For reliable assessment of ventilation inhomogeneity, multiple-breath washout (MBW) systems should be realistically validated. We describe a new lung model for in vitro validation under physiological conditions and the assessment of a new nitrogen (N2)MBW system.
The N2MBW setup indirectly measures the N2 fraction (FN2) from main-stream carbon dioxide (CO2) and side-stream oxygen (O2) signals: FN2 = 1−FO2−FCO2−FArgon. For in vitro N2MBW, a double chamber plastic lung model was filled with water, heated to 37°C, and ventilated at various lung volumes, respiratory rates, and FCO2. In vivo N2MBW was undertaken in triplets on two occasions in 30 healthy adults. Primary N2MBW outcome was functional residual capacity (FRC). We assessed in vitro error (√[difference]2) between measured and model FRC (100–4174 mL), and error between tests of in vivo FRC, lung clearance index (LCI), and normalized phase III slope indices (Sacin and Scond).
The model generated 145 FRCs under BTPS conditions and various breathing patterns. Mean (SD) error was 2.3 (1.7)%. In 500 to 4174 mL FRCs, 121 (98%) of FRCs were within 5%. In 100 to 400 mL FRCs, the error was better than 7%. In vivo FRC error between tests was 10.1 (8.2)%. LCI was the most reproducible ventilation inhomogeneity index.
Citation: Singer F, Houltz B, Latzin P, Robinson P, Gustafsson P (2012) A Realistic Validation Study of a New Nitrogen Multiple-Breath Washout System. PLoS ONE 7(4): e36083. https://doi.org/10.1371/journal.pone.0036083
Editor: Dominik Hartl, University of Tübingen, Germany
Received: February 22, 2012; Accepted: March 26, 2012; Published: April 27, 2012
Copyright: © 2012 Singer et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research project received funding from the European Union Seventh Framework Programme FP7/2007–2013 under grant agreement n° 270194, as part of the Airway Disease PRedicting Outcomes through Patient Specific Computational Modelling (AirPROM) project (www.airprom.eu). It also received funding from the Västra Götaland Region Research Council, Sweden. The authors acknowledge the support of the European Respiratory Society, Fellowship STRTF fellowship n°81-2011, and the Federal Department of Economic Affairs Switzerland, Commission for Technology and Innovation (CTI), Innovation Promotion Agency (http://www.bbt.admin.ch/kti/), unrestricted educational grant no. 11661.1 PFLS-LS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: Dr. Latzin and Dr. Isler (Eco Medics AG) received an unrestricted educational national grant (CTI) to assess a single-breath washout application based on the current equipment (Exhalyzer D). Dr. Latzin does not have any further conflicts of interest to disclose. This does not alter the authors' adherence to all the PLoS ONE policies on sharing data and materials.
Multiple-breath inert gas washout (MBW) tests are used to assess uniformity of ventilation distribution in infants, children, and adults . Both global indices of ventilation inhomogeneity such as the lung clearance index (LCI) and specific indices of non-uniform gas mixing in the conducting and acinar airway zones (Scond and Sacin) are frequently reported –. The accuracy of these indices relies directly or indirectly on correctly measured functional residual capacity (FRC). Therefore current guidelines for lung function testing recommend in vitro FRC measurements over the full range of lung volumes in question at various respiratory frequencies , .
FRC measurement validation is commonly assessed using calibration syringes to simulate FRC and tidal breathing washout . However, in vivo accuracy of FRC measurements depends on the individual performance under physiological conditions of the gas and flow sensors used, ignored by the syringe. Given the increasing interest in MBW as a clinical outcome measure there is an urgent need for improved validation models which incorporate conditions encountered during clinical testing (i.e. variations in temperature, pressure and humidity over the breath cycle).
This report describes (i) the development and utility of a lung model incorporating simulated body temperature, pressure and water vapor saturation (BTPS) conditions, and (ii) the in vitro and in vivo performance of a commercial N2MBW system (Exhalyzer D®, Eco Medics AG, Duernten, Switzerland). Primary outcome was the accuracy and precision with which FRC can be generated and measured in vitro and the reproducibility of FRC in vivo in healthy adults. Secondary outcomes were the reproducibility of ventilation inhomogeneity indices and their correlation in healthy adults.
