Consensus statement for inert gas washout measurement using multiple- and single- breath tests

Paul D. Robinson, Philipp Latzin, Sylvia Verbanck, Graham L. Hall, Alexander Horsley, Monika Gappa, Cindy Thamrin, Hubertus G.M. Arets, Paul Aurora, Susanne I. Fuchs, Gregory G. King, Sooky Lum, Kenneth Macleod, Manuel Paiva, Jane J. Pillow, Sarath Ranganathan, Felix Ratjen, Florian Singer, Samatha Sonnappa, Janet Stocks, Padmaja Subbarao, Bruce R. Thompson, Per M. Gustafsson
European Respiratory Journal 2013 41: 507-522; DOI: 10.1183/09031936.00069712

This article has a correction. Please see:

Abstract

Inert gas washout tests, performed using the single- or multiple-breath washout technique, were first described over 60 years ago. As measures of ventilation distribution inhomogeneity, they offer complementary information to standard lung function tests, such as spirometry, as well as improved feasibility across wider age ranges and improved sensitivity in the detection of early lung damage. These benefits have led to a resurgence of interest in these techniques from manufacturers, clinicians and researchers, yet detailed guidelines for washout equipment specifications, test performance and analysis are lacking. This manuscript provides recommendations about these aspects, applicable to both the paediatric and adult testing environment, whilst outlining the important principles that are essential for the reader to understand. These recommendations are evidence based, where possible, but in many places represent expert opinion from a working group with a large collective experience in the techniques discussed.

Finally, the important issues that remain unanswered are highlighted. By addressing these important issues and directing future research, the hope is to facilitate the incorporation of these promising tests into routine clinical practice.

Figure

INTRODUCTION

The architecture of the airway tree promotes even distribution and optimal mixing of inhaled gas with resident gas. Multiple-breath and single-breath inert gas washout tests (MBW and SBW, respectively) assess the efficiency of ventilation distribution [1, 2]: in principle, efficiency of inert marker gas clearance from the lungs, or gas mixing within the time frame of a single breath, respectively. Suitable inert gases must be safe to inhale at the concentrations used, not participate in gas exchange, and not dissolve significantly in blood or other tissues. Options include both endogenous (nitrogen: N2, and argon) and exogenous gases (sulfur hexafluoride: SF6, helium: He, and methane). Marked ventilation distribution abnormalities occur in obstructive lung disease [3, 4] despite normal ventilatory capacity as measured by spirometry [5–10]. Washout tests may provide insight into mechanisms behind abnormal ventilation distribution and localisation of pathology. MBW is particularly attractive as it uses either relaxed tidal breathing (mostly in paediatric settings) or a fixed tidal volume (usually 1 L in adults) without need for maximal effort, thereby offering feasibility in all age groups [5, 7, 9, 11–14], driving recent strong paediatric interest. Despite this and unique insights into disease onset, widespread clinical use has yet to be achieved and further work that is required is limited by a lack of carefully validated robust commercial washout systems.

Washout recording systems determine inspired and expired inert gas volumes, by continuously measuring inert gas concentrations synchronised with respiratory flow. The overall aims of this standardisation document are to promote and facilitate use of open-circuit washout systems (i.e. minimal rebreathing of expired air), and achieve quality assured results, comparable between laboratories, using validated systems suitable across age groups and disease conditions. This paper is directed to manufacturers, researchers, clinicians and respiratory technicians. Recommendations are made for testing infants, children and adults, reflecting broad clinical and research interest. Application in different age groups may require age-specific modifications, assumptions and limitations. Specific aims of this document are to: 1) describe the principles and physiological concepts behind MBW and SBW tests; 2) outline equipment requirements, appropriate system quality control and validation; 3) describe available washout outcomes, factors influencing their calculation, and insights provided into underlying mechanisms of ventilation distribution inhomogeneity; 4) provide recommendations and test acceptability criteria in different age groups; and 5) highlight important future research.

Recommendations will continue to evolve as further insight is gained. Clinical utility has been summarised elsewhere [15–19]. Key recommendations are summarised in table 1.

View this table:
Table 1– Key recommendations from this standardisation document
Figure 1–
Figure 1–

Example of a typical single-breath washout (SBW) trace. Nitrogen gas (N2) expirogram showing calculation of phase III slope (SIII) in a vital capacity SBW test in a 60-yr-old smoker. SIII is calculated between 25% and 75% of the expired volume (SIII 4.4%·L−1), to avoid the contribution of phase IV. The four phases of the expirogram are also demonstrated: phase I (absolute dead space), phase II (bronchial phase), phase III (alveolar phase) and phase IV (fast rising phase at end of expiration). Closing volume (CV) is the expired volume (L) from the start of the upward deflection where phase IV starts, to the end of the breath. If residual volume (RV) is known, closing capacity (CC) can be calculated: CC = CV+RV. VT,exp: expired tidal volume.

Figure 2–
Figure 2–

Example of a typical multiple-breath washout (MBW) trace. Time series display of a) volume and b) nitrogen gas (N2) from an N2 MBW test in a female aged 15 yrs with cystic fibrosis. Stable breathing and end-tidal inert gas concentration are seen prior to commencing the washout phase.

Figure 3–
Figure 3–

Schematic illustration of a generic inert gas washout system. The figure illustrates a generic washout system. Hardware required for washout is relatively simple: a flow meter, a fast responding inert gas analyser, a gas delivery system and a patient interface. The equipment-related deadspace volume (VD) can be divided into pre- and post-gas sampling points. Post-gas sampling point VD effectively introduces a small rebreathing chamber. Pre-gas sampling point VD is an extension of anatomical VD.

MECHANISMS OF VENTILATION DISTRIBUTION INHOMOGENEITY

Ventilation distribution occurs by convection and diffusion [20]. Three principal mechanisms generate inhomogeneity [21]. 1) Convection-dependent inhomogeneity (CDI) in the conducting airway zone (i.e. airways proximal to terminal bronchioles) [22]. 2) Diffusion-limitation related inhomogeneity in pathologically enlarged acinar structures (rare). 3) Interaction between convection and diffusion in an intermediate zone at the level of the diffusion-convection front.

In adult healthy lungs, this quasi-stationary diffusion-convection front, which determines where these mechanisms can operate, is thought to arise around the acinar entrance [23]. Inhomogeneity of ventilation distribution is reflected in delayed MBW marker-gas clearance, raised SBW phase III slope (SIII), explained in figure 1, and magnitude and progression of MBW concentration normalised phase III slopes (SnIII) through subsequent breaths (fig. 2); in the latter, SIII normalisation by expired alveolar inert gas concentration is required to compare progression.

CDI results from differences in specific ventilation between lung units sharing branch points in the conducting airway zone in combination with sequential filling and emptying among these units [24]. CDI contributes to increased SIII in SBW and generates a continuous rise in SnIII through subsequent MBW breaths [25]. Diffusion convection-interaction-dependent inhomogeneity (DCDI), which occurs in the region of the acinar entrance, increases SnIII if structural asymmetry is present at branch points (e.g. differences in cross-sectional area and/or subtended lung volumes). In normal adult lungs, DCDI is the major contributor to SBW SIII [24] and DCDI contribution to MBW SnIII reaches its maximum at approximately five breaths [25].

SBW AND MBW TESTS

SBW and MBW assess ventilation distribution inhomogeneity at differing lung volumes. The most widely used is the N2 SBW test [1], which involves a vital capacity (VC) manoeuvre performed at low constant flow (400–500 mL·s−1): exhalation to residual volume (RV), inhalation of 100% oxygen gas (O2) to total lung capacity (TLC), then washout during exhalation from TLC to RV [1, 26], where SIII is measured over the mid portion of the expirogram (fig. 1). For exogenous inert gas SBW, the inert gas is washed in during inhalation from RV to TLC, before washout during exhalation to RV. VC SBW SIII is influenced to a greater degree by gravitational and nongravitational inter-regional differences in gas distribution and airway closure during the inspiratory phase [27–29], compared to tidal breathing protocols. Actual peripheral airway contribution to VC SBW SIII is uncertain. Modification by initial wash-in from functional residual capacity (FRC) to either TLC or a volume above FRC (e.g. 1 L) [30], better reflects inhomogeneity present during near-tidal breathing and may be a more sensitive index of peripheral airway involvement [31].

