Application and uses of electronic noses for clinical diagnosis on urine samples: A review

The electronic nose is able to provide useful information through the analysis of the volatile organic compounds in body fluids, such as exhaled breath, urine and blood. This paper focuses on the review of electronic nose studies and applications in the specific field of medical diagnostics based on the analysis of the gaseous headspace of human urine, in order to provide a broad overview of the state of the art and thus enhance future developments in this field. The research in this field is rather recent and still in progress, and there are several aspects that need to be investigated more into depth, not only to develop and improve specific electronic noses for different diseases, but also with the aim to discover and analyse the connections between specific diseases and the body fluids odour. Further research is needed to improve the results obtained up to now; the development of new sensors and data processing methods should lead to greater diagnostic accuracy thus making the electronic nose an effective tool for early detection of different kinds of diseases, ranging from infections to tumours or exposure to toxic agents

Innovative diagnostic methods for early prostate cancer detection through urine analysis: A review

Prostate cancer is the second most common cause of cancer death among men. It is an asymptomatic and slow growing tumour, which starts occurring in young men, but can be detected only around the age of 40-50. Although its long latency period and potential curability make prostate cancer a perfect candidate for screening programs, the current procedure lacks in specificity. Researchers are rising to the challenge of developing innovative tools able of detecting the disease during its early stage that is the most curable. In recent years, the interest in characterisation of biological fluids aimed at the identification of tumour-specific compounds has increased significantly, since cell neoplastic transformation causes metabolic alterations leading to volatile organic compounds release. In the scientific literature, different approaches have been proposed. Many studies focus on the identification of a cancer-characteristic “odour fingerprint” emanated from biological samples through the application of sensorial or senso-instrumental analyses, others suggest a chemical characterisation of biological fluids with the aim of identifying prostate cancer (PCa)-specific biomarkers. This paper focuses on the review of literary studies in the field of prostate cancer diagnosis, in order to provide an overview of innovative methods based on the analysis of urine, thereby comparing them with the traditional diagnostic procedures

Transferable Odor Differentiation Models for Infectious Disease Diagnostics

__Abstract__ In recent years the interest for the application of an electronic nose (eNose) in medical Diagnostics is increasing. There is a need for this since eNose Diagnostics is non-invasive, easy to run, fast and cheap. The eNoses, now on the market, however, turn out to be unsuitable for large-scale application. This is mainly due to insufficient reproducibility of measurement results. In this work an eNose is used which is cheap and suited for mass applications. The usage of advanced temperature control guarantees the reproducibility between eNoses. In practice, this means that a once developed analysis model for a specific disease easily can be transferred to any number of other eNoses. Application of mass-produced components keeps the cost low. In the research it is shown that temperature variation is the main cause of the significant differences in measurement characteristic between the metal oxide sensors on which the eNose is based. To illustrate the practical applicability pilot studies are described for sepsis (bacterial infection of the blood), tuberculosis (TB) and metritis (infection of the uterus in cows). In the sepsis and metritis studies the measurements were conducted in the headspace of the blood cultures and uterus mucus respectively. In the tuberculosis study the exhaled breath of patients analyzed. For the sepsis diagnostics 30 eNoses are used to identify 11 to identify clinical relevant pathogens in blood. The eNose can significantly speed up the diagnostic process: on average 78% of the pathogens were correctly identified within 6-8 hours after inoculation in contrast to the 24 hours typically needed with the current methods. The TB-study was conducted in Dhaka (Bangladesh) with 3 eNoses. It turned out to be possible to distinguish between healthy people and those with active TB infection [sensitivity 93.5%, specificity 85.3%] but also to identify an active TB infection in a group of TB suspects [sensitivity 76.5%, specificity 87.2%]. These results are significantly better than the much-used screening test based on microscopy. Currently there is no objective diagnosis for metritis. A vet performs the diagnosis based on a number of characteristics such as temperature and appearance of the sample. The eNose proved to be more reliable and objective than a control panel of veterinarians [sensitivity 100%, specificity 91.6%]

