• real-time analysis;
  • drug analysis;
  • breath analysis;
  • ambient mass spectrometry


  1. Top of page
  2. Abstract

Future individualized patient treatment will need tools to monitor the dose and effects of administrated drugs. Mass spectrometry may become the method of choice to monitor drugs in real time by analyzing exhaled breath. This review describes the monitoring of exhaled drugs in real time by mass spectrometry. The biological background as well as the relevant physical properties of exhaled drugs are delineated. The feasibility of detecting and monitoring exhaled drugs is discussed in several examples. The mass spectrometric tools that are currently available to analyze breath in real time are reviewed. The technical needs and state of the art for on-site measurements by mass spectrometry are also discussed in detail. Off-line methods, which give support and are an important source of information for real-time measurements, are also discussed. Finally, some examples of drugs that have already been successfully detected in exhaled breath, including propofol, fentanyl, methadone, nicotine, and valproic acid are presented. Real-time monitoring of exhaled drugs by mass spectrometry is a relatively new field, which is still in the early stages of development. New technologies promise substantial benefit for future patient monitoring and treatment. © 2013 Wiley Periodicals, Inc. Mass Spec Rev 33: 394–413, 2014


  1. Top of page
  2. Abstract

Analyzing breath is very convenient since it is non-invasive and provides instantaneous information about a subject's health status. Although breath is considered as a fairly easily accessible matrix as compared to blood, urine, or tissue, it is delicate to analyze and still widely unexplored for the monitoring of exhaled metabolites and drugs in real time. New ionization methods for mass spectrometry have been developed, which now allow this kind of monitoring. This field is still at the stage of method development rather being routinely used in biological or pharmaceutical research or clinical applications. We believe that it is useful to survey the topic of real-time monitoring of exhaled drugs by mass spectrometry at this early stage, to point out current shortcomings and to guide future developments.

Prior to focusing on particular drugs, breath analysis has been developed for diagnostics. Only very few specific diseases are actually diagnosed by analyzing exhaled breath. It has been known for a long time that the smell of exhaled acetone is an indicator for diabetes (Buszewski et al., 2007; Španel et al., 2007). Also, the determination of exhaled hydrogen to indicate lactate intolerance (Oberacher et al., 2011) or the detection of urea in exhaled breath to identify the infection with Helicobacter pylori are used in medical diagnosis (Kim et al., 2012). The monitoring of nitric oxide is well established in asthma therapy (Risby & Solga, 2006). More complex diseases such as head and neck cancer (Hakim et al., 2011), lung cancer (Mazzone et al., 2012), or COPD (Cazzola & Novelli, 2010) are gradually getting into the focus of modern breath research. A relevant example was published by McCulloch et al. (2006), who detailed how to train dogs to identify patients with lung cancer. The ongoing trend of using breath for diagnostics shows that many metabolites are exhaled and can potentially be used as diagnostic markers (Di Francesco et al., 2005; Grob et al., 2008; Chambers et al., 2012; Kim et al., 2012). As a new topic, instead of using exhaled metabolites to diagnose complex disease, it is possible to detect compounds or drugs which have been administered for therapy. This extension of the diagnostic approach is the beginning of a new field of applied breath analysis.

Customized patient treatment that takes individual metabolism into account is of increasing importance in modern medicine (Crews et al., 2012). Body mass index, health status, polymedication, addiction, and the genes influence the therapeutic dose needed. Therefore, therapeutic drug monitoring (TMD) using either pharmacodynamic or pharmacokinetic parameters is generally used (Mayer & Hollt, 2006). TDM is often required for drugs with a narrow therapeutic range, where small modulations in drug concentrations can have dramatic consequences in terms of safety and efficacy. Real-time breath sampling enables access to immediate information about the pharmacokinetics of drugs. This is of particular importance for emergency, anesthesia and critical care patients, where rapidly changing plasma concentrations of drugs (opioids for instance) are the rule. Knowing the exact body drug concentration would allow the physician to immediately adjust the required drug dose before facing any inconveniences for the patient. To obtain rapid and accurate drug concentration measurements, fast and sensitive instruments that are easy to handle are required. For drug and metabolite measurement, mass spectrometry, which is one of the most sensitive and universal analytical tools, could play a key role in this future individualized patient treatment.

This review focuses on the methods, applications, and compounds of importance for real-time breath analysis by mass spectrometry. Several investigations have already been performed and the challenges and needs will be discussed. First we will explain the physiological background. The physical and chemical properties of exhaled dugs are discussed next. The units to define exhaled concentrations, also for comparison to classical off-line and real-time methods are presented. Existing and recently published ionization methods for real-time breath analysis by mass spectrometry are shown in detail. The needs and capabilities of a mass spectrometer to be used in this field, especially for on-site measurements are presented as well. Finally, several examples of drugs that have been monitored in breath are presented in detail.


  1. Top of page
  2. Abstract

If metabolites and drugs are exhaled, where could they come from and what are the properties needed for any compound to be released via exhaled breath? To understand this issue, the physiology of breathing as well as the pharmacology needs to be discussed. Also the question how to evaluate, calculate, and compare exhaled concentrations is discussed in this section.

A. Physiological Basis

The respiratory system (Fig. 1) includes an upper (mouth, nose, pharynx, and larynx) and lower airway system (trachea, bronchi, and bronchiole), a gas exchange system (alveolar-capillary system), a muscular pump with inspiratory and expiratory movements and a control system in the brain with nerves to and from all parts of the respiratory system. In adults, the surface of the gas exchange system is approximately 100 m2 and the capillary volume containing blood is approximately 500 mL (Gehr et al., 1981). The air volume in the airway system and in the alveolar space is approximately 7 L in adults. A maximum of approximately 5 L can be exhaled by a young adult using all expiratory muscles (=forced vital capacity). A normal breath is approximately 0.5 L (=tidal volume) and approximately 15 breaths occur per minute while resting. Approximately 1/3 of the expired air (∼150 mL) had no gas exchange (=physiological dead space = anatomic and alveolar dead space). The perfusion of the capillary system of the lungs depends on the cardiac function measured as cardiac output. The cardiac output in an adult while resting is approximately 4.5–5 L/min. The ratio of alveolar ventilation (ventilation minus physiological dead space ventilation) to perfusion is close to 1 (normally slightly inferior). The alveolar-capillary system is a relatively thin surface with a thickness in the micrometer range and permits an extensive diffusion of molecules or compounds. This membrane is essential for life because it is where gas exchange of oxygen and carbon dioxide takes place. Capnometry (Fig. 2) is a method to monitor exhaled carbon dioxide and to follow the dynamics of breathing. During the first part of expiration, and related to the physiological dead space, no carbon dioxide can be measured. At the peak concentration of CO2 (PetCO2) air that was interacting with the alveolar surface directly is exhaled. Alveoli are covered with a thin surfactant and the lower airway system is covered with a thin surface liquid, so-called epithelial lining fluid (ELF). Exhaled air of a spontaneously breathing human is warm (37°C), water saturated and also includes saliva. The overall composition of the exhaled air, its temperature, humidity, percentage of alveolar space, dead space, and volume is significantly influenced by the person's health status and breathing mode. Moreover, the mode of breathing may influence the composition of exhaled breath. For example, it is different if someone is hyperventilating (reduced PetCO2), gets artificially ventilated (less humidity, more non-ventilated areas), or is breathing calmly. For research it is always useful to use reproducible conditions such as artificial ventilation or forced breath (to breathe out the whole volume).