MBW assesses ventilation distribution inhomogeneity during tidal breathing from FRC, by examining inert gas clearance over a series of breaths. Exogenous gas washout requires an initial wash-in phase. MBW requires only passive cooperation and minimal coordination, but is more time consuming. It appears to be the most informative of these tests. In contrast to MBW, SBW SIII using a single inert gas does not separate CDI and DCDI contributions, though some information about location of pathological processes may be gained by comparing simultaneous SBW SIII of inert gases with widely different molecular mass (as described in the section entitled Impact of inert gas choice). SBW may be sufficient for some patient groups: in patients for whom DCDI is thought to be the main mechanism, SBW initiated from FRC approximates the first tidal expiration of a MBW, which contains most of the DCDI information. Studies directly comparing SBW and MBW are rare or non-existent.

EQUIPMENT SPECIFICATIONS

Key components and principles exist when designing washout devices (fig. 3). Individual component recommendations are summarised in table 2 and section E2 in the online supplementary material. It is unlikely that all individual criteria outlined will be fulfilled by any one system, which is why overall system performance during validation and subsequent testing is the central aspect (table 3). Recommendations for online and offline washout software are summarised in tables 4 and 5.

View this table:
Table 2– Summary of component recommendations for inert gas washout system characteristics
View this table:
Table 3– Overall recommendations for washout systems
View this table:
Table 4– Recommendations for online washout software
View this table:
Table 5– Recommendations for offline washout software

Accurately measured flow and inert gas concentration must be meticulously synchronised. Asynchrony between flow and gas signals in real-time measurement is due to gas sample transit time from airstream to inert gas analyser and/or gas analyser response time. Inert gas concentration measurements should ideally occur across the mainstream to minimise the error introduced by streaming, and be synchronous with flow signal. Mainstream gas analysers generally have shorter rise times than sidestream analysers but may introduce additional equipment deadspace, which in turn may have detrimental effects on ventilation during testing. Short analyser rise times become increasingly important as breathing rate increases, such as in young infants. Overall contribution of characteristics such as these determines suitability for different age ranges, as illustrated by the detailed discussion of current published systems as shown in section E2.7 in the online supplementary material.

VALIDATION OF WASHOUT EQUIPMENT

Recommended washout equipment validation is FRC measurement accuracy: FRC values within 5% of known volume for at least 95% of values [32] across the range of lung volumes, VT and respiratory rates encountered during subsequent clinical testing [34, 35]. Validation should assess all stages of measurement including post-data acquisition processing procedures, such as body temperature, ambient pressure, saturated with water (BTPS) correction. Recently, optimised lung model design [36] has incorporated simulated BTPS conditions for validation of both established and emerging MBW systems (fig. 4) [35] and is the recommended approach. Validation should be repeated if significant changes in hardware or software algorithms occur [39]. All MBW ventilation inhomogeneity indices depend on accurate FRC determination, but FRC validation alone may not be sufficient to ensure accuracy of derived ventilation distribution indices. During subsequent clinical or research testing, biological controls should monitor measurement stability (e.g. three to four healthy staff members performing MBW in triplicate, monthly). Marked variation beyond normal observed pattern should prompt further careful evaluation of device performance and procedures.

Figure 4–
Figure 4–

Recommended lung model for functional residual capacity (FRC) validation incorporating body temperature, ambient pressure, saturated with water vapour (BTPS) conditions and mimicking in vivo clinical testing conditions. The lung model consists of two separate chambers, an inner and an outer chamber. The inner chamber is partially divided (communicating at its inferior aspect) into two compartments: the lung compartment (A) and the ventilated compartment (B). FRC volume is generated by filling the inner chamber with distilled water to a measured height and calculated from known geometric dimensions. Water in the outer chamber is heated (C) such that inner chamber water temperature reaches 37°C, and a portable ventilator (D) is connected to the ventilated compartment of the inner chamber and transmitted hydraulic pressure generates the lung chamber breathing pattern: chosen to simulate physiological tidal volume (VT)/FRC, VT and respiratory rates likely to be encountered during intended clinical testing [35]. For example, whilst VT remains similar (8 mL·kg−1) across age ranges, FRC changes from ∼20 mL·kg−1 in infants [37] to 40 mL·kg−1 in adults [38]. Multiple-breath washout equipment can be attached to the outlet of the lung compartment (E) during validation tests.

A variety of factors may generate differences in reported indices between centres (table 6), and until standardisation is achieved, normative data is at best tentative and likely to be inert gas, equipment and software specific. Experimental conditions under which normative data are obtained should be clearly described in manuscripts.

View this table:
Table 6– Factors that lead to variation in measured indices between centres and recording systems

SUITABILITY OF CURRENT WASHOUT SYSTEMS ACROSS AGE GROUPS

The only current system applicable across all age groups is custom built and based on the respiratory mass spectrometer (RMS). RMS is the current gold standard gas analyser offering simultaneous measurement of multiple gases in constant conditions, full linearity, low sample flow and short response time [39]. This custom washout system exists in several centres [5, 7, 40–42], but may be too expensive and impractical for widespread use.

In MBW using N2, inhalation of 100% O2 may alter breathing patterns in infants [43] and subsequent MBW outcomes, but impact on breathing pattern beyond infancy is considered minimal. As an alternative to emission spectrophotometer N2 analyser systems (requiring vacuum pumps), indirect N2 measurement systems have been proposed based on simultaneous O2 and CO2 measurement [35] or changes in molar mass (MM) [34] (see section E3 in the online supplementary material). Potential for additive errors with indirect measurement places even greater emphasis on adequate quality control.

MM based measurement of SF6 or He are also feasible [44–46]. Mainstream MM SF6 washout has been validated in infants [46, 47]; however, lack of validated correction algorithms for detrimental temperature and humidity fluctuations limit utility beyond infancy [48]. Sidestream MM washout incorporating Nafion® tubing to stabilise temperature and humidity [49] has been validated for older age groups [38, 50], but current equipment deadspace volume (VD) precludes use in infancy.

Modified photoacoustic analyser based systems have been validated for use in adults and school age children [9, 51], but are not currently commercially available. Feasibility into younger ages will depend on minimisation of longer analyser response times. Detrimental impact of high sample flow used in these systems on measured flows may be reduced by gas sensor placement distal to flow measurement, but requires careful evaluation. Sampling bias flow gas during low expiratory flows must also be avoided. The commercially available photoacoustic analyser based closed circuit system is not discussed in this manuscript [52].

OUTCOMES

Functional residual capacity

FRC measured by MBW (FRCgas) represents the volume of lung gas, at end expiration (assessed at the breath immediately preceding washout), in direct communication with the airway opening, excluding gas trapped in lung regions not ventilated by tidal breaths. FRCgas is, therefore, often lower than plethysmographic FRC, especially in obstructive lung disease [53]. FRCgas = VIG/Cet,IG (initial–final), where: VIG is net volume of inert gas expired, and Cet is end-tidal concentration of inert gas. VIG is the sum of the integral products of exhaled flow and gas concentration for each washout breath, corrected for re-inspired gas, contained within the VD after the post-gas sampling point (fig. 3, see section E5.2 in online supplementary material).

Measured FRC can be corrected to represent different points in the airstream: FRC at the airway opening is calculated as FRC measured at the gas sampling point, FRCgs, minus pre-gas sampling point VD. FRC used in ventilation inhomogeneity index calculations must correspond to a common airstream measurement point (see section E6.2 in the online supplementary material).

Calculated FRC may continue to increase through the washout, particularly in subjects with airway disease and in N2-based MBW (see section entitled Impact of inert gas choice), yet studies rarely disclose when FRC measurement is determined. FRC end analysis threshold should correspond to the end-test threshold used for ventilation inhomogeneity indices (e.g. 1/40 of starting end-tidal concentration for lung clearance Index (LCI). The effect of variation in FRC end-point on other FRC-derived indices may be significant. Methodology for reported FRC values should be clearly described.

Measures of ventilation distribution inhomogeneity

A large number of ventilation distribution indices can be derived from information contained within SBW or MBW [21, 54, 55] (see section E6.1 in the online supplementary material): 1) SBW SIII, reflecting combined CDI and DCDI contributions, unless simultaneously performed with marker gases of widely different MM. 2) MBW global ventilation inhomogeneity indices, reflecting efficiency of marker gas clearance. 3) MBW SnIII analysis, distinguishing CDI and DCDI mechanisms. 4) Airway closure and trapped gas volume (VTG) assessment from SBW and MBW, respectively.

Depending on the pathology under study, relationships between MBW-derived indices (e.g. Sacin, Scond and LCI) may help identify the type of structural changes generating increased ventilation distribution inhomogeneity [56].

