The consensus of the 5 assessors matched the QCT in the left lung for 77 % of the patients (ƙ:0.425) and in the right lung for 82 % (ƙ:0.524).

CONCLUSIONS

Our results show that the interobserver agreement between five expert CT-assessors was only fair to moderate when evaluating the most destructed lobe. CT-assessor consensus improved matching with QCT determination of lobar destruction compared to individual assessor determinations. Because some CT-features are associated with treatment outcomes and important for optimal patient selection of bronchoscopic lung volume reduction treatment, we recommend including more than one CT-reviewer and supported by QCT measurements.

The CT pulmonary vascular parameters and disease severity in COPD patients on acute exacerbation: a correlation analysis

Background

It is necessary to analyze the CT pulmonary vascular parameters and disease severity in chronic obstructive pulmonary disease (COPD) patients to provide evidence support for the management of COPD.

Methods

COPD patients on acute exacerbation admitted to our hospital from COPD patients from January 2019 to March 2020 was selected. The characteristics and ratio of the cross-sectional area (CSA) of small pulmonary vessels to the total area of the lung field, and the ratio of pulmonary artery and aorta (PA/A) cross-sectional diameter in patients with COPD were analyzed.

Results

A total of 128 COPD patients were included. There were significant differences in the duration of COPD, smoking history, the PaO₂, PaCO₂, pH, and FEV1, FVC and FEV1/FVC among COPD patients with different severity (all p < 0.05). The duration of COPD, smoking, PaO₂, PaCO₂, CSA and PA/A were correlated with the COPD severity (all p < 0.05). Both CSA, PA/A were correlated with post BD FEV1 (all p < 0.05). The cutoff value of CSA and PA/A for the diagnosis of severe COPD was 0.61 and 0.87 respectively, and the AUC of CSA and PA/A for the diagnosis of severe COPD was 0.724 and 0.782 respectively.

Conclusions

Patients with CSA ≤ 0.61 and PA/A ≥ 0.87 may have higher risks for severe COPD, and more studies are needed in the future to further elucidate the management of COPD.

COPD Imaging on a 3rd Generation Dual-Source CT: Acquisition of Paired Inspiratory-Expiratory Chest Scans at an Overall Reduced Radiation Risk

As stated by the Fleischner Society, an additional computed tomography (CT) scan in expiration is beneficial in patients with chronic obstructive pulmonary disease (COPD). It was thus the aim of this study to evaluate the radiation risk of a state-of-the-art paired inspiratory-expiratory chest scan compared to inspiration-only examinations. Radiation doses to 28 organs were determined for 824 COPD patients undergoing routine chest examinations at three different CT systems-a conventional multi-slice CT (MSCT), a 2nd generation (2nd-DSCT), and 3rd generation dual-source CT (3rd-DSCT). Patients examined at the 3rd-DSCT received a paired inspiratory-expiratory scan. Organ doses, effective doses, and lifetime attributable cancer risks (LAR) were calculated. All organ and effective doses were significantly lower for the paired inspiratory-expiratory protocol (effective doses: 4.3 ± 1.5 mSv (MSCT), 3.0 ± 1.2 mSv (2nd-DSCT), and 2.0 ± 0.8 mSv (3rd-DSCT)). Accordingly, LAR was lowest for the paired protocol with an estimate of 0.025 % and 0.013% for female and male patients (50 years) respectively. Image quality was not compromised. Paired inspiratory-expiratory scans can be acquired on 3rd-DSCT systems at substantially lower dose and risk levels when compared to inspiration-only scans at conventional CT systems, offering promising prospects for improved COPD diagnosis.

Feasibility of bronchial wall quantification in low- and ultralow-dose third-generation dual-source CT: An ex vivo lung study

PURPOSE

To investigate image quality and bronchial wall quantification in low- and ultralow-dose third-generation dual-source computed tomography (CT).

METHODS

A lung specimen from a formerly healthy male was scanned using third-generation dual-source CT at standard-dose (51 mAs/120 kV, CTDI_vol 3.41 mGy), low-dose (1/4th and 1/10th of standard dose), and ultralow-dose setting (1/20th). Low kV (70, 80, 90, and Sn100 kV) scanning was applied in each low/ultralow-dose setting, combined with adaptive mAs to keep a constant dose. Images were reconstructed at advanced modeled iterative reconstruction (ADMIRE) levels 1, 3, and 5 for each scan. Bronchial wall were semi-automatically measured from the lobar level to subsegmental level. Spearman correlation analysis was performed between bronchial wall quantification (wall thickness and wall area percentage) and protocol settings (dose, kV, and ADMIRE). ANOVA with a post hoc pairwise test was used to compare signal-to-noise ratio (SNR), noise and bronchial wall quantification values among standard- and low/ultralow-dose settings, and among ADMIRE levels.