Figure 1. Schematic design of the respiratory system: The upper respiratory system consists of the mouth, nose, pharynx, and larynx. This part is covered with oral fluid, saliva, and mucus. The trachea connects the upper system with the lower respiratory system, which consist of bronchia, bronchiole, and alveoli. The bronchia and bronchiole distribute the air into a network of very small tubes, which end in the alveoli, where the main gas exchange occurs. One alveolus is shown in detail on the bottom. The gas and molecule exchange occurs through the wall of the alveoli, which is magnified next to it. Some metabolites present in blood can pass the capillary wall into the interstitial space and the alveolar epithelium. The epithelial lining liquid is the last barrier where the metabolites are finally exchanged with the alveolar space (Kiem & Schentag, 2008).

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Figure 2. Schematic drawing of a normal capnogram: CO2 is measured to follow the breathing dynamics. One breath cycle is shown. Phase I is the end of inhalation and the beginning of exhalation. Gas sampled during this phase represents anatomical dead-space air and would typically not contain CO2 and endogenous VOCs. Phase II reflects the appearance of CO2 and a steep upstroke of CO2 tension in the normal capnogram. Gas sampled during this phase typically contains a mixture of alveolar and dead-space air. Phase III reflects the alveolar or expiratory plateau. As the result of alveolar emptying, PetCO2 represents the end tidal concentration (Miekisch & Schubert, 2006).

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B. Origin of Exhaled Molecules

The origin of exhaled compounds in breath is discussed in numerous articles in the literature (Shimouchi et al., 2010; Beck et al., 2011a; Cristescu et al., 2011; Gamez et al., 2011; Hakim et al., 2011; Kamysek et al., 2011; Chambers et al., 2012; Kim et al., 2012; Larsson et al., 2012). Several thousand volatile organic compounds (VOCs) have been detected in breath (Phillips, 1992; Grote & Pawliszyn, 1997; Phillips et al., 1999). Risby (2008) concluded that compounds found in breath need a sufficient vapor pressure to be released, albeit without making any quantitative statements (Risby & Solga, 2006). Other authors such as Effros or Dwyer (Effros et al., 2003; Dwyer, 2004; Corradi et al., 2009; Grossherr et al., 2009a; Johnson & Morawska, 2009; Holmgren et al., 2011; Zakharkina et al., 2011) show that aerosols are formed during exhalation. It has been shown by several authors (Griese et al., 2002; Effros et al., 2003; Garey et al., 2004; Soyer et al., 2006; Larsson et al., 2012) that even inorganic ions and proteins are exhaled. Exhaled breath particles were, for example, collected on silicon wafers and analyzed by time of flight secondary ion mass spectrometry (TOF-SIMS); ions of up to 800 m/z were found by Almstrand et al. (2009).

However, there is no consensus about the mechanism of how metabolites (or drugs) are transferred from the blood flow in the lung into exhaled breath. It is well known that to be found in the ELF, drugs must diffuse across the alveolar capillary wall, the interstitial fluid, and the alveolar epithelial cells (Fig. 1). While a paracellular transport is possible through the fenestrated pulmonary capillaries, this type of drug transport is impossible through the alveolar epithelial cells, which are linked by tight junctions. Therefore, to reach the ELF, drugs must diffuse through the alveolar epithelial cells themselves (Kiem & Schentag, 2008). Drug-dependent factors that could influence the passage of drugs into the ELF include protein binding, lipophilicity, and molecular weight. Smaller and more lipophilic substances are more likely to diffuse through the alveolar capillary wall. Once a substance/drug has crossed this barrier, several factors will influence its concentration in breath. Physical and chemical properties, as well as applied and exhaled concentrations of some drug-like compounds are summarized in Table 1. The Henry constant represents the vapor pressure of a compound over an ideal solution; log P (log of the octane–water distribution coefficient) characterizes its lipophilicity. The compounds detected all have some lipophilic character and are found in the pg/L to ng/L range (for compounds of low volatility). The lipophilic character could assist the exhalation in two respects. The alveolar membrane, which is made of collagen, is quite non-polar. Therefore, lipophilic compounds (such as most non-metabolized drugs) tend to diffuse through it more efficiently (less interaction). In addition, lipophilic compounds tend to accumulate at the liquid surface (in aqueous solutions) and vaporize more efficiently. This surface accumulation would also enhance the concentration in exhaled aerosol droplets. In addition to these properties the formation of exhaled aerosols is strongly dependent on the breathing mode.

Table 1. List of detected exhaled drugsThumbnail image of
  • Molecular mass, pKa, log P, half-life was provided by Drug Bank (Wishart et al., 2006; Wishart et al., 2008; Knox et al., 2011) and Henry constant simulated by SPARC (Hilal et al., 2003).

  • A quantitative estimation of the concentration of exhaled drugs is difficult to make, since the data are not sufficient to develop a theoretical model. Nevertheless, it is important to get some idea about the potential concentration of an exhaled drug to define the necessary performance of an analytical method. As a rough estimation, the data presented suggest an exhaled concentration in the range of low pg/L for most of the compounds. To estimate the required sensitivity for real-time measurements, an average exhaled concentration of 1 pg/L is assumed. At a breath flow rate of 3 L/min, approximately 3 pg/min or 0.05 pg/sec would reach the mass spectrometer. For a drug of a molecular weight of approximately 300 g/mol, a real-time sensitivity of approximately 0.2 fmol/sec needs to be achieved.

    1. Comparison of Exhaled Concentrations in Off-Line and Real-Time Methods

    The concentrations expressed in Table 1 have been evaluated by real-time and off-line methods. To compare these two main sampling strategies and to compare evaluated concentration in exhaled breath correctly, it is necessary to discuss how to calculate and express the concentrations in breath correctly. Especially in a field where analytical–chemical technologies and medical investigations meet, it is important to clarify the meaning of a measured concentration. It is thus necessary to define the conditions of how breath was sampled (volume, time, accumulation, and pre-concentration) to be able to compare different methods.

    For VOCs it is very common to express the concentration as parts per million, billion, or trillion (ppm, ppb, ppt). Since these are ratios, it must be specified whenever the ratio is understood as volume, mole, or mass fraction. In breath, the ratio usually refers to the volume fraction. To avoid misinterpretation, it is highly recommended to declare this by using ppm(V), ppb(V), or ppt(V). An alternative is to express exhaled concentrations in weight (or mol) per volume. This unit is also correct if the exhaled molecule is carried as an aerosol particle (since an aerosol has no well-defined molar volume). These ways of expression are comparable for real-time and off-line methods. For real-time methods a different approach was used to take the time resolution of the whole setup into account. The number of molecules that reach the ion source per time unit expressed as femtomoles per second (fmol/sec) is a well suited unit to directly compare different systems. This unit was used in our earlier work to compare APCI and EESI and to compare the sensitivity of different setups (Berchtold et al., 2011; Meier et al., 2011, 2012b).

    Let us consider nicotine as an example. If nicotine is exhaled with a concentration of 2 ng/L, this could also be expressed as 12 pmol/L (using a molecular weight of 163 g/mol) or as a volume fraction of 294 ppt(V) (assuming an ideal gas with a molar volume of 24.47 L/mol). For comparing different mass spectrometric systems, we recommend using units of femtomoles per second. An exhaled concentration of 2 ng/L would translate to 102 fmol/sec for an exhalation rate of 0.5 L/min. If an off-line sampling method such as solid phase microextraction (SPME) is used, the result may look a bit different and the expression in fmol/sec is not very useful anymore: for example, if a person is breathing with an average flow of 0.5 L/min for 10 min, and assuming that the SPME tube was loaded by an assistant gas flow of 300 mL/min and the trapping capacity as well as the recovery would be sufficiently high (both near 100%), an absolute amount of 6 ng would be trapped. If the SPME is then extracted with 1 mL solvent and injected into a LC-MS system (again assuming 100% extraction efficiency), the concentration detected will be 6 ng/mL (which would have to be calculated back correctly).