Global measures

LCI is the most commonly reported MBW index in current paediatric literature, and defined as the number of FRC lung turnovers (TO; calculated as CEV/FRC) required to reduce alveolar tracer-gas concentration to a given fraction of its starting concentration, historically 1/40 (2.5%) [57]. Alveolar tracer-gas concentration has been estimated in various ways. In paediatric studies Cet is widely used, despite potential variability in end-tidal point. Identification of end-test threshold for LCI has not been systematically validated, but we recommend using the first of three consecutive breaths with a Cet <1/40 to avoid premature test termination with small breaths. LCI is calculated as the ratio of cumulative expired volume (CEV) to FRC, with CEV defined as the sum of all expiratory VT over the washout including this first post-threshold. This introduces a small bias (overestimation); however, the value of interpolated or more complicated curve fit methods to determine exact threshold crossing values is unclear. Alternate methods used should be explicitly stated.

Ideally indices should be assessed at airway opening without external VD. However, this is, not feasible and VT should be corrected for equipment VD as appropriate (see section E6.2 in the online supplementary material). Post-gas sampling point VD can be reliably estimated from water displacement; however, pre-gas sampling point VD determination may be challenging, due to streaming within the facemask or filter [58]. Applied pre- and post-gas sampling point corrections should be clearly described. Where VD correction is implemented, it is advised that both corrected and uncorrected LCI values are reported.

In clinical and modelling studies indices, such as LCI, have small but significant relationships to underlying respiratory patterns (VT, VD and FRC) particularly under disease conditions [54, 59, 60]. Effects of variation in respiratory rate and VT can be minimised using moment analysis (see section E6.4 in the online supplementary material). This describes the degree of skewness of the washout curve to the right, as mean dilution numbers (MDN) or moment ratios [61]. VD-independent assessment is feasible by correcting CEV for airways VD (VD,aw) and using cumulative expired alveolar volume in calculations (CEValv; e.g. alveolar MDN [59] and alveolar LCI [62]). VD,aw, measured using Fowler or Langley methods (see section E4.2 in the online supplementary material) [63, 64], should be based on CO2 VD,aw, or the first few washout breaths of inert gas VD,aw, as the latter increases during MBW [25] due to early washout of very well ventilated lung regions with short pathways to the airway opening. However, moment ratio truncation to facilitate between–subject comparison (e.g. to 8 TO [65]), may detrimentally affect sensitivity [66], and feasibility. Healthy subjects may also require longer washout periods to reach these higher turnover values, and accurate measurement may be compromised by limited signal resolution and high relative noise at the low gas concentrations encountered.

Normalised SnIII analysis

MBW SnIII analysis has a theoretical [67], experimental [68], and lung modelling basis [69–72] from morphometric data in healthy adults [22], to distinguish ventilation inhomogeneity arising from DCDI and CDI mechanisms, expressed as the clinical indices Sacin and Scond, respectively [72] (fig. 5). For Sacin and Scond determination, SIII and gas concentrations must be accurately determined down to breaths with very low concentrations (see section E6.6 in the online supplementary material) and may not be feasible for all washout systems.

Figure 5–
Figure 5–

Normalised phase III slope (SnIII) analysis. Multiple-breath washout recording illustrating derived phase III slope parameters. Measured concentration SnIII, (SnIII,measured) for each breath is plotted against its corresponding lung turnover, calculated as cumulative expired volume/functional residual capacity (TO), value. Progressive SnIII values increase throughout the TO range considered. If this does not occur, the quality of the recording should be closely examined. The index of convection-dependent inhomogeneity (CDI; Scond), is calculated as the increase in measured SnIII per unit TO between ∼1.5–6.0 TO per unit TO. For explanation purposes the diffusion convection-interaction-dependent inhomogeneity (DCDI) contribution to the SnIII for each breath is also plotted (SnIII,DCDI) This is calculated by subtracting the CDI contribution to SnIII for each breath from the SnIII,measured for each breath. In other words, for each breath, SnIII,measured value equals SnIII,DCDI value minus CDI contribution. Sacin is defined as the DCDI contribution to the first breath SnIII,DCDI. The complete contribution of the DCDI mechanism reaches a plateau beyond TO 1.5 and is equivalent to the intercept of the Scond regression line. These indices rely on the fact that DCDI generates a horizontal asymptote and CDI does not and are, therefore, only valid in cases where SnIII does not show a horizontal asymptote.

SIII is dependent on many factors, both linear and non-linear, at least in healthy adult lungs: pre-inspiratory lung volume, inspired and expired volumes, and flow [1, 20, 42, 73–78]. Consequently, these factors should ideally be kept similar between subjects to maintain diffusion-convection front location, and allow changes in indices to be linked to changes in corresponding lung structures. Breath holds at end-inspiration flatten SIII and should be minimised [30, 63]. The beating heart generates flow pulses within airways [79] causing cardiogenic gas mixing. Cardiogenic oscillations superimposed onto SIII add to signal noise. Automated SnIII calculation algorithms exist [80], but subjective observation is still necessary to review estimated slope accuracy.

Trapped gas volume

Airway closure occurs in lung units approaching regional RV [81], but may also occur at higher regional lung volumes in infants, older adults [82], obese subjects [83], and in the presence of peripheral airway obstruction. It may be a prominent phenomenon in airway disease. If present, the VTG can be measured during MBW by including five inspiratory capacity breaths after conventional end-test threshold is reached and measuring the volume of lung recruited (see section E6.3 in the online supplementary material). VTG measurement with both resident and exogenous MBW has been established for infants and children [84, 85]. Importantly, this method estimates only the gas volumes recruitable during these large breaths.

Closing volume and closing capacity

Closing volume (CV) and closing capacity require accurate determination of SBW phase III to phase IV transition (fig. 1). CV reflects airway closure occurring preferentially in dependent lung regions and peripheral airway obstruction [81, 86, 87]. Relative merits of these indices have been reviewed elsewhere [88]. Although feasible in adults [89], paediatric utility of CV is limited [90]. Automated identification of phase IV is feasible [91].

IMPACT OF INERT GAS CHOICE

Derived indices may differ depending on the gas used for a number of reasons. Gas diffusion rate is inversely proportional to the square root of the MM, but convective distribution is unaffected. Consequently, diffusion-convection front location is more proximal for lighter gases versus heavier gases (e.g. He versus SF6 MM is 4 versus 146 g·mol−1, respectively). Greater series VD for SF6, compared to He, generates higher LCI values, irrespective of ventilation distribution itself. In healthy lungs SF6 SIII are greater than He SIII, but may reverse in lung pathology [92–94]. In addition, rate of diffusive equilibration in enlarged peripheral air spaces (e.g. emphysema) may differ depending on gas choice generating differential SIII increase. Homogeneity of gas distribution present at the start of washout may differ depending on whether naturally resident or exogenous gas is used. Measurable differences may be informative. In simultaneous He and SF6 measurements, disease processes distal to the acinar entrance generate greater abnormality in SF6 indices, whereas disease processes proximal to the acinar entrance but in the zone of the convection-diffusion front will affect He indices preferentially. However, if disease processes affect SF6 and He SIII to a similar extent, no relative SIII difference occurs [95].

Advantages of N2 washout include widespread availability and affordability of 100% O2, and avoidance of patient connection to equipment during wash-in periods between tests minimising patient discomfort. N2 is resident in all lung units including very slowly ventilated lung compartments and may offer improved sensitivity to detect abnormality, compared to other inert gases, which may not equilibrate fully within these regions during wash-in. However, disadvantages also exist. Thresholds at which factors such as age, sleep state and sedation interact with 100% O2 to affect breathing pattern remain unclear. N2 is not truly inert and tissue N2, present due to high atmospheric N2 partial pressure, diffuses from blood into alveoli along concentration gradients. This diffusion is greatest in well-ventilated lung regions washed out during initial portions of the test, and contribute to exhaled N2 later in the washout, potentially introducing greater error in longer tests (e.g. FRC overestimation). Estimation and correction of tissue N2 contribution is difficult due to limited available data to base correction [96], and adjustment for tissue N2 is not currently recommended [97].

Whilst different inert gas concentrations used in the literature are safe (e.g. 4% SF6 and 4% He), additional factors influence inert gas selection. SF6 may have adverse health effects at higher concentrations [98] and significant greenhouse potential [99]. Feasibility of scavenging following testing is unclear. SF6 is not universally approved for testing (e.g. USA and France). Low density of He renders it more susceptible to leaks during testing, which may aid leak detection. Cost of exogenous gas is increasing in many countries, partly due to increasing logistical requirements when used as a medical gas.

