In the search for new non-invasive diagnostic methods, healthcare researchers have turned their attention to exhaled human breath. Breath consists of thousands of molecular compounds in very low concentrations, in the order of parts per million by volume (ppm_v), parts per billion by volume (ppb_v) and parts per trillion by volume (ppt_v). They are the result of the different biological process taking place inside the body. When a disease is present the production of specific molecules is altered. In this work in particular, we investigate two cases. One being the concentration of acetone on minors with type 1 diabetes (T1D). In the second case we compare the breath of three groups to establish
significant differences and to identify relevant molecules. The groups under study are healthy children, children with asthma and children with cystic fibrosis (CF). 
The main challenges in human breath research are the detection of concentration changes in small quantities and the establishment of a direct relation between specific molecules and particular diseases. We use quantum cascade lasers (QCLs), a multipass cell and Mercury Cadmium Telluride (MCT) detectors to study the absorption of the molecular components of breath. We improve the identification of molecules by applying a multiline fitting algorithm. 
The different molecules present in breath have a strong absorption signature in the mid-infrared. For this reason we use QCLs emitting in the region between 832 and 1262.55 cm^-1. In this region each molecular species has a unique absorption fingerprint that allows its identification. The absorption is magnified by increasing the interaction distance between the light of the QCLs and the gas sample. We use a multipass cell with two astigmatic mirrors. The multiple reflections in the mirrors provide an effective interaction distance of 54.36 meters inside a volume of only 0.6 liters. For the detection we use MCT detectors directly because the QCLs emit a very specific wavenumber at a time. The absorption spectra are built by scanning the wavenumber of the QCLs twice: first with the multipass cell empty, to build a reference, and then with the breath sample to measure the absorption. 
The scan of the QCLs eliminates the need of extra elements to separate the wavenumbers to build the absorption spectra. However, scanning over a broad wavenumber region introduces a new challenge: to guarantee its repeatability. This includes the assurance that the QCLs emit the same wavenumbers with the same intensities in every single scan. Only by minimizing the variability between independent scans we can create reliable absorption spectra and improve the sensitivity of the setup. We use two MCT detectors to monitor the intensity fluctuations. One detector is dedicated to monitor the intensity fluctuations of the QCLs while the other detector measures the intensity of the QCLs after the light has crossed the multipass cell. The variation of the wavenumber emission produces that independent scans are warped and uncorrelated with respect to each other. We implement two methods to correlate the measurements taken with the empty multipass cell and the measurements with the breath samples: a scan correlation using selected wavenumbers and a scan correlation using semiparametric time warping. Both methods are successful in obtaining a meaningful absorption spectrum. The selection of wavenumbers is more adequate to study molecules with a smooth profile and the semiparametric time warping method is more suitable for molecules with sharp absorption features. The result of the wavenumber and intensity corrections give the system a noise equivalent absorption sensitivity (NEAS) of 2.99×10⁻⁷cm⁻¹Hz^−1/2. With this NEAS we can detect ppb_v concentrations of acetone in presence of 2% of water in the same wavenumber region. The complexity of the gas mixture in breath makes the identification of specific molecular components difficult. We implement a multiline fitting algorithm to analyze specific molecules and determine their concentrations. We use this method to study the concentration of acetone and methane in the exhaled breath of healthy children. For acetone we use its absorption signature in the 1150 - 1250 cm^-1 region. Our results show that the production of acetone in healthy children is below the standard range established for healthy adults, between 0.39 and 1.09 ppm_v. But the information and studies in this regard are limited and therefore more studies should be performed. In the case of methane we use its absorption fingerprint between 1258 and 1262.5 cm^-1. The methane concentration in the breath of the participants is below 1 ppm_v, which classifies them as non-producers. Given the small number of participants, eleven, this result is in accordance with previous reports establishing that only 10% to 20% of the children are methane producers. We perform a specific study to investigate the acetone concentration in the exhaled