RESULTS

Bronchial wall quantification had no correlation with dose level, kV, or ADMIRE level (|correlation coefficients| < 0.3). SNR and noise showed no statistically significant differences at different kV in the same ADMIRE level (1, 3, or 5) and in the same dose group (P > 0.05). Generally, there were no significant differences in bronchial wall quantification among the standard- and low/ultralow-dose settings, and among different ADMIRE levels (P > 0.05).

CONCLUSION

The combined use of low/ultralow-dose scanning and ADMIRE does not influence bronchial wall quantification compared to standard-dose CT. This specimen study suggests the potential that an ultralow-dose scan can be used for bronchial wall quantification.

Prediction of air trapping or pulmonary hyperinflation by forced spirometry in COPD patients: results from COSYCONET

Background

Air trapping and lung hyperinflation are major determinants of prognosis and response to therapy in chronic obstructive pulmonary disease (COPD). They are often determined by body plethysmography, which has limited availability, and so the question arises as to what extent they can be estimated via spirometry.

Methods

We used data from visits 1–5 of the COPD cohort COSYCONET. Predictive parameters were derived from visit 1 data, while visit 2–5 data was used to assess reproducibility. Pooled data then yielded prediction models including sex, age, height, and body mass index as covariates. Hyperinflation was defined as ratio of residual volume (RV) to total lung capacity (TLC) above the upper limit of normal. (ClinicalTrials.gov identifier: NCT01245933).

Results

Visit 1 data from 1988 patients (Global Initiative for Chronic Obstructive Lung Disease grades 1–4, n=187, 847, 766, 188, respectively) were available for analysis (n=1231 males, 757 females; mean±sd age 65.1±8.4 years; forced expiratory volume in 1 s (FEV₁) 53.1±18.4 % predicted (% pred); forced vital capacity (FVC) 78.8±18.8 % pred; RV/TLC 0.547±0.107). In total, 7157 datasets were analysed. Among measures of hyperinflation, RV/TLC showed the closest relationship to FEV₁ % pred and FVC % pred, which were sufficient for prediction. Their relationship to RV/TLC could be depicted in nomograms. Even when neglecting covariates, hyperinflation was predicted by FEV₁ % pred, FVC % pred or their combination with an area under the curve of 0.870, 0.864 and 0.889, respectively.

Conclusions

The degree of air trapping/hyperinflation in terms of RV/TLC can be estimated in a simple manner from forced spirometry, with an accuracy sufficient for inferring the presence of hyperinflation. This may be useful for clinical settings, where body plethysmography is not available.

This proposed method allows estimation of hyperinflation in COPD by spirometry, obviating the need for body plethysmography or further techniques. Results are depicted in easily applicable nomograms that can be used in clinical practice.https://bit.ly/3c0tUNL

Increased Airway Wall Thickness in Interstitial Lung Abnormalities and Idiopathic Pulmonary Fibrosis

RATIONALE

There is increasing evidence that aberrant processes occurring in the airways may precede the development of idiopathic pulmonary fibrosis (IPF); however, there has been no prior confirmatory data derived from imaging studies.

OBJECTIVES

To assess quantitative measures of airway wall thickness (AWT) in populations characterized for interstitial lung abnormalities (ILA) and for IPF.

METHODS

Computed tomographic imaging of the chest and measures of AWT were available for 6,073, 615, 1,167, and 38 participants from COPDGene (Genetic Epidemiology of COPD study), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints study), and the Framingham Heart Study (FHS) and in patients with IPF from the Brigham and Women's Hospital Herlihy Registry, respectively. To evaluate these associations, we used multivariable linear regression to compare a standardized measure of AWT (the square root of AWT for airways with an internal perimeter of 10 mm [Pi10]) and characterizations of ILA and IPF by computed tomographic imaging of the chest.

