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Parametric response mapping on chest computed tomography associates with clinical and functional parameters in chronic obstructive pulmonary disease.

ABSTRACT: In the search for specific phenotypes of chronic obstructive pulmonary disease (COPD) computed tomography (CT) derived Parametric Response Mapping (PRM) has been introduced. This study evaluates the association between PRM and currently available biomarkers of disease severity in COPD.Smokers with and without COPD were characterized based on questionnaires, pulmonary function tests, body plethysmography, and low-dose chest CT scanning. PRM was used to calculate the amount of emphysema (PRMEmph) and non-emphysematous air trapping (i.e. functional small airway disease, PRMfSAD). PRM was first compared with other biomarkers for emphysema (Perc15) and air trapping (E/I-ratioMLD). Consequently, linear regression models were utilized to study associations of PRM measurements with clinical parameters.166 participants were included with a mean ± SD age of 50.5 ± 17.7 years. Both PRMEmph and PRMfSAD were more strongly correlated with lung function parameters as compared to Perc15 and E/I-ratioMLD. PRMEmph and PRMfSAD were higher in COPD participants than non-COPD participants (14.0% vs. 1.1%, and 31.6% vs. 8.2%, respectively, both p < 0.001) and increased with increasing GOLD stage (all p < 0.001). Multivariate analysis showed that PRMfSAD was mainly associated with total lung capacity (TLC) (? = -7.90, p < 0.001), alveolar volume (VA) (? = 7.79, p < 0.001), and residual volume (? = 6.78, p < 0.001), whilst PRMEmph was primarily associated with Kco (? = 8.95, p < 0.001), VA (? = -6.21, p < 0.001), and TLC (? = 6.20, p < 0.001).PRM strongly associates with the presence and severity of COPD. PRM therefore appears to be a valuable tool in differentiating COPD phenotypes.

SUBMITTER: Pompe E

PROVIDER: S-EPMC5555031 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Parametric response mapping on chest computed tomography associates with clinical and functional parameters in chronic obstructive pulmonary disease.

Pompe Esther E Galbán Craig J CJ Ross Brian D BD Koenderman Leo L Ten Hacken Nick Ht NH Postma Dirkje S DS van den Berge Maarten M de Jong Pim A PA Lammers Jan-Willem J JJ Mohamed Hoesein Firdaus Aa FA

Respiratory medicine 20161125

<h4>Background</h4>In the search for specific phenotypes of chronic obstructive pulmonary disease (COPD) computed tomography (CT) derived Parametric Response Mapping (PRM) has been introduced. This study evaluates the association between PRM and currently available biomarkers of disease severity in COPD.<h4>Methods</h4>Smokers with and without COPD were characterized based on questionnaires, pulmonary function tests, body plethysmography, and low-dose chest CT scanning. PRM was used to calculate ...[more]

PMID: 28137496

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Project description:ObjectiveEmphysema and small-airway disease are the two major components of chronic obstructive pulmonary disease (COPD). We propose a novel method of quantitative computed tomography (CT) emphysema air-trapping composite (EAtC) mapping to assess each COPD component. We analyzed the potential use of this method for assessing lung function in patients with COPD.Materials and methodsA total of 584 patients with COPD underwent inspiration and expiration CTs. Using pairwise analysis of inspiration and expiration CTs with non-rigid registration, EAtC mapping classified lung parenchyma into three areas: Normal, functional air trapping (fAT), and emphysema (Emph). We defined fAT as the area with a density change of less than 60 Hounsfield units (HU) between inspiration and expiration CTs among areas with a density less than -856 HU on inspiration CT. The volume fraction of each area was compared with clinical parameters and pulmonary function tests (PFTs). The results were compared with those of parametric response mapping (PRM) analysis.ResultsThe relative volumes of the EAtC classes differed according to the Global Initiative for Chronic Obstructive Lung Disease stages (p < 0.001). Each class showed moderate correlations with forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity (FVC) (r = -0.659-0.674, p < 0.001). Both fAT and Emph were significant predictors of FEV1 and FEV1/FVC (R² = 0.352 and 0.488, respectively; p < 0.001). fAT was a significant predictor of mean forced expiratory flow between 25% and 75% and residual volume/total vital capacity (R² = 0.264 and 0.233, respectively; p < 0.001), while Emph and age were significant predictors of carbon monoxide diffusing capacity (R² = 0.303; p < 0.001). fAT showed better correlations with PFTs than with small-airway disease on PRM.ConclusionThe proposed quantitative CT EAtC mapping provides comprehensive lung functional information on each disease component of COPD, which may serve as an imaging biomarker of lung function.

