Paired inspiratory-expiratory chest CT scans to assess for small airways disease in COPD.
Ontology highlight
ABSTRACT: Background
Gas trapping quantified on chest CT scans has been proposed as a surrogate for small airway disease in COPD. We sought to determine if measurements using paired inspiratory and expiratory CT scans may be better able to separate gas trapping due to emphysema from gas trapping due to small airway disease.Methods
Smokers with and without COPD from the COPDGene Study underwent inspiratory and expiratory chest CT scans. Emphysema was quantified by the percent of lung with attenuation?ResultsIn 8517 subjects with complete data, Exp(-856) was highly correlated with emphysema. The measures based on paired inspiratory and expiratory CT scans were less strongly correlated with emphysema. Exp(-856), E/I MLA and RVC(856-950) were predictive of spirometry, exercise capacity and quality of life in all subjects and in subjects without emphysema. In subjects with severe emphysema, E/I MLA and RVC(856-950) showed the highest correlations with clinical variables.Conclusions
Quantitative measures based on paired inspiratory and expiratory chest CT scans can be used as markers of small airway disease in smokers with and without COPD, but this will require that future studies acquire both inspiratory and expiratory CT scans.
SUBMITTER: Hersh CP
PROVIDER: S-EPMC3627637 | biostudies-literature | 2013 Apr
REPOSITORIES: biostudies-literature
Publications
Paired inspiratory-expiratory chest CT scans to assess for small airways disease in COPD.
Hersh Craig P CP Washko George R GR Estépar Raúl San José RS Lutz Sharon S Friedman Paul J PJ Han MeiLan K MK Hokanson John E JE Judy Philip F PF Lynch David A DA Make Barry J BJ Marchetti Nathaniel N Newell John D JD Sciurba Frank C FC Crapo James D JD Silverman Edwin K EK
Respiratory research 20130408
<h4>Background</h4>Gas trapping quantified on chest CT scans has been proposed as a surrogate for small airway disease in COPD. We sought to determine if measurements using paired inspiratory and expiratory CT scans may be better able to separate gas trapping due to emphysema from gas trapping due to small airway disease.<h4>Methods</h4>Smokers with and without COPD from the COPDGene Study underwent inspiratory and expiratory chest CT scans. Emphysema was quantified by the percent of lung with a ...[more]
Similar Datasets
Project description:ObjectivesDensitometry on paired inspiratory and expiratory multidetector computed tomography (MDCT) for the quantification of air trapping is an important approach to assess functional changes in airways diseases such as cystic fibrosis (CF). For a regional analysis of functional deficits, an accurate lobe segmentation algorithm applicable to inspiratory and expiratory scans is beneficial.Materials and methodsWe developed a fully automated lobe segmentation algorithm, and subsequently validated automatically generated lobe masks (ALM) against manually corrected lobe masks (MLM). Paired inspiratory and expiratory CTs from 16 children with CF (mean age 11.1±2.4) acquired at 4 time-points (baseline, 3mon, 12mon, 24mon) with 2 kernels (B30f, B60f) were segmented, resulting in 256 ALM. After manual correction spatial overlap (Dice index) and mean differences in lung volume and air trapping were calculated for ALM vs. MLM.ResultsThe mean overlap calculated with Dice index between ALM and MLM was 0.98±0.02 on inspiratory, and 0.86±0.07 on expiratory CT. If 6 lobes were segmented (lingula treated as separate lobe), the mean overlap was 0.97±0.02 on inspiratory, and 0.83±0.08 on expiratory CT. The mean differences in lobar volumes calculated in accordance with the approach of Bland and Altman were generally low, ranging on inspiratory CT from 5.7±52.23cm3 for the right upper lobe to 17.41±14.92cm3 for the right lower lobe. Higher differences were noted on expiratory CT. The mean differences for air trapping were even lower, ranging from 0±0.01 for the right upper lobe to 0.03±0.03 for the left lower lobe.ConclusionsAutomatic lobe segmentation delivers excellent results for inspiratory and good results for expiratory CT. It may become an important component for lobe-based quantification of functional deficits in cystic fibrosis lung disease, reducing necessity for user-interaction in CT post-processing.