    To avoid misinterpretation it is necessary to provide very detailed information about the sampling. The units used are interchangeable as long as the conditions (exhalation rate, recoveries, etc.) are available. If breath concentrations are measured, exhaled flow rate, sampling flow rate, and pre-concentration factors need to be indicated.

    C. Sample Collection for Off-Line Analysis

    Although this review focuses on real-time evaluations, it is also important to mention off-line methods. Off-line, in this context, means that breath sampling and analysis are performed in at least two independent steps. Although these methods do not provide detailed pharmacokinetic information, they are very sensitive, due to the pre-concentration step. Many of the low volatility drugs reported in Table 1 were measured by off-line methods only; therefore it is important to discuss these methods here.

    Three main strategies exist to sample breath off-line: adsorption (e.g., via solid phase extraction), sampling in containers or bags, and breath condensation. These methods are shown schematically in Figure 3. The choice of the perfect sampling method depends on the compound addressed, the way of sampling (active breathing people or artificial ventilation) and if quantitative results are needed.


    Figure 3. Off-line methods for sampling breath via adsorption, bag extraction, and condensation are shown and compared. Various modifications and combinations of these methods are used. Breath sampled with all the methods displayed is analyzed by GC- or LC-MS either after thermal desorption or extraction. Further details are given in the text.

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    1. Adsorption Units

    Adsorbtion material is usually used to trap analytes with a relatively high volatility. VOCs were trapped on sorbent tubes and analyzed by gas chromatography mass spectrometry (GC-MS) in the early stages of breath research (Phillips et al., 1999). This technology was further refined by the use of SPME, which was applied in several studies (Miekisch & Schubert, 2006; Menezes et al., 2009). SPME and sorbent tubes provide the possibility to sample for a long time and thus to obtain a high pre-concentration factor (≫100,000) (Menezes et al., 2009). Compounds that are trapped are either thermally desorbed and directly measured by GC-MS or extracted with a solvent and injected into a GC-MS, or liquid chromatography mass spectrometry (LC-MS) instrument, respectively. SPME for the sampling of VOCs was even automated for patient monitoring, as described by Mieth et al. (Mieth et al., 2009, 2010; Ueta et al., 2009). Not only VOCs can be analyzed by the use of adsorbtion material, also compounds of low volatility such as exhaled methadone have been detected (Beck et al., 2011b). In this case, sorbent traps are employed, which retain exhaled breath for some time to enhance the interaction between the sorbent material and compounds in breath.

    Despite the enormous variety of adsorbtion materials that achieve high levels of sensitivity and selectivity, there are also some disadvantages to this method. Usually it is time consuming and the sorbent material is relatively expensive. Additionally, the choice of the adsorbtion material is very important to efficiently trap and release the molecules of interest. Another drawback is the high risk of degradation of the analyte on the adsorbtion material or during the release. This is a problem when quantification is needed since it is very difficult to determine accurate recovery factors for the whole process.

    2. Sampling in Containers or Bags

    A different approach is to use bags or containers (Di Francesco et al., 2005) with a defined volume (up to 20 L) to sample breath. The trapped breath is either injected directly into an ion source for direct mass spectrometric analysis (Beauchamp et al., 2008) or alternatively extracted with a solvent prior to analysis. The most important method to mention here is the sampling in plastic bags, for example Tedlar® bags (Beauchamp et al., 2008). In the case of extraction, the bags are washed out with solvent after sampling to achieve sample pre-concentration. The solvent is evaporated and pre-concentration factors of approximately 1:200,000 are possible (20 L breath to 100 µL solution). Contrary to adsorption tubes, no selection of the adsorbtion material has to be made and all exhaled compounds are introduced into the container. Compounds of low volatility are accessible, for example, by analyzing the pre-concentrated solution by a LC-MS. Bags or containers are used to sample exhaled breath of persones who are able to actively fill them (like inflating a balloon). The interfacing of bags with an artificial ventilation circuit appears difficult since the backpressure of the inlet valves of sampling bags is too high. Although bags may be very efficient for sampling of compounds of low volatility, they were usually used to sample VOCs (Schwoebel et al., 2011).

    Bags are well suited for quantitative experiments, since their volume is well defined and the extraction and pre-concentration process is easily validated by the use of an internal standard added to the bag. Unlike sorbent systems where the retention of compounds depends on the sorbent material used, bags allow the sampling of all exhaled compounds The drawback of using bags or containers is the limited sampling volume, and thus a limited accumulation factor, which limits the sensitivity that can be achieved.

    3. Condensation

    The most prominent sampling method to detect compounds of low volatility in exhaled breath is exhaled breath condensate (EBC). Breath is condensed inside of a glass or polytetrafluoroethylene (PTFE) container at temperatures between 0 and −80°C. EBC contains water and all compounds of low volatility in breath. Figure 4 illustrates how breath condensate is collected. For ECB analysis, a high level of pre-concentration is possible since a large volume of exhaled breath can be accumulated. In some cases, the adsorption and the condensation are combined as it has been done for the detection of exhaled methadone (Beck et al., 2011c). The condensate is then either injected directly into a LC-MS or a short sample preparation (extraction) is applied. EBC was already reviewed in detail (Horvath et al., 2005; Rosias et al., 2006, 2008; Montuschi, 2009; Reinhold & Knobloch, 2010; Cathcart et al., 2012) and critical details such as recommendations for sampling and accessible analytes have been discussed. An EBC collection system was recently interfaced with an artificial ventilation machine (Carter et al., 2012). Proteins, which are non-volatile compounds, have been detected in EBC as described in the review by Reinhold and Knobloch (2010). DNA was also identified in several investigations (Carpagnano et al., 2005). Nevertheless, whether DNA is really exhaled in case of an infection is still unclear. The DNA of viruses and bacteria related to lung disease has not always been detected in EBC of infected patients (Jain et al., 2007; Costa et al., 2011).


    Figure 4. Representation of two EBC systems: A homemade EBC collecting system (A) consists of two glass containers that form of a double wall of glass. The inner side of the glass is cooled by ice. EBC is collected between the two glass surfaces. A commercially available condenser (EcoScreen®) (B). EBC is collected in the collecting vial highlighted by the arrow. A commercially available portable condenser (RTube®) (C). Reprinted with permission from Montuschi and Barnes (2002). Copyright 2002 Elsevier.

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    Off-line techniques for breath sampling are also still under investigation. For VOCs the combination SPME and GC-MS seems to be the most sensitive method (Martin et al., 2010; Szulejko et al., 2010) and is considered to be the gold standard in breath analysis of VOCs (Van den Velde et al., 2008). The presence of compounds of low volatility in breath is supported by investigations carried out with ECB (although still discussed for some compounds).

    Results from off-line techniques provide important support for real-time methods. They give an idea about concentrations and nature of exhaled compounds and their metabolites. They also offer the possibility to store samples over a long time to confirm the results with a second method or measurement, maybe even years later (e.g., with new technology). Off-line techniques have been reviewed before and there was “no quantum leap” in the technology in this field recently (Wilson & Monster, 1999; Egeghy et al., 2002; Szulejko et al., 2010; Carter et al., 2012).


    1. Top of page
    2. Abstract

    Real-time breath analysis is the main focus of this review. Real-time breath analysis, in a medical context, is understood in the way that information (such as a compound's concentration) is available for the medical staff on a time scale of seconds to minutes. The classical patient monitoring, such as the monitoring of oxygen in blood, exhaled CO2 (Arnold et al., 1996), or monitoring by an electrocardiogram is well established and is a very important aspect of patient treatment in intensive care or surgery. Even anesthetic gases such as isofluran can be monitored by sensors in an on-line fashion (Compton & Northing, 1990). Mass spectrometry, for real-time patient monitoring, needs to provide information comparable to these well-established methods. Sensitivity, selectivity, scan speed, and robustness are the most important factors for real-time monitoring of exhaled drugs. In addition, instruments used should be either portable or available on-site in a clinic or a hospital, for example, in an operation theater next to the patient.