Nitrogen multiple-breath washout setup
We used an unmodified open-circuit N2MBW hardware and software package (Exhalyzer D® and Spiroware® 3.1, Eco Medics AG) for all recordings, and an in-house customized software based on TestPoint™ (Capital Equipment Corp, Billerica, MA, USA) for off-line data processing and analyses. Flow was measured using a mainstream ultrasonic flowmeter and used to derive tidal volumes . Gas concentrations were measured by a side-stream laser O2 sensor (Oxigraf, Inc, Mountain View, CA, USA) and a main-stream infra-red CO2 sensor (Capnostat® 5, Respironics Novametrix LLC, Wallingford, CT, USA). In this device, FN2 is measured indirectly based on Dalton's law of partial pressures: FN2 = 1−FO2−FCO2−FArgon (FArgon = FN2 * 0.00934/0.78084). The FArgon (0.00934) is treated as a fixed proportion of the FN2 assuming similar washout during N2MBW. Daily two-point calibration and verification of the flow and O2 sensors, and zero calibration of the CO2 sensor were performed. The O2 sensor has a slower 10–90% response time (140 ms) than the CO2 sensor (55 ms). To align their signals, a speeding algorithm was applied to the O2 signal reducing its response to approximately 110 ms , . Gas signals were synchronized to the flow signal using the re-inspired post-capillary dead space to produce a step response in CO2 and O2. The gas signal vectors were time shifted to the point in time when the post-capillary dead space had been inhaled such that a 50% change in gas signal deflection then occurred. This was repeated over a minimum of ten washout breaths and median “delay times” for CO2 (50 ms) and O2 (565 ms) were used for signal alignment. Quality of superimposition of the inverted O2 signal on the CO2 signal was assessed visually.
Lung (model) resident FN2 was washed out using 100% O2 applied via open circuit at either 200 mL/s for 100–400 mL FRCs or at 1000 mL/s for 500–4200 mL FRCs and in vivo, respectively (Figure 1). These bypass flows were chosen to exceed maximum tidal inspiratory flows and to minimize rebreathing of CO2 or N2. For respective lung volumes (Table 1) we used post-capillary dead space reducers (infant set 1, preschool set 2, adult set 3) and hygienic inserts (Spirette) provided by the manufacturer (Eco Medics AG). These reduced equipment related post-capillary dead space (volume between CO2/O2 sampling point and bypass) to 1.5 mL, 16 mL, and 26.9 mL, respectively, as measured by water displacement. Bacteria filters (air eco slimline, Vickers Ind Est, LA, UK) had 30 mL dead space and were used for preschool and adult sets. Accordingly, pre-capillary dead space (volume between lung compartment top and CO2/O2 sampling point) was 37.9 mL in the large model and 3 mL in the small model, respectively. Apparatus resistance was measured by a pressure transducer (Timeter RT200, Allied Healthcare Products Inc., MO, USA). We applied pure O2 and increased flows stepwise between 0–200 mL/s for the infant set, 0–500 mL/s for the preschool set, and 0–770 mL/s for the adult set with bacteria filters in place. Maximum resistances were 0.03, 0.06, and 0.19 kPa/L*s, respectively, and complied with the recommendations of previous standards , .
The lung and ventilation compartments are partly filled with distilled water, their volumes are 6.94 L and 11.72 L, respectively. The outer chamber's volume is 67.73 L, filled with distilled water and constantly heated to 37°C. The dashed line reflects the water level determining tidal volume and functional residual capacity (FRC) at in- and expiratory end-tidal levels. FRC is the volume of air contained in the model at end-tidal expiration. One mm on the tape measure corresponds to 18.7 mL volume. FRC range is 0.5–4.2 L. O2 = sampling point of the side-stream oxygen sensor. CO2 = sampling point of the main-stream carbon dioxide sensor. Flowhead = main-stream ultrasonic flowmeter.
The lung model
The framework of the lung model was constructed from acrylic glass (Soloplex, Tidaholm, Sweden) and consisted of two rigid chambers: An inner chamber divided into two communicating compartments (via their lower aspect) termed the lung and the ventilation compartment, and an outer chamber (Figure 1). Two different size models were constructed to allow for both infant (100 to 400 mL) and children/adult (500 to 4200 mL) lung model volumes. The inner chamber was filled with distilled water until the desired FRC was achieved, measured as the end-expiratory water level using a transparent vertical tape measure fixed to the lung compartment. FRC volume was determined geometrically from known dimensions: one millimeter corresponded to 18.7 mL in the large and to 4.8 mL in the small lung model. The lung model was placed inside a water tank which served to heat the water in the inner chamber to 37°C, monitored using a thermostat. To simulate various breathing patterns, a bi-level positive airway pressure ventilator (Vivo 30, Breas Medical AB, Mölnlycke, Sweden) for the large lung model, or a 100 mL calibration syringe (Hans Rudolph Inc, Shawnee, KS, USA) for the small lung model was connected to the top of the ventilation compartment and exerted hydraulic pressure transmitted through to the lung compartment. During ventilation, temperature and humidity were measured every third FRC trial inside the lung compartment using a thermocouple thermometer (BAT-12 Microprobe Thermometer, Physitemp Instruments, Inc. New Jersey, USA) and a monolithic humidity sensor (HIH-4602-L-CP, linear humidity sensor, Honeywell, Minneapolis, USA).