RESULTS

In COPDGene, ECLIPSE, and FHS, research participants with ILA had increased measures of Pi10 compared with those without ILA. Patients with IPF had mean measures of Pi10 that were even greater than those noted in research participants with ILA. After adjustment for important covariates (e.g., age, sex, race, body mass index, smoking behavior, and chronic obstructive pulmonary disease severity when appropriate), research participants with ILA had increased measures of Pi10 compared with those without ILA (0.03 mm in COPDGene, 95% confidence interval [CI], 0.02-0.03; P < 0.001; 0.02 mm in ECLIPSE, 95% CI, 0.005-0.04; P = 0.01; 0.07 mm in FHS, 95% CI, 0.01-0.1; P = 0.01). Compared with COPDGene participants without ILA older than 60 years of age, patients with IPF were also noted to have increased measures of Pi10 (2.0 mm, 95% CI, 2.0-2.1; P < 0.001). Among research participants with ILA, increases in Pi10 were correlated with reductions in lung volumes in some but not all populations.

CONCLUSIONS

These results demonstrate that measurable increases in AWT are consistently noted in research participants with ILA and in patients with IPF. These findings suggest that abnormalities of the airways may play a role in, or be correlated with, early pathogenesis of pulmonary fibrosis.

Clinical Implementation of Deep Learning in Thoracic Radiology: Potential Applications and Challenges

Chest X-ray radiography and computed tomography, the two mainstay modalities in thoracic radiology, are under active investigation with deep learning technology, which has shown promising performance in various tasks, including detection, classification, segmentation, and image synthesis, outperforming conventional methods and suggesting its potential for clinical implementation. However, the implementation of deep learning in daily clinical practice is in its infancy and facing several challenges, such as its limited ability to explain the output results, uncertain benefits regarding patient outcomes, and incomplete integration in daily workflow. In this review article, we will introduce the potential clinical applications of deep learning technology in thoracic radiology and discuss several challenges for its implementation in daily clinical practice.

Dynamic-Ventilatory Digital Radiography in Air Flow Limitation: A Change in Lung Area Reflects Air Trapping

OBJECTIVE

The aim of this study was to determine the utility of dynamic-ventilatory digital radiography (DR) for pulmonary function assessment in patients with airflow limitation.

METHODS

One hundred and eighteen patients with airflow limitation (72 patients with lung cancer before surgery, 35 patients with chronic obstructive pulmonary disease [COPD], 6 patients with asthma, and 5 patients with asthma-COPD overlap syndrome) were assessed with dynamic-ventilatory DR. The patients were instructed to inhale and exhale slowly and maximally. Sequential chest X-ray images were captured in 15 frames per second using a dynamic flat-panel imaging system. The relationship between the lung area and the rate of change in the lung area due to respiratory motion with respect to pulmonary function was analyzed.

RESULTS

The rate of change in the lung area from maximum inspiration to maximum expiration (Rs ratio) was associated with the RV/TLC ratio (r = 0.48, p < 0.01) and the percentage of the predicted FEV1 (r = -0.33, p < 0.01) in patients with airflow limitations. The Rs ratio also decreased in an FEV1-dependent manner.

CONCLUSION

The rate of change in the lung area due to respiratory motion evaluated with dynamic DR reflects air trapping. Dynamic DR is a potential tool for the comprehensive assessment of pulmonary function in patients with COPD.

Regenerative Metaplastic Clones in COPD Lung Drive Inflammation and Fibrosis

Chronic obstructive pulmonary disease (COPD) is a progressive condition of chronic bronchitis, small airway obstruction, and emphysema that represents a leading cause of death worldwide. While inflammation, fibrosis, mucus hypersecretion, and metaplastic epithelial lesions are hallmarks of this disease, their origins and dependent relationships remain unclear. Here we apply single-cell cloning technologies to lung tissue of patients with and without COPD. Unlike control lungs, which were dominated by normal distal airway progenitor cells, COPD lungs were inundated by three variant progenitors epigenetically committed to distinct metaplastic lesions. When transplanted to immunodeficient mice, these variant clones induced pathology akin to the mucous and squamous metaplasia, neutrophilic inflammation, and fibrosis seen in COPD. Remarkably, similar variants pre-exist as minor constituents of control and fetal lung and conceivably act in normal processes of immune surveillance. However, these same variants likely catalyze the pathologic and progressive features of COPD when expanded to high numbers.

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.

