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The total-breath method yields higher values of DLCO and TLC than the conventional method



The 2017 ATS/ERS technical standard for measuring the single-breath diffusing capacity (DLCO) proposed the “rapid-gas-analyzer” (RGA) or, equivalently, “total-breath” (TB) method for the determination of total lung capacity (TLC). In this study, we compared DLCO and TLC values estimated using the TB and conventional method, and how estimated TLC using these two methods compared to that determined by body plethysmography.


A total of 95 people with COPD (GOLD grades 1–4) and 23 healthy subjects were studied using the EasyOne Pro (ndd Medical Technologies, Switzerland) and Master Screen Body (Vyaire Medical, Höchberg, Germany).


On average the TB method resulted in higher values of DLCO (mean ± SD Δ = 0.469 ± 0.267; 95%CI: 0.420; 0.517 mmol*min-1*kPa-1) and TLC (Δ = 0.495 ± 0.371; 95%CI: 0.427; 0.562 L) compared with the conventional method. In healthy subjects the ratio between TB and conventional DLCO was close to one. TLC estimated using both methods was lower than that determined by plethysmography. The difference was smaller for the TB method (Δ = 1.064 ± 0.740; 95%CI: 0.929; 1.199 L) compared with the conventional method (Δ = 1.558 ± 0.940; 95%CI: 1.387; 1.739 L). TLC from body plethysmography could be estimated as a function of TB TLC and FEV1 Z-Score with an accuracy (normalized root mean square difference) of 9.1%.


The total-breath method yielded higher values of DLCO and TLC than the conventional analysis, especially in subjects with COPD. TLC from the total-breath method can also be used to estimate plethysmographic TLC with better accuracy than the conventional method.

The study is registered under NCT04531293.

Peer Review reports

Results in short

The 2017 ERS/ATS standards for single-breath carbon monoxide uptake in the lung proposed the “total-breath method” for the single-breath maneuver. We found that this method yielded higher values of DLCO and TLC than the conventional method.


The single-breath diffusing capacity (DLCO) of the lung for carbon monoxide is a well-established functional measure with multiple clinical applications [1, 2]. In 2017, the ATS/ERS published recommendations for its measurement covering technical and methodological requirements. In addition to the conventional method, the technical standard described a procedure for the determination of alveolar volume (VA) in the assessment of diffusing capacity that was introduced in 1985 [3] and then [4] named the rapid gas analyzer (RGA) method, or alternatively [5] total-breath (TB) method. Instead of considering only an average value from a limited sample volume as in conventional sampling (CS), the total-breath method relies on measuring the entire course of exhaled tracer gas concentration, using a rapid gas analyzer (RGA). VA and the corresponding total lung capacity (TLC) are then derived from a mass-balance equation using the entire concentration curve (Fig. 1) [4]. As the total-breath method uses more of the available measured data, it offers the prospect to provide more accurate estimates of lung volume than the conventional method. Since the value of DLCO depends on that of VA, a change in method would also change DLCO values.

Fig. 1
figure 1

Illustration of the two approaches regarding the total-breath method (TB) using a rapid gas analyzer (RGA) and the conventional sampling (CS) of the inert tracer gas during expiration in the single-breath assessment of CO diffusing capacity of the lung. Although the RGA provides a continuous signal over the whole course of expiration, in the CS method only a defined sample of 500 mL is used (see Materials and methods)

Since the values of TLC estimated via gas dilution are affected by inhomogeneity of ventilation, a key feature of COPD [6], the observed differences between the total-breath and the conventional method should become greater in people with more severe COPD. Moreover, the well-known difference between TLC measured via gas dilution and TLC measured via body plethysmography [7] might become smaller with the total-breath method, potentially improving the estimation of plethysmographic TLC from gas dilution.

We aimed to determine the impact of using the total-breath method in healthy subjects and those with COPD of different severities, by comparing DLCO and TLC estimated using the conventional and total-breath method. TLC values were also compared with those measured by body plethysmography.