| S-EPMC5890971 | biostudies-literature
Project description:We evaluated pulmonary sequelae in COVID-19 survivors by quantitative inspiratory-expiratory chest CT (QCT) and explored abnormal pulmonary diffusion risk factors at the 6-month follow-up. This retrospective study enrolled 205 COVID-19 survivors with baseline CT data and QCT scans at 6-month follow-up. Patients without follow-up pulmonary function tests were excluded. All subjects were divided into group 1 (carbon monoxide diffusion capacity [DLCO] < 80% predicted, n = 88) and group 2 (DLCO ≥ 80% predicted, n = 117). Clinical characteristics and lung radiological changes were recorded. Semiquantitative total CT score (0-25) was calculated by adding five lobes scores (0-5) according to the range of lesion involvement (0: no involvement; 1: < 5%; 2: 5-25%; 3: 26-50%; 4: 51-75%; 5: > 75%). Data was analyzed by two-sample t-test, Spearman test, etc. 29% survivors showed air trapping by follow-up QCT. Semiquantitative CT score and QCT parameter of air trapping in group 1 were significantly greater than group 2 (p < 0.001). Decreased DLCO was negatively correlated with the follow-up CT score for ground-glass opacity (r = - 0.246, p = 0.003), reticulation (r = - 0.206, p = 0.002), air trapping (r = - 0.220, p = 0.002) and relative lung volume changes (r = - 0.265, p = 0.001). COVID-19 survivors with lung diffusion deficits at 6-month follow-up tended to develop air trapping, possibly due to small-airway impairment.
| S-EPMC9070972 | biostudies-literature
Project description:BackgroundPartial volume averaging and tilt relative to the scan plane on transverse images limit the accuracy of airway wall thickness measurements on CT scan, confounding assessment of the relationship between airway remodeling and clinical status in COPD. The purpose of this study was to assess the effect of partial volume averaging and tilt corrections on airway wall thickness measurement accuracy and on relationships between airway wall thickening and clinical status in COPD.MethodsAirway wall thickness measurements in 80 heavy smokers were obtained on transverse images from low-dose CT scan using the open-source program Airway Inspector. Measurements were corrected for partial volume averaging and tilt effects using an attenuation- and geometry-based algorithm and compared with functional status.ResultsThe algorithm reduced wall thickness measurements of smaller airways to a greater degree than larger airways, increasing the overall range. When restricted to analyses of airways with an inner diameter < 3.0 mm, for a theoretical airway of 2.0 mm inner diameter, the wall thickness decreased from 1.07 ± 0.07 to 0.29 ± 0.10 mm, and the square root of the wall area decreased from 3.34 ± 0.15 to 1.58 ± 0.29 mm, comparable to histologic measurement studies. Corrected measurements had higher correlation with FEV₁, differed more between BMI, airflow obstruction, dyspnea, and exercise capacity (BODE) index scores, and explained a greater proportion of FEV1 variability in multivariate models.ConclusionsCorrecting for partial volume averaging improves accuracy of airway wall thickness estimation, allowing direct measurement of the small airways to better define their role in COPD.
| S-EPMC3653346 | biostudies-literature
Project description: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.
| S-EPMC7097831 | biostudies-literature
Project description:Rationale: DNA methylation is an epigenetic modification that is highly disrupted in response to cigarette smoke and involved in a wide spectrum of malignant and non-malignant diseases, but surprisingly not previously assessed in small airways of patients with chronic obstructive pulmonary disease (COPD). Small airways are the primary sites of airflow obstruction in COPD. We sought to determine whether DNA methylation patterns are disrupted in small airway epithelia of COPD patients, and evaluate whether changes in gene expression are associated with these disruptions. Methods: Genome-wide methylation and gene expression analysis were performed on small airway epithelial DNA and RNA obtained from the same patient during bronchoscopy, using Illumina's Infinium HM27 and Affymetrix's Genechip Human Gene 1.0 ST arrays. To control for known effects of cigarette smoking on DNA methylation, methylation and gene expression profiles were compared between former smokers (FS) with and without COPD matched for age, pack years and years of smoking cessation. Results: Our results indicate that aberrant DNA methylation is i) a genome-wide phenomenon in small airways of patients with COPD and ii) associated with altered expression of genes and pathways important to COPD, such as the Nrf2 oxidative response pathway. Conclusions: DNA methylation is likely an important mechanism contributing to modulation of genes important to COPD pathology. Since these methylation events may underlie disease-specific gene-expression changes, their characterization is a critical first step towards the development of epigenetic markers and an opportunity for developing novel epigenetic therapeutic interventions for COPD. Bisulphite converted DNA from small airway (airways less than <2 mm in diameter) from 38 former smokers: 15 subjects with COPD (post bronchodilator FEV1/FVC ratio <70% and FEV1 predicted M-bM-^IM-$ 80%) and 21 with normal lung function, were hybridized to the Illumina Infinium 27k Human Methylation Beadchip.