Influence of Inspiratory/Expiratory CT Registration on Quantitative Air Trapping

RATIONALE AND OBJECTIVES

The aim of this study was to assess variability in quantitative air trapping (QAT) measurements derived from spatially aligned expiration CT scans.

MATERIALS AND METHODS

Sixty-four paired CT examinations, from 16 school-age cystic fibrosis subjects examined at four separate time intervals, were used in this study. For each pair, visually inspected lobe segmentation maps were generated and expiration CT data were registered to the inspiration CT frame. Measurements of QAT, the percentage of voxels on the expiration CT scan below a set threshold were calculated for each lobe and whole-lung from the registered expiration CT and compared to the true values from the unregistered data.

RESULTS

A mathematical model, which simulates the effect of variable regions of lung deformation on QAT values calculated from aligned to those from unaligned data, showed the potential for large bias. Assessment of experimental QAT measurements using Bland-Altman plots corroborated the model simulations, demonstrating biases greater than 5% when QAT was approximately 40% of lung volume. These biases were removed when calculating QAT from aligned expiration CT data using the determinant of the Jacobian matrix. We found, by Dice coefficient analysis, good agreement between aligned expiration and inspiration segmentation maps for the whole-lung and all but one lobe (Dice coefficient > 0.9), with only the lingula generating a value below 0.9 (mean and standard deviation of 0.85 ± 0.06).

CONCLUSION

The subtle and predictable variability in corrected QAT observed in this study suggests that image registration is reliable in preserving the accuracy of the quantitative metrics.

Abnormalities on Chest Computed Tomography and Lung Function Following an Intense Dust Exposure: A 17-Year Longitudinal Study

Fire Department of the City of New York (FDNY) firefighters experienced intense dust exposure working at the World Trade Center (WTC) site on and after 11/9/2001 (9/11). We hypothesized that high-intensity WTC exposure caused abnormalities found on chest computed tomography (CT). Between 11/9/2001–10/9/2018, 4277 firefighters underwent a clinically-indicated chest CT. Spirometric measurements and symptoms were recorded during routine medical examinations. High-intensity exposure, defined as initial arrival at the WTC on the morning of 9/11, increased the risk of bronchial wall thickening, emphysema, and air trapping. Early post-9/11 symptoms of wheeze and shortness of breath were associated with bronchial wall thickening, emphysema, and air trapping. The risk of accelerated forced expiratory volume at one second (FEV₁) decline (>64 mL/year decline) increased with bronchial wall thickening and emphysema, but decreased with air trapping. The risk of airflow obstruction also increased with bronchial wall thickening and emphysema but decreased with air trapping. In a previously healthy occupational cohort, high-intensity WTC exposure increased the risk for CT abnormalities. Bronchial wall thickening and emphysema were associated with respiratory symptoms, accelerated FEV₁ decline, and airflow obstruction. Air trapping was associated with respiratory symptoms, although lung function was preserved. Physiologic differences between CT abnormalities suggest that distinct types of airway injury may result from a common exposure.

Advances in spirometry testing for lung function analysis

Introduction: Spirometry, the most common lung function test, is used to evaluate individuals with respiratory complaints or known respiratory disease. However, its underutilization and the misinterpretation of its parameters are causes for concern. Areas covered: This review describes new spirometry-derived metrics, new reference equations, recent recommendations for presentation of results, recent spirometry-based prevalence studies, and technological advances in spirometry equipment. Expert opinion: The underutilization of spirometry can be overcome by increasing access to portable, hand-held, and user-friendly spirometers, together with strategies that increase awareness of the importance of spirometry. New metrics derived from spirometry, together with traditional spirometric criteria, can identify individuals with structural lung disease and respiratory morbidity. Some problems with the reference equations were solved by the Global Lung Function Initiative (GLI), which covers a wider age range and more ethnic groups and provides limits of normality using the z-score. Despite these advantages, the GLI equations lack data from large populations (especially those from Africa, South Asia, and Latin America) and greater representation of older people. Another disadvantage attributed to the GLI is the lack of predicted values for peak expiratory flow and other airflows, limiting the interpretation of the maximal expiratory flow-volume curve.

Airway quantification using adaptive statistical iterative reconstruction-V on wide-detector low-dose CT: a validation study on lung specimen

PURPOSE

To evaluate the accuracy of airway quantification of adaptive statistical iterative reconstruction (ASIR)-V on low-dose CT using a human lung specimen.