Materials and methods

Recruitment of the study population

Consecutive patients with the clinical diagnosis of COPD [8] were recruited from the pulmonary department at the Hirslanden Hospital Zurich, Switzerland. Healthy subjects, who had no history of respiratory disease, were recruited from hospital staff. Subjects with other types of lung disease than COPD were excluded. The study protocol ( NCT04531293, first trial registration 28/08/2020) was approved by the local ethics committee (Kantonale Ethikkommission Zürich (Cantonal Ethics Committee), BASEC 2020–02139), and all participants gave their written informed consent. All experiments were performed in accordance with relevant guidelines and regulations, in particular the Declaration of Helsinki.


Spirometry was performed using the EasyOne Pro (ndd Medical Technologies, Switzerland) following international recommendations [9]. Forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and their ratio FEV1/FVC were reported, with predicted values from GLI (Global Lung Function Initiative) [10]. Lung volume from body plethysmography (TLCbody) was estimated using the Master Screen Body (Vyaire Medical, Höchberg, Germany). Diffusing capacity for carbon monoxide (CO) was determined in a single-breath maneuver using the EasyOne Pro (ndd Medical Technologies, Switzerland) and the integrated rapid gas analyzer. The single-breath maneuver was performed twice, separated by at least 5 min [11], and expiration was terminated if a volume plateau was reached. Data was analyzed conventionally by averaging over a defined sample of expiratory volume (conventional sample of 500 mL, CS), or utilizing the total time course of in- and expiration (total-breath, TB) for helium concentration (see Fig. 1). The conventional analysis was available in the EasyOne Pro device (software version V3.7.2.2), which has been shown to yield reliable values in previous studies [12,13,14,15]. The total-breath analysis was performed via a custom algorithm after export of the raw data, using the entire tracer gas (helium) concentration during inspiration and expiration (see Fig. 1) within a mass-balance equation. DLCO and TLC were calculated using the residual concentration of helium in the exhaled air as measured at the start of each test. VA was related to TLC by dead space computed as 2.2 mL/kg body weight for BMI < 30 kg/m2, and by height2 (in m) divided by 189.4 for BMI ≥ 30 kg/m2 [4]. Predicted values were taken from the Global Lung Function Initiative reference equations [10, 16].

Statistical analysis

Continuous data were summarized as mean values and standard deviations (SD). Bland–Altman plots were used to assess the agreement between estimates of DLCO and TLC obtained by different methods. Pearson’s correlation coefficients and linear regression analysis were employed to quantify associations between a set of explanatory variables (sex, age, height, BMI, Z-Scores of FEV1 or FEV1/FVC) and the differences between the values of TLC or DLCO determined by the two different methods, whereby FEV1 or FEV1/FVC were tested separately due to their collinearity. A similar approach was followed with plethysmographic TLC as dependent variable. Adjusted R2 values and residual standard deviations (RSD) were used to quantify the accuracy of predictions. Groups were compared using the unpaired t-test, or analysis of variance (ANOVA) with post-hoc comparisons according to Duncan in case of more than two independent groups. Outcome values estimated in the same subject were compared using the paired t-test.

The concordance between variables was quantified by their normalized root mean square difference (NSD), defined as standard deviation of the individual differences between two variables divided by their mean value [17]. This is a measure of the residual error of estimation of one variable from another variable after removing their potential systematic difference (bias). The sample size was based on findings by Horstman et al. [5]. Following the aim to detect a difference of the magnitude of 50% of its standard deviation in three pairwise comparisons at a total alpha of 0.05 and a power of 0.95, at least 69 subjects were needed; due to the probably higher variability particularly in patients with severe COPD we aimed at a final size of n = 120. Statistical significance was assumed for a type I error of p < 0.05. All statistical analyses were performed using the package SPSS (Version 26, IBM, Armonk, NY, USA).


Study population

Data from 23 healthy subjects and 95 patients with COPD were available for analysis (Table 1). Subjects with airflow obstruction included all four GOLD grades; with more subjects with GOLD 1 and 2 compared to 3 and 4 (Table 1).

