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. 2017 Jan 9;18(1):9.
doi: 10.1186/s12931-016-0484-7.

Non-linear parameters of specific resistance loops to characterise obstructive airways diseases

Marko Topalovic  1 , Vasileios Exadaktylos  2 , Thierry Troosters  1   3 , Geert Celis  1 , Jean-Marie Aerts  2 , Wim Janssens  4
Affiliations

Non-linear parameters of specific resistance loops to characterise obstructive airways diseases

Marko Topalovic et al. Respir Res. .

Abstract

Background: Specific resistance loops appear in different shapes influenced by different resistive properties of the airways, yet their descriptive ability is compressed to a single parameter - its slope. We aimed to develop new parameters reflecting the various shapes of the loop and to explore their potential in the characterisation of obstructive airways diseases.

Methods: Our study included 134 subjects: Healthy controls (N = 22), Asthma with non-obstructive lung function (N = 22) and COPD of all disease stages (N = 90). Different shapes were described by geometrical and second-order transfer function parameters.

Results: Our parameters demonstrated no difference between asthma and healthy controls groups, but were significantly different (p < 0.0001) from the patients with COPD. Grouping mild COPD subjects by an open or not-open shape of the resistance loop revealed significant differences of loop parameters and classical lung function parameters. Multiple logistic regression indicated RV/TLC as the only predictor of loop opening with OR = 1.157, 95% CI (1.064-1.267), p-value = 0.0006 and R2 = 0.35. Inducing airway narrowing in asthma gave equal shape measures as in COPD non-openers, but with a decreased slope (p < 0.0001).

Conclusion: This study introduces new parameters calculated from the resistance loops which may correlate with different phenotypes of obstructive airways diseases.

Keywords: Airway resistance; Asthma; Body-plethysmography; Chronic obstructive pulmonary disease; Pulmonary function tests.

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Figures

Fig. 1
Fig. 1
Comparison of typical specific resistance loops: a Healthy subject, b Asthma subject, c COPD subject; Examples of asthma and COPD are having almost identical sGAW (=0.60 [1/ kPa*sec]), yet they are visually completely different due to different resistive mechanisms
Fig. 2
Fig. 2
Panel I Geometrical parameters in COPD subject: a Area of the loop, b Roundness, c Median point, d Asynchrony, e sG0.5. Panel II Examples of input–output relationship presented over time: a Healthy subject, b Asthma subject, c COPD subject; Solid line represents flow (model output), dashed line is volume shift (model input). Transfer function model explains how input transforms to output. Panel III Visualisation of model performance with modelled expiration (red line) over the original loop (blue line): a Healthy subject (NMRSE = 95%), b Post methacholine asthma subject (NMRSE = 92%), c COPD subject (NMRSE = 94%)
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