METHOD

A lung specimen was scanned on Revolution CT with low-dose settings (20 mAs, 40 mAs and 60 mAs/100 kV) and standard-dose setting (100 mAs/120 kV). CT images were reconstructed using lung kernel with eleven ASIR-V levels from 0 to 100% with 10% interval. ASIR-V level from 0 to 100% with 10% interval was reconstructed on lung kernel. Wall area percentage (%WA) and wall thickness (WT) were measured.

RESULTS

Radiation dose of 20 mAs, 40 mAs and 60 mAs low-dose settings reduced by 87.6%, 75.2% and 62.8% compared to that on standard dose, respectively. Low-dose settings significantly decreased image SNR (p < 0.05) and increased noise (p < 0.001). ASIR-V level exponentially improved image SNR and linearly decreased image noise (all p < 0.001). The mean airway measurement ratios of low-dose to standard-dose were within 2% variation for %WA and within 3% variation for WT. Most %WA and WT values showed no obvious correlation with ASIR-V levels.

CONCLUSION

ASIR-V showed to improve image quality in low radiation dose. However, low-dose settings and ASIR-V strength did not significantly influence airway quantification values, although variation in measurements slightly increased with dose reduction.

Using a spatial point process framework to characterize lung computed tomography scans

Pulmonary emphysema is a destructive disease of the lungs that is currently diagnosed via visual assessment of lung Computed Tomography (CT) scans by a radiologist. Visual assessment can have poor inter-rater reliability, is time consuming, and requires access to trained assessors. Quantitative methods that reliably summarize the biologically relevant characteristics of an image are needed to improve the way lung diseases are characterized. The goal of this work was to show how spatial point process models can be used to create a set of radiologically derived quantitative lung biomarkers of emphysema. We formalized a general framework for applying spatial point processes to lung CT scans, and developed a Shot Noise Cox Process to quantify how radiologically based emphysematous tissue clusters into larger structures. Bayesian estimation of model parameters was done using spatial Birth-Death MCMC (BD-MCMC). In simulations, we showed the BD-MCMC estimation algorithm is able to accurately recover model parameters. In an application to real lung CT scans from the COPDGene cohort, we showed variability in the clustering characteristics of emphysematous tissue across disease subtypes that were based on visual assessments of the CT scans.

Predictors of Response to Endobronchial Coil Therapy in Patients With Advanced Emphysema

BACKGROUND

The Lung Volume Reduction Coil Treatment in Patients With Emphysema (RENEW) trial reported improvements in quality of life, pulmonary function, and exercise performance following endobronchial coil treatment.

OBJECTIVES

The purpose of this post hoc analysis was to identify baseline predictors, including quantitative CT measures, that identify patients most likely to significantly benefit from endobronchial coil therapy.

METHODS

Quantitative CT analysis by an independent radiology laboratory and a qualitative evaluation by five blinded experts of the baseline thoracic CT imaging were performed. Univariate and multivariate logistic regression analyses were performed to elucidate characteristics associated with clinical response.

RESULTS

In total, 125 patients underwent coil treatment and had evaluable 12-month follow-up results. Of these, 78 patients received treatment of lobes with the highest emphysematous destruction determined by quantitative CT analysis (quantitative visual match [QVM]+), and 47 received treatment in at least one lobe that was not the most destroyed (QVM-). From the 78 patients with QVM+ treatment, a subgroup of 50 patients (64%) was identified with baseline residual volume > 200% predicted, emphysema score > 20% low attenuation area, and absence of airway disease. In this subgroup, greater lobar residual volume reduction in the treated lobes was achieved, which was associated with significant mean ± SE improvement in FEV₁ (15.2 ± 3.1%), St. George's Respiratory Questionnaire (-12 ± 2 points), and residual volume (-0.57 ± 0.13 L).

DISCUSSION

This post hoc analysis found that both significant hyperinflation (residual volume ≥ 200% predicted) and CT analysis are critical for patient selection and treatment planning for endobronchial coil therapy. Quantitative CT analysis is important to identify optimal lobar treatment and to exclude patients with insufficient emphysema (< 20% low attenuation area), whereas visual assessment identifies patients with signs of airway disease associated with worse outcomes.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT01608490; URL: www.clinicaltrials.gov.