Computed tomography predictors of response to endobronchial valve lung reduction treatment

• Verfasst von: Schuhmann, Maren [VerfasserIn]
• Verfasst von: Gompelmann, Daniela [VerfasserIn]
• Verfasst von: Eberhardt, Ralf [VerfasserIn]
• Verfasst von: Heußel, Claus Peter [VerfasserIn]
• Verfasst von: Herth, Felix [VerfasserIn]
• Titel: Computed tomography predictors of response to endobronchial valve lung reduction treatment
• Titelzusatz: comparison with Chartis
• Verf.angabe: Maren Schuhmann, Philippe Raffy, Youbing Yin, Daniela Gompelmann, Ipek Oguz, Ralf Eberhardt, Derek Hornberg, Claus Peter Heussel, Susan Wood, and Felix J.F. Herth
• E-Jahr: 2015
• Jahr: 30 January 2015
• Umfang: 8 S.
• Fussnoten: Gesehen am 24.07.2017
• Titel Quelle: Enthalten in: American journal of respiratory and critical care medicine
• Ort Quelle: New York, NY : American Thoracic Society, 1959
• Jahr Quelle: 2015
• Band/Heft Quelle: 191(2015), 7, Seite 767-774
• ISSN Quelle: 1535-4970
• DOI: doi:10.1164/rccm.201407-1205OC
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1561146439

Abstract

Rationale: Chartis Pulmonary Assessment System (Pulmonx Inc., Redwood, CA) is an invasive procedure used to assess collateral ventilation and select candidates for valve-based lung volume reduction (LVR) therapy. Quantitative computed tomography (QCT) is a potential alternative to Chartis and today consists primarily of assessing fissure integrity (FI).Objectives: In this retrospective analysis, we aimed to determine QCT predictors of LVR outcome and compare the QCT model with Chartis in selecting likely responders to valve-based LVR treatment.Methods: Baseline CT scans of 146 subjects with severe emphysema who underwent endobronchial valve LVR were analyzed retrospectively using dedicated lung quantitative imaging software (Apollo; VIDA Diagnostics, Coralville, IA). A lobar volume reduction greater than 350 ml at 3 months was considered to be indicative of positive response to treatment. Thirty-four CT baseline variables, including quantitative measurements of FI, density, and vessel volumetry, were used to feed a multiple logistic regression analysis to find significant predictors of LVR outcome. The primary predictors were then used in 33 datasets with Chartis results to evaluate the relative performance of QCT versus Chartis.Measurements and Main Results: FI (P < 0.0001) and low attenuation clusters (P = 0.01) measured in the treated lobe and vascular volumetric percentage of patient’s detected smallest vessels (P = 0.02) were identified as the primary QCT predictors of LVR outcome. Accuracy for QCT patient selection based on these primary predictors was comparable to Chartis (78.8 vs. 75.8%).Conclusions: Quantitative CT led to comparable results to Chartis for classifying LVR and is a promising tool to effectively select patients for valve-based LVR procedures.