Feasibility and clinical applications of multiple breath wash-out (MBW) testing using sulphur hexafluoride in adults with bronchial asthma.
Frederik TrinkmannSteffi A LenzJulia SchäferJoshua GawlitzaMichele SchroeterTobias GradingerIbrahim AkinMartin BorggrefeThomas GanslandtJoachim SaurPublished in: Scientific reports (2020)
Ventilation heterogeneity is frequent in bronchial asthma and can be assessed using multiple breath wash-out testing (MBW). Most data is available in paediatric patients and using nitrogen as a tracer gas. We aimed to evaluate sulphur hexafluoride (SF6) MBW in adult asthmatics. Spirometry, whole-body plethysmography, impulse oscillometry and SF6-MBW were prospectively performed. MBW parameters reflecting global (lung clearance index, LCI), acinar (Sacin) and conductive (Scond) ventilation heterogeneity were derived from three consecutive wash-outs. LCI was calculated for the traditional 2.5% and an earlier 5% stopping point that has the potential to reduce wash-out times. 91 asthmatics (66%) and 47 non-asthmatic controls (34%) were included in final analysis. LCI2.5 and LCI5 were higher in asthmatics (p < 0.001). Likewise, Sacin and Scond were elevated (p < 0.001 and p < 0.01). Coefficient of variation was 3.4% for LCI2.5 and 3.5% for LCI5 in asthmatics. Forty-one asthmatic patients had normal spirometry. ROC analysis revealed an AUC of 0.906 for the differentiation from non-asthmatic controls exceeding diagnostic performance of individual and conventional parameters (AUC = 0.819, p < 0.05). SF6-MBW is feasible and reproducible in adult asthmatics. Ventilation heterogeneity is increased as compared to non-asthmatic controls persisting in asthmatic patients with normal spirometry. Diagnostic performance is not affected using an earlier LCI stopping point while reducing wash-out duration considerably.
Keyphrases
- lung function
- chronic obstructive pulmonary disease
- end stage renal disease
- cystic fibrosis
- newly diagnosed
- single cell
- air pollution
- ejection fraction
- chronic kidney disease
- prognostic factors
- intensive care unit
- magnetic resonance
- patient reported outcomes
- machine learning
- pet imaging
- big data
- artificial intelligence
- gold nanoparticles
- contrast enhanced