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The bedside Exhaled Drug MONitor – EDMON measures exhaled propofol in ppbv every minute based on multi-capillary column – ion mobility spectrometry (MCC-IMS). The MCC pre-separates gas samples, thereby reducing the influence of the high humidity in human breath. However, preliminary analyses identified substantial measurement deviations between dry and humid calibration standards. We therefore performed an analytical validation of the EDMON to evaluate the influence of humidity on measurement performance. A calibration gas generator was used to generate gaseous propofol standards measured by an EDMON device to assess linearity, precision, carry-over, resolution, and the influence of different levels of humidity at 100% and 1.7% (without additional) relative humidity (reference temperature: 37°C). EDMON measurements were roughly half the actual concentration without additional humidity and roughly halved again at 100% relative humidity. Standard concentrations and EDMON values correlated linearly at 100% relative humidity (R²=0.97). The measured values were stable over 100min with a variance ≤ 10% in over 96% of the measurements. Carry-over effects were low with 5% at 100% relative humidity after 5min of equilibration. EDMON measurement resolution at 100% relative humidity was 0.4 and 0.6 ppbv for standard concentrations of 3 ppbv and 41 ppbv. The influence of humidity on measurement performance was best described by a second-order polynomial function (R²≥0.99) with influence reaching a maximum at about 70% relative humidity. We conclude that EDMON measurements are strongly influenced by humidity and should therefore be corrected for sample humidity to obtain accurate estimates of exhaled propofol concentrations.

BACKGROUND Volatile anesthetics potentially trigger malignant hyperthermia crises in susceptible patients. We therefore aimed to identify preparation procedures for the Draeger Primus that minimize residual concentrations of desflurane and sevoflurane with and without activated charcoal filtration. METHODS A Draeger Primus test workstation was primed with 7% desflurane or 2.5% sevoflurane for 2 hours. Residual anesthetic concentrations were evaluated with five preparation procedures, three fresh gas flow rates, and three distinct applications of activated charcoal filters. Finally, non-exchangeable and autoclaved parts of the workstation were tested for residual emission of volatile anesthetics. Concentrations were measured by multicapillary column-ion mobility spectrometry with limits of detection/quantification being

Exhaled aliphatic aldehydes were proposed as non-invasive biomarkers to detect increased lipid peroxidation in various diseases. As a prelude to clinical application of the multicapillary column–ion mobility spectrometry for the evaluation of aldehyde exhalation, we, therefore: (1) identified the most abundant volatile aliphatic aldehydes originating from in vitro oxidation of various polyunsaturated fatty acids, (2) evaluated emittance of aldehydes from plastic parts of the breathing circuit, (3) conducted a pilot study for in vivo quantification of exhaled aldehydes in mechanically ventilated patients. Pentanal, hexanal, heptanal, and nonanal were quantifiable in the headspace of oxidizing polyunsaturated fatty acids, with pentanal and hexanal predominating. Plastic parts of the breathing circuit emitted hexanal, octanal, nonanal, and decanal, whereby nonanal and decanal were ubiquitous and pentanal or heptanal not being detected. Only pentanal was quantifiable in breath of mechanically ventilated surgical patients with a mean exhaled concentration of 13 ± 5 ppb. An explorative analysis suggested that pentanal exhalation is associated with mechanical power—a measure for the invasiveness of mechanical ventilation. In conclusion, exhaled pentanal is a promising non-invasive biomarker for lipid peroxidation inducing pathologies, and should be evaluated in future clinical studies, particularly for detection of lung injury.