    Biasioli has reviewed real-time monitoring of breath by mass spectrometry in 2011 (Biasioli et al., 2011). In 2005, Amman and Smith have also reviewed many of the available methods in this field in a textbook (Amann & Smith, 2013). The focus of these publications was a broad overview and not the monitoring of drugs by mass spectrometry. Before the technical details of the available instruments are discussed, it is important to define the need for mass spectrometric measurements of breath in real time in some more detail. To analyze breath by mass spectrometry, molecules of interest must be ionized. A highly efficient ionization process is required to reach the high sensitivity needed. Finally, the concentration should be displayed immediately to the medical staff (close to the patient). The sampling and the ionization of breath need to be direct, without loss of compound. Table 2 gives an overview of some salient features of all methods of importance for breath analysis by mass spectrometry.

    Table 2. Real-time and off-line methods for breath analysis by mass spectrometry and related techniquesThumbnail image of

    A. Ionization Methods for Real-Time Breath Analysis

    The five most important ionization methods that are being used for real-time breath analysis are discussed in this section. These are shown schematically in Figure 5, and their properties are compared with off-line methods in Table 2. They are divided into vacuum ionization (EI, SIFT, and PTR-MS) and ambient ionization techniques (APCI and SESI/EESI). A detailed review of ambient ionization methods was given by Covey and colleagues in 2009 (Covey et al., 2009) and in the same year by Chen et al. (Chen et al., 2009b).


    Figure 5. The most important real-time ionization techniques are compared. In SIFT-MS, a microwave-assisted plasma generates precursor ions. These ions are pre-selected by a quadrupole. The precursor ions are mixed with breath and charges are transferred. In PTR-MS, a corona discharge in water vapor is used to produce the precursor ions and water clusters. These clusters are transported by an electric field in the direction of the MS inlet. Exhaled molecules are ionized in the proton transfer reaction tube by proton transfer. The tidal buffer tube allows sampling of breath from the lower lung region (alveolar). The ions formed in the reaction tube are transported into the inlet of the mass spectrometer by an additional electric field. In APCI-MS, the breath flow is heated and ionized by a corona discharge or another source of precursor ions at atmospheric pressure. In SESI/EESI MS, exhaled breath is also transported through a heated tube. Breath is mixed with the cloud of a clean (only water, methanol, acid) electrospray plume.

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    1. Electron Impact Ionization

    Electron impact (EI) ionization is the classical method for the identification of unknown compounds, especially in GC-MS. In EI, a heated filament generates electrons that are accelerated in vacuum, usually to 70 eV. These electrons ionize sample molecules by the process inline image (Hoffmann & Stroobant, 2007) EI-MS was used to detect exhaled VOCs (Risby, 2008). For drugs, it was used to detect servoflurane, and other anesthetic gases (Elokhin et al., 2011). EI-MS is limited to volatile compounds. The main drawback for real-time ionization by EI-MS is the formation of fragments, which overlap if no separation is used prior to ionization. Although many compounds are identified according to their fragments (by the use of a library) prior separation is in most cases absolutely necessary, which makes the use of EI-MS for the real-time detection difficult. Nevertheless, EI-MS in combination with gas chromatography is well established and considered to be the “gold standard” for the detection and identification of exhaled VOCs (Risby & Solga, 2006).

    2. Selected Ion Flow Tube Mass Spectrometry

    Selected ion flow tube (SIFT) mass spectrometry uses a chemical ionization method at sub ambient pressure (Adams & Smith, 1976). This method provides a selective and efficient ionization. SIFT-MS is based on the reaction of NO+, O2+, or H3O+ (generated by a microwave-induced plasma), which are pre-selected by a quadrupole and injected into a field-free reaction tube at less than 1 mbar (Diskin et al., 2002). It was introduced for breath analysis in 1996 by Španel and Smith (Španel & Smith, 1996). In 1999, the quantification of isoprene in breath was shown (Španel et al., 1999). Many applications followed in the years after, which were reviewed in 2005 (Smith & Španel, 2005) and compared with proton transfer reaction mass spectrometry (PTR-MS) (Smith & Španel, 2011). SIFT-MS was used in applications to detect various metabolites in the breath of children (Enderby et al., 2009). SIFT-MS measures volatile breath components only (Boshier et al., 2010a, 2010b) and showed nice capabilities for the monitoring of artificially ventilated patients (Boshier et al., 2011). In this article, breath was sampled by a direct bypass in the artificial ventilation circuit and directed into the SIFT-MS setup (Fig. 6). The sensitivity was in the range of parts per billion for isoprene, acetone and propofol. Boshier et al. also showed how to monitor these compounds in parallel during a surgery. Volatile compounds in the breath of smokers were detected up to an m/z of 230 (significant signal below m/z 140) (Kushch et al., 2008). The latest developments of SIFT-MS for breath analysis have been summarized by Španel et al. (Španel & Smith, 2011). SIFT is a well-suited method for the quantification of volatile compounds in breath or in the headspace over solutions (Smith et al., 2003). The main reason for this is that the reaction of the pre-courser ions is very quantitative and predictable. The investigation of breath from the mouth or nose cavity did not show significant differences for the concentration of volatile compounds (Smith et al., 2008). Figure 7 shows a typical example of the real-time determination of isoprene and acetone (Turner et al., 2006).


    Figure 6. A schematic representation (not to scale) of the ventilation circuit and the SIFT-MS sampling manifold used for on-line intra-operative breath analysis. The sampling line (made from PEEK) is approximately 5 m long. The point of connection between the ventilator circuit and the first 50 cm of the PEEK tubing was heated to 70°C using a heater tape with a percentage controller to avoid condensation of water vapor and condensable trace gases. The continuous sample flow rate that naturally occurred in the SIFT-MS instrument (determined by a heated calibrated capillary) was typically 30 mL/min, which was considerably smaller than the ventilation rate. Reprinted with permission from Boshier et al. (2011). Copyright 2011 Royal Society of Chemistry.

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    Figure 7. A: Example of a SIFT-MS ion signal time profile showing the count rates (in counts per second, c sec−1) of the precursor ions (NO+) and their hydrates and the characteristic product ions isoprene (C5H8+, m/z 68) and acetone ((CH3)2CONO+, m/z 88) obtained during three consecutive exhalations as a function of time (in sec). B: Quantitative analyses of the isoprene and acetone levels are obtained using the ion signal ratios from (a), together with the known reaction time and the known sample and carrier gas flow rates. Both alveolar portions of the exhalation and the ambient air portion that is used to calculate the mean exhalation levels and the levels in the laboratory air are indicated. Reprinted with permission from Turner et al. (2006). Copyright 2006 IOP Sciences.

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    Although SIFT-MS is a very sensitive and potent method for real-time measurement of volatile compounds, the transfer of neutral analytes into the vacuum region seems to be insufficient for compounds of low volatility in breath. In addition no commercial setup is available and the interface between the ion source and the mass spectrometer is custom made.

