posted on 2015-07-02, 15:14authored bySherif Gonem, S. Hardy, N. Buhl, Ruth Hartley, Marcia Soares, R. Kay, R. Costanza, P. Gustafsson, Christopher E. Brightling, J. Owers-Bradley, Salman Siddiqui
Background
The multiple breath washout (MBW) parameter Sacin is thought to be a marker of acinar
airway involvement, but has not been validated using quantitative imaging techniques in
asthma.
Objective
We aimed to utilise 3He diffusion magnetic resonance (
3 He-MR) at multiple diffusion
timescales and quantitative computed tomography (CT) densitometry to determine the nature
of acinar airway involvement in asthma.
Methods
Thirty-seven patients with asthma and seventeen age-matched healthy controls underwent
spirometry, body plethysmography, MBW (using the tracer gas sulphur hexafluoride) and
He-MR. A subset of patients with asthma (n = 27) underwent quantitative CT densitometry.
Results
Ninety-four percent (16/17) of patients with an elevated Sacin had GINA treatment steps 4/5
asthma and 13/17 had refractory disease. The apparent diffusion coefficient (ADC) of 3
He at 1s was significantly higher in
patients with Sacin-high asthma compared to healthy controls (0.024 vs 0.017, p < 0.05). Sacin
correlated strongly with ADC at 1s (R = 0.65, p < 0.001), but weakly with ADC at 13ms (R =
0.38, p < 0.05). ADC at both 13ms and 1s correlated strongly with the mean lung density
expiratory / inspiratory ratio, a CT marker of expiratory air trapping (R = 0.77, p < 0.0001 for
ADC at 13ms; R = 0.72, p < 0.001 for ADC at 1s).
Conclusion
Sacin is associated with alterations in long-range diffusion
within the acinar airways and gas trapping. The precise anatomical nature and mechanistic
role in severe asthma requires further evaluation.
Funding
This paper presents independent research funded by the National Institute for Health Research (NIHR). This work was partly funded through research collaborations with Chiesi Farmaceutici S. P. A. and Novartis Pharmaceuticals. Additional funding was received from the Airway Disease PRedicting Outcomes through Patient Specific Computational Modelling (AirPROM) project (funded through an FP7 European Union grant).
History
Citation
Journal of Allergy and Clinical Immunology, 2016, 137(2) pp.417–425
Author affiliation
/Organisation/COLLEGE OF MEDICINE, BIOLOGICAL SCIENCES AND PSYCHOLOGY/School of Medicine/Department of Infection, Immunity and Inflammation
Version
AM (Accepted Manuscript)
Published in
Journal of Allergy and Clinical Immunology
Publisher
Elsevier for American Academy of Allergy, Asthma and Immunology, Mosby