breath of T1D patients. We analyze the breath of two minors and one adult T1D patient, and the breath of one healthy volunteer. Simultaneously, we measure the blood glucose and ketone concentrations in blood to inspect their relation with acetone in exhaled breath. For each volunteer, we performed a series of measurements over a period of time, including overnight fasting of 11 ± 1 hours and during ketosis-hyperglycemia events for the minors. The results highlight the importance of performing personalized studies because the response of the minors to the presence of ketosis was consistent but unique for each individual. As in the case of healthy children mentioned above, we also find that the acetone concentration in the breath of T1D minors in stable conditions is lower than the standard range for healthy adults. This emphasizes the need to perform more studies with children and specifically with T1D minors. We strongly believe that a better understanding of the production of acetone in exhaled breath can help to develop new diagnostic methods. For example, it can be used to detect chronic ketosis, which is a condition that many children present in the early stages of T1D. In many cases children live with chronic ketosis for years before being diagnosed with T1D. By detecting abnormal concentrations of acetone we can help to diagnose T1D earlier. In a separate study we explore the clinical applicability of our spectroscopic setup by comparing the exhaled breath of 35 healthy children, 39 children with stable asthma and 15 with stable CF. Their age range is 6 – 18 years. We collect two to four exhaled breath samples in Tedlar bags and obtain their absorption spectrum in the region between 832 and 1262.55 cm^-1. The results show a poor repeatability (Spearman’s ρ = 0.36 to 0.46) and agreement of the complete profiles. However, we identify wavenumber regions where the profiles are significantly different. Using these regions and the information from two molecular databases we present a list of molecules that can be used to discriminate between healthy children and children with asthma or CF. Our suggestion is to perform more studies and use the identified molecules as basis to understand the underlying inflammatory processes of asthma and CF. This study shows that the identification of the molecular components of exhaled breath is important and may be useful to develop new personalized treatments. Because scientists like to dream about the future, we also explore the future possibilities in exhaled breath research. We strongly believe the next generation of exhaled breath systems will be a hybrid between optical detection systems, electrochemical methods and nanotechnology. This idea is firmly supported by the latest developments in small hollow waveguides for lasers and the most advanced pre-concentration and filtering methods for gas samples. Furthermore, the growing interest in new, non-invasive medical systems is making exhaled breath research a very important player in the global economy. We cannot foresee all the benefits exhaled breath research can offer to society but without doubt its value is immense.@en

Exhaled breath analysis is a potential non-invasive tool for diagnosing and monitoring airway diseases. Gas chromatography-mass spectrometry and electrochemical sensor arrays are the main techniques to detect volatile organic compounds (VOC) in exhaled breath. We developed a broadband quantum cascade laser spectroscopy technique for VOC detection and identification. The objective of this study was to assess the repeatability of exhaled breath profiling with broadband quantum cascade laser-based spectroscopy and to explore the clinical applicability by comparing exhaled breath samples from healthy children with those from children with asthma or cystic fibrosis (CF). Healthy children and children with stable asthma or stable CF, aged 6-18 years, were included. Two to four exhaled breath samples were collected in Tedlar bags and analyzed by quantum cascade laser spectroscopy to detect VOCs with an absorption profile in the wavenumber region between 832 and 1262.55 cm^-1. We included 35 healthy children, 39 children with asthma and 15 with CF. Exhaled breath VOC profiles showed poor repeatability (Spearman's rho = 0.36 to 0.46) and agreement of the complete profiles. However, we were able to discriminate healthy children from children with stable asthma or stable CF and identified VOCs that were responsible for this discrimination. Broadband quantum cascade laser-based spectroscopy detected differences in VOC profiles in exhaled breath samples between healthy children and children with asthma or CF. The combination of a relatively easy and fast method and the possibility of molecule identification makes broadband quantum cascade laser-based spectroscopy attractive to investigate the diagnostic and prognostic potential of volatiles in exhaled breath.

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