    3. Proton Transfer Reaction Mass Spectrometry

    Proton transfer is, like SIFT, a chemical ionization method operating at reduced pressure. In PTR-MS, the precursor ions are produced by a corona discharge in evaporated water. The discharge forms water cluster and hydronium ions. Hydronium ions are strong proton donors and well-known pre-curser ions. The hydronium ions are transferred into the reaction tube by ion lenses. Pre-cursor ions and exhaled neutrals are mixed in the reaction tube and charges (protons) are transferred. A field in the direction of the mass spectrometer inlet transports the ions formed to the inlet. The concept of proton transfer reaction for mass spectrometry is well known and has already been used in the 1960s (Moran & Hamill, 1963) for the investigation of ion-molecule reactions (Chatterjee et al., 1991). PTR-MS in the configuration shown in Figure 5 has been developed by Hansel et al. (1995). This design was developed for breath analysis and has been optimized to monitor breath in real time (Lindinger et al., 1998). Subsequently a buffered end tidal sampling system was introduced to analyze only the fraction of breath originating from the deeper part of the lung (Beauchamp et al., 2008). Improved sensitivity (pptV), mass resolution (>6,000), and accuracy by the use of a time-of-flight mass spectrometer were shown additionally (Jordan et al., 2009a). PTR-MS is able to monitor compounds such as ethanol (Tan et al., 2010) at various sampling sites (nose, mouth, artificial ventilation). An interesting project was the long-time breath monioring of sleeping patients (Amann et al., 2004). PTR-MS is very sensitive to volatile compounds (ppt or pg/L) (Jordan et al., 2009b; Graus et al., 2010) and is able to measure in the mass range between m/z 30 and 200 (Table 2). A more detailed and very recent review of PTR-MS is given by Kim et al. (2012) as well as by Zhan et al. (2013). PTR-MS is the only complete real-time breath analyis system for mass spectrometry, that is comercially available ( The most popular example for PTR-MS measurements of an exhaled drug is the detection of propofol (Takita et al., 2007). Propofol is an important drug for anesthesia and is discussed in more detail in a later section.

    Proton transfer reaction mass spectrometry (PTR-MS) is, like SIFT-MS and EI-MS, also limited to volatile molecules (Cristescu et al., 2011). Ionization methods, which operate at reduced pressure need the sample molecules to be transferred into the vacuum prior to ionization. Therefore it is much harder to analyze compounds of low volatility with these methods.

    4. Atmospheric Pressure Chemical Ionization

    Atmospheric pressure chemical ionization (APCI) is a widespread chemical ionization method, which is used in GC-MS and is closely related to PTR-MS or SIFT-MS. APCI performs ionization at atmospheric pressure and thus minimizes any loss of compound due to an inefficient transport of neutral molecules into the vacuum. APCI was introduced in the 1970s by Horning et al. (Horning et al., 1973; Carroll et al., 1974) as a sensitive ionization method at atmospheric pressure. Pre-curser ions such as H3O+ are formed in APCI, which are then used to ionize the sample molecules in the gas phase. Precursor ions can be formed by a corona discharge in helium, nitrogen, or other gasses, including air. A corona discharge or a corona field is usually formed by applying high voltage (kV) to a sharp needle, which is placed in the reaction gas close to the sample gas flow. The primary ions formed are either used to transfer charges directly to the sample molecule or to form reactive intermediates such as water clusters or hydronium ions (Giao & Jordan, 1968; Good et al., 1970; Horning et al., 1973; Carroll et al., 1974).

    Atmospheric pressure chemical ionization (APCI) is often used as an ionization method in combination with liquid chromatographic separation if electrospray ionization cannot be applied due to the solvents used, for example, if a normal phase or a hydrophobic interaction stationary phase is employed. APCI shows great ability for the ionization of polar molecules in the gas phase. The ions observed are usually singly protonated or deprotonated species. Disadvantages are the need for completely evaporated sample molecules and the relatively high risk of fragmentation (Byrdwell, 2001). Lovett et al. introduced APCI-MS for breath analysis in the late 1970s (Lovett et al., 1979). Already in the 1980s, Benoit et al. showed the possibility to use APCI for real-time applications (Benoit et al., 1983). APCI thus represents one of the first established ambient ionization methods for real-time breath analysis by mass spectrometry (Huang et al., 1990). Even skin gases were analyzed directly as an alternative to breath analysis (Shimouchi et al., 2010). Zehentbauer et al. (2000) showed that humidity leads to an enhancement of the signal intensity. The detection of flavors in the mouth cavity after swallowing food was possible with APCI-MS as well (Van Loon et al., 2005). Taylor and Linforth (2003) compared APCI with ESI and showed the ability of APCI to ionize also compounds of low volatility (e.g., glucose, sucrose and citric acid). Therefore, APCI can be potentially used for real-time drug monitoring. Over the years, the “classical” direct current needle based APCI approach has been modified to include different modes of chemical ionization at atmospheric pressure. Plasmas generated by alternating current (or radio frequency), microwaves or direct current discharges were used to produce precursor ions in helium, argon, or air (Shen & Satzger, 1991; Andrade et al., 2008; Harper et al., 2008). APCI is considered to be robust, sensitive, and reproducible. Nevertheless, most applications reported in the field of breath analysis were related to exhaled food flavors (Friel et al., 2007; Ashraf et al., 2010). We have recently used APCI in a comparative study to quantify exhaled nicotine after smoking, and to measure a pharmacokinetic profile of nicotine, as shown in Figure 8 (Berchtold et al., 2011). Additionally the sensitivity for other drugs such as fentanyl, naloxone, morphine, and sulfentanil has been determined with standards, which was, however, insufficient (>100 fmol/sec) for further investigations in exhaled breath.


    Figure 8. Time evolution of the nicotine signal in an ambient pressure chemical ionization experiment. Every dot represents the accumulated counts for nicotine (m/z 163) of one deep breath that lasts for approximately 30 sec. The dots before 0 min refer to the background level before smoking. The solid line refers to a second measurement, with quantification and six breath strokes averaged per point (the inset shows the calibration). Reprinted with permission from Berchtold et al. (2011). Copyright 2011 Elsevier.

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    A special and rarely used APCI configuration employs a beta radiation ion source (Steeb et al., 2009). Possibly due to the difficult handling of radiation based ion sources, they are not found in the literature for breath analysis by mass spectrometry. Their common application is for stand-alone ion mobility mass spectrometry systems (IMS). IMS is not reviewed in this article, but is mentioned in a later section on the hyphenation of IMS with mass spectrometers.

    Atmospheric pressure chemical ionization (APCI) appears to be a very robust and reliable method to ionize drugs that may occur in exhaled breath. The main drawback is the formation of fragments and the limitation to gaseous sample molecules, which is usually achieved by extensive heating but can cause thermal decomposition. To our knowledge, the newest APCI configurations have not been used to analyze breath. New APCI configurations such as direct analysis in real time (DART) (Musah et al., 2012) could be benificial for the ionization of exhaled molucules such as drugs.

    5. SESI/EESI

    Extractive electrospray ionization (EESI) and secondary electrospray ionization (SESI) are two ambient ionization methods that were introduced separately. Due to their technical similarities, they are discussed here under one heading. In these two techniques, the sample, such as breath, is directly mixed with the ion cloud of an electrospray ionization (ESI) source. This primary electrospray is provided by a clean solvent spray that is sprayed by applying a high voltage and sometimes additionally with pneumatic assistance. The charge transfer happens in the ion could, either in a liquid–liquid extraction step (Wang et al., 2012) or by a gas-phase charge transfer step (Meier et al., 2011).

    The ability of electrospray ionization to serve as a post-ionization method has already been recognized in the early days after the invention of ESI (Yamashita & Fenn, 1984). In the following years, this was usually viewed as problematic since it caused background signals derived, for example, from plasticizers in the ambient air or from remaining sample matrix in the ion source (Keller et al., 2008). This was turned into an advantage in 1998 when an electrospray was used on purpose to ionize gas-phase molecules (Lee & Shiea, 1998; Wang et al., 1998).