In vitro study
Static signal linearity of the N2MBW system was assessed over the full range of O2, CO2, and N2 fractions encountered during N2MBW testing and performed at 37°C with 100% relative humidity: By increasing FO2 stepwise (60 steps), FO2 ranged from 15–100%, FCO2 from 0–6%, and FN2 from 0–79%. The reference for measured gas concentrations was a respiratory mass spectrometer (AMIS 2000; Innovision A/S, Odense, Denmark).
In vitro assessments of the N2MBW system performance were undertaken as triplicate FRC measurements (n = 150) across 50 different nominal FRCs (100 to 4200 mL), over two days. Ventilator pressures in the large model or syringe stroke volumes in the small volume were chosen to achieve physiological tidal volumes (VT), VT over FRC ratios (VT/FRC), and respiratory rates (RR) for each FRC setting (Table 1). To assess the possible influence of different FCO2 on FRC measurement accuracy, the lung compartment was washed-in with either ambient air (0.05% CO2) or CO2 enriched air (n = 45, Carboair®, Aiolos Medical, Karlstad, Sweden) prior to N2MBW. Carboair® contains 5% CO2 and balance air.
In vivo study
Thirty-two healthy adults performed N2MBW on two test occasions within a three week period. All subjects had a standardized interview on respiratory health. Inclusion criteria were adults aged 19 to 70 years with a smoking history less than five pack-years, no history of acute or chronic airway disease, and no on-going medication potentially affecting lung function. N2MBW was performed in the sitting position using a nose clip with the dead space reducer (set 3), hygienic insert, and bacterial filter in place. N2MBW was done in triplets with between-test intervals exceeding the washout time. The subjects were instructed to breathe regularly with relaxed expirations. The washout phase was terminated once end-tidal FN2 was less than 1/40th of the starting FN2 for at least three breaths.
The in vivo study was approved by the Ethics Committee of the University of Gothenburg Sweden. We obtained informed consent from all participants involved in the study.
Nitrogen multiple-breath washout outcomes
FRC was calculated as net expired N2 volume (expired N2 volume minus re-inspired N2 volume) divided by the difference of FN2 at start of MBW minus FN2 at end of MBW. Pre-capillary dead space was subtracted from FRC such that the reported FRC corresponds to the volume of the inner compartment of the lung model or FRC at the airway opening in the in vivo recordings. Indices of ventilation inhomogeneity were calculated from in vivo N2MBW trials. Because LCI, Sacin, and Scond relate inversely to ventilation efficiency, their values increase with increasing ventilation inhomogeneity. LCI was calculated as cumulative expired gas volume (CEV) required to reduce FN2 to 1/40th of the starting FN2, divided by FRC. Two phase III slope (SIII) indices, Scond and Sacin, were calculated. Automated SIII fitting over 50–95% of expired volume was performed for each breath and manually adjusted to exclude phase II or IV from the linear regression fit. SIII was normalized (SnIII) by dividing SIII by the mean FN2 over SIII and multiplying SIII with VT, and averaged per breath from the three N2MBWs . Mean SnIII per breath was then plotted against the corresponding mean lung volume turnover (TO = CEV/FRC) for each breath. Scond is defined as the rate of SnIII increase between lung volume turnovers 1.5 and 6.0. Sacin is defined as the first breath SnIII value minus the convection-dependent inhomogeneity contribution to this value .
