Novel measure of lung function for assessing disease activity in asthma

The Lognormal Lung: A new approach to quantifying lung inhomogeneity in COPD

Early diagnosis and disease phenotyping in COPD are currently limited by the use of spirometry, which may remain normal despite significant small-airways disease and which may not fully capture a patient’s underlying pathophysiology. In this study we explored the use of a new non-invasive technique that assesses gas-exchange inhomogeneity in patients with COPD of varying disease severity (according to GOLD Stage), compared with age-matched healthy controls. The technique, which combines highly accurate measurement of respiratory gas exchange using a bespoke molecular flow sensor and a mechanistic mathematical model of the lung, provides new indices of lung function: the parameters σCL, σCd, and σVD represent the standard deviations of distributions for alveolar compliance, anatomical deadspace and vascular conductance relative to lung volume, respectively. It also provides parameter estimates for total anatomical deadspace and functional residual capacity (FRC). We demonstrate that these parameters are robust and sensitive, and that they can distinguish between healthy individuals and those with mild-moderate COPD (stage 1–2), as well as distinguish between mild-moderate COPD (stage 1–2) and more severe (stage 3–4) COPD. In particular, σCL, a measure of unevenness in lung inflation/deflation, could represent a more sensitive non-invasive marker of early or mild COPD. In addition, by providing a multi-dimensional assessment of lung physiology, this technique may also give insight into the underlying pathophysiological phenotype for individual patients. These preliminary results warrant further investigation in larger clinical research studies, including interventional trials.

Accurate real-time FENO expirograms using complementary optical sensors

The fraction of exhaled nitric oxide (F_ENO) 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 F_ENO 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 (F_ENOgrams) were measured and compared for eight healthy volunteers. The F_ENOgrams appear to differ qualitatively between individuals and the hope is that the dynamic information encoded in these F_ENOgrams 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.