2014-02-28 | E-GEOD-55454 | biostudies-arrayexpress
Project description:Rationale: DNA methylation is an epigenetic modification that is highly disrupted in response to cigarette smoke and involved in a wide spectrum of malignant and non-malignant diseases, but surprisingly not previously assessed in small airways of patients with chronic obstructive pulmonary disease (COPD). Small airways are the primary sites of airflow obstruction in COPD. We sought to determine whether DNA methylation patterns are disrupted in small airway epithelia of COPD patients, and evaluate whether changes in gene expression are associated with these disruptions. Methods: Genome-wide methylation and gene expression analysis were performed on small airway epithelial DNA and RNA obtained from the same patient during bronchoscopy, using Illumina's Infinium HM27 and Affymetrix's Genechip Human Gene 1.0 ST arrays. To control for known effects of cigarette smoking on DNA methylation, methylation and gene expression profiles were compared between former smokers (FS) with and without COPD matched for age, pack years and years of smoking cessation. Results: Our results indicate that aberrant DNA methylation is i) a genome-wide phenomenon in small airways of patients with COPD and ii) associated with altered expression of genes and pathways important to COPD, such as the Nrf2 oxidative response pathway. Conclusions: DNA methylation is likely an important mechanism contributing to modulation of genes important to COPD pathology. Since these methylation events may underlie disease-specific gene-expression changes, their characterization is a critical first step towards the development of epigenetic markers and an opportunity for developing novel epigenetic therapeutic interventions for COPD.
2014-02-28 | GSE55454 | GEO
Project description:Exertional prolonged expiration should be identified as a therapeutic target in COPD. The efficacy of expiratory or inspiratory pressure load training (EPT/IPT) based on the degree of prolonged expiration was investigated. A total of 21 patients with COPD were divided into two groups according to the exertional change in the inspiratory duty cycle (TI/Ttot). For 12 weeks, patients whose exertional TI/Ttot decreased received EPT (EPT group, n=11, mean percentage forced expiratory volume in 1 s (%FEV1), 32.8%) and those whose exertional TI/Ttot increased received IPT (IPT group, n=10, mean %FEV1, 45.1%). The therapeutic responses were as follows. In both groups, endurance time (EPT, +5.7 min, p<0.0001; IPT, +6.1 min, p=0.0004) on the constant work rate exercise test (WRET) and peak oxygen uptake increased (EPT, p=0.0028; IPT, p=0.0072). In the EPT group the following occurred: 1) soon after commencement of exercise with the constant WRET, the expiratory tidal volume (VTex) increased, reducing dyspnoea; 2) VTex and mean expiratory flow increased and then prolonged expiration (p=0.0001) improved at peak exercise with the incremental exercise test (ET); and 3) St. George's Respiratory Questionnaire total, activity and impact scores were improved. In the IPT group, on both the constant WRET and incremental ET, breathing frequency increased, which led to greater exercise performance with effort dyspnoea. This study showed the benefits of EPT/IPT on exercise performance. If the choice of managing COPD with EPT/IPT is appropriate, inexpensive EPT/IPT may become widespread as home-based training.
| S-EPMC7456645 | biostudies-literature
Project description:PurposeTo establish a method for quantitatively estimating the extent of the communication between the cyst and the airway in cystic lung diseases (CLDs) and evaluate its diagnostic utility in differentiating among CLDs.Materials and methodsSeventy-one patients (mean age, 49.9 years; age range, 25-79 years) with CLDs who underwent paired inspiratory and expiratory CT between July 2015 and July 2018 were enrolled in this prospective study. Participants were divided into three groups based on their diagnosis: Birt-Hogg-Dubé syndrome (BHDS) group (15 participants), lymphangioleiomyomatosis (LAM) group (43 participants), and other diseases (OT) group (13 participants). Total lung volume (TLV) and low-attenuation area volume (LAAV) were calculated at inspiration and expiration. The collapsibility of the LAAV was determined as the expiration-to-inspiration (E/I) ratio of LAAV (E/I ratio LAAV). The cyst-airway communicating index (CACI), the ratio of the LAAV change between inspiration and expiration to the TLV change between inspiration and expiration, was also determined. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic utility for differentiating diseases.ResultsThe E/I ratio LAAV was significantly higher in the BHDS group (0.69; 95% confidence interval [CI]: 0.61, 0.78) than in the LAM (0.33; 95% CI: 0.28, 0.38) (P < .001) and the OT (0.51; 95% CI: 0.38, 0.64) (P = .038) groups. The CACI was significantly lower in the BHDS group (0.89; 95% CI: 0.61, 1.17) than in the LAM (1.89; 95% CI: 1.76, 2.0) (P < .001) and the OT (1.539; 95% CI: 1.21, 1.86) (P = .003) groups. There was no significant difference in the area under the ROC curve of the CACI (0.881; 95% CI: 0.7749, 0.987) and the E/I ratio LAAV (0.877; 95% CI: 0.791, 0.963) for differentiating BHDS from other diseases.ConclusionQuantitative analysis using paired inspiratory and expiratory CT for estimating the extent of cyst-airway communication in CLDs is useful when distinguishing BHDS from other diseases.Supplemental material is available for this article.© RSNA, 2020See also the commentary by Chung in this issue.