Linearity of sensors compared to mass spectrometry was assessed using uni-variable linear regression and respective signal offsets (linear model intercept) and gains (linear model slope) with their 95% confidence intervals (CI) were reported. Intra-test variability of both model and measured FRCs as generated by the model and measured by the N2MBW setup, respectively, was calculated as intra-test coefficient of variation (CV = SD/mean*100). Accuracy of FRC measurements was expressed as (i) absolute (mL) difference (difference between measured FRC minus model FRC), (ii) relative (%) difference (difference*100 divided by model FRC), and as (iii) relative error (square-root of the squared relative difference). Acceptable upper limit was 5% error according to current infant lung function standards . We reported coefficient of repeatability (CR) calculated as 1.96*SD of differences between paired measurements . The CR estimates the 95% range of technical variability due to measurement error in vitro or the technical and physiological between-test variability in vivo. We assessed Bland Altman plots , and the relation of error with FRC, breathing pattern, different lung model gases, and between tests using uni- and multi-variable linear regression models and paired t-tests. P-values<0.05 were considered statistically significant and all analyses were done using Stata™ (Stata Statistical Software: Release 11. College Station, TX: StataCorp LP).
Lung model performance
The lung model successfully generated 146 (97%) out of 150 FRCs (range 100–4174 mL) under BTPS conditions. Mean (SD) of temperature and humidity were 35.9 (1.3)°C and 97.9 (1.0)%, respectively, obtained from 18 measurements. Following water refilling, four gas temperature drops of 3°C were observed and respective FRC recordings were subsequently excluded. Realistic breathing patterns were applied with VT between 30 and 877 mL, VT/FRC between 0.14 and 0.55, and RR between 10 and 35 min−1. The intra-test variability of FRCs generated by the lung models was low overall, CV mean (SD) was 0.07 (0.31)%, and lower in the large model compared to the small model: CV mean (SD) was 0.03 (0.15)% and 0.23 (0.64)%, p = 0.108, respectively. The potential parallax error of reading water levels using the tape measure was estimated as one mm corresponding to 18.7 mL and 4.8 mL in the large and small lung model, respectively. Relating these volumes to the nominal FRC, the relative mean (range) parallax error was 1.2 (0.4–3.7)% and 2.9 (1.2–4.8)% in the large lung and small model, respectively.
In vitro performance of the nitrogen multiple-breath washout setup
The O2, CO2, and N2 signals were linear over the full range. R2 was >0.99 for all signals (Table 2). The N2MBW setup accurately measured FRC with low intra-test variability (Figure 2, Table 3). Of 146 FRC measurements one measurement was excluded due to incomplete N2 washout. In 48 triplicate FRC measurements, mean (SD) of CV was 1.4 (1.7)%. Absolute mean (SD) difference between measured and model FRC was 9.2 (52.3) mL, relative difference was −0.2 (2.9)%. Of 145 FRCs measured between 100 mL and 4200 mL, 130 (90%) FRC measurements were within the 5% of model FRCs (Figures 2, 3). Mean (SD) error was 2.3 (1.7)% in all measurements. In the large lung model (500 to 4174 mL FRCs), 121/124 (98%) of FRCs were within the 5% error limit, error range was 0.0–6.5%. In the small lung model (100 to 400 mL FRCs), 9 (43%) out of 21 FRCs were within the 5% error limit, error range was 1.0–7.1%.
Bland Altman plot  of measured functional residual capacity (FRC) minus lung model FRC plotted vs. mean of measured and model FRC. Differences (open circles), and mean difference, and upper and lower limits of agreement (mean difference ±1.96 SD of differences) are given as dashed lines for the small lung model and as solid lines for the large lung model. Figure 2a gives absolute FRC differences (mL). For the small and large lung model, mean differences are −10.2 mL and 12.5 mL, upper limits of agreement are 9.9 mL and 121.9 mL, and lower limits of agreement are −30.3 mL and −96.8 mL, respectively. Figure 2b gives relative FRC differences (%). For the small and large lung model, mean differences are −3.8% and 0.4%, upper limits of agreement are 3.6% and 4.7%, and lower limits of agreements are −11.2% and −4.0%, respectively.
Functional residual capacity (FRC) measurement error (%) is plotted against lung model FRC. The error data are displayed as open circles for the small model (100–400 mL FRCs) and closed circles for the large model (500–4200 mL FRCs). The dashed line gives the 5% limit of acceptable measurement error, the dotted lines reflect possible nominal volume bias due to reading parallax error (one mm) in the small and large lung model.
Errors in FRC measurements in lung models containing either ambient or CO2 enriched air were similar. Comparing the mean (SD) error using ambient air (n = 102) vs. CO2 enriched air (n = 43), the mean (SD) error was 2.2 (1.7)% vs. 2.6 (1.8)%, p = 0.185. Errors in FRCs measurements recorded on day one (n = 72) vs. day two (n = 73) differed, mean (SD) error 1.6 (1.0)% vs. 2.1 (1.4)%, p = 0.024. There was a positive association between error and RR (R2 = 0.24, p<0.001), and negative associations with VT (R2 = 0.16, p<0.001), mean expiratory flow (R2 = 0.15, p<0.001), measurement duration (R2 = 0.12, p<0.001), and FRC (R2 = 0.09, p<0.001). Accounting for RR in a multi-variable regression model, the association of error with mean expiratory flow remained significant (p = 0.036) but not with VT, measurement duration, or FRC.