Table 1 Characteristics of the patients

Agreement between the duplicate assessments

The time between the duplicate assessments was at minimum 312 s, with a median (quartiles) of 342 (330; 363) seconds. The repeatability of DLCO from the duplicate measurements was high for both the TB and CS method, mean values (95%CI) of differences between 1st and 2nd assessments being -0.002 (-0.069; 0.065) and -0.008 (-0.070; -0.055) mmol*min-1*kPa-1, respectively. Similar repeatability was observed for TLC, mean values (95%CI) of differences being -0.010 (-0.049; 0.029) and -0.018 (-0.050, 0.014) L for the TB and the CS method, respectively. Therefore, the mean values of the duplicate assessments were used in all subsequent analyses.

Lung diffusing capacity for CO

The correlation between the values of DLCOTB and DLCOCS was high (r = 0.994; p < 0.001). To elucidate their relationship in detail, Fig. 2A shows a Bland–Altman plot of the difference of DLCOTB and DLCOCS versus their mean value. On average (± SD), DLCOTB was higher by 0.469 ± 0.267 (95%CI: 0.420; 0.517; p < 0.001) mmol*min-1*kPa-1 than DLCOCS. The difference was systematically offset and not a function of the magnitude of DLCO, as it was not correlated with the mean value. The NSD between both values was 4.3%.

Fig. 2
figure 2

Bland–Altman plots of the difference between DLCOTB and DLCOCS (Panel A) or TLCTB and TLCCS (Panel B) versus their respective mean values. There was no statistical relationship between the difference and the mean. The lines indicate a difference of zero, and the three groups of healthy control subjects and patients of GOLD grades 1/2 or 3/4 are indicated by different symbols and colors

Accounting for sex, age, height and BMI as covariates, the difference between DLCOTB and DLCOCS increased as the FEV1/FVC Z-Score decreased (adjusted R2 = 0.216, Fig. 3A, p < 0.001). A similar result was observed for the ratio of DLCOTB to DLCOCS (adjusted R2 = 0.423, Fig. 3B). Both associations were weaker in terms of adjusted R2, when using the Z-Score of FEV1, indicating the adequacy of FEV1/FVC as associated index of airway obstruction.

Fig. 3
figure 3

Relationship of the difference between DLCOTB and DLCOCS (panel A) and their ratio (panel B) to the Z-Score of FEV1/FVC. The horizontal lines indicate a ratio of one or a difference of zero, respectively, and the three groups of healthy control subjects and patients of GOLD grades 1/2 or 3/4 are indicated by different symbols and colors

Total lung capacity obtained via diffusing capacity manoeuvre

Over the whole range of values, the correlation between TLCTB and TLCCS was high (r = 0.953; p < 0.001). Figure 2B shows the results of Bland–Altman plots of the difference of TLCTB and TLCCS versus their mean value. Mean (± SD) TLCTB was higher by 0.495 ± 0.371 L than TLCCS (95%CI: 0.427; 0.562 L; p < 0.001). Their difference did not significantly correlate with their mean value, and the NSD was 6.7%.

Using sex, age, height and BMI as covariates, again the Z-Score of FEV1/FVC was found to be significantly associated with the difference between TLCTB and TLCCS (p < 0.001, adjusted R2 0.417) or their ratio (p < 0.001, adjusted R2 0.429) and being superior to the Z-Score of FEV1.

Relationship of TLC from single-breath test to TLC from body plethysmography

Both TLCCS and TLCTB were correlated with TLCbody (r = 0.709 and 0.824, respectively; p < 0.001 each). The mean (± SD) difference (95%CI) between TLCbody and TLCCS was 1.558 ± 0.940 (95%CI: 1.387; 1.739) L and between TLCbody and TLCTB 1.064 ± 0.740 (95%CI: 0.929; 1.199) L; for the differences in single groups see Table 1. The corresponding NSD values were 15.4% for TLCCS and 11.7% for TLCTB. Thus, TLCTB was closer to TLCbody than TLCCS.