ACCEPTABILITY CRITERIA FOR TESTING

Quality control during testing is critical and extends beyond equipment performance and software feedback to also include close observation by the operator of the subject’s behaviour during testing and how this affects the data obtained. Adequate operator training and appreciation of all factors influencing test results is essential. Recommended acceptability criteria for MBW and SBW are summarised in tables 7 and 8.

View this table:
Table 7– Multiple-breath washout (MBW) measurement acceptability criteria
View this table:
Table 8– Single-breath washout (SBW) measurement quality control

Multiple-breath washout

Primary index of interest may differ between paediatric and adult testing (e.g. LCI and SnIII indices in the current literature, respectively) influencing test termination criteria and acceptability. Recommendations contained within this document attempt to provide a unified approach.

Breathing pattern

Measured FRC reflects lung volume at which washout is commenced (i.e. end-expiratory level). Stability of resting lung volumes before and throughout washout is critical [46, 48]. In infants, intrinsic FRC resetting during critical periods, visible as sighs, should prompt test exclusion. In general, large inspiratory breaths during washout may mobilise trapped gas and small inspiratory or expiratory breaths may result in steeper SIII. End-tidal volumes below FRC may result in steeper SIII and occurrence of phase IV, especially in obstructive lung disease. For SnIII analysis, first breath quality (in particular adherence to target inhalation and exhalation volume) is critical for accurate Sacin.

Relaxed tidal breathing has historically been used for global MBW derived indices. Studies introducing adult SnIII analysis used a strict 1 L VT breathing regimen [101], chosen as a compromise between 1) maintaining physiological breathing conditions, 2) obtaining sufficient phase III to compute its slope, and 3) having sufficient SnIII data points for statistically valid regression from ∼TO 1.5–6.0 [101]. This strict protocol is not feasible in all ages, or in more advanced obstructive disease. In addition, due to marked variations in lung size, 1 L may greatly exceed normal VT and not be appropriate. In an attempt to implement SnIII analysis in younger ages during regular breathing (typically aged ≤16 yrs), the following criterion for breath acceptability, based on a similar principle, is proposed: each breath must have sufficient phase III to compute SIII (at least 50% of VT). For tests fulfilling this criterion, volume compensation is then performed on SnIII: SnIII is multiplied by FRC (to correct for differences in lung size) and then by VT/FRC (to account for variations in SIII due to changes in breathing pattern). This net multiplication of SnIII by VT (in L) facilitates comparison among subjects of differing lung sizes, yet needs to be critically interpreted in any particular study setting (see section E6.5 in the online supplementary material). Where implemented, we recommend that both corrected and uncorrected Sacin and Scond values are reported, such that posteriori analyses are possible, if and when this or other correction methods are validated. Insufficient SIII for accurate estimation limits feasibility in infants [105].

Visual breathing pattern feedback may be useful to guide older adolescents and adults [9] but is problematic in younger subjects, for whom distraction with videos is recommended [6]. Measurements in infants should be performed during quiet nonrapid eye-movement sleep, with or without the use of sedation. No comparative study exists showing the potential effect of sedation on washout indices.

Test termination

MBW test termination after alveolar concentration (usually Cet) falls below 1/40 of starting concentration for three consecutive breaths allows standard LCI to be calculated. For standard SnIII analysis and moment ratios MBW should pass beyond 6 and 8 TO, respectively [65].

FRC repeatability

Previously recommended within–session FRC repeatability criteria (within 10%, [106, 107]) have poor feasibility in paediatric testing [108], and may lengthen total testing time significantly. Repeatability within 10% should be viewed as encouraging. Tests should be carefully examined for technical issues if this is not met. Automatic exclusion of tests should occur if FRC differs by >25% from median FRC over three tests.

In older children, FRC increases by >20% moving supine to sitting [109], but effects of transition from testing supine infants to seated preschoolers is unclear. Postural effects on ventilation distribution may also depend on severity and topographical location of airways disease. Consideration of these factors should also occur when comparing upright ventilation distribution tests to supine imaging studies.

Single-breath washout

The need to maintain inspiratory and expiratory flows strictly between 400–500 mL·s−1 and achieve reproducible VC manoeuvres currently limits feasibility to adults and children >12 yrs [18]. SIII volume compensation, using a similar approach to MBW, in this case by multiplying SIII by VC, is feasible but not formally validated. It is unclear how much variation in historical predicted SIII values [18] is due to physiological intrinsic or technical factors.

FUTURE WORK AND CONCLUSIONS

Important questions remaining unanswered for commercial and research washout systems, SBW and MBW test procedure and subsequent analysis are summarised in table 9. Challenges arise when interpreting washout tests in infants and children where relationships between VD/VT and VT/FRC and calculated indices must be considered. This is particularly relevant when undertaking studies of early lung disease or treatment effects to ensure that reported differences don’t reflect alterations in respiratory patterns alone. Longitudinal data for ventilation inhomogeneity indices during normal lung development with age are needed. Influence of sex and ethnic background is unclear.

View this table:
Table 9– Important areas of interest for future studies

Anatomical distinction between ventilation inhomogeneity represented by Scond and Sacin relies on diffusion–convection front location, which has been simulated in an adult lung using available lung structure and airway dimensions. Extending applicability of such indices into childhood and disease processes requires further simulation of the diffusion-convection front based on realistic anatomical data. Beyond post mortem data, anatomical and functional data obtained using modern computed tomography scanning techniques or hyperpolarised noble gas magnetic resonance imaging studies may provide this. Simulation studies in realistic lung models could also be used to validate VT correction of SnIII to compare ventilation inhomogeneity between varying age groups with varying VD, VT, and FRC. Until formal validation, studies incorporating SnIII analysis should ideally include matched healthy control data for comparison and report both uncorrected and corrected values. Formal objective quality control thresholds for test acceptance and breath exclusion are also required. Shortening test duration whilst maintaining sensitivity and specificity will enhance feasibility and incorporation into routine clinical testing. Efforts to investigate ways to achieve this are already underway [108, 112].

Inert gas washout provides unique physiological information, which at the very least forms an important complement to current methods in the adult lung function laboratory, while offering improved feasibility and sensitivity compared to spirometry in younger children. A number of important challenges lie ahead for integration into routine clinical care. Standardisation of procedures and development of robust appropriately validated affordable commercial equipment is essential. This will only be achievable if manufacturers work in collaboration with researchers, as we seek to address the important issues and questions that remain unanswered. This standardisation document provides the basis for this future work.

Acknowledgments

This consensus statement has been endorsed by the European Respiratory Society and the American Thoracic Society.

The author affiliations are as follows. P.D. Robinson: Dept of Respiratory Medicine, The Children’s Hospital at Westmead, and Airway Physiology and Imaging, Woolcock Institute of Medical Research, Sydney, Australia, and UCL Institute of Child Health, Portex Respiratory Unit, London, UK; P. Latzin: Division of Respiratory Medicine, Dept of Paediatrics, Inselspital and University of Bern, Bern, Switzerland; S. Verbanck: Respiratory Division, University Hospital, Brussels, Belgium; G.L. Hall: Telethon Institute for Child Health Research, Centre for Child Health Research, University of Western Australia, and Respiratory Medicine, Princess Margaret Hospital for Children, Perth, Australia, and Division of Respiratory Medicine, Physiology and Experimental Medicine, Hospital for Sick Children, Toronto, ON, Canada; A. Horsley: Manchester Adult Cystic Fibrosis Centre, University Hospitals South Manchester, Wythenshawe Hospital, Manchester, UK; M. Gappa: Children’s Hospital and Research Institute for the Prevention of Allergies and Respiratory Diseases in Children, Marien-Hospital, Wesel, Germany; C. Thamrin: Airway Physiology and Imaging, Woolcock Institute of Medical Research, Sydney, Australia, and Division of Respiratory Medicine, Dept of Paediatrics, Inselspital, and University of Bern, Bern, Switzerland; H.G.M. Arets: Dept of Paediatric Pulmonology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands; P. Aurora: UCL Institute of Child Health, Portex Respiratory Unit, and Respiratory Medicine, Great Ormond Street Hospital for Children NHS Trust, London, UK; S. Fuchs: Children’s Hospital and Research Institute for the Prevention of Allergies and Respiratory Diseases in Children, Marien-Hospital, Wesel, Germany; G.G. King: Airway Physiology and Imaging, Woolcock Institute of Medical Research, and Dept of Respiratory Medicine, Royal North Shore Hospital, Sydney, Australia; S. Lum: UCL Institute of Child Health, Portex Respiratory Unit, London, UK; K. Macleod: Dept of Child Life and Health, Royal Hospital for Sick Children, University of Edinburgh, Edinburgh, UK; M. Paiva: Respiratory Division, University Hospital Erasme, Université Libre de Bruxelles, Brussels, Belgium; J.J. Pillow: Centre for Neonatal Research and Education, School of Paediatrics and Child Health and School of Women’s and Infants’ Health, University of Western Australia, and King Edward and Princess Margaret Hospitals, Perth, Australia; S. Ranganathan: Dept of Respiratory Medicine, Royal Children’s Hospital, and Murdoch Children’s Research Institute, Melbourne, Australia; F. Ratjen: Division of Respiratory Medicine, Dept of Paediatrics, The Hospital for Sick Children, Toronto, ON, Canada; F. Singer: Division of Respiratory Medicine, Dept of Paediatrics, Inselspital and University of Bern, Bern, Switzerland; S. Sonnappa: UCL Institute of Child Health, Portex Respiratory Unit, and Respiratory Medicine, Great Ormond Street Hospital for Children NHS Trust, London, UK; J. Stocks: UCL Institute of Child Health, Portex Respiratory Unit, London, UK; P. Subbarao: Division of Respiratory Medicine, Dept of Paediatrics, The Hospital for Sick Children, Toronto, ON, Canada; B.R. Thompson: Physiology Service, Dept of Allergy, Immunology and Respiratory Medicine, The Alfred Hospital, Melbourne, Australia; P.M. Gustafsson: Dept of Paediatrics, Central Hospital, Skövde, and Sahlgrenska Academy, University of Gothenburg, Gothenburg Sweden.