| S-EPMC7978012 | biostudies-literature
Project description:PurposeTo develop and validate a computed tomography (CT) harmonization technique by combining noise-stabilization and autocalibration methodologies to provide reliable densitometry measurements in heterogeneous acquisition protocols.MethodsWe propose to reduce the effects of spatially variant noise such as nonuniform patterns of noise and biases. The method combines the statistical characterization of the signal-to-noise relationship in the CT image intensities, which allows us to estimate both the signal and spatially variant variance of noise, with an autocalibration technique that reduces the nonuniform biases caused by noise and reconstruction techniques. The method is firstly validated with anthropomorphic synthetic images that simulate CT acquisitions with variable scanning parameters: different dosage, nonhomogeneous variance of noise, and various reconstruction methods. We finally evaluate these effects and the ability of our method to provide consistent densitometric measurements in a cohort of clinical chest CT scans from two vendors (Siemens, n = 54 subjects; and GE, n = 50 subjects) acquired with several reconstruction algorithms (filtered back-projection and iterative reconstructions) with high-dose and low-dose protocols.ResultsThe harmonization reduces the effect of nonhomogeneous noise without compromising the resolution of the images (25% RMSE reduction in both clinical datasets). An analysis through hierarchical linear models showed that the average biases induced by differences in dosage and reconstruction methods are also reduced up to 74.20%, enabling comparable results between high-dose and low-dose reconstructions. We also assessed the statistical similarity between acquisitions obtaining increases of up to 30% points and showing that the low-dose vs high-dose comparisons of harmonized data obtain similar and even higher similarity than the observed for high-dose vs high-dose comparisons of nonharmonized data.ConclusionThe proposed harmonization technique allows to compare measures of low-dose with high-dose acquisitions without using a specific reconstruction as a reference. Since the harmonization does not require a precalibration with a phantom, it can be applied to retrospective studies. This approach might be suitable for multicenter trials for which a reference reconstruction is not feasible or hard to define due to differences in vendors, models, and reconstruction techniques.
| S-EPMC7251983 | biostudies-literature
Project description:ObjectivesAn artificial intelligence model was adopted to identify mild COVID-19 pneumonia from computed tomography (CT) volumes, and its diagnostic performance was then evaluated.MethodsIn this retrospective multicenter study, an atrous convolution-based deep learning model was established for the computer-assisted diagnosis of mild COVID-19 pneumonia. The dataset included 2087 chest CT exams collected from four hospitals between 1 January 2019 and 31 May 2020. The true positive rate, true negative rate, receiver operating characteristic curve, area under the curve (AUC) and convolutional feature map were used to evaluate the model.ResultsThe proposed deep learning model was trained on 1538 patients and tested on an independent testing cohort of 549 patients. The overall sensitivity was 91.5% (195/213; p < 0.001, 95% CI: 89.2-93.9%), the overall specificity was 90.5% (304/336; p < 0.001, 95% CI: 88.0-92.9%) and the general AUC value was 0.955 (p < 0.001).ConclusionsA deep learning model can accurately detect COVID-19 and serve as an important supplement to the COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) test.Key points• The implementation of a deep learning model to identify mild COVID-19 pneumonia was confirmed to be effective and feasible. • The strategy of using a binary code instead of the region of interest label to identify mild COVID-19 pneumonia was verified. • This AI model can assist in the early screening of COVID-19 without interfering with normal clinical examinations.
| S-EPMC7971359 | biostudies-literature