In vivo performance of the nitrogen multiple-breath washout setup
Thirty out of 32 healthy adults (15 females) successfully performed N2MBW on two test occasions with a mean (SD) of 12.2 (5.1) days in between. Mean (range) age was 49.3 (21–69) years. Two males did not achieve leak-free N2MBW. All subjects had normal spirometry indices. Mean (SD) z-scores  of forced expiratory volume in one second (FEV1), FEV1/forced vital capacity, and forced expiratory flow between 25–75% of expired volume (FEF25–75) were 0.75 (0.86), 0.24 (0.81), and 0.32 (0.82), respectively.
In vivo FRC intra-test variability was greater than measured in model FRC: CV mean (SD) was 4.5 (3.2)% vs. 1.4 (1.7)%, p<0.001. Likewise the in vivo FRC error between tests was greater compared to the in vitro FRC error measured in the models: Error mean (SD) was 10.1 (8.2)% vs. 2.3 (1.7)%, p<0.001. Reproducibility of ventilation inhomogeneity indices differed significantly with the LCI representing the most reproducible index (Table 3). In vivo reproducibility for LCI was better than for FRC, and markedly better than for Sacin and Scond (Figures 4, 5). LCI was correlated with Sacin (Pearson r = 0.61, p<0.001) but not with Scond (r = 0.17, p = 0.377). Sacin was correlated with Scond (r = 0.44, p = 0.016). Estimates of repeatability (CV) and reproducibility (CR) of FRC and ventilation inhomogeneity indices were not associated with number of days between tests or the subject's age and gender (data not shown).
Bland Altman plot  of functional residual capacity (FRC) measured on two study days within three weeks in 30 healthy adults. Absolute FRC differences (Figure 4a), relative FRC differences (Figure 4b), mean difference and upper and lower limits of agreement (lines) are plotted against mean FRC of both tests. Mean difference is −15.4 mL (−1.1%), upper and lower limits of agreement are 793.3 mL (23.2%) and −824.1 mL (−25.4%).
Bland Altman plot  of lung clearance index (LCI) measured on two study days within three weeks in 30 healthy adults. Absolute LCI differences (Figure 5a), relative LCI differences (Figure 5b), mean difference and upper and lower limits of agreement (lines) are plotted against mean LCI of both study days. Mean difference is −0.13 (−1.8%), upper and lower limits of agreement are 0.55 (7.6%) and −0.81 (−11.2%).
This is the first study demonstrating that an available N2MBW system accurately and reliably measures FRC over the wide range of lung volumes and different breathing patterns encountered from early childhood to adulthood. This study also shows that BTPS conditions can be implemented into lung model studies to bench-test MBW equipment under realistic conditions. In vitro FRC can be measured with only 5% error over FRC volumes between 600 and 4200 mL with the N2MBW system. In FRCs below 600 mL, the error is better than 7%. N2MBW measurements in healthy adults show that LCI is more reproducible than FRC, Sacin, and Scond. Variability of FRC measured in vivo is higher than in vitro suggesting substantial physiological fluctuation of FRC in humans .
Comparison to previous lung model studies
Data on quality of signals and their integration under realistic conditions are essential for appropriate evaluation of MBW setups . As an initial step, linearity of O2, CO2, and N2 signals was confirmed over the full measurement range in heated humid conditions encountered during clinical N2MBW testing. We improved a lung model described by Brunner et al. , which was originally ventilated manually and the water contained within the model was not heated. In addition to the incorporation of BTPS conditions, physiological breathing patterns were applied. These conditions recreate the stress the system is exposed to during clinical testing across wide age ranges. Previous in vitro lung models lacked one or more important physiological aspects –.
The current N2MBW system precisely measures lung volumes between 600 and 4200 mL. In this volume range approximating late preschool age to large sized adults, the in vitro measurement error was below 5% in all FRCs (Figure 3). Importantly, this N2MBW system is not susceptible to different FCO2. Indirect N2 measurement may be susceptible to drift in FCO2 as the current N2 signal or, e.g. molar mass, are sum signals of gas fractions including the FCO2 .
