PHYSIOLOGIC AND QUANTITATIVE COMPUTED TOMOGRAPHY DIFFERENCES BETWEEN CENTRILOBULAR AND PANLOBULAR EMPHYSEMA IN COPD

Bullous Parametric Response Map for Functional Localization of COPD

Advanced bronchoscopic lung volume reduction treatment (BLVR) is now a routine care option for treating patients with severe emphysema. Patterns of low attenuation clusters indicating emphysema and functional small airway disease (fSAD) on paired CT, which may provide additional insights to the target selection of the segmental or subsegmental lobe of the treatments, require further investigation. The low attenuation clusters (LACS) were segmented to identify the scalar and spatial distribution of the lung destructions, in terms of 10 fractions scales of low attenuation density (LAD) located in upper lobes and lower lobes. The LACs of functional small airway disease (fSAD) were delineated by applying the technique of parametric response map (PRM) on the co-registered CT image data. Both emphysematous LACs of inspiratory CT and fSAD LACs on expiratory CT were used to derive the coefficients of the predictive model for estimating the airflow limitation. The voxel-wise severity is then predicted using the regional LACs on the co-registered CT to indicate the functional localization, namely, the bullous parametric response map (BPRM). A total of 100 subjects, 88 patients with mild to very severe COPD and 12 control participants with normal lung functions (FEV₁/FVC % > 70%), were evaluated. Pearson’s correlations between FEV₁/FVC% and LAV%_HU-950 of severe emphysema are − 0.55 comparing to − 0.67 and − 0.62 of LAV%_HU-856 of air-trapping and LAV%_fSAD respectively. Pearson’s correlation between FEV₁/FVC% and FEV₁/FVC% predicted by the proposed model using LAD% of HU-950 and fSAD on BPRM is 0.82 (p < 0.01). The result of the Bullous Parametric Response Map (BPRM) is capable of identifying the less functional area of the lung, where the BLVR treatment is aimed at removing from a hyperinflated area of emphysematous regions.

Association Between Air Pollution and Lung Lobar Emphysema in COPD

The development of emphysema has been linked to air pollution; however, the association of air pollution with the extent of lobar emphysema remains unclear. This study examined the association of particulate matter <2.5 μm in aerodynamic diameters (PM_2.5) (≤2.5 μm), nitrogen dioxide (NO₂), and ozone (O₃) level of exposure with the presence of emphysema in 86 patients with chronic obstructive pulmonary disease (COPD). Exposure to the air pollution estimated using the land-use regression model was associated with lung function, BODE (a body mass index, degree of obstruction, dyspnea severity, and exercise capacity index) quartiles, and emphysema measured as low-attenuation areas on high-resolution CT (HR-CT) lung scans. Using paraseptal emphysema as the reference group, we observed that a 1 ppb increase in O₃ was associated with a 1.798-fold increased crude odds ratio of panlobular emphysema (p < 0.05). We observed that PM_2.5 was associated with BODE quartiles, modified Medical Research Council (mMRC) dyspnea score, and exercise capacity (all p < 0.05). We found that PM_2.5, NO₂, and O₃ were associated with an increased degree of upper lobe emphysema and lower lobe emphysema (all p < 0.05). Furthermore, we observed that an increase in PM_2.5, NO₂, and O₃ was associated with greater increases in upper lobe emphysema than in lower lobe emphysema. In conclusion, exposure to O₃ can be associated with a higher risk of panlobular emphysema than paraseptal emphysema in patients with COPD. Emphysema severity in lung lobes, especially the upper lobes, may be linked to air pollution exposure in COPD.

Biomechanical CT metrics are associated with patient outcomes in COPD

BACKGROUND

Traditional metrics of lung disease such as those derived from spirometry and static single-volume CT images are used to explain respiratory morbidity in patients with COPD, but are insufficient. We hypothesised that the mean Jacobian determinant, a measure of local lung expansion and contraction with respiration, would contribute independently to clinically relevant functional outcomes.

METHODS

We applied image registration techniques to paired inspiratory-expiratory CT scans and derived the Jacobian determinant of the deformation field between the two lung volumes to map local volume change with respiration. We analysed 490 participants with COPD with multivariable regression models to assess strengths of association between traditional CT metrics of disease and the Jacobian determinant with respiratory morbidity including dyspnoea (modified Medical Research Council), St Georges Respiratory Questionnaire (SGRQ) score, 6-min walk distance (6MWD) and the Body Mass Index, Airflow Obstruction, Dyspnoea and Exercise Capacity (BODE) index, as well as all-cause mortality.

RESULTS

The Jacobian determinant was significantly associated with SGRQ (adjusted regression coefficient β=-11.75,95% CI -21.6 to -1.7; p=0.020), and with 6MWD (β=321.15, 95% CI 134.1 to 508.1; p<0.001), independent of age, sex, race, body mass index, FEV₁, smoking pack-years, CT emphysema, CT gas trapping, airway wall thickness and CT scanner type. The mean Jacobian determinant was also independently associated with the BODE index (β=-0.41, 95% CI -0.80 to -0.02; p=0.039) and mortality on follow-up (adjusted HR=4.26, 95% CI 0.93 to 19.23; p=0.064).

CONCLUSIONS

Biomechanical metrics representing local lung expansion and contraction improve prediction of respiratory morbidity and mortality and offer additional prognostic information beyond traditional measures of lung function and static single-volume CT metrics.

TRIAL REGISTRATION NUMBER

NCT00608764; Post-results.

A Five-Level Wavelet Decomposition and Dimensional Reduction Approach for Feature Extraction and Classification of MR and CT Scan Images

This paper presents a two-dimensional wavelet based decomposition algorithm for classification of biomedical images. The two-dimensional wavelet decomposition is done up to five levels for the input images. Histograms of decomposed images are then used to form the feature set. This feature set is further reduced using probabilistic principal component analysis. The reduced set of features is then fed into either K nearest neighbor algorithm or feed-forward artificial neural network, to classify images. The algorithm is compared with three other techniques in terms of accuracy. The proposed algorithm has been found better up to 3.3%, 12.75%, and 13.75% on average over the first, second, and third algorithm, respectively, using KNN and up to 6.22%, 13.9%, and 14.1% on average using ANN. The dataset used for comparison consisted of CT Scan images of lungs and MR images of heart as obtained from different sources.

Clinical-Radiologic-Pathologic Correlation of Smoking-Related Diffuse Parenchymal Lung Disease

The direct toxicity of cigarette smoke and the body's subsequent response to this lung injury leads to a wide array of pathologic manifestations and disease states that lead to both reversible and irreversible injury to the large airways, small airways, alveolar walls, and alveolar spaces. These include emphysema, bronchitis, bronchiolitis, acute eosinophilic pneumonia, pulmonary Langerhans cell histiocytosis, respiratory bronchiolitis, desquamative interstitial pneumonia, and pulmonary fibrosis. Although these various forms of injury have different pathologic and imaging manifestations, they are all part of the spectrum of smoking-related diffuse parenchymal lung disease.

Distinct emphysema subtypes defined by quantitative CT analysis are associated with specific pulmonary matrix metalloproteinases

BACKGROUND

Emphysema is characterised by distinct pathological sub-types, but little is known about the divergent underlying aetiology. Matrix-metalloproteinases (MMPs) are proteolytic enzymes that can degrade the extracellular matrix and have been identified as potentially important in the development of emphysema. However, the relationship between MMPs and emphysema sub-type is unknown. We investigated the role of MMPs and their inhibitors in the development of emphysema sub-types by quantifying levels and determining relationships with these sub-types in mild-moderate COPD patients and ex/current smokers with preserved lung function.

METHODS

Twenty-four mild-moderate COPD and 8 ex/current smokers with preserved lung function underwent high resolution CT and distinct emphysema sub-types were quantified using novel local histogram-based assessment of lung density. We analysed levels of MMPs and tissue inhibitors of MMPs (TIMPs) in bronchoalveolar lavage (BAL) and assessed their relationship with these emphysema sub-types.

RESULTS

The most prevalent emphysema subtypes in COPD subjects were mild and moderate centrilobular (CLE) emphysema, while only small amounts of severe centrilobular emphysema, paraseptal emphysema (PSE) and panlobular emphysema (PLE) were present. MMP-3, and -10 associated with all emphysema sub-types other than mild CLE, while MMP-7 and -8 had associations with moderate and severe CLE and PSE. MMP-9 also had associations with moderate CLE and paraseptal emphysema. Mild CLE occurred in substantial quantities irrespective of whether airflow obstruction was present and did not show any associations with MMPs.

CONCLUSION

Multiple MMPs are directly associated with emphysema sub-types identified by CT imaging, apart from mild CLE. This suggests that MMPs play a significant role in the tissue destruction seen in the more severe sub-types of emphysema, whereas early emphysematous change may be driven by a different mechanism.

TRIAL REGISTRATION

Trial registration number NCT01701869 .

Panlobular Emphysema: Enhancing Visibility with Quantitative Computed Tomography

Rationale: Several chronic obstructive pulmonary disease (COPD) studies have evaluated risk factors for emergency department (ED) visits or hospitalizations, and found insufficient data available about social and demographic factors that drive these behaviors. This U.S. study was designed to describe the characteristics of COPD patients with ED visits or a hospitalization and to investigate how often common COPD comorbidities are present in these individuals. Methods: Data for 7180 COPD patients regarding demographic factors, comorbidities, smoking status, and ED visits or hospitalization was obtained from the 2012 Behavioral Risk Factor Surveillance System (BRFSS) survey. Logistic regression analysis was used to adjust demographic factors and smoking status to model the correlation between patients with ED visits or hospitalizations and morbidities generating odds ratios (OR) and confidence intervals (CI). Results: Among diagnosed COPD patients in the BRFSS, 16.5% had ED visits or hospitalization in the previous year. These individuals were younger, had a lower socio-economic status (lower education, lower income, and more often unemployed) and 23.4% of the individuals could not visit a doctor because of the financial difficulties compared to 16.7% who had no visit (p<0.0001 for all comparisons). The prevalence of comorbidities was higher in those with ED visits or hospitalization compared to those without. Conclusion: In a population representative of COPD patients, lower socio-economic status and higher comorbidities are associated with ED visits or hospitalization. Studies are needed to further elucidate the complex relationship between COPD, comorbidities, and ED visits or hospitalization.