Comparing spirometry, impulse oscillometry with computed tomography for assessing small airway dysfunction in subjects with and without chronic obstructive pulmonary disease
Abstract Background Studies on consistency among spirometry, impulse oscillometry (IOS), and histology for detecting small airway dysfunction (SAD) remain scarce. Considering invasiveness of lung histopathology, we aimed to compare spirometry and IOS with chest computed tomography (CT) for SAD detec...
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2025-01-01
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| Online Access: | https://doi.org/10.1186/s12890-025-03507-1 |
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| author | Suyin Huang Fan Wu Zhishan Deng Jieqi Peng Cuiqiong Dai Lifei Lu Kunning Zhou Xiaohui Wu Qi Wan Gaoying Tang Shengtang Chen Changli Yang Yongqing Huang Shuqing Yu Pixin Ran Yumin Zhou |
| author_facet | Suyin Huang Fan Wu Zhishan Deng Jieqi Peng Cuiqiong Dai Lifei Lu Kunning Zhou Xiaohui Wu Qi Wan Gaoying Tang Shengtang Chen Changli Yang Yongqing Huang Shuqing Yu Pixin Ran Yumin Zhou |
| author_sort | Suyin Huang |
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| description | Abstract Background Studies on consistency among spirometry, impulse oscillometry (IOS), and histology for detecting small airway dysfunction (SAD) remain scarce. Considering invasiveness of lung histopathology, we aimed to compare spirometry and IOS with chest computed tomography (CT) for SAD detection, and evaluate clinical characteristics of subjects with SAD assessed by these three techniques. Methods We collected baseline data from the Early COPD (ECOPD) study. CT-defined SAD was defined as parametric response mapping quantifying SAD (PRMfSAD) ≥ 15%. Spirometry-defined SAD was defined as at least two of maximal mid-expiratory flow (MMEF), forced expiratory flow 50% (FEF50), and forced expiratory flow 75% (FEF75) less than 65% of predicted. IOS-defined SAD was defined as peripheral airway resistance R5 − R20 > 0.07 kPa/L/s. The consistency of spirometry, IOS and CT for diagnosing SAD was assessed using Kappa coefficient. Correlations among the three techniques-measured small airway function parameters were assessed by Spearman correlation analysis. Results 2055 subjects were included in the final analysis. There was low agreement in SAD assessment between spirometry and CT (Kappa = 0.126, 95% confidence interval [CI]: 0.106 to 0.146, p < 0.001), between IOS and CT (Kappa = 0.266, 95% CI: 0.219 to 0.313, p < 0.001), as well as among spirometry, IOS, and CT (Kappa = 0.056, 95% CI: 0.029 to 0.082, p < 0.001). The correlation was moderate (|r|: 0.5 to 0.7, p < 0.05) between spirometry and CT-measured small airway function parameters, and weak (|r|< 0.4, p < 0.05) between IOS and CT-measured small airway function parameters. Only spirometry-defined SAD group had more lower lung function (FEV1/FVC: adjusted difference=-10.7%, 95% CI: -13.5% to -7.8%, p < 0.001) and increased airway wall thickness (Pi 10: adjusted difference = 0.3 mm, 95% CI: 0 to 0.6 mm, p = 0.046) than only CT-defined SAD group. Only IOS-defined SAD group had better lung function (FEV1/FVC: adjusted difference = 3.9%, 95% CI: 1.9 to 5.8%, p < 0.001), less emphysema (inspiratory LAA− 950: adjusted difference=-2.1%, 95% CI:-3.1% to -1.1%, P < 0.001; PRMEmph: adjusted difference=-2.3%, 95% CI: -3.2% to -1.4%, p < 0.001), and thicker airway wall (Pi 10: adjusted difference = 0.2 mm, 95% CI: 0.1 mm to 0.4 mm, p = 0.005) than only CT-defined SAD group. Conclusions There was low consistency in the assessment of SAD between spirometry and CT, between IOS and CT, as well as among spirometry, IOS, and CT. Clinical trial number Not applicable. |
| format | Article |
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| institution | Kabale University |
| issn | 1471-2466 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pulmonary Medicine |
| spelling | doaj-art-c7db215789414c01af0f81d46eec5c4b2025-02-02T12:06:39ZengBMCBMC Pulmonary Medicine1471-24662025-01-0125111310.1186/s12890-025-03507-1Comparing spirometry, impulse oscillometry with computed tomography for assessing small airway dysfunction in subjects with and without chronic obstructive pulmonary diseaseSuyin Huang0Fan Wu1Zhishan Deng2Jieqi Peng3Cuiqiong Dai4Lifei Lu5Kunning Zhou6Xiaohui Wu7Qi Wan8Gaoying Tang9Shengtang Chen10Changli Yang11Yongqing Huang12Shuqing Yu13Pixin Ran14Yumin Zhou15State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityWengyuan People’s HospitalWengyuan People’s HospitalLianping County People’s HospitalLianping County People’s HospitalState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease & National Center for Respiratory Medicine & Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical UniversityAbstract Background Studies on consistency among spirometry, impulse oscillometry (IOS), and histology for detecting small airway dysfunction (SAD) remain scarce. Considering invasiveness of lung histopathology, we aimed to compare spirometry and IOS with chest computed tomography (CT) for SAD detection, and evaluate clinical characteristics of subjects with SAD assessed by these three techniques. Methods We collected baseline data from the Early COPD (ECOPD) study. CT-defined SAD was defined as parametric response mapping quantifying SAD (PRMfSAD) ≥ 15%. Spirometry-defined SAD was defined as at least two of maximal mid-expiratory flow (MMEF), forced expiratory flow 50% (FEF50), and forced expiratory flow 75% (FEF75) less than 65% of predicted. IOS-defined SAD was defined as peripheral airway resistance R5 − R20 > 0.07 kPa/L/s. The consistency of spirometry, IOS and CT for diagnosing SAD was assessed using Kappa coefficient. Correlations among the three techniques-measured small airway function parameters were assessed by Spearman correlation analysis. Results 2055 subjects were included in the final analysis. There was low agreement in SAD assessment between spirometry and CT (Kappa = 0.126, 95% confidence interval [CI]: 0.106 to 0.146, p < 0.001), between IOS and CT (Kappa = 0.266, 95% CI: 0.219 to 0.313, p < 0.001), as well as among spirometry, IOS, and CT (Kappa = 0.056, 95% CI: 0.029 to 0.082, p < 0.001). The correlation was moderate (|r|: 0.5 to 0.7, p < 0.05) between spirometry and CT-measured small airway function parameters, and weak (|r|< 0.4, p < 0.05) between IOS and CT-measured small airway function parameters. Only spirometry-defined SAD group had more lower lung function (FEV1/FVC: adjusted difference=-10.7%, 95% CI: -13.5% to -7.8%, p < 0.001) and increased airway wall thickness (Pi 10: adjusted difference = 0.3 mm, 95% CI: 0 to 0.6 mm, p = 0.046) than only CT-defined SAD group. Only IOS-defined SAD group had better lung function (FEV1/FVC: adjusted difference = 3.9%, 95% CI: 1.9 to 5.8%, p < 0.001), less emphysema (inspiratory LAA− 950: adjusted difference=-2.1%, 95% CI:-3.1% to -1.1%, P < 0.001; PRMEmph: adjusted difference=-2.3%, 95% CI: -3.2% to -1.4%, p < 0.001), and thicker airway wall (Pi 10: adjusted difference = 0.2 mm, 95% CI: 0.1 mm to 0.4 mm, p = 0.005) than only CT-defined SAD group. Conclusions There was low consistency in the assessment of SAD between spirometry and CT, between IOS and CT, as well as among spirometry, IOS, and CT. Clinical trial number Not applicable.https://doi.org/10.1186/s12890-025-03507-1Computed tomographyImpulse oscillometryParametric response mappingSmall airway dysfunctionSpirometry |
| spellingShingle | Suyin Huang Fan Wu Zhishan Deng Jieqi Peng Cuiqiong Dai Lifei Lu Kunning Zhou Xiaohui Wu Qi Wan Gaoying Tang Shengtang Chen Changli Yang Yongqing Huang Shuqing Yu Pixin Ran Yumin Zhou Comparing spirometry, impulse oscillometry with computed tomography for assessing small airway dysfunction in subjects with and without chronic obstructive pulmonary disease BMC Pulmonary Medicine Computed tomography Impulse oscillometry Parametric response mapping Small airway dysfunction Spirometry |
| title | Comparing spirometry, impulse oscillometry with computed tomography for assessing small airway dysfunction in subjects with and without chronic obstructive pulmonary disease |
| title_full | Comparing spirometry, impulse oscillometry with computed tomography for assessing small airway dysfunction in subjects with and without chronic obstructive pulmonary disease |
| title_fullStr | Comparing spirometry, impulse oscillometry with computed tomography for assessing small airway dysfunction in subjects with and without chronic obstructive pulmonary disease |
| title_full_unstemmed | Comparing spirometry, impulse oscillometry with computed tomography for assessing small airway dysfunction in subjects with and without chronic obstructive pulmonary disease |
| title_short | Comparing spirometry, impulse oscillometry with computed tomography for assessing small airway dysfunction in subjects with and without chronic obstructive pulmonary disease |
| title_sort | comparing spirometry impulse oscillometry with computed tomography for assessing small airway dysfunction in subjects with and without chronic obstructive pulmonary disease |
| topic | Computed tomography Impulse oscillometry Parametric response mapping Small airway dysfunction Spirometry |
| url | https://doi.org/10.1186/s12890-025-03507-1 |
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