This study is able to disentangle technical from physiological aspects contributing to FRC variability. Comparing the in vitro CR of FRC (4.6%) with in vivo (24.9%), inherent physiological variability of FRC may explain 20.3% (or relatively 82%) of between-test variability in adults. Validation studies exclusively performed in vivo do not allow differentiation between technical and physiological variability , . In infants, the FRC error between tests may exceed 20% , .
Ventilation inhomogeneity indices
The current N2MBW setup can be easily applied to measure ventilation inhomogeneity indices in vivo. These measures correlate as shown previously , . LCI, in particular, had high repeatability and reproducibility in healthy adults. The specific indices of non-uniform gas mixing in the conducting and acinar airway zones (Scond and Sacin) were more variable. Between-test reproducibility of LCI (CR = 9.5%) was markedly higher than for Sacin (49.2%) and Scond (41.4%). In a recent study , comparable between-test reproducibility of LCI, Sacin, and Scond was reported in healthy adults performing a sulfur hexafluoride MBW protocol with tidal breathing restricted to one liter VT. The small technical error of FRC observed in vitro strongly suggests higher physiological variability of these SnIII indices compared to volume indices (FRC, LCI). SnIII depends on breathing pattern , which was not restricted in this study. Interestingly, LCI is even more reproducible than FRC as also shown in healthy children . This may reflect the fact that LCI is a robust volume ratio (CEV/FRC), cancelling the effect of physiological changes in lung volumes.
While the large lung model was suited for the MBW bench test, the small model may require adjustments. Automated ventilation and a laser sensor for determining nominal FRC could improve the infant lung model. Parallax error in the large model was small enough to avoid over- or underestimation of nominal FRCs (Figure 3).
Within the small technical measurement error of FRC, RR and tidal flow were correlated with error. Whether this association was causal leading to signal asynchrony or rather a surrogate for flow-dependent temperature and humidity fluctuations hampering adequate BTPS correction remains to be determined . We hypothesize that the apparatus dead space volumes behave as systems taking up and delivering heat energy and moisture non-linearly over breath cycles. Reduced dead space and dynamic BTPS and synchronization algorithms may further decrease measurement error.
The current and previous models did not allow assessment of “tissue” N2 contribution to the lung inherent FN2. This contribution is difficult to estimate and account for, as available data are limited . In adults with more advanced lung disease, duration of N2MBW and bias from tissue N2 may increase, and intervals between tests should be adapted accordingly .
Availability of realistic validation protocols will aid the transition of MBW from promising research tool into routine clinical use. This is the first validation of an available N2MBW setup using physiological in vitro test conditions. Many other MBW setups remain to be validated and are either customized, expensive, or have been taken off the market , , , . N2MBW is also advantageous to using foreign tracer gases because 100% O2 is economic, readily available in all hospitals, and non-polluting.
The between-test variability of ventilation inhomogeneity indices reported here sheds further light on their natural variability over time. The CR aids estimating clinically relevant change in lung function outcomes for future intervention studies. Given a hypothetical intervention in the current study, a decrease of LCI of 0.68 units (9.5%) would constitute a physiological change with 95% probability. Further longitudinal studies in disease groups, such as cystic fibrosis where variability is increased, are required –. In infants and preschool-aged children, safety of N2MBW and variability of N2MBW indices need to be determined.
The performance of MBW setups can be realistically assessed using a new in vitro lung model producing BTPS conditions and representative breathing patterns. This lung model protocol is suitable for validation of other MBW systems. The new N2MBW system accurately and precisely measures lung volumes between 600 and 4200 mL. Future work may extend this into smaller lung volumes and younger age groups. The LCI represents the most reproducible N2MBW in vivo outcome as compared to FRC, Scond, and Sacin. This study may aid the transition of this important type of lung function test from being a promising research tool to becoming a routine method in clinical practice.
The authors would like to thank the healthy control subjects for their participation in the study, Mrs. Linda Berg (R.T.) and Emilia Viklund (R.T.) for skilful technical assistance, and Mr. Edward P Bergsten for technical support. The authors would like to express their gratitude to Urs Frey, Markus Roos, Sophie Yammine, and Chiara Abbas for providing scientific support.
Conceived and designed the experiments: FS BH PL PR PG. Performed the experiments: FS BH PR PG. Analyzed the data: FS PG. Contributed reagents/materials/analysis tools: FS BH PL PG. Wrote the paper: FS PL PR PG. Qualified as the guarantor of the paper, took responsibility for the integrity of the work as a whole, from inception to published article: PG.
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