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Modeling pulmonary gas exchange and single-exhalation profiles of carbon monoxide
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Applied Laser Spectroscopy)
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. (Applied Laser Spectroscopy, TEC-Lab)ORCID iD: 0000-0002-5065-7786
2018 (English)In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, article id 927Article in journal (Refereed) Published
Abstract [en]

Exhaled breath carbon monoxide (eCO) is a candidate biomarker for non-invasive assessment of oxidative stress and respiratory diseases. Standard end-tidal CO analysis, however, cannot distinguish, whether eCO reflects endogenous CO production, lung diffusion properties or exogenous sources, and is unable to resolve a potential airway contribution. Coupling real-time breath gas analysis to pulmonary gas exchange modeling holds promise to improve the diagnostic value of eCO. A trumpet model with axial diffusion (TMAD) is used to simulate the dynamics of CO gas exchange in the respiratory system and corresponding eCO concentrations for the first time. The mass balance equation is numerically solved employing a computationally inexpensive routine implementing the method of lines, which provides the distribution of CO in the respiratory tract during inhalation, breath-holding and exhalation with 1 mm spatial and 0.01 s temporal resolution. Initial estimates of the main TMAD parameters, the maximum CO fluxes and diffusing capacities in alveoli and airways, are obtained using healthy population tissue, blood and anatomical data. To verify the model, mouth-exhaled expirograms from two healthy subjects, measured with a novel, home-built laser-based CO sensor, are compared to single-exhalation profiles simulated using actual breath sampling data, such as exhalation flow rate (EFR) and volume. A very good agreement is obtained in exhalation phases I and III for EFRs between 55 and 220 ml/s and after 10 s and 20 s of breath-holding, yielding a unique set of TMAD parameters. The results confirm the recently observed EFR dependence of CO expirograms and suggest that measured end-tidal eCO is always lower than alveolar and capillary CO. Breath-holding allows the observation of close-to-alveolar CO concentrations and increases the sensitivity to the airway TMAD parameters in exhalation phase I. A parametric simulation study shows that a small increase in airway flux can be distinguished from an increase in alveolar flux, and that slight changes in alveolar flux and diffusing capacity have a significantly different effect on phase III of the eCO profiles.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2018. Vol. 9, article id 927
Keywords [en]
carbon monoxide (CO), pulmonary gas exchange, computational modeling, real-time breath gas analysis, single-exhalation profile, laser absorption spectroscopy
National Category
Physiology Bioinformatics (Computational Biology) Atom and Molecular Physics and Optics
Identifiers
URN: urn:nbn:se:umu:diva-150270DOI: 10.3389/fphys.2018.00927ISI: 000440204000001OAI: oai:DiVA.org:umu-150270DiVA, id: diva2:1236192
Available from: 2018-07-31 Created: 2018-07-31 Last updated: 2018-11-01Bibliographically approved
In thesis
1. Real-time breath gas analysis of carbon monoxide: laser-based detection and pulmonary gas exchange modeling
Open this publication in new window or tab >>Real-time breath gas analysis of carbon monoxide: laser-based detection and pulmonary gas exchange modeling
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Realtidsanalys av kolmonoxid i utandningsluften : detektion med laserspektroskopi och modellering av gasutbytet i lungorna
Abstract [en]

Breath gas analysis is a promising approach for non-invasive medical diagnostics and physiological monitoring. Real-time, breath-cycle resolved biomarker detection facilitates data interpretation and has the potential to improve the diagnostic value of breath tests as exhalation profiles carry spatiotemporal information about biomarker origin and gas exchange in the respiratory tract. This thesis presents and scrutinizes a novel methodology for the analysis of real-time breath data, where single-exhalation profiles are simulated using a pulmonary gas exchange model and least-squares fitted to measured expirograms to extract airway and alveolar contributions and diffusing capacities. The methodology is demonstrated on exhaled breath carbon monoxide (eCO), a candidate biomarker for oxidative stress and respiratory diseases. The thesis mainly covers (1) the construction of a compact optical sensor based on tunable diode laser absorption spectroscopy (TDLAS) in the mid-infrared region (4.7 μm) for selective and precise real-time detection of CO in breath and ambient air (detection limit 9 ± 5 ppb at 0.1 s), (2) the design of an advanced online breath sampling system, (3) the implementation of a trumpet model with axial diffusion (TMAD) to simulate the CO gas exchange, and (4) the application of extended eCO analysis in clinical studies to establish the healthy non-smoker baseline of the eCO parameters and to study the response to CO and wood smoke exposure. It is shown that the TMAD adequately describes the gas exchange during systemic CO elimination for different breathing patterns, and that there is no difference between eCO parameters from mouth- and nose exhalations. Expirogram shape and eCO parameters exhibit a dependence on the exhalation flow rate, but for a given breathing maneuverer, the parameters lie in a narrow range. Airway CO is close to and correlates with ambient air CO, indicating negligible airway production in the healthy population. The alveolar diffusing capacity is independent of endogenous CO, even after exposure to elevated exogenous CO, and could be used to assess lung diffusion abnormalities. Compared to CO exposure, no clear additional effect of exposure to wood smoke particles on eCO is observed. The discrimination between endogenous and exogenous CO sources remains a challenge.

