Dorothea Cornelia Theilig 1 , Ralf-Harto Huebner 2 , Konrad Neumann 3 , Alexander Poellinger 4 , Felix Doellinger 1 Show Affiliations »
Abstract
PURPOSE: Evaluation of emphysema distribution with quantitative computed tomography (qCT) prior to endoscopic lung volume reduction (ELVR) is recommended. The aim of this study was to determine which of the commonly assessed qCT parameters prior to endoscopic lung volume reduction (ELVR) best predicts outcome of treatment. MATERIALS AND METHODS: 50 patients who underwent technically successful ELVR at our institution were retrospectively analyzed. We performed quantitative analysis of the CT scans obtained prior to ELVR and carried out Mann-Whitney U-tests and a logistic regression analysis to identify the qCT parameters that predict successful outcome of ELVR in terms of improved forced expiratory volume in 1 second (FEV1). RESULTS: In the Mann-Whitney U-test, the interlobar emphysema heterogeneity index (p = 0.008) and the pulmonary emphysema score (p = 0.022) showed a statistically significant difference between responders and non-responders. In multiple logistic regression analysis only the interlobar emphysema heterogeneity index (p = 0.008) showed a statistically significant impact on the outcome of ELVR, while targeted lobe volume, total lung volume, targeted lobe emphysema score and total lung emphysema score did not. CONCLUSION: Of all commonly assessed quantitative CT parameters, only the heterogeneity index definitely allows prediction of ELVR outcome in patients with advanced chronic obstructive pulmonary disease (COPD). KEY POINTS: · Quantitative CT is recommended prior to ELVR.. · The relevance of the obtained parameters from quantitative CT remains controversial.. · This study confirms that only the emphysema heterogeneity index has a definite impact.. CITATION FORMAT: · Theilig DC, Huebner R, Neumann K et al. Selecting Patients for Lobar Lung Volume Reduction Therapy: What Quantitative Computed Tomography Parameters Matter?. Fortschr Röntgenstr 2019; 191: 40 - 47. © Georg Thieme Verlag KG Stuttgart · New York.
PURPOSE: Evaluation of emphysema distribution with quantitative computed tomography (qCT) prior to endoscopic lung volume reduction (ELVR) is recommended. The aim of this study was to determine which of the commonly assessed qCT parameters prior to endoscopic lung volume reduction (ELVR) best predicts outcome of treatment. MATERIALS AND METHODS: 50 patients who underwent technically successful ELVR at our institution were retrospectively analyzed. We performed quantitative analysis of the CT scans obtained prior to ELVR and carried out Mann-Whitney U-tests and a logistic regression analysis to identify the qCT parameters that predict successful outcome of ELVR in terms of improved forced expiratory volume in 1 second (FEV1). RESULTS: In the Mann-Whitney U-test, the interlobar emphysema heterogeneity index (p = 0.008) and the pulmonary emphysema score (p = 0.022) showed a statistically significant difference between responders and non-responders. In multiple logistic regression analysis only the interlobar emphysema heterogeneity index (p = 0.008) showed a statistically significant impact on the outcome of ELVR, while targeted lobe volume, total lung volume, targeted lobe emphysema score and total lung emphysema score did not. CONCLUSION: Of all commonly assessed quantitative CT parameters, only the heterogeneity index definitely allows prediction of ELVR outcome in patients with advanced chronic obstructive pulmonary disease (COPD). KEY POINTS: · Quantitative CT is recommended prior to ELVR.. · The relevance of the obtained parameters from quantitative CT remains controversial.. · This study confirms that only the emphysema heterogeneity index has a definite impact.. CITATION FORMAT: · Theilig DC, Huebner R, Neumann K et al. Selecting Patients for Lobar Lung Volume Reduction Therapy: What Quantitative Computed Tomography Parameters Matter?. Fortschr Röntgenstr 2019; 191: 40 - 47. © Georg Thieme Verlag KG Stuttgart · New York.
Entities: Chemical
Mesh： See more »
Year: 2018
PMID： 30308688 DOI： 10.1055/a-0638-0058
Source DB: PubMed Journal: Rofo ISSN： 1438-9010