We then elucidated the relationship between TLC values from gas dilution and plethysmography using regression analysis, assuming that their relationship depended on airway obstruction [18] choosing the Z-Scores of FEV1 or FEV1/FVC that should always be available in practice, in addition to sex, age, height, BMI as covariates. The dependent variables were the ratios or differences of TLCCS and TLCTB versus TLCbody. In terms of adjusted R2, the Z-Score of FEV1 turned out to be slightly superior to that of FEV1/FVC for all of these outcomes. Figure 4A shows the ratios TLCCS/TLCbody and TLCTB/TLCbody plotted against the Z-Score of FEV1, and Fig. 4B the respective differences.

Fig. 4
figure 4

Association between the FEV1 Z-Score, and either the ratio (panel A) or the difference (panel B) between TLCCS determined by the conventional method and TLCTB determined by the total-breath method, divided by TLCbody from body plethysmography. The two methods are indicated by different symbols (see insert) and collectively indicated by TLCdiffu on the vertical axes. The horizontal line indicates the value of one (panel A) or zero (panel B)

Using linear regression analysis with TLCTB as the only predictor, TLCbody could be estimated with a residual error of 0.720 L, which was reduced to 0.621 L by inclusion of the Z-Score of FEV1 (adjusted R2 0.676 and 0.756, respectively). Using TLCCS as predictor, the residual errors were 0.895 and 0.745 L, respectively (adjusted R2 0.499, 0.651). The NSD for the estimation of TLCbody from TLCTB and FEV1 Z-Score was 9.1%, for the estimation from TLCCS and FEV1 Z-Score 10.8%.


The recommended total-breath method for estimation of CO diffusing capacity (DLCO) and total lung capacity (TLC) resulted in higher values compared to the conventional analysis. The difference between estimates increased with the degree of spirometrically assessed airway obstruction in patients with COPD. Notably, total-breath TLC more closely agreed with TLC from body plethysmography; the latter could be estimated within less than 10% deviation, when taking into account the degree of airway obstruction.

In clinical practice, the single-breath manoeuvre is primarily performed to determine DLCO, while the assessment of VA, or equivalently TLC, is often secondary. The higher values of DLCO estimated using the TB method are relevant for at least two reasons. First, DLCO is a marker of parenchymal and/or pulmonary vascular dysfunction and airspace destruction, which typically occur in COPD and other lung diseases [1]. In contrast to computed tomography, DLCO has the advantage that it can be assessed repeatedly without radiation and is more affordable. However, in longitudinal analyses a change of method will require careful interpretation regarding comparability of values. Second, higher DLCO values using the TB method may require adaption of categorizations of clinical severity. As the ratio of DLCOCS to DLCOTB was close to one in healthy subjects (Fig. 3A, Table 1), mean predicted values may be kept but quantification of disease severity in COPD in terms of Z-Scores would be affected, if there should be differences in variance and consequently Z-Scores between the two methods; in contrast, grading in percent predicted might be less affected. In addition, further research is needed to reveal whether DLCOTB is superior to DLCOCS in showing better correlations with diagnostic features such as CT-based emphysema scores. No safety- or performance-related issues were observed with the TB method, as the changes solely referred to the mode of data evaluation.

Using the total-breath method, we found higher values for TLC, or equivalently VA, and DLCO. This raises the question to which extent the ratio of DLCO to VA, i.e. the transfer coefficient KCO, was affected. Its value, however, did not change, as the total-breath method altered VA and thereby DLCO by the same factor. The fact that KCO was not affected is relevant, as it is considered as valuable for the identification of causes underlying limitations of gas exchange capacity, in combination with DLCO [1, 2].

For the estimation of TLC via diffusion, the total volume was determined from helium dilution, taking into account the deadspace volume of the apparatus. In clinical practice, most often VA is chosen as volume parameter, requiring the assessment of anatomical deadspace. Moreover, the computation of DLCO involves VA and not TLC. Instead of a fixed deadspace volume of 150 mL, we used volumes computed from either body weight or height, depending on BMI, as previously recommended [4]. An additional analysis using a fixed value of 150 mL showed that, on average, the results regarding DLCO and VA were virtually unaffected by the choice of the method (data not shown). For optimal estimation of dilution, we used the concentration of helium measured in the exhaled air at the start of each test and separated all duplicate assessments by more than 5 min, in line with recommendations [4]. The validity of assessments was underscored by the fact that the duplicate values showed only very small and non-significant differences.