Project description:BackgroundChronic obstructive pulmonary disease (COPD) poses a substantial global health burden, demanding advanced diagnostic tools for early detection and accurate phenotyping. In this line, this study seeks to enhance COPD characterization on chest computed tomography (CT) by comparing the spatial and quantitative relationships between traditional parametric response mapping (PRM) and a novel self-supervised anomaly detection approach, and to unveil potential additional insights into the dynamic transitional stages of COPD.MethodsNon-contrast inspiratory and expiratory CT of 1,310 never-smoker and GOLD 0 individuals and COPD patients (GOLD 1-4) from the COPDGene dataset were retrospectively evaluated. A novel self-supervised anomaly detection approach was applied to quantify lung abnormalities associated with COPD, as regional deviations. These regional anomaly scores were qualitatively and quantitatively compared, per GOLD class, to PRM volumes (emphysema: PRMEmph, functional small-airway disease: PRMfSAD) and to a Principal Component Analysis (PCA) and Clustering, applied on the self-supervised latent space. Its relationships to pulmonary function tests (PFTs) were also evaluated.ResultsInitial t-Distributed Stochastic Neighbor Embedding (t-SNE) visualization of the self-supervised latent space highlighted distinct spatial patterns, revealing clear separations between regions with and without emphysema and air trapping. Four stable clusters were identified among this latent space by the PCA and Cluster Analysis. As the GOLD stage increased, PRMEmph, PRMfSAD, anomaly score, and Cluster 3 volumes exhibited escalating trends, contrasting with a decline in Cluster 2. The patient-wise anomaly scores significantly differed across GOLD stages (p < 0.01), except for never-smokers and GOLD 0 patients. In contrast, PRMEmph, PRMfSAD, and cluster classes showed fewer significant differences. Pearson correlation coefficients revealed moderate anomaly score correlations to PFTs (0.41-0.68), except for the functional residual capacity and smoking duration. The anomaly score was correlated with PRMEmph (r = 0.66, p < 0.01) and PRMfSAD (r = 0.61, p < 0.01). Anomaly scores significantly improved fitting of PRM-adjusted multivariate models for predicting clinical parameters (p < 0.001). Bland-Altman plots revealed that volume agreement between PRM-derived volumes and clusters was not constant across the range of measurements.ConclusionOur study highlights the synergistic utility of the anomaly detection approach and traditional PRM in capturing the nuanced heterogeneity of COPD. The observed disparities in spatial patterns, cluster dynamics, and correlations with PFTs underscore the distinct - yet complementary - strengths of these methods. Integrating anomaly detection and PRM offers a promising avenue for understanding of COPD pathophysiology, potentially informing more tailored diagnostic and intervention approaches to improve patient outcomes.

Project description:BackgroundThe fractal dimension characterizing the cumulative size distribution of low attenuation area (LAA) clusters, identified with a fixed threshold such as -?950 Hounsfield Units (HU), on computed tomography (CT) sensitively detects parenchymal destruction in chronic obstructive pulmonary disease (COPD) even when the percent LAA (LAA%), a standard emphysema index, is unchanged. This study examines whether the cumulative size distribution of LAA clusters, defined with thresholds of the 15th, 25th, and 35th percentiles of a CT density histogram instead of the fixed-threshold of -?950 HU, exhibits a fractal property and whether its fractal dimension (D'15, D'25, and D'35, respectively) provides additional structural information in emphysematous lungs that is difficult to detect with the conventional -?950-HU-based fractal dimension (D950).MethodsChest inspiratory CT scans and pulmonary functions were cross-sectionally examined in 170 COPD subjects. A proxy for the inspiration level at CT scan was obtained by dividing CT-measured total lung volume (CT-TLV) by physiologically measured total lung capacity. Moreover, long-term (>?5 years) changes in D950 and the new fractal dimensions were longitudinally evaluated in 17 current and 42 former smokers with COPD.ResultsD950, but not D'15, D'25, or D'35 was weakly correlated with the proxy for the inspiration. D950, D'25, and D'35 but not D'15 correlated with LAA% and diffusion capacity. In the long-term longitudinal study, LAA% was increased and D950 and D'35 were decreased in both current and former smokers, while D'25 was decreased only in current smokers and D'15 was not changed in either group. The longitudinal changes in D'25 but not those in LAA%, D950, D'15, and D'35 were greater in current smokers than in former smokers. This greater change in D'25 in current smokers was confirmed after adjusting the change in CT-TLV and the baseline D'25.ConclusionsD'25 reflects diffusion capacity in emphysematous lungs and is robust against inspiration levels during CT scans. This new fractal dimension might provide additional structural information that is difficult to detect with the conventional D950 and LAA% and allow for more sensitive evaluation of emphysema progression over time.

Project description:RationaleThe rate of decline of lung function is greater than age-related change in a substantial proportion of patients with chronic obstructive pulmonary disease, even after smoking cessation. Regions of the lung adjacent to emphysematous areas are subject to abnormal stretch during respiration, and this biomechanical stress likely influences emphysema initiation and progression.ObjectivesTo assess whether quantifying this penumbra of lung at risk would predict FEV1 decline.MethodsWe analyzed paired inspiratory-expiratory computed tomography images at baseline of 680 subjects participating in a large multicenter study (COPDGene) over approximately 5 years. By matching inspiratory and expiratory images voxel by voxel using image registration, we calculated the Jacobian determinant, a measure of local lung expansion and contraction with respiration. We measured the distance between each normal voxel to the nearest emphysematous voxel, and quantified the percentage of normal voxels within each millimeter distance from emphysematous voxels as mechanically affected lung (MAL). Multivariable regression analyses were performed to assess the relationship between the Jacobian determinant, MAL, and FEV1 decline.Measurements and main resultsThe mean (SD) rate of decline in FEV1 was 39.0 (58.6) ml/yr. There was a progressive decrease in the mean Jacobian determinant of both emphysematous and normal voxels with increasing disease stage (P < 0.001). On multivariable analyses, the mean Jacobian determinant of normal voxels within 2 mm of emphysematous voxels (MAL2) was significantly associated with FEV1 decline. In mild-moderate disease, for participants at or above the median MAL2 (threshold, 36.9%), the mean decline in FEV1 was 56.4 (68.0) ml/yr versus 43.2 (59.9) ml/yr for those below the median (P = 0.044).ConclusionsAreas of normal-appearing lung are mechanically influenced by emphysematous areas and this lung at risk is associated with lung function decline. Clinical trial registered with www.clinicaltrials.gov (NCT00608764).

Dataset Information

Parametric response mapping on chest computed tomography associates with clinical and functional parameters in chronic obstructive pulmonary disease.

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Parametric response mapping on chest computed tomography associates with clinical and functional parameters in chronic obstructive pulmonary disease.

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