Lung Computational Models and the Role of the Small Airways in Asthma

Abstract

Rationale: Asthma is characterized by disease within the small airways. Several studies have suggested that forced oscillation technique-derived resistance at 5 Hz (R5) - resistance at 20 Hz (R20) is a measure of small airway disease; however, there has been limited validation of this measurement to date.Objectives: To validate the use of forced oscillation R5 - R20 as a measure of small airway narrowing in asthma, and to investigate the role that small airway narrowing plays in asthma.Methods: Patient-based complete conducting airway models were generated from computed tomography scans to simulate the impact of different degrees of airway narrowing at different levels of the airway tree on forced oscillation R5 - R20 (n = 31). The computational models were coupled with regression models in an asthmatic cohort (n = 177) to simulate the impact of small airway narrowing on asthma control and quality of life. The computational models were used to predict the impact on small airway narrowing of type-2 targeting biologics using pooled data from two similarly design randomized, placebo-controlled biologic trials (n = 137).Measurements and Main Results: Simulations demonstrated that narrowing of the small airways had a greater impact on R5 - R20 than narrowing of the larger airways and was associated (above a threshold of approximately 40% narrowing) with marked deterioration in both asthma control and asthma quality of life, above the minimal clinical important difference. The observed treatment effect on R5 - R20 in the pooled trials equated to a predicted small airway narrowing reversal of approximately 40%.Conclusions: We have demonstrated, using computational modeling, that forced oscillation R5 - R20 is a direct measure of anatomical narrowing in the small airways and that small airway narrowing has a marked impact on both asthma control and quality of life and may be modified by biologics.

Keywords: asthma; forced oscillation technique; imaging; integrative modelling; small airways.

Figure 1.

Diagram of the integrated modeling approach. The diagram shows many of the different clinical, statistical, and computational components that are used together in this integrated study. This includes the patient subset that underwent computed tomography (CT) scans, leading to the creation of patient-based lung structures, and personalized forced oscillation technique (FOT) modeling, as well as the larger asthmatic cohort used to create regressive links between FOT outcomes and more standardized asthmatic assessments. This integrative approach leads to a deeper understanding of the links between underlying physiology and patient outcomes. ACQ = asthma control questionnaire; AQLQ = asthma quality-of-life questionnaire; IOS = impulse oscillometry; R5 = resistance at 5 Hz; R20 = resistance at 20 Hz; RDBP = randomized, double-blind, placebo-controlled. Some components of Figure 1 were created (with permission) using stock photos from freepik.com.

Figure 2.

Analysis of the response of simulated resistance at 5 Hz (R5) − resistance at 20 Hz (R20) to airway constriction. (A and B) The ability of the model to simulate healthy subjects (black circles) and subjects with asthma (red squares) patient values is first shown, with R2 values for (A) R5: 0.35 and (B) R20: 0.27, and strong statistical significance (P < 0.05) in both cases. (C and D) The response of R5 − R20 to homogeneous (C) and heterogeneous (D) constrictions at different depths (denoted by Strahler order) is given. In both cases, R5 − R20 is seen to peak when constricting smaller airways (orders 1–6), and then decrease under upper airway constriction. (E and F) The response of R5 − R20 to small airway constriction is further illustrated by comparing homogeneous (E) and heterogeneous (F) constriction of all small airways (orders 1–6) and central airways (orders 7–12). A consistently stronger response is seen from the small airways. (E and F) R5 (right axis) and R5 − R20 (left axis) are both given, with R5 showing a larger response but a smaller distinction (particularly comparative to baseline values) between small and central airway constriction.

Figure 3.

Relative contributions of small airways, central airways, and upper airway/cheek shunting to resistance at 5 Hz (R5) and resistance at 20 Hz (R20). The simulated relative contributions are shown for a healthy subject under mild constriction (20%) and severe constriction (50%) of all small airways, alongside the resistance and reactance curves from 2 to 35 Hz. In all three cases, small airways contribute more significantly to R5 than R20, with the magnitude of this effect increasing with disease severity. This suggests that R5 − R20 responds most strongly to small airway constriction.

Figure 4.

Stratification of the clinical study population according to FVC z-score and FEV₁/FVC lower limit of normal (LLN). Stratification according to spirometry culminated in three different groups: gas trapping, asthma/chronic obstructive pulmonary disease overlap, and early small airway disease. Pie charts show the percentage of patients in each group with resistance at 5 Hz (R5) − resistance at 20 Hz (R20) greater than 100% predicted, using the 95th percentile KORA (Cooperative Health Research in the Augsburg Region) cohort quantile–quantile regression equations (pie charts: black part corresponds to R5 − R20 > 100% predicted and white part corresponds to R5 − R20 ≤ 100% predicted). Further clinical details for each group can be found in Table E1. ACQ = asthma control questionnaire.

Figure 5.

Simulated response of asthma control questionnaire (ACQ) and asthma quality-of-life questionnaire (AQLQ) to airway constriction. The translation of the response of resistance at 5 Hz − resistance at 20 Hz to small and central airway constriction into ACQ and AQLQ uses regressive models from Table 1. Results were calculated using the mean regression parameter value for resistance at 5 Hz − resistance at 20 Hz (black line), as well as the 95% confidence interval (colored bands). For both ACQ and AQLQ, a much more severe response is seen under small airway constriction than central airway constriction, even after accounting for the uncertainty of the regression.