    Extractive electrospray ionization (EESI) has been introduced by Chen et al. in 2006 (Chen et al., 2006) and has been used for many applications since, for example, for the identification of perfumes (Chingin et al., 2008), the identification of ripeness of fruit (Chen et al., 2007a), for skin vapor analysis (Chen et al., 2009a), as well as for breath analysis (Chen et al., 2007a; Ding et al., 2009). EESI was used to quantify nicotine (Ding et al., 2009) in breath and to detect a new metabolite of valproic acid (VPA) in exhaled breath (Gamez et al., 2011).

    Secondary electrospray ionization (SESI) was introduced in 2000 for the detection of illicit drugs (Wu et al., 2000) and was further developed for breath analysis by de la Mora and co-workers (Martinez-Lozano and de la Mora, 2007, 2008). They modified the atmospheric pressure interface (API) chamber to fill it with either humidified air or breath, which impinged laterally on the ion cloud of charged clusters and precursor ions from a nano-ESI spray. They also showed that a higher level of humidity has an enhancing effect on SESI sensitivity (Martinez-Lozano & de la Mora, 2008). For later application, SESI was optimized and characterized in detail by Dillon et al. (2010).

    Secondary electrospray ionization is now used as a general term to describe both of these methods (EESI and former SESI). Although this method is not simply a variation of APCI, the mechanism is closely related to that of APCI (Sinues et al., 2012). SESI and EESI are also well suited for ionizing compounds of low volatility. Since the ionization is performed at ambient conditions, there is no difficult transport of neutral sample molecules into the vacuum (as for PTR-MS, SIFT-MS, or EI-MS). EESI, for example, has been shown to be capable of detecting caffeine on the skin of a person after drinking coffee, just by sampling from a small skin area (Chen et al., 2009a). This is an enormous sensitivity considering the possible concentration of caffeine on the skin (<1 fmol/cm2 theoretically). Although the same sensitivity has never been published again for EESI, the detection of chemicals of higher concentration such as nicotine after smoking and VPA has been shown in breath. VPA as well as nicotine are discussed in detail in the examples section. It has been shown that the efficiency of SESI is approximately 100 times lower than that of direct ESI and therefore not sufficient to ionize compounds below the pg/L range in the gas phase (Meier et al., 2011). Nevertheless, the ions detected by SESI or EESI have higher masses compared to any other techniques (m/z up to 500). Since aerosols are easily transported at atmospheric pressure, EESI and SESI are capable of detecting compounds of low volatility in breath that may be contained in aerosol droplets (Gu et al., 2010).

    A further sensitivity enhancement has recently been acheived by Meier et al. (2012a,2012b) by performing SESI in a specially designed ion funnel. Figure 9 shows the design of this system. Ion funnels are important elements for ion transmission inside the different vacuum stages of a mass spectrometer (Kelly et al., 2010). They can also serve to guide ions from ambient pressure into the high vacuum region of a mass spectrometer (Shaffer et al., 1997, 1998). In SESI and EESI, the main loss of analyte and charges happens in front of the mass spectrometer due to Coulomb repulsion and the resulting dispersion of the formed ions. The use of an atmospheric-pressure ion funnel improved the efficiency of ionization by a factor of 1000 (Meier et al., 2012a, 2012b). This technology is still under development and has not yet been used for the detection of drugs in exhaled breath.


    Figure 9. Schematic of the atmospheric pressure ion funnel ion source developed by Meier et al. (2012a). Breath is transported via a heated interface into a secondary electrospray ion source. Three electrosprays are arranged symmetrically around the sample inlet, which is positioned in the center of the ion funnel. The ion funnel itself transports and focuses the ions formed into the MS inlet.

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    The main advantage of APCI, SESI, and EESI for ionizing compounds of low volatility is the API, which even allows compounds transported via aerosols into the ion source without major losses. EESI and SESI are soft ionization methods and as opposed to APCI, no fragments occur. There is also no need to evaporate all of the aerosols before it enters the ion source. The lack of sensitivity can be offset by the use of an ion funnel, which renders these methods the most promising for real-time breath analysis.

    6. IMS-MS

    Ion mobility (without mass spectrometry) is a very important technique for breath analysis and the most important competition for mass spectrometry based methods. The hyphenation of IMS (or related techniques) with mass spectrometers is a powerful combination to provide an additional dimension for analyzing ions since the IMS stage is often located between the ion source and the MS. It is briefly discussed here.

    Ion separation techniques such as ion mobility spectrometry (IMS) (Cohen & Karasek, 1970; Eiceman & Karpas, 2005; Kanu et al., 2008) and differential mobility spectrometry (DMS) (Davis et al., 2010) are classical methods for breath analysis that include the formation of ions and their separation. In a recent study, Vautz et al. showed how to identify various signals in IMS of exhaled breath after consuming an eucalyptol containing lozenge (Vautz et al., 2009). Figure 10 shows typical data obtained by an IMS system, which illustrates its ability to separate ions and to identify compounds according to their drift time in an electric field. The connection of such systems to mass spectrometers has been shown (Rus et al., 2010), but has not been used for breath analysis so far. Ion mobility has been used as an ion separation method without a mass spectrometer as detector, for many different sample matrices (including breath) (Arce et al., 2008; Baumbach, 2009; Vautz et al., 2009). IMS systems often use a beta emitter to generate ions (Brosi et al., 1951). Other ionization methods such as ESI (Wittmer et al., 1994) or APCI (Tabrizchi et al., 2000) have also been employed. The use of multi capillary IMS (MCC-IMS) (Perl et al., 2009) allowed a high level of sensitivity to be achieved and was used for cancer investigation and for the detection of various exhaled metabolites (Baumbach, 2009). Reynolds et al. have shown a combination of IMS-MS and thermal desorption (sorbent traps) for the detection of volatiles in breath (Reynolds et al., 2010). The hyphenation of various types of IMS with mass spectrometers is described in a review by Borsdorf et al. (2011). Finally, IMS is a powerful addition to ionization techniques at atmospheric pressure and providing an additional level of selectivity without loss of the sensitivity.


    Figure 10. The peaks identified from comparison with analyte databases are indicated in a cut-out of the MCC/IMS chromatogram in a 3D visualization. Reprinted with permission from Vautz et al. (2009). Copyright 2011 IOPSciences.

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    B. Mass Spectrometric Instrumentation, Including Mobile Instruments

    Mass spectrometers have been developed for the needs of industry. Powerful bench-top instruments with a high level of reliability and sensitivity were developed for routine analysis. Real-time breath analysis is a small field and is not recognized by the big mass spectrometer producing companies. The needs for an instrument for real-time breath analysis are in fact a bit different. In addition to sensitivity, reliability, scan speed, resolution and mass accuracy, the capability of measuring on-site also needs to be considered. For PTR-MS and SIFT-MS, custom-made mass spectrometers are used, which provide some ability to be used on-site. For SESI/EESI and APCI every mass spectrometer that incorporates an ambient ion source can be used. However, most of the investigations published were performed on standard bench top instruments. This is very feasible for research projects where the patients and healthy controls are able to move to the instrument. However, for real-time medical applications the mass spectrometer needs to be used on site, next to the patient. Most instruments used in research are big and noisy and are not made for this purpose.