Advances in Electronic-Nose Technologies Developed for Biomedical Applications

The research and development of new electronic-nose applications in the biomedical field has accelerated at a phenomenal rate over the past 25 years. Many innovative e-nose technologies have provided solutions and applications to a wide variety of complex biomedical and healthcare problems. The purposes of this review are to present a comprehensive analysis of past and recent biomedical research findings and developments of electronic-nose sensor technologies, and to identify current and future potential e-nose applications that will continue to advance the effectiveness and efficiency of biomedical treatments and healthcare services for many years. An abundance of electronic-nose applications has been developed for a variety of healthcare sectors including diagnostics, immunology, pathology, patient recovery, pharmacology, physical therapy, physiology, preventative medicine, remote healthcare, and wound and graft healing. Specific biomedical e-nose applications range from uses in biochemical testing, blood-compatibility evaluations, disease diagnoses, and drug delivery to monitoring of metabolic levels, organ dysfunctions, and patient conditions through telemedicine. This paper summarizes the major electronic-nose technologies developed for healthcare and biomedical applications since the late 1980s when electronic aroma detection technologies were first recognized to be potentially useful in providing effective solutions to problems in the healthcare industry

Data reduction in headspace analysis of blood and urine samples for robust bacterial identification

This paper demonstrates the application of chemical headspace analysis to the problem of classifying the presence of bacteria in biomedical samples by using computational tools. Blood and urine samples of disparate forms were analysed using a Cyrano Sciences C320 electronic nose together with an Agilent 4440 Chemosensor. The high dimensional data sets resulting from these devices present computational problems for parameter estimation of discriminant models. A variety. of data reduction and pattern recognition techniques were employed in an attempt to optimise the classification process. A 100% successful classification rate for the blood data from the Agilent 4440 was achieved by combining a Sammon mapping with a radia( basis function neural network. In comparison a successful classification rate of 80% was achieved for the urine data from the C320 which were analysed using a novel nonlinear time series model. (c) 2005 Elsevier Ireland Ltd. All rights reserve

Electronic nose implementation for biomedical applications

The growing rate of diabetes and undiagnosed diabetes related diseases is becoming a worldwide major health concern. The motivation of this thesis was to make use of a technology called the ‘electronic nose’ (eNose) for diagnosing diseases. It presents a comprehensive study on metabolic and gastro-intestinal disorders, choosing diabetes as a target disease. Using eNose technology with urinary volatile organic compounds (VOCs) is attractive as it allows non-invasive monitoring of various molecular constituents in urine. Trace gases in urine are linked to metabolic reactions and diseases. Therefore, urinary volatile compounds were used for diagnosis purposes in this thesis. The literature on existing eNose technologies, their pros and cons and applications in biomedical field was thoroughly reviewed, especially in detecting headspace of urine. Since the thesis investigates urinary VOCs, it is important to discover the stability of urine samples and their VOCs in time. It was discovered that urine samples lose their stability and VOCs emission after 9 months. A comprehensive study with 137 diabetic and healthy control urine samples was done to access the capability of commercially available eNose instruments for discrimination between these two groups. Metal oxide gas sensor based commercial eNose (Fox 4000, AlphaMOS Ltd) and field asymmetric ion mobility spectrometer (Lonestar, Owlstone Ltd) were used to analyse volatiles in urinary headspace. Both technologies were able to distinguish both groups with sensitivity and specificity of more than 90%. Then the project moved onto developing a Non-dispersive infrared (NDIR) sensor system that is non-invasive, low-cost, precise, rapid, simple and patient friendly, and can be used at both hospitals and homes. NDIR gas sensing is one of the most widely used optical gas detection techniques. NDIR system was used for diagnosing diabetes and gastro related diseases from patient’s wastes. To the best of the authors’ knowledge, this is the first and only developed tuneable NDIR eNose system. The developed optical eNose is able to scan the whole infrared range between 3.1μm and 10.5 μm with step size of 20 nm. To simulate the effect of background humidity and temperature on the sensor response, a gas test rig system that includes gas mixture, VOC generator, humidity generator and gas analyser was designed to enable the user to have control of gas flow, humidity and temperature. This also helps to find out system’s sensitivity and selectivity. Finally, after evaluating the sensitivity and selectivity of optical eNose, it was tested on simple and complex odours. The results were promising in discriminating the odours. Due to insufficient sample batches received from the hospital, synthetic urine samples were purchased, and diabetic samples were artificially made. The optical eNose was able to successfully separate artificial diabetic samples from non-diabetic ones

Mimicking the human olfactory system: a portable e-­mucosa

The study of electronic noses has been an active area of research for over 25 years. Commercial instruments have been successfully deployed within niche application areas, for example, the food, beverage and pharmaceutical industries. However, these instruments are still inferior to their human counterparts and have not achieved mainstream success. Humans can distinguish and identify many thousands of different aromas, even at very low concentration levels, with relative ease. The human olfactory system is extremely sophisticