Lung densitometry to assess progression of emphysema in chronic obstructive pulmonary disease: time to apply in the clinic?

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

Background

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

Methods

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

Results

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

Conclusions

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

Electronic supplementary material

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

Predicting all-cause and lung cancer mortality using emphysema score progression rate between baseline and follow-up chest CT images: A comparison of risk model performances

Purpose

Normalized emphysema score is a protocol-robust CT biomarker of mortality. We aimed to improve mortality prediction by including the emphysema score progression rate–its change over time–into the models.

Method and materials

CT scans from 6000 National Lung Screening Trial CT arm participants were included. Of these, 1810 died (445 lung cancer-specific). The remaining 4190 survivors were sampled with replacement up to 24432 to approximate the full cohort. Three overlapping subcohorts were formed which required participants to have images from specific screening rounds. Emphysema scores were obtained after resampling, normalization, and bullae cluster analysis of the original images. Base models contained solely the latest emphysema score. Progression models included emphysema score progression rate. Models were adjusted by including baseline age, sex, BMI, smoking status, smoking intensity, smoking duration, and previous COPD diagnosis. Cox proportional hazard models predicting all-cause and lung cancer mortality were compared by calculating the area under the curve per year follow-up.

Results

In the subcohort of participants with baseline and first annual follow-up scans, the analysis was performed on 4940 participants (23227 after resampling). Area under the curve for all-cause mortality predictions of the base and progression models 6 years after baseline were 0.564 (0.564 to 0.565) and 0.569 (0.568 to 0.569) when unadjusted, and 0.704 (0.703 to 0.704) to 0.705 (0.704 to 0.705) when adjusted. The respective performances predicting lung cancer mortality were 0.638 (0.637 to 0.639) and 0.643 (0.642 to 0.644) when unadjusted, and 0.724 (0.723 to 0.725) and 0.725 (0.725 to 0.726) when adjusted.

Conclusion

Including emphysema score progression rate into risk models shows no clinically relevant improvement in mortality risk prediction. This is because scan normalization does not adjust for an overall change in lung density. Adjusting for changes in smoking behavior is likely required to make this a clinically useful measure of emphysema progression.

Lung function and CT lung densitometry in 37- to 39-year-old individuals with alpha-1-antitrypsin deficiency

BACKGROUND

Alpha-1-antitrypsin (AAT) deficiency is a hereditary disorder that predisposes to emphysema. A cohort of severe (PiZZ) and moderate (PiSZ) AAT-deficient newborn infants was identified by the Swedish national neonatal AAT screening program in 1972-1974 and has been followed-up since birth. Our aim was to study whether the cohort has signs of emphysema in pulmonary function tests (PFTs) and computed tomography (CT) densitometry at 38 years of age in comparison with an age-matched control group, randomly selected from the population registry.

METHODS

Forty-one PiZZ, 18 PiSZ, and 61 control subjects (PiMM) underwent complete PFTs, measurement of resistance and reactance in the respiratory system by impulse oscillometry (IOS)/forced oscillation technique (FOT), and CT densitometry. The results were related to self-reported smoking habits.

RESULTS

The total lung capacity (TLC) % of the predicted value was significantly higher in the PiZZ ever-smokers than in the PiZZ never-smokers (P<0.05), PiSZ never-smokers (P=0.01) and the PiMM never-smokers (P=0.01). The residual volume (RV) % of the predicted value was significantly higher in the PiZZ ever-smokers compared to the PiMM never-smokers (P<0.01). The PiZZ ever-smokers had a significantly lower carbon monoxide transfer coefficient (Kco) than the PiSZ never-smokers (P<0.01) and PiMM never-smokers (P<0.01). Respiratory system resistance at 5 Hz (P<0.01), at 20 Hz (P<0.01), and the area of low reactance (Alx; P<0.05) were significantly lower and respiratory system reactance at 5 Hz (P<0.05) was significantly higher in PiZZ subjects compared to the PiMM subjects. No statistically significant differences in the CT densitometry parameters were found between the Pi subgroups.

CONCLUSION

The physiological parameters in the PiZZ ever-smokers showed evidence of hyperinflation and emphysema before the age of 40 years.

Pulmonary Emphysema Quantification on Ultra-Low-Dose Computed Tomography Using Model-Based Iterative Reconstruction With or Without Lung Setting

OBJECTIVES

To evaluate the influence of model-based iterative reconstruction (MBIR) with lung setting and conventional setting on pulmonary emphysema quantification by ultra-low-dose computed tomography (ULDCT) compared with standard-dose CT (SDCT).

METHODS

Forty-five patients who underwent ULDCT (0.18 ± 0.02 mSv) and SDCT (6.66 ± 2.69 mSv) were analyzed in this retrospective study. Images were reconstructed using filtered back projection (FBP) with smooth and sharp kernels and MBIR with conventional and lung settings. Extent of emphysema was evaluated using fully automated software. Correlation between ULDCT and SDCT was assessed by interclass correlation coefficiency (ICC) and Bland-Altman analysis.

RESULTS

Excellent correlation was seen between MBIR with conventional setting on ULDCT and FBP with smooth kernel on SDCT (ICC, 0.97; bias, -0.31%) and between MBIR with lung setting on ULDCT and FBP with sharp kernel on SDCT (ICC, 0.82; bias, -2.10%).

CONCLUSION

Model-based iterative reconstruction improved the agreement between ULDCT and SDCT on emphysema quantification.

Lung densitometry: why, how and when

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

Normalizing computed tomography data reconstructed with different filter kernels: effect on emphysema quantification

Objectives

To propose and evaluate a method to reduce variability in emphysema quantification among different computed tomography (CT) reconstructions by normalizing CT data reconstructed with varying kernels.