    The development of small, mobile, and even portable mass spectrometers is a separate field that is directly connected with the task of real-time monitoring (not exclusively for drugs in breath). Therefore it is necessary to discuss this aspect in some detail, especially since many developments in this field are limited to academic research. The main challenge of miniaturizing mass spectrometers is the need for sufficiently strong pumps to maintain the high vacuum. One way to reduce the pump size is to reduce the gas volume transported in to the mass spectrometer. This is realized, for example, with the use of separation systems (e.g., GC) and sub-ambient ionization techniques such as electron impact ionization (EI). Mobile quadrupole mass spectrometer in combination with miniaturized GC systems have been shown by Smith et al. to be useful for the detection of chemical warfare agents (Smith et al., 2004). Such GC-MS systems have a limited gas load, which allows to maintain the vacuum in relatively pressure tolerant quadrupoles (Shortt et al., 2005) or ion traps (Contreras et al., 2008). A portable quadrupole mass spectrometer equipped with an electron impact ion source was used for the detection of halothane, isoflurane, and servoflurane (Turner et al., 2008). The system used in this approach is displayed in Figure 11. This system, which has the size of a suitcase, was used to monitor anesthetized horses on-site. The size of this system is suitable for mass spectrometers for on-site use. A different approach is the suitcase time of flight (TOF) mass spectrometer (Ecelberger et al., 2004). This system is based on a membrane inlet system to maintain the vacuum (Kotiaho et al., 1991; Johnson et al., 2000; Ketola et al., 2002). This strategy is very effective, although the membrane is selective and limited to VOCs. Other mobile devices for breath analysis such as the proton transfer reaction mass spectrometer (PTR-MS) reduce the delivered volume through the use of a smaller inlet and an intermediate pressure region (80 mbar). Such mobile quadrupole (Lindinger et al., 1998, 376) or TOF spectrometers are on wheels (Jordan et al., 2009b, 88) and have been commercialized (Ionicon/Ionimed, Innsbruck, AT). For ambient ionization methods such as APCI, SESI, and EESI, mobile systems have to be constructed in a different way (Badman & Cooks, 2000). There are series of mobile and portable instruments introduced by the Cooks group (Gao et al., 2006; Fico et al., 2007; Keil et al., 2007; Janfelt et al., 2008; Yang et al., 2008; Ouyang et al., 2009; Huang et al., 2010), which enable the use of ambient ion sources. These small ion traps use a pulsed gas inlet to run with very small pumps and still maintain the vacuum (Emary et al., 1990). The pulsed gas inlet allows the connection to ambient ionization techniques (Collings & Romaschin, 2009). Nevertheless, the performance of these rectilinear ion traps is quite limited. The systems have to be considered as prototypes although they are already partially commercialized (Aston Labs, West Lafayette, IN). The sensitivity is only in the range of ppm, and mass accuracy and mass resolution are not anywhere close to these of bench top instruments (Berchtold et al., 2011). Nevertheless, the development of portable ion traps is an important step towards truly mobile mass spectrometers for patient monitoring. For ambient mass spectrometry, there is no mass spectrometer available yet that delivers the required sensitivity and reliability for on-site operation. Bench-top instruments could be modified for on-site application without significant loss of performance.


    Figure 11. Field-portable miniature quadrupole mass spectrometry (QMS) and vacuum system for the detection of anesthetic gases. Reprinted with permission from Turner et al. (2008). Copyright 2008 W.B./Saunders Co.

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    Every ambient inlet instrument on the market could theoretically be used for on-site breath analysis in combination with an ambient ionization technique (EESI, SESI, APCI). As a compromise for the targeted detection of exhaled drugs, ion traps seem to best fit the needs. Traps may be quite slow in terms of scanning speed (0.1–1 sec), but they allow the accumulation of specific ions. In the single ion monitoring (SIM) mode, only ions of a certain mass-to-charge ratio are trapped. Ion traps also allow fragmenting the trapped ions (MSn), which enhances selectivity and sensitivity. The selectivity is enhanced due to specific fragments and sensitivity by reducing the observed background. Finally, ion trap mass spectrometers can be converted into mobile devices since they are able to operate at relatively high pressure, thus allowing to reduce the pump size.

    Many types of mass spectrometers are suitable to be modified for mobile use/breath analysis. A system as big as a bench-top instrument, which may be placed on a movable cart is already sufficient for on-site experiments. For targeted analysis, ion-trap or triple quadrupole instruments are very beneficial, and they can be made quite small, too. Triple quadrupoles are fast and sensitive, whereas ion traps are slower, but allow the accumulation of ions for a longer time period. The use of Q-ToF instruments as mobile devices is less likely, since they need a better vacuum. However, their scan speed and high resolution is very appealing, especially in studies where several m/z values must be monitored in parallel, or if unknown drug metabolites are analyzed. FT-ICR instruments are unfortunately by far too large for mobile applications.


    1. Top of page
    2. Abstract

    A detailed overview of the reported drug-like compounds in breath is shown in Table 1. The most important examples are discussed in this section, to illustrate the state-of-the-art in the field in more detail. The compounds chosen are examples of quite low volatility and representative drug-like structures. Endogenous metabolites, which may have drug-like properties are not mentioned.

    A. Propofol

    Propofol is a frequently used drug to induce and maintain anesthesia. It is usually administrated intravenously. It is relatively short acting; therefore it is continuously infused after the first injection to reach the initial anesthesia or sedation. Plasma concentrations of around 1 µg/mL are used for sedation and 8–7 µg/mL for anesthesia (Smith et al., 1994). Propofol was detected in real time by PTR and SIFT–MS as well as off-line by SPME-GC-MS (Kamysek et al., 2011). The reported concentrations in exhaled breath are comparable between all the studies. Propofol at a plasma concentration of 1–11 µg/mL leads to exhaled concentration in the range of 0–39 ppbV (0–280 ng/L). Propofol is quite lipophilic and compared to other compounds, quite volatile. However, propofol is already considered to be a compound with low volatility (bp 256°C/Henry constant 1.48 × 10−5 atm m3/mol). PTR-MS as a commercial system thus provides the sufficient sensitivity to monitor propofol in exhaled air.

    Recently, the correlation between blood and exhaled breath concentrations of propofol was investigated by Kamysek and co-workers in an animal model (Kamysek et al., 2011). Figure 12 shows the pharmacokinetics of propofol after stomach administration in anesthetized animals during artificial ventilation. This graph underscored the need for monitoring exhaled drugs. The different kinetics, observed depend on the dose and individual metabolism.


    Figure 12. A curve showing exhaled propofol concentration after injecting propofol into the stomach (via a stomach tube). After intubation, patients received a bolus injection of 2 mg/kg propofol (time 0). Exhaled propofol was measured with a proton transfer reaction mass spectrometer and the moving averages of 10 replicates are indicated here as solid lines. An obvious surge in exhaled propofol after the administration of propofol was observed in all patients. Reprinted with permission from Takita et al. (2007). Copyright 2011 Lippincott Williams & Wilkins.

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    B. Fentanyl

    Fentanyl is a synthetic opioid used for anesthesia and analgesia. Its use is comparable to morphine, but the dose required is approximately 100 times lower for the same effect. Fentanyl is mostly administered by intravenous, transdermal, or sublingual routes. Fentanyl is quite lipophilic and significantly less volatile than propofol.

    Wang et al. (2009) reported the detection of fentanyl in exhaled breath by SPME GC-MS. In this study, children (body weights around 40 kg) were treated with relatively high doses (0.6–1.5 mg) of fentanyl. Concentration in the range of 20 ng/L was found in exhaled breath, which is fairly high compared to the very low Henry constant (1.66 × 10−11 atm m3/mol). Despite its low volatility, and probably due to its significant lipophilicity (log P = 3.9) and the relatively small molecular weight (336 Da), this drug is expected to diffuse easily through the alveolar epithelial cells and therefore to be exhaled as part of the aerosol droplets.