Compared with TLC from body plethysmography, TLCTB differed less than TLC obtained by the conventional method, especially in severe COPD (see Figs. 3 and 4). The difference between TB and plethysmographic TLC could be described as a function of the FEV1 Z-Score. The NSD values compared favourably with those reported for different methods providing estimates of plethysmographic TLC [17], including helium and nitrogen washout, CT, and a newly proposed plethysmographic method [17] that showed an NSD of 8–9% compared to standard body plethysmography. Taking NSD as a measure, our observations suggest that the TB method provides more accurate estimates of TLC than the conventional approach, especially in COPD, and that the accuracy is sufficient for clinical purposes.

Regarding plethysmographic TLC, we identified FEV1 as best parameter to describe the differences from TLC values obtained by the single-breath method. In a previous study [18], the method of multiple-breath helium dilution was used for comparison with VA assessed via single-breath dilution, and a computational method was described to derive estimates of multiple-breath TLC from single-breath VA. The difference between these values depended on airway obstruction quantified via the ratio FEV1/FVC, thereby underlining that spirometric indices can account for the differences between TLC estimates from different procedures. It remains to be assessed whether the ability of TB analysis to provide better estimates also has the potential to improve clinical interpretation and diagnostic insight from functional data.

The difference between plethysmographic and diffusion-based TLC approached a constant offset in healthy subjects with high FEV1 Z-scores (see Fig. 4B), which was in the range of 0.5 to 1.0 L. One might assume a homogeneous distribution of the tracer gas over the lungs in healthy subjects after deep inspiration, and thus only a small difference between plethysmographic and diffusion-based volumes, despite sampling errors [19]. As body plethysmographs are not subjected to the same strict requirements of comparability as commercial spirometers, the difference observed could also be due to a bias in the assessment of static lung volumes. For example, when comparing a plethysmograph of the brand that we used with that of another manufacturer, we previously found systematic differences of about 0.67 L in TLC in patients with COPD [20]. It is intriguing that in the study by O’Donnell and co-workers [21] body plethysmographic TLC appeared to be shifted upwards by about 0.5 to 1 L compared to CT-based values of TLC. Thus, potential differences between devices from different manufacturers have to be taken into account when comparing plethysmographic with diffusion-based TLC. As systematic differences between devices by different manufacturers might affect the interpretation of data in terms of predicted values, this topic seem worth of further examination.


The number of patients of GOLD grades 3 and 4 was smaller than that of grades 1 and 2. A higher number of grade 3 and 4 patients might have allowed a more detailed investigation of the factors that explain the difference between plethysmographic TLC and TLC assessed by the TB method, as well as the difference between DLCO values determined by conventional and TB method. On the other hand, this question would probably have benefitted more from additional information such as CT scans in these patients, which were not possible in this study. Such information might be suitable to explain part of the differences between the methods compared in this work. In addition, two of the healthy control subjects showed a Z-Score of less than -1.645 for FEV1/FVC. This was a percentage expected by chance, and we left these subjects in the group as we aimed to achieve a continuum of airway obstruction; their omission did not qualitatively change the results. We also considered the fact that the control group was much younger than the COPD group, as an advantage instead of a limitation, since we aimed to include a group for the comparison of the methods, in which optimal lung ventilation and thus minimal differences between parameters could be assumed. From a clinical point of view, the inclusion of patients with restrictive lung disorders or with asthma would have been of interest. Although these patients probably would show similar results as the healthy control subjects, unexpected findings might occur that could be informative for phenotyping. We do not know, whether the TB method is available in other devices than that used in the present study; if that is the case, such devices should be compared to warrant a standard. Moreover, the use of methane instead of helium as tracer gas might result in lower values of TLC particularly in patients with severe COPD and therefore increase the discrepancy from plethysmographic TLC. In addition, it might be helpful to assess TLCbody using equipment from different manufacturers, as there is no obligatory standardization regarding these devices.