Other members of the working group who contributed early on in the production of this work were H.A.W.M. Tiddens, (Rotterdam, the Netherlands), S.M. Schulzke (Basel, Switzerland), A. Schibler (Brisbane, Australia) and R.S. Tepper (Indianapolis, IN, USA).

Footnotes

  • After publication of the erratum in the November 2013 issue of the European Respiratory Journal, the online version of this article has been revised.

  • For editorial comments see page 500.

  • This article has supplementary material available from www.erj.ersjournals.com

  • Statement of Interest

    Statement of interest for P.D. Robinson, M. Gappa, G.G. King, J.J. Pillow, and F. Ratjen can be found at www.erj.ersjournals.com/site/misc/statements.xhtml

REFERENCES

  1. 1.↵
    1. Fowler WS
    . Lung function studies; uneven pulmonary ventilation in normal subjects and in patients with pulmonary disease. J Appl Physiol 1949; 2: 283–299.
    OpenUrlFREE Full Text
  2. 2.↵
    1. Robertson JS,
    2. Siri WE,
    3. Jones HB
    . Lung ventilation patterns determined by analysis of nitrogen elimination rates; use of mass spectrometer as a continuous gas analyzer. J Clin Invest 1950; 29: 577–590.
    OpenUrlCrossRefPubMedWeb of Science
  3. 3.↵
    1. Venegas JG,
    2. Winkler T,
    3. Musch G,
    4. et al
    . Self-organized patchiness in asthma as a prelude to catastrophic shifts. Nature 2005; 434: 777–782.
    OpenUrlCrossRefPubMedWeb of Science
  4. 4.↵
    1. van Beek EJ,
    2. Hill C,
    3. Woodhouse N,
    4. et al
    . Assessment of lung disease in children with cystic fibrosis using hyperpolarized 3-Helium MRI: comparison with Shwachman score, Chrispin-Norman score and spirometry. Eur Radiol 2007; 17: 1018–1024.
    OpenUrlCrossRefPubMedWeb of Science
  5. 5.↵
    1. Aurora P,
    2. Bush A,
    3. Gustafsson P,
    4. et al
    . Multiple-breath washout as a marker of lung disease in preschool children with cystic fibrosis. Am J Respir Crit Care Med 2005; 171: 249–256.
    OpenUrlCrossRefPubMedWeb of Science
  6. 6.↵
    1. Aurora P,
    2. Gustafsson P,
    3. Bush A,
    4. et al
    . Multiple breath inert gas washout as a measure of ventilation distribution in children with cystic fibrosis. Thorax 2004; 59: 1068–1073.
    OpenUrlAbstract/FREE Full Text
  7. 7.↵
    1. Gustafsson PM,
    2. Aurora P,
    3. Lindblad A
    . Evaluation of ventilation maldistribution as an early indicator of lung disease in children with cystic fibrosis. Eur Respir J 2003; 22: 972–979.
    OpenUrlAbstract/FREE Full Text
  8. 8.
    1. Fuchs SI,
    2. Sturz J,
    3. Junge S,
    4. et al
    . A novel sidestream ultrasonic flow sensor for multiple breath washout in children. Pediatr Pulmonol 2008; 43: 731–738.
    OpenUrlCrossRefPubMedWeb of Science
  9. 9.↵
    1. Horsley AR,
    2. Gustafsson PM,
    3. Macleod KA,
    4. et al
    . Lung clearance index is a sensitive, repeatable and practical measure of airways disease in adults with cystic fibrosis. Thorax 2008; 63: 135–140.
    OpenUrlAbstract/FREE Full Text
  10. 10.↵
    1. Aurora P,
    2. Stanojevic S,
    3. Wade A,
    4. et al
    . Lung clearance index at 4 years predicts subsequent lung function in children with cystic fibrosis. Am J Rep Crit Care Med 2011; 183: 752–758.
    OpenUrlCrossRef
  11. 11.↵
    1. Kjellman B
    . Lung function in children with pneumonia. With special reference to distribution of inspired air and regional lung function. Scand J Respir Dis 1968; 49: 185–201.
    OpenUrlPubMed
  12. 12.
    1. Shao H,
    2. Sandberg K,
    3. Sjoqvist BA,
    4. et al
    . Moment analysis of multibreath nitrogen washout in healthy preterm infants. Pediatr Pulmonol 1998; 25: 52–58.
    OpenUrlCrossRefPubMedWeb of Science
  13. 13.
    1. Hulskamp G,
    2. Lum S,
    3. Stocks J,
    4. et al
    . Association of prematurity, lung disease and body size with lung volume and ventilation inhomogeneity in unsedated neonates: a multicentre study. Thorax 2009; 64: 240–245.
    OpenUrlAbstract/FREE Full Text
  14. 14.↵
    1. Lum S,
    2. Gustafsson P,
    3. Ljungberg H,
    4. et al
    . Early detection of cystic fibrosis lung disease: multiple-breath washout versus raised volume tests. Thorax 2007; 62: 341–347.
    OpenUrlAbstract/FREE Full Text
  15. 15.↵
    1. Fuchs SI,
    2. Gappa M
    . Lung clearance index: clinical and research applications in children. Paediatr Respir Rev 2011; 12: 264–270.
    OpenUrlCrossRefPubMed
  16. 16.
    1. Gangell CL,
    2. Hall GL,
    3. Stick SM,
    4. et al
    . Lung function testing in preschool-aged children with cystic fibrosis in the clinical setting. Pediatr Pulmonol 2010; 45: 419–433.
    OpenUrlPubMed
  17. 17.
    1. Horsley A
    . Lung clearance index in the assessment of airways disease. Respir Med 2009; 103: 793–799.
    OpenUrlCrossRefPubMed
  18. 18.↵
    1. Robinson PD,
    2. Goldman MD,
    3. Gustafsson PM
    . Inert gas washout: theoretical background and clinical utility in respiratory disease. Respiration 2009; 78: 339–355.
    OpenUrlCrossRefPubMedWeb of Science
  19. 19.↵
    1. Robinson PD,
    2. Latzin P,
    3. Gustafsson P
    . Multiple-breath washout. Eur Respir Monogr 2010; 47: 87–104.
    OpenUrl
  20. 20.↵
    1. Paiva M
    . Gas transport in the human lung. J Appl Physiol 1973; 35: 401–410.
    OpenUrlFREE Full Text
  21. 21.↵
    1. Engel LA,
    2. Paiva M
    . Gas Mixing and Distribution in the Lung. Marcel Dekker, Inc., New York, 1985.
  22. 22.↵
    1. Haefeli-Bleuer B,
    2. Weibel ER
    . Morphometry of the human pulmonary acinus. Anat Rec 1988; 220: 401–414.
    OpenUrlCrossRefPubMedWeb of Science
  23. 23.↵
    1. Engel LA
    . Gas mixing within the acinus of the lung. J Appl Physiol 1983; 54: 609–618.
    OpenUrlAbstract/FREE Full Text
  24. 24.↵
    1. Prisk GK,
    2. Lauzon AM,
    3. Verbanck S,
    4. et al
    . Anomalous behavior of helium and sulfur hexafluoride during single-breath tests in sustained microgravity. J Appl Physiol 1996; 80: 1126–1132.
    OpenUrlAbstract/FREE Full Text
  25. 25.↵
    1. Crawford AB,
    2. Makowska M,
    3. Paiva M,
    4. et al
    . Convection- and diffusion-dependent ventilation maldistribution in normal subjects. J Appl Physiol 1985; 59: 838–846.
    OpenUrlAbstract/FREE Full Text
  26. 26.↵
    1. Comroe JH Jr.,
    2. Fowler WS
    . Lung function studies. VI. Detection of uneven alveolar ventilation during a single breath of oxygen. Am J Med 1951; 10: 408–413.
