Accurate real-time FENO expirograms using complementary optical sensors

• Published in: Journal of breath research Vol. 14; no. 4; p. 047102
• Main Authors: Petralia, Lorenzo S, Bahl, Anisha, Peverall, Rob, Richmond, Graham, Couper, John H, Hancock, Gus, Robbins, Peter A, Ritchie, Grant A D
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.10.2020
• Subjects: Airway management; asthma; Biomarkers; CEAS; laser spectroscopy; Nitric oxide; Spectrum analysis; two-compartment model
• ISSN: 1752-7155; 1752-7163
• DOI: 10.1088/1752-7163/ab9c31

The fraction of exhaled nitric oxide (FENO) is an important biomarker for the diagnosis and management of asthma and other pulmonary diseases associated with airway inflammation. In this study we report on a novel method for accurate, highly time-resolved, real time detection of FENO at the mouth. The experimental arrangement is based on a combination of optical sensors for the determination of the temporal profile of exhaled NO and CO2 concentrations. Breath CO2 and exhalation flow are measured at the mouth using diode laser absorption spectroscopy (at 2 μm) and differential pressure sensing, respectively. NO is determined in a sidestream configuration using a quantum cascade laser based, cavity-enhanced absorption cell (at 5.2 μm) which simultaneously measures sidestream CO2. The at-mouth and sidestream CO2 measurements are used to enable the deconvolution of the sidestream NO measurement back to the at-mouth location. All measurements have a time resolution of 0.1 s, limited by the requirement of a reasonable limit of detection for the NO measurement, which on this timescale is 4.7 ppb (2 σ). Using this methodology, NO expirograms (FENOgrams) were measured and compared for eight healthy volunteers. The FENOgrams appear to differ qualitatively between individuals and the hope is that the dynamic information encoded in these FENOgrams will provide valuable additional insight into the location of the inflammation in the airways and potentially predict a response to therapy. A validation of the measurements at low-time resolution is provided by checking that results from previous studies that used a two-compartment model of NO production can be reproduced using our technology.