The total-breath method for computing TLC and DLCO from a single-breath manoeuvre, as recommended by the 2017 ATS/ERS DLCO technical standard, yielded higher values of DLCO than the conventional analysis, particularly in subjects with COPD. Moreover, TLC values were higher and closer to those from body plethysmography. These could be predicted with an accuracy of less than 10%, especially after inclusion of FEV1 as additional variable. The observations suggest that the total-breath method yields more accurate values than the conventional method. Whether it additionally has the potential to improve clinical interpretation and provide novel diagnostic insight from functional data, remains to be studied.

Availability of data and materials

The authors can be contacted by qualified researchers to get access to the data presented in this work; for this purpose, either the first or the last author can be contacted.



American Thoracic Society


Carbon monoxide


Chronic obstructive pulmonary disease


Conventional sample

Δ :



Transfer factor for CO


European Respiratory Society

FEV1 :

Forced expiratory volume in 1 s


Forced vital capacity


Global Lung Function Initiative


Global Initiative for Chronic Obstructive Lung Disease


Transfer coefficient for CO


Normalized root mean square difference


Rapid gas analyzer


Standard deviation




Total lung capacity


Alveolar volume


  1. Neder JA, Berton DC, Muller PT, O’Donnell DE. Incorporating lung diffusing capacity for carbon monoxide in clinical decision making in chest medicine. Clin Chest Med. 2019;40(2):285–305.

    Article  PubMed  Google Scholar 

  2. Hughes JMB, Pride NB. Examination of the Carbon Monoxide Diffusing Capacity (D l CO ) in relation to Its K co and V a components. Am J Respir Crit Care Med. 2012;186(2):132–9.

    Article  PubMed  Google Scholar 

  3. Graham BL, Mink JT, Cotton DJ. Effect of breath-hold time on DLCO(SB) in patients with airway obstruction. J Appl Physiol. 1985;58(4):1319–25.

    Article  CAS  PubMed  Google Scholar 

  4. Graham BL, Brusasco V, Burgos F, et al. 2017 ERS/ATS standards for single-breath carbon monoxide uptake in the lung. Eur Respir J. 2017;49(1):1600016.

    Article  PubMed  Google Scholar 

  5. Horstman MJM, Mertens FW, Schotborg D, Hoogsteden HC, Stam H. Comparison of total-breath and single-breath diffusing capacity in healthy volunteers and COPD patients. Chest. 2007;131(1):237–44.

    Article  PubMed  Google Scholar 

  6. Brusasco V, Barisione G, Crimi E. Pulmonary physiology: Future directions for lung function testing in COPD: Lung physiology in COPD. Respirology. 2015;20(2):209–18.

    Article  PubMed  Google Scholar 

  7. Pisi R, Aiello M, Calzetta L, et al. Ventilation heterogeneity in asthma and COPD: the value of the poorly communicating fraction as the ratio of total lung capacity to alveolar volume. Respiration. 2021;100(5):404–10.

    Article  PubMed  Google Scholar 

  8. GOLD I. GOLD Report 2022. 2022.

    Google Scholar 

  9. Graham BL, Steenbruggen I, Miller MR, et al. Standardization of spirometry 2019 update. Am J Respir Crit Care Med. 2019;200(8):e70–88.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Quanjer PH, Stanojevic S, Cole TJ, et al. Multi-ethnic reference values for spirometry for the 3–95-yr age range: the global lung function 2012 equations. Eur Respir J. 2012;40(6):1324–43.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Jensen RL, Crapo RO. diffusing capacity: how to get it right. Respir CARE. 2003;48(8):6.

    Google Scholar 

  12. Gochicoa-Rangel L, Pérez-Padilla R, Vázquez-García JC, et al. Long-term stability of a portable carbon monoxide single-breath diffusing capacity instrument. Respir Care. 2017;62(2):231–5.