    OpenUrlCrossRefPubMedWeb of Science
  27. 27.↵
    1. Anthonisen NR,
    2. Robertson PC,
    3. Ross WR
    . Gravity-depende sequential emptying of lung regions. J Appl Physiol 1970; 28: 589–595.
    OpenUrlFREE Full Text
  28. 28.
    1. Olson LE,
    2. Rodarte JR
    . Regional differences in expansion in excised dog lung lobes. J Appl Physiol 1984; 57: 1710–1714.
    OpenUrlAbstract/FREE Full Text
  29. 29.↵
    1. Wilson TA,
    2. Olson LE,
    3. Rodarte JR
    . Effect of variable parenchymal expansion on gas mixing. J Appl Physiol 1987; 62: 634–639.
    OpenUrlAbstract/FREE Full Text
  30. 30.↵
    1. Kjellmer I,
    2. Sandqvist L,
    3. Berglund E
    . Alveolar plateau of the single breath nitrogen elimination curve in normal subjects. J Appl Physiol 1959; 14: 105–108.
    OpenUrlAbstract/FREE Full Text
  31. 31.↵
    1. Van Muylem A,
    2. De Vuyst P,
    3. Yernault JC,
    4. et al
    . Inert gas single-breath washout and structural alteration of respiratory bronchioles. Am Rev Respir Dis 1992; 146: 1167–1172.
    OpenUrlCrossRefPubMedWeb of Science
  32. 32.↵
    1. Frey U,
    2. Stocks J,
    3. Coates A,
    4. et al
    . Specifications for equipment used for infant pulmonary function testing. Eur Respir J 2000; 16: 731–740.
    OpenUrlAbstract
  33. 33.
    1. Bates JH,
    2. Schmalisch G,
    3. Filbrun D,
    4. et al
    . Tidal breath analysis for infant pulmonary function testing. Eur Respir J 2000; 16: 1180–1192.
    OpenUrlAbstract
  34. 34.↵
    1. Fuchs SI,
    2. Buess C,
    3. Gappa M
    . In vitro validation of nitrogen multiple breath washout using ultrasonic equipment. Eur Respir J 2011; 38: Suppl. 55, 355s
    OpenUrl
  35. 35.↵
    1. Singer F,
    2. Houltz B,
    3. Latzin P,
    4. et al
    . A realistic validation study of a new nitrogen multiple-breath washout system. PLoS One 2012; 7: e36083
    OpenUrlCrossRefPubMed
  36. 36.↵
    1. Brunner JX,
    2. Wolff G,
    3. Cumming G,
    4. et al
    . Accurate measurement of N2 volumes during N2 washout requires dynamic adjustment of delay time. J Appl Physiol 1985; 59: 1008–1012.
    OpenUrlAbstract/FREE Full Text
  37. 37.↵
    1. Hulskamp G,
    2. Pillow JJ,
    3. Dinger J,
    4. et al
    . Lung function tests in neonates and infants with chronic lung disease of infancy: functional residual capacity. Pediatr Pulmono 2006; 41: 1–22.
    OpenUrlCrossRef
  38. 38.↵
    1. Zeltner TB,
    2. Caduff JH,
    3. Gehr P,
    4. et al
    . The postnatal development and growth of the human lung. I. Morphometry. Respir Physiolo 1987; 67: 247–267.
    OpenUrlCrossRef
  39. 39.↵
    1. Arieli R
    . Mass spectrometer for respiratory research. Respir Physiol Neurobiol 2010; 170: 183–184.
    OpenUrlCrossRefPubMed
  40. 40.↵
    1. Amin R,
    2. Subbarao P,
    3. Jabar A,
    4. et al
    . Hypertonic saline improves the LCI in paediatric CF patients with normal lung function. Thorax 2010; 65: 379–383.
    OpenUrlAbstract/FREE Full Text
  41. 41.
    1. Green K,
    2. Buchvald FF,
    3. Marthin JK,
    4. et al
    . Ventilation inhomogeneity in children with primary ciliary dyskinesia. Thorax 2011; 67: 49–53.
    OpenUrlPubMedWeb of Science
  42. 42.↵
    1. Gronkvist M,
    2. Bergsten E,
    3. Gustafsson PM
    . Effects of body posture and tidal volume on inter- and intraregional ventilation distribution in healthy men. J Appl Physiol 2002; 43: 634–642.
    OpenUrl
  43. 40.
    1. Schibler A,
    2. Schneider M,
    3. Frey U,
    4. et al
    . Moment ratio analysis of multiple breath nitrogen washout in infants with lung disease. Eur Respir J 2000; 15: 1094–1101.
    OpenUrlAbstract
  44. 44.↵
    1. Fuchs SI,
    2. Buess C,
    3. Lum S,
    4. et al
    . Multiple breath washout with a sidestream ultrasonic flow sensor and mass spectrometry: a comparative study. Pediatr Pulmonol 2006; 41: 1218–1225.
    OpenUrlCrossRefPubMedWeb of Science
  45. 45.
    1. Fuchs SI,
    2. Gappa M
    . Helium cannot simply be exchanged for SF6 in multiple breath washout. Eur Respir J 2009; 34: Suppl. 53, 204s
    OpenUrl
  46. 46.↵
    1. Pillow JJ,
    2. Ljungberg H,
    3. Hülskamp G,
    4. et al
    . Functional residual capacity measurements in healthy infants: ultrasonic flow meter versus a mass spectrometer. Eur Respir J 2004; 23: 763–768.
    OpenUrlAbstract/FREE Full Text
  47. 47.↵
    1. Schibler A,
    2. Hall GL,
    3. Businger F,
    4. et al
    . Measurement of lung volume and ventilation distribution with an ultrasonic flow meter in healthy infants. Eur Respir J 2002; 20: 912–918.
    OpenUrlAbstract/FREE Full Text
  48. 48.↵
    1. Latzin P,
    2. Sauteur L,
    3. Thamrin C,
    4. et al
    . Optimized temperature and deadspace correction improve analysis of multiple breath washout measurements by ultrasonic flowmeter in infants. Pediatr Pulmonol 2007; 42: 888–897.
    OpenUrlCrossRefPubMedWeb of Science
  49. 49.↵
    1. Mauritz KA,
    2. Moore RB
    . State of understanding of nafion. Chem Rev 2004; 104: 4535–4585.
    OpenUrlCrossRefPubMedWeb of Science
  50. 50.↵
    1. Fuchs SI,
    2. Eder J,
    3. Ellemunter H,
    4. et al
    . Lung clearance index: normal values, repeatability, and reproducibility in healthy children and adolescents. Pediatr Pulmonol 2009; 44: 1180–1185.
    OpenUrlCrossRefPubMedWeb of Science
  51. 51.↵
    1. Macleod KA,
    2. Horsley AR,
    3. Bell NJ,
    4. et al
    . Ventilation heterogeneity in children with well controlled asthma with normal spirometry indicates residual airways disease. Thorax 2009; 64: 33–37.
    OpenUrlAbstract/FREE Full Text
  52. 52.↵
    1. Pittman JE,
    2. Johnson RC,
    3. Jones PW,
    4. et al
    . Variability of a closed, rebreathing setup for multiple breath wash-out testing in children. Pediatr Pulmonol 2012; 47: 1242–1250.
    OpenUrlCrossRefPubMed
  53. 53.↵
    1. Kraemer R,
    2. Baldwin DN,
    3. Ammann RA,
    4. et al
    . Progression of pulmonary hyperinflation and trapped gas associated with genetic and environmental factors in children with cystic fibrosis. Respir Res 2006; 7: 138
    OpenUrlCrossRefPubMed
  54. 54.↵
    1. Larsson A,
    2. Jonmarker C,
    3. Werner O
    . Ventilation inhomogeneity during controlled ventilation. Which index should be used. J Appl Physiol 1988; 65: 2030–2039.
    OpenUrlAbstract/FREE Full Text
  55. 55.↵
    1. Pillow JJ,
    2. Frerichs I,
    3. Stocks J
    . Lung function tests in neonates and infants with chronic lung disease: global and regional ventilation inhomogeneity. Pediatr Pulmonol 2006; 41: 105–121.
    OpenUrlCrossRefPubMedWeb of Science
  56. 56.↵
    1. Verbanck S,
    2. Paiva M,
    3. Schuermans D,
    4. et al
    . Relationships between the lung clearance index and conductive and acinar ventilation heterogeneity. J Appl Physio 2012; 112: 782–790.
    OpenUrlAbstract/FREE Full Text
  57. 57.↵
    1. Bouhuys A,
    2. van Lennep H
    . Effect of body posture on gas distribution in the lungs. J Appl Physiol 1962; 17: 38–42.
    OpenUrlAbstract/FREE Full Text
  58. 58.↵
    1. Saatci E,
    2. Miller DM,
    3. Stell IM,
    4. et al
    . Dynamic dead space in face masks used with noninvasive ventilators: a lung model study. Eur Respir J 2004; 23: 129–135.
    OpenUrlAbstract/FREE Full Text
  59. 59.↵
    1. Habib RH,
    2. Lutchen KR
    . Moment analysis of a multibreath nitrogen washout based on an alveolar gas dilution number. Am Rev Respir Dis 1991; 144: 513–519.
    OpenUrlCrossRefPubMedWeb of Science
  60. 60.↵
    1. Schulzke SM,
    2. Hall GL,
    3. Nathan EA,
    4. et al
    . Lung volume and ventilation inhomogeneity in preterm infants at 15–18 months corrected age. J Pediatr 2010; 156: 542–549.e2.
    OpenUrlCrossRefPubMedWeb of Science
  61. 61.↵
    1. Saidel GM,
    2. Salmon RB,
    3. Chester EH
    . Moment analysis of multibreath lung washout. J Appl Physiol 1975; 38: 328–334.
    OpenUrlAbstract/FREE Full Text
  62. 62.↵
    1. Haidopoulou K,
    2. Lum S,
    3. Turcu S,
    4. et al
    . Alveolar LCI vs. standard LCI in detecting early CF lung disease. Respir Physiol Neurobiol 2012; 180: 247–251.
    OpenUrlCrossRefPubMed
  63. 63.↵
    1. Fowler WS
    . Lung function studies; the respiratory dead space. Am J Physiol 1948; 154: 405–416.
    OpenUrlWeb of Science
  64. 64.↵
    1. Langley F,
    2. Even P,
    3. Duroux P,
    4. et al
    . Conséquences ventilatoires de l′occlusion unilatérale de l′artère pulmonaire [Ventilatory consequences of unilateral pulmonary artery occlusion]. Les Colloques des l’Institut National de la Santé et de la Recherche Médicale 1975; 51: 209–212.
    OpenUrl
  65. 65.↵
    1. Saniie J,
    2. Saidel GM,
    3. Chester EH
    . Real-time moment analysis of pulmonary nitrogen washout. J Appl Physiol 1979; 46: 1184–1190.
    OpenUrlAbstract/FREE Full Text
  66. 66.↵
    1. Robinson PD,
    2. Lindblad A,
    3. Gustafsson PM
    . Comparison of the utility of multiple breath inert gas washout parameters in cystic fibrosis. Thorax 2010; 65: 659
    OpenUrlFREE Full Text
  67. 67.↵
    1. Paiva M
    . Two new pulmonary functional indexes suggested by a simple mathematical model. Respiration 1975; 32: 389–403.
    OpenUrlCrossRefPubMedWeb of Science
  68. 68.↵
    1. Paiva M,
    2. van Muylem A,
    3. Engel LA
    . Slope of phase III in multibreath nitrogen washout and washin. Bull Eur Physiopathol Respir 1982; 18: 273–280.
    OpenUrlPubMedWeb of Science
  69. 69.↵
    1. Dutrieue B,
    2. Vanholsbeeck F,
    3. Verbanck S,
    4. et al
    . A human acinar structure for simulation of realistic alveolar plateau slopes. J Appl Physiol 2000; 89: 1859–1867.
    OpenUrlAbstract/FREE Full Text
  70. 70.
    1. Paiva M,
    2. Engel LA
    . Model analysis of gas distribution within human lung acinus. J Appl Physiol 1984; 56: 418–425.
    OpenUrlAbstract/FREE Full Text
  71. 71.
    1. Verbanck S,
    2. Paiva M
    . Model simulations of gas mixing and ventilation distribution in the human lung. J Appl Physiol 1990; 69: 2269–2279.
    OpenUrlAbstract/FREE Full Text
  72. 72.↵
    1. Verbanck S,
    2. Paiva M
    . Gas mixing in the airways and airspaces. Compr Physiol 2011; 1: 835–882.
    OpenUrl
  73. 73.
    1. Cumming G,
    2. Horsfield K,
    3. Jones JG,
    4. et al
    . The influence of gaseous diffusion on the alveolar plateau at different lung volumes. Respir Physiol 1967; 2: 386–398.
    OpenUrlCrossRefPubMedWeb of Science
  74. 74.
    1. Jones JG
    . The effect of preinspiratory lung volume on the result of the single breath O2 test. Respir Physiol 1967; 2: 375–385.
    OpenUrlCrossRefPubMedWeb of Science
  75. 75.
    1. Crawford AB,
    2. Cotton DJ,
    3. Paiva M,
    4. et al
    . Effect of airway closure on ventilation distribution. J Appl Physiol 1989; 66: 2511–2515.
    OpenUrlAbstract/FREE Full Text
  76. 76.
    1. Crawford AB,
    2. Cotton DJ,
    3. Paiva M,
    4. et al
    . Effect of lung volume on ventilation distribution. J Appl Physiol 1989; 66: 2502–2510.
    OpenUrlAbstract/FREE Full Text
  77. 77.
    1. Lacquet LM,
    2. van Muylem A
    . He and SF6 single-breath expiration curves. Comparison with the Paiva-Engel model. Bull Eur Physiopathol Respir 1982; 18: 239–246.
    OpenUrlPubMedWeb of Science
  78. 78.
    1. Crawford AB,
    2. Makowska M,
    3. Engel LA
    . Effect of tidal volume on ventilation maldistribution. Respir Physiol 1986; 66: 11–25.
    OpenUrlCrossRefPubMedWeb of Science
  79. 79.↵
    1. West JB,
    2. Hugh-Jones P
    . Pulsatile gas flow in bronchi caused by the heart beat. J Appl Physiol 1961; 16: 697–702.
    OpenUrlAbstract/FREE Full Text
  80. 80.↵
    1. Stuart-Andrews CR,
    2. Kelly VJ,
    3. Sands SA,
    4. et al
    . Automated detection of the phase III slope during inert gas washout testing. J Appl Physiol 2012; 112: 1073–1081.
    OpenUrlAbstract/FREE Full Text
  81. 81.↵
    1. Engel LA,
    2. Grassino A,
    3. Anthonisen NR
    . Demonstration of airway closure in man. J Appl Physiol 1975; 38: 1117–1125.
    OpenUrlAbstract/FREE Full Text
  82. 82.↵
    1. Leblanc P,
    2. Ruff F,
    3. Milic-Emili J
    . Effects of age and body position on "airway closure" in man. J Appl Physiol 1970; 28: 448–451.
    OpenUrlFREE Full Text
  83. 83.↵
    1. Benedik PS,
    2. Baun MM,
    3. Keus L,
    4. et al
    . Effects of body position on resting lung volume in overweight and mildly to moderately obese subjects. Respir Care 2009; 54: 334–339.
    OpenUrlAbstract/FREE Full Text
  84. 84.↵
    1. Gustafsson PM,
    2. Johansson HJ,
    3. Dahlback GO
    . Pneumotachographic nitrogen washout method for measurement of the volume of trapped gas in the lungs. Pediatr Pulmonol 1994; 17: 258–268.
    OpenUrlCrossRefPubMedWeb of Science
  85. 85.↵
    1. Gustafsson PM,
    2. Kallman S,
    3. Ljungberg H,
    4. et al
    . Method for assessment of volume of trapped gas in infants during multiple-breath inert gas washout. Pediatr Pulmonol 2003; 35: 42–49.