Systemic inflammation alters the composition of exhaled breath, possibly helping clinicians diagnose conditions such as sepsis. We therefore evaluated changes in exhaled breath of rats given tumor necrosis factor-alpha (TNF-&alpha, ). Thirty male Sprague-Dawley rats were randomly assigned to three groups (n = 10 each) with intravenous injections of normal saline (control), 200 &micro, g&middot, kg&minus, 1 bodyweight TNF-&alpha, (TNF-&alpha, 200), or 600 &micro, 600), and were observed for 24 h or until death. Animals were ventilated with highly-purified synthetic air to analyze exhaled air by multicapillary column&ndash, ion mobility spectrometry. Volatile organic compounds (VOCs) were identified from a database. We recorded blood pressure and cardiac output, along with cytokine plasma concentrations. Control rats survived the 24 h observation period, whereas mean survival time decreased to 22 h for TNF-&alpha, 200 and 23 h for TNF-&alpha, 600 rats. Mean arterial pressure decreased in TNF-&alpha, groups, whereas IL-6 increased, consistent with mild to moderate inflammation. Hundreds of VOCs were detected in exhalome. P-cymol increased by a factor-of-two 4 h after injection of TNF-&alpha, 600 compared to the control and TNF-&alpha, 200. We found that 1-butanol and 1-pentanol increased in both TNF-&alpha, groups after 20 h compared to the control. As breath analysis distinguishes between two doses of TNF-&alpha, and none, we conclude that it might help clinicians identify systemic inflammation.

Die Atemluft eines Menschen zu diagnostischen Zwecken zu analysieren, hat verschiedene Vorteile gegenüber anderen Methoden, wie beispielsweise Untersuchungen des Blutes. Die Atemluft ist stets verfügbar und ihre Gewinnung ist sicher, da kein Eingriff in den Körper notwendig ist. Wird zur Analyse der Atemluft die Multikapillarsäulen-Ionenmobilitätspektrometrie (MCC-IMS) verwendet, so ist die Messung innerhalb weniger Minuten abgeschlossen und könnte theoretisch direkt ausgewertet werden. Damit dies möglich wird, müssen die entstehenden Rohmessungen jedoch automatisch verarbeitet werden. Dies geschieht im Augenblick noch durch eine manuelle Begutachtung der Rohmessungen. Um diesen Goldstandard durch automatische Verfahren ersetzen zu können, wurden in dieser Arbeit zahlreiche Algorithmen-Kombinationen getestet. Da es in der Atemluftanalyse häufig das Ziel ist, kranke und gesunde Personen voneinander zu unterscheiden, wurden die Methoden auf drei verschiedene entsprechende Datensätze angewendet und zusätzlich verschiedene Klassifikationsalgorithmen getestet. Eine automatische Algorithmenkombination, die gute Ergebnisse für die einzelnen Analyseschritte erzielt, wurde für den zukünftigen Einsatz empfohlen. Der zweite Abschnitt der Arbeit beschäftigte sich mit Einflussfaktoren auf die Atemluft bei MCC-IMS-Messungen. Dabei wurden die Effekte des Geschlechts, des Raucherstatus, Beeinflussung durch ein Nahrungsmittel und der Einfluss des verwendeten Gerätes untersucht. Insbesondere die Messungen der beiden untersuchten Geräte wiesen deutliche Unterschiede auf. Diese wurden in der Arbeit ausführlich untersucht und Ansätze zur Lösung des Problems vorgestellt.

We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related volatile organic compounds (VOCs). Since the amount of these compounds varies with health status, breathomics holds great promise to deliver non-invasive diagnostic tools. Thus, the main aim of breathomics is to find patterns of VOCs related to abnormal (for instance inflammatory) metabolic processes occurring in the human body. Recently, analytical methods for measuring VOCs in exhaled air with high resolution and high throughput have been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start with the detailed pre-processing pipelines for breathomics data obtained from gas-chromatography mass spectrometry and an ion-mobility spectrometer coupled to multi-capillary columns. The outcome of data pre-processing is a matrix containing the relative abundances of a set of VOCs for a group of patients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus of this paper. We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the community to understand how to profit from a particular method. In parallel, we hope to make the community aware of the existing data fusion methods, as yet unresearched in breathomics.