Methods

We included 369 subjects from the COPDGene study. For each subject, spirometry and a chest CT reconstructed with two kernels were obtained using two different scanners. Normalization was performed by frequency band decomposition with hierarchical unsharp masking to standardize the energy in each band to a reference value. Emphysema scores (ES), the percentage of lung voxels below -950 HU, were computed before and after normalization. Bland-Altman analysis and correlation between ES and spirometry before and after normalization were compared. Two mixed cohorts, containing data from all scanners and kernels, were created to simulate heterogeneous acquisition parameters.

Results

The average difference in ES between kernels decreased for the scans obtained with both scanners after normalization (7.7 ± 2.7 to 0.3 ± 0.7; 7.2 ± 3.8 to -0.1 ± 0.5). Correlation coefficients between ES and FEV₁, and FEV₁/FVC increased significantly for the mixed cohorts.

Conclusions

Normalization of chest CT data reduces variation in emphysema quantification due to reconstruction filters and improves correlation between ES and spirometry.

Key Points

• Emphysema quantification is sensitive to the reconstruction kernel used.

• Normalization allows comparison of emphysema quantification from images reconstructed with varying kernels.

• Normalization allows comparison of emphysema quantification obtained with scanners from different manufacturers.

• Normalization improves correlation of emphysema quantification with spirometry.

• Normalization can be used to compare data from different studies and centers.

Role of p53 in lung tissue remodeling

The tumor suppressor gene p53 regulates a wide range of cellular processes including cell cycle progression, proliferation, apoptosis and tissue development and remodeling. Lung cell apoptosis and tissue remodeling have critical roles in many lung diseases. Abnormal proliferation or resistance to apoptosis of lung cells will lead to structural changes of many lung tissues, including the pulmonary vascular wall, small airways and lung parenchyma. Among the many lung diseases caused by vascular cell apoptosis and tissue remodeling are chronic obstructive pulmonary disease, bronchial asthma and pulmonary arterial hypertension. Recent advances in biology and medicine have provided new insights and have resulted in new therapeutic strategies for tissue remodeling in human and animal models. This review is focused on lung disease susceptibility associated with the p53 pathway and describes molecular mechanisms upstream and downstream of p53 in lung tissue remodeling. Improved understanding of structural changes associated with pulmonary vascular remodeling and lung cell apoptosis induced by the p53 pathway may new provide therapeutic targets.

Impact of emphysema heterogeneity on pulmonary function

Objectives

To investigate the association between emphysema heterogeneity in spatial distribution, pulmonary function and disease severity.

Methods and Materials

We ascertained a dataset of anonymized Computed Tomography (CT) examinations acquired on 565 participants in a COPD study. Subjects with chronic bronchitis (CB) and/or bronchodilator response were excluded resulting in 190 cases without COPD and 160 cases with COPD. Low attenuations areas (LAAs) (≤950 Hounsfield Unit (HU)) were identified and quantified at the level of individual lobes. Emphysema heterogeneity was defined in a manner that ranged in value from −100% to 100%. The association between emphysema heterogeneity and pulmonary function measures (e.g., FEV1% predicted, RV/TLC, and DLco% predicted) adjusted for age, sex, and smoking history (pack-years) was assessed using multiple linear regression analysis.

Results

The majority (128/160) of the subjects with COPD had a heterogeneity greater than zero. After adjusting for age, gender, smoking history, and extent of emphysema, heterogeneity in depicted disease in upper lobe dominant cases was positively associated with pulmonary function measures, such as FEV1 Predicted (p<.001) and FEV1/FVC (p<.001), as well as disease severity (p<0.05). We found a negative association between HI% , RV/TLC (p<0.001), and DLco% (albeit not a statistically significant one, p = 0.06) in this group of patients.

Conclusion

Subjects with more homogeneous distribution of emphysema and/or lower lung dominant emphysema tend to have worse pulmonary function.

Improved correlation between CT emphysema quantification and pulmonary function test by density correction of volumetric CT data based on air and aortic density

OBJECTIVES

To determine the improvement of emphysema quantification with density correction and to determine the optimal site to use for air density correction on volumetric computed tomography (CT).

METHODS

Seventy-eight CT scans of COPD patients (GOLD II-IV, smoking history 39.2±25.3 pack-years) were obtained from several single-vendor 16-MDCT scanners. After density measurement of aorta, tracheal- and external air, volumetric CT density correction was conducted (two reference values: air, -1,000 HU/blood, +50 HU). Using in-house software, emphysema index (EI) and mean lung density (MLD) were calculated. Differences in air densities, MLD and EI prior to and after density correction were evaluated (paired t-test). Correlation between those parameters and FEV1 and FEV1/FVC were compared (age- and sex adjusted partial correlation analysis).

RESULTS

Measured densities (HU) of tracheal- and external air differed significantly (-990 ± 14, -1016 ± 9, P<0.001). MLD and EI on original CT data, after density correction using tracheal- and external air also differed significantly (MLD: -874.9 ± 27.6 vs. -882.3 ± 24.9 vs. -860.5 ± 26.6; EI: 16.8 ± 13.4 vs. 21.1 ± 14.5 vs. 9.7 ± 10.5, respectively, P<0.001). The correlation coefficients between CT quantification indices and FEV1, and FEV1/FVC increased after density correction. The tracheal air correction showed better results than the external air correction.

CONCLUSION

Density correction of volumetric CT data can improve correlations of emphysema quantification and PFT.