Abstract [sv]

Detektion av spårgaser i utandningsluften har stor potential för icke-invasiv medicinsk diagnostik och fysiologisk övervakning. Realtid andningsgasanalys av enskilda andningscykler underlättar datatolkningen och kan förbättra det diagnostiska värdet av andningstester, eftersom utandningsprofiler bär spatiotemporal information om biomarkörens ursprung och gasutbyte i andningssystemet. Denna avhandling presenterar och granskar en ny analysmetod, där utandningsprofiler simuleras med hjälp av en matematisk modell för gasutbytet, och anpassas till uppmätta expirogram för att bestämma luftvägs- och alveolära bidrag och diffusionsförmågor. Metoden demonstreras på utandad kolmonoxid (eCO), en potentiell biomarkör för oxidativ stress och respiratoriska sjukdomar. Avhandlingen omfattar huvudsakligen (1) konstruktionen av en kompakt optisk sensor baserat på mid-infraröd diodlaserabsorptionsspektroskopi (TDLAS) vid 4.7 μm för selektiv och precis realtidsmätning av CO i utandnings- och omgivningsluften (detektionsgräns 9 ± 5 ppb vid 0.1 s), (2) design av ett avancerat system för online provtagning, (3) adaption av en matematisk lungmodell med axiell diffusion (TMAD) för simulation av CO gasutbytet, och (4) tillämpningen av utökad eCO analys i kliniska studier för att fastställa baslinjen för eCO parametrarna i friska icke-rökare, och för att studera effekten av exponering för CO och trärök. Det visas att modellen väl beskriver gasutbytet under systemiskt CO utsläpp för olika andningsmönster, och att det inte finns någon skillnad mellan eCO parametrarna från utandning via mun och näsa. Utandningsprofilerna och eCO parametrarna ändras beroende på utandningsflödet, men för ett visst andningsmönstret ligger parametrarna i ett smalt område. Koncentrationen av CO i luftvägarna ligger nära och korrelerar med CO i omgivningsluften, vilket indikerar att CO produktionen i luftvägarna är försumbart hos den friska befolkningen. Den alveolär diffusionsförmågan är oberoende av endogen CO, även efter exponering för förhöjd exogen CO, och kan möjligtvis användas för att diagnosticera en nedsatt diffusionsförmåga. Jämfört med exponering för CO observeras ingen tydlig ytterligare effekt av exponering för trärökpartiklar. Att åtskilja endogena och exogena eCO källor förbli en utmaning.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2018. p. 95
Keywords
carbon monoxide (CO), pulmonary gas exchange, computational modeling, real-time breath gas analysis, single-exhalation profile, laser absorption spectroscopy, nonlinear least-squares fitting, breath sampling, baseline level, diurnal variation, healthy population, exposure study
National Category
Physiology Bioinformatics (Computational Biology) Atom and Molecular Physics and Optics Medical Laboratory and Measurements Technologies
Research subject
Physics; Physiology
Identifiers
urn:nbn:se:umu:diva-152099 (URN)978-91-7601-930-6 (ISBN)
Public defence
2018-10-19, Lilla hörsalen KBE301, KBC-huset, Umeå, 09:00 (English)
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Supervisors
Available from: 2018-09-28 Created: 2018-09-26 Last updated: 2018-10-18Bibliographically approved

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