    Article  PubMed  Google Scholar 

  13. Balasubramanian A, MacIntyre NR, Henderson RJ, et al. Diffusing capacity of carbon monoxide in assessment of COPD. Chest. 2019;156(6):1111–9.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Criner RN, Hatt CR, Galbán CJ, et al. Relationship between diffusion capacity and small airway abnormality in COPDGene. Respir Res. 2019;20(1):269.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Sakornsakolpat P, McCormack M, Bakke P, et al. Genome-wide association analysis of single-breath D l CO. Am J Respir Cell Mol Biol. 2019;60(5):523–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Stanojevic S, Graham BL, Cooper BG, et al. Official ERS technical standards: global lung function initiative reference values for the carbon monoxide transfer factor for Caucasians. Eur Respir J. 2017;50(3):1700010.

    Article  PubMed  Google Scholar 

  17. Berger KI, Adam O, Dal Negro RW, et al. Validation of a novel compact system for the measurement of lung volumes. Chest. 2021;159(6):2356–65.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Punjabi NM, Shade D, Wise RA. Correction of single-breath helium lung volumes in patients with airflow obstruction. Chest. 1998;114(3):907–18.

    Article  CAS  PubMed  Google Scholar 

  19. Thompson BR, Kim Prisk G, Peyton P, Pierce RJ, Rochford PD. Inhomogeneity of ventilation leads to unpredictable errors in measured DLCO. Respir Physiol Neurobiol. 2005;146(2–3):205–14.

    Article  PubMed  Google Scholar 

  20. Alter P, Orszag J, Wouters E, Vogelmeier C, Jörres RA. Differences in the measurement of functional residual capacity between body plethysmographs of two manufacturers. Int J Chron Obstruct Pulmon Dis. 2022;17:1477.

    Article  PubMed  PubMed Central  Google Scholar 

  21. O’Donnell CR, Bankier AA, Stiebellehner L, Reilly JJ, Brown R, Loring SH. Comparison of plethysmographic and helium dilution lung volumes. Chest. 2010;137(5):1108–15.

    Article  PubMed  Google Scholar 

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We would like to thank the Clinical Trial Unit (CTU) of the Hirslanden Clinic Zurich for the support provided in this study.


The study was funded by ndd Medical Technologies, Technopark Zurich, Zurich, Switzerland.

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Authors and Affiliations



CB: Writing and revision of the manuscript, assessments, data analysis, design of the study; AP: Revision of the manuscript, assessments, design of the study; HM: Writing and revision of the manuscript, design of the study; BT: Writing and revision of the manuscript; SS: Writing and revision of the manuscript; RAJ: Writing and revision of the manuscript, data analysis. All authors reviewed the manuscript.

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Correspondence to Rudolf A. Jörres.

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Ethics approval and consent to participate

The study protocol ( NCT04531293, first trial registration 28/08/2020) was approved by the local ethics committee (Kantonale Ethikkommission Zürich (Cantonal Ethics Committee Zurich), BASEC 2020–02139), and all participants gave their written informed consent. All experiments were performed in accordance with relevant guidelines and regulations, in particular the Declaration of Helsinki.

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Not applicable.

Competing interests

Research support: Christian Buess, employee of ndd reports financial support, administrative support, article publishing charges, and equipment, drugs, or supplies were provided by ndd Switzerland

Relationships: Christian Buess reports a relationship with ndd Switzerland that includes: employment.

Patents and Intellectual Property: There are not patents to disclose.

Other Activities: Helgo Magnussen received compensation for medical advice until 2022. Bruce Thompson and Sanja Stanojevic are members of the Advisory Board of ndd that has been created in 2023. Rudolf A. Jörres and Andreas Piecyk have nothing to disclose.

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Jörres, R.A., Buess, C., Piecyk, A. et al. The total-breath method yields higher values of DLCO and TLC than the conventional method. BMC Pulm Med 24, 127 (2024).

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