    Proof that fentanyl is exhaled is also confirmed by the work of Gold et al. (2006, 2010), which showed that operation theaters and artificial ventilators are contaminated with fentanyl. Fentanyl in the hospital environment is usually used intravenously and the only logical explanation for their finding is that it was exhaled. However, fentanyl was not measured in real-time. Grossherr et al. (2009b) monitored fentanyl and propofol by PTR-MS, but found that fentanyl could not be detected in real-time by this system. Finally, Berchtold et al. (2011) showed that fentanyl is detectable by APCI or EESI in the gas phase down to 248 fmol/sec, which would refer to 5 ng/L (breathing of 1 L/min). This is theoretically sufficient to monitor fentanyl in exhaled breath. However, this value was measured with standards and could be significantly changed if the same is measured in real patients.

    C. Methadone

    Methadone is an opioid drug with a relatively high lipophilicity and low volatility. It is used in the treatment of heroin abuse with usual daily doses of 80–120 mg (Joseph et al., 2000). Beck et al. (2011a) showed that methadone is exhaled at relatively high concentrations of 22–1,147 pg/L. The study was carried out with participants who were drug abusers undergoing treatment. Each received methadone doses of approximately 100 mg per day and breath was trapped on filters and extracted for GC-MS analysis. Despite the fact that only offline measurements were made, this study represents a good example for the analysis of non-volatile drugs in exhaled breath.

    D. Nicotine

    Nicotine is the main addictive drug in tobacco products. Typical nicotine concentrations in plasma are up to 15 ng/mL (Benowitz et al., 1994). Although it is not used as a therapeutic drug treatment (besides as smoking replacement therapy), it is a convenient model for studying compound passage in exhaled breath, especially since it is legally available, and does not require complicated medical evaluation prior to application.

    Ding et al. (2009) used extractive ESI to ionize nicotine after smoking. Real-time measurements were performed, and approximately 5.5–6.1 ng/L as peak concentrations (two different subjects) were observed. Although the concentration was determined at several stages, the dynamics was plotted as a relative signal only (not quantified). Additionally, the main metabolite of nicotine, cotinine was shown to have a very typical kinetic behavior too. Berchtold et al. (2011) detected nicotine in a comparable setup via APCI. This study showed the pharmacokinetics of nicotine in the range of 1–6 ng/L, which is comparable to the study of Ding et al. Figure 8 shows the quantification and pharmacokinetics of nicotine in real time.

    E. Valproic Acid

    Valproic acid (VPA) is primarily used as an antiepileptic drug. Doses of 900–2,400 mg (8–39 mg/kg body weight) per day are usually administrated orally (Mattson et al., 1978). VPA has a broad spectrum of antiepileptic effects and is distributed in all organs (Aly & Abdel-Latif, 1980). VPA is a typical drug that needs a constant, relatively high dose to show sustaining effects (Krämer & Walden, 2002), resulting thus in high plasmatic concentrations. 3-Heptanone was identified as a potential marker for VPA in exhaled breath by PTR-MS, but it was not possible to match the exhaled concentration with VPA blood values (Erhart et al., 2009). A more recent study by Gamez et al. (Gamez et al., 2011) using EESI showed a different metabolite. At m/z 160, an intense signal is observed in patients under VPA treatment. This signal was assigned to an ammonium complex of a new VPA metabolite (4-OH-VPA-gamma lactone). The pharmacokinetics and the relation between EESI signal and plasma values are shown in Figure 13. The example of VPA shows that besides non-metabolized drugs, exhaled breath can be a matrix used for the detection of new unknown metabolites.


    Figure 13. Top: Signal variation of the exhaled breath VPA marker at m/z = 160 as a function of time for a volunteer taking a daily dose of four Depakines Chrono 500 tablets (m) and for a volunteer who took a single dose of two tablets. In the single dose experiment, the elimination follows first order kinetics with a half-life of 9.24 hr. Bottom: Correlation of the signal intensity at m/z = 143 with the free VPA fraction measured in blood. The dashed lines indicate 95% confidence bands around the linear fit (solid line) with y = 7.7601x−1 (R2 = 0.89). Reprinted with permission from Gamez et al. (2011). Copyright 2011 Royal Society of Chemistry.

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    1. Top of page
    2. Abstract

    Breath is an easily accessible matrix for patient monitoring and, compared to blood or urine, it represents a matrix of relatively low complexity. The respiratory system comprises a large and very thin exchange surface, which allows compounds to diffuse from blood into breath. Therefore, exhaled breath consists of many compounds, which originate from the blood. A large number of compounds has been detected in exhaled breath. The concentration of these compounds ranges from ppm (µg/L) to ppt (pg/L), where compounds of higher volatility and lipophilicity are exhaled at higher concentrations. The pharmacokinetics, which have been monitored for nicotine, VPA, and propofol, suggest a close relationship between blood and breath concentrations. To measure volatile compounds, sub-ambient methods such as EI-MS, SIFT-MS, or PTR-MS seem to provide the best sensitivity. For compounds with Henry constants below 10−6 atm m3/mol, ambient ionization techniques such as APCI, EESI, and SESI are the best choice for real-time measurements. Nevertheless, the detection of compounds of low volatility, which includes most drugs and their metabolites, is still a big challenge for real-time breath analysis because of their low concentration in breath (pg/L). Therefore, off-line techniques such as EBC analysis are very important in providing complementary information. The sensitivity of an ambient ionization technique such as SESI can be enhanced through the use of atmospheric pressure ion funnels, which provide a 1,000-fold improvement in sensitivity.

    Mass spectrometers for mobile applications (for on-site monitoring of patients), are commercially available for sub-ambient ionization methods (PTR-MS) only. Although there have been some developments for mobile ambient mass spectrometers, a lot of effort is still required to arrive at a fully operational setup for on-site APCI, EESI, or SESI measurements. Examples such as propofol, nicotine, fentanyl, and methadone show that the monitoring of exhaled drugs is possible by ambient mass spectrometric techniques. The detection of many drugs might be possible in the near future.

    This field still faces many challenges and the real-time detection of drugs in breath is still at an early stage; however, the first important steps have been taken. We predict that real-time breath monitoring will become an important application for mass spectrometry, and will be of significant importance in future medical investigations.

    The most important figure of merit for detecting drugs of low volatility in exhaled breath is sensitivity. A well-optimized ambient ionization system based on APCI or SESI, supported by an ion funnel system seems to be best strategy to detect compounds of a volatility and lipophilicity lower than fentanyl. Combining this with and a mobile mass spectrometer is also important. To operate a mobile set-up at the highest level of robustness, reliability, sensitivity, small bench top instruments such as a triple quadrupole or an ion trap should be used. Regarding the experimental design, the analysis of exhaled breath during artificial ventilation is an interesting scenario for real-time measurement. The stable breathing rate and volume support quantitative measurement and would allow investigating the relation between exhaled and blood concentrations more accurately. Finally, the suitability to use breath analysis for real-time monitoring has to be proven.


    1. Top of page
    2. Abstract

    atmospheric pressure chemical ionization


    deoxyribonucleic acid


    exhaled breath condensate


    extractive electrospray ionization


    electron impact


    epithelial lining fluid


    electrospray ionization


    electron volt (1.602 × 10−19 J)


    gas chromatography


    gas chromatography mass spectrometry


    high performance liquid chromatography


    liquid chromatography mass spectrometry

    Log P

    logarithmic partition coefficient octanole/water


    mol, number of molecules, 6.022 × 1023


    mass spectrometry


    proton transfer reaction


    secondary electrospray ionization


    selected ion flow tube mass spectrometry


    solid phase microextraction


    therapeutic drug monitoring




    volatile organic compound


    1. Top of page
    2. Abstract

    We thank Pablo M-L Sinues (ETH) and Lukas Meier for reviewing the manuscript and their helpful suggestions. We thank the Swiss National Science Foundation for financial support (grant no. K-23K1-122264).


    1. Top of page
    2. Abstract
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