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica Associadas ao aumento crescente da obesidade mundial encontram-se diversas patologias tais como a diabetes mellitus, a hipertensão, a resistência insulínica, a disfunção endotelial e, em último caso, doenças cardiovasculares. À problemática destas doenças para a saúde da população acrescem-se ainda os custos financeiros associados ao diagnóstico e tratamento das mesmas e ainda o desconforto para o próprio paciente. Actualmente, a avaliação destas patologias é feita através da análise de matrizes biológicas recolhidas com recurso a métodos invasivos. Assim sendo, este trabalho teve como objectivo estudo e desenvolvimento de uma técnica não-invasiva, mais rápida, de baixo custo e indolor para o paciente que servirá para uma futura avaliação de diversas patologias através da análise de metabolitos voláteis presentes no fluido lacrimal através da técnica de Espectrometria de Mobilidade Iónica acoplada a uma coluna multicapilar (MCC-IMS). O presente estudo foi efectuado como “prova de conceito”, uma vez que se trata de um estudo pioneiro a nível internacional. Para tal, foi desenvolvido o protocolo e efectuada a recolha da lágrima de 9 indivíduos com patologia e 9 de controlo. Após a recolha, foi realizada uma análise dos compostos orgânicos voláteis (VOCs) presentes na lágrima servindo as amostras para avaliação da eficácia do método em estudo. Com o objectivo da familiarização com a técnica foi, inicialmente, realizado um workshop teórico-prático intitulado “Introdução à Espectrometria de Mobilidade Iónica no contexto de análise de ar exalado”. Este trabalho foi realizado em colaboração com a Faculdade de Ciências e Tecnologia da UNL, Faculdade de Ciências Médicas da UNL e NMT, S.A. Os resultados foram apresentados numa comunicação em painel na conferência iMed 4.0 na FCM/UNL. Esta tese originou um artigo aceite para publicação e apresentação oral na conferência Biostec 2013 e está também em preparação um artigo a submeter para publicação no International Journal of Ion Mobility Spectrometry.

Recentemente, a técnica de Espectrometria de Mobilidade Iónica associada a uma coluna multicapilar (MCC-IMS) tem sido aplicada à análise do ar exalado dos seres humanos. O ar que é expelido na respiração contém compostos orgânicos voláteis (VOCs) que possuem informação importante relativa ao estado metabólico do sujeito. Existem inúmeras vantagens na utilização desta tecnologia relativamente às técnicas de rastreio através do sangue, designadamente o facto de ser um processo não doloroso, não invasivo e a recolha de amostras não necessita de ser efectuada por pessoal médico especializado. Esta técnica está a ser desenvolvida com progressos no diagnóstico precoce do cancro do pulmão (entre outros) ou da doença pulmonar obstrutiva crónica (DPOC), e também para controlo da medicação ou na fase terapêutica. Esta técnica é utilizada para detetar analitos em matrizes voláteis através da sua mobilidade iónica e combina alta sensibilidade através de um limite de deteção da ordem dos baixos ppbv [ng/L], com baixos custos de manutenção. O principal objectivo do trabalho desenvolvido nesta dissertação foi a projecção e implementação de uma interface gráfica que permita a detecção automática dos picos presentes nos espectros 3D de MCC-IMS. Para esta finalidade foi implementado um algoritmo que permite obter a informação acerca da posição e intensidade dos máximos de cada pico. A identificação automática de compostos relativos a cada pico detectado foi igualmente implementada através da ligação à base de dados existente, passível de ser aumentada no decorrer das medições experimentais. Além disso, foi desenvolvida uma ferramenta que permite eliminar influências da matriz, seja do ar ambiente, do sistema ou outro, por meio da subtracção dos espectros de background aos espectros experimentais. A interface desenvolvida foi testada para diferentes medições experimentais de aquisição dos espectros de ar exalado com a tecnologia de MCC-IMS e os resultados obtidos foram apresentados como comunicação científica de painel na Conferência iMed 4.0 em 2012 na FCM-UNL e na Conferência Internacional Breath Analysis Summit, na Alemanha em Junho de 2013.