    OpenUrlCrossRefPubMedWeb of Science
  86. 86.↵
    1. Hughes JM,
    2. Rosenzweig DY,
    3. Kivitz PB
    . Site of airway closure in excised dog lungs: histologic demonstration. J Appl Physiol 1970; 29: 340–344.
    OpenUrlFREE Full Text
  87. 87.↵
    1. Burger EJ Jr.,
    2. Macklem P
    . Airway closure: demonstration by breathing 100 percent O2 at low lung volumes and by N2 washout. J Appl Physiol 1968; 25: 139–148.
    OpenUrlFREE Full Text
  88. 88.↵
    1. Milic-Emili J,
    2. Torchio R,
    3. D’Angelo E
    . Closing volume: a reappraisal (1967-2007). Eur J Appl Physiol 2007; 99: 567–583.
    OpenUrlCrossRefPubMedWeb of Science
  89. 89.↵
    1. Sixt R,
    2. Bake B,
    3. Oxhoj H
    . The single-breath N2-test and spirometry in healthy non-smoking males. Eur J Respir Dis 1984; 65: 296–304.
    OpenUrlPubMedWeb of Science
  90. 90.↵
    1. Michaelson ED,
    2. Wanner A,
    3. Watson H,
    4. et al
    . Distribution of ventilation in normal children. Chest 1979; 76: 658–662.
    OpenUrlCrossRefPubMedWeb of Science
  91. 91.↵
    1. Hankinson JL
    . Computer determined closing volumes. Comput Biomed Res 1977; 10: 247–257.
    OpenUrlCrossRefPubMed
  92. 92.↵
    1. Ljungberg HK,
    2. Gustafsson PM
    . Peripheral airway function in childhood asthma, assessed by single-breath He and SF6 washout. Pediatr Pulmonol 2003; 36: 339–347.
    OpenUrlCrossRefPubMedWeb of Science
  93. 93.
    1. Van Muylem A,
    2. Baran D
    . Overall and peripheral inhomogeneity of ventilation in patients with stable cystic fibrosis. Pediatr Pulmonol 2000; 30: 3–9.
    OpenUrlCrossRefPubMedWeb of Science
  94. 94.↵
    1. Van Muylem A,
    2. Verbanck S,
    3. Estenne M
    . Monitoring the lung periphery of transplanted lungs. Respir Physiol Neurobiol 2005; 148: 141–151.
    OpenUrlCrossRefPubMedWeb of Science
  95. 95.↵
    1. Olfert IM,
    2. Prisk GK
    . Effect of 60 degrees head-down tilt on peripheral gas mixing in the human lung. J Appl Physiol 2004; 97: 827–834.
    OpenUrlAbstract/FREE Full Text
  96. 96.↵
    1. Lundin G
    . Nitrogen elimination during oxygen breathing. Acta Physiol Scand Suppl 1953; 111: 130–143.
    OpenUrl
  97. 97.↵
    1. Kjellman B
    . Ventilatory efficiency, capacity and lung volumes in healthy children. Scand J Clin Lab Invest 1969; 23: 19–29.
    OpenUrlCrossRefPubMed
  98. 98.↵
    1. Ostlund A,
    2. Sporrong A,
    3. Linnarsson D,
    4. et al
    . Effects of sulphur hexafluoride on psychomotor performance. Clin Physiol 1992; 12: 409–418.
    OpenUrlCrossRefPubMedWeb of Science
  99. 99.↵
    1. Houghton JT,
    2. Ding Y,
    3. Griggs DJ,
    4. et al
    . Climate Change 2001. Cambridge, Cambridge University Press, 2001.
  100. 100.
    1. Schulzke SM,
    2. Deeptha K,
    3. Sinhal S,
    4. et al
    . Nasal versus face mask for multiple-breath washout technique in preterm infants. Pediatr Pulmonol 2008; 43: 858–865.
    OpenUrlCrossRefPubMed
  101. 101.↵
    1. Verbanck S,
    2. Schuermans D,
    3. Van Muylem A,
    4. et al
    . Ventilation distribution during histamine provocation. J Appl Physiol 1997; 83: 1907–1916.
    OpenUrlAbstract/FREE Full Text
  102. 102.
    1. Downie SR,
    2. Salome CM,
    3. Verbanck S,
    4. et al
    . Ventilation heterogeneity is a major determinant of airway hyperresponsiveness in asthma, independent of airway inflammation. Thorax 2007; 62: 684–689.
    OpenUrlAbstract/FREE Full Text
  103. 103.
    1. Sigurs N,
    2. Aljassim F,
    3. Kjellman B,
    4. et al
    . Asthma and allergy patterns over 18 years after severe RSV bronchiolitis in the first year of life. Thorax 2010; 65: 1045–1052.
    OpenUrlAbstract/FREE Full Text
  104. 104.
    1. Salamon E,
    2. Gain K,
    3. Hall GL
    . Wait time effect on repeat multiple breath nitrogen washout FRC. Eur Respir J 2010; 36:54, 656s
    OpenUrl
  105. 105.↵
    1. Aurora P,
    2. Kozlowska W,
    3. Stocks J
    . Gas mixing efficiency from birth to adulthood measured by multiple-breath washout. Respir Physiol Neurobiol 2005; 148: 125–139.
    OpenUrlCrossRefPubMedWeb of Science
  106. 106.↵
    1. Wanger J,
    2. Clausen JL,
    3. Coates A,
    4. et al
    . Standardisation of the measurement of lung volumes. Eur Respir J 2005; 26: 511–522.
    OpenUrlAbstract/FREE Full Text
  107. 107.↵
    1. Newth CJ,
    2. Enright P,
    3. Johnson RL
    . Multiple-breath nitrogen washout techniques: including measurements with patients on ventilators. Eur Respir J 1997; 10: 2174–2185.
    OpenUrlCrossRefPubMedWeb of Science
  108. 108.↵
    1. Robinson PD,
    2. Stocks J,
    3. Aurora P,
    4. et al
    . Abbreviated multi-breath washout for calculation of lung clearance index. Pediatr Pulmonol 2012 [in press DOI: 10.1002/ppul.22618].
  109. 109.↵
    1. Gustafsson PM
    . Pulmonary gas trapping increases in asthmatic children and adolescents in the supine position. Pediatr Pulmonol 2003; 36: 34–42.
    OpenUrlCrossRefPubMedWeb of Science
  110. 110.
    1. Latzin P,
    2. Roth S,
    3. Thamrin C,
    4. et al
    . Lung volume, breathing pattern and ventilation inhomogeneity in preterm and term infants. PLoS One 2009; 4: e4635
    OpenUrlCrossRefPubMed
  111. 111.
    1. Hutten GJ,
    2. van Eykern LA,
    3. Latzin P,
    4. et al
    . Relative impact of respiratory muscle activity on tidal flow and end expiratory volume in healthy neonates. Pediatr Pulmonol 2008; 43: 882–891.
    OpenUrlCrossRefPubMedWeb of Science
  112. 112.↵
    1. Singer F,
    2. Stern G,
    3. Thamrin C,
    4. et al
    . Tidal volume single breath washout of two tracer gases–a practical and promising lung function test. PloS One 2011; 6: e17588
    OpenUrlCrossRefPubMed
View Abstract
Back to top
View this article with LENS
Email
Print
Citation Tools

Consensus statement for inert gas washout measurement using multiple- and single- breath tests
Paul D. Robinson, Philipp Latzin, Sylvia Verbanck, Graham L. Hall, Alexander Horsley, Monika Gappa, Cindy Thamrin, Hubertus G.M. Arets, Paul Aurora, Susanne I. Fuchs, Gregory G. King, Sooky Lum, Kenneth Macleod, Manuel Paiva, Jane J. Pillow, Sarath Ranganathan, Felix Ratjen, Florian Singer, Samatha Sonnappa, Janet Stocks, Padmaja Subbarao, Bruce R. Thompson, Per M. Gustafsson
European Respiratory Journal Mar 2013, 41 (3) 507-522; DOI: 10.1183/09031936.00069712
Reddit logo Technorati logo Twitter logo Connotea logo Facebook logo Mendeley logo
Full Text (PDF)

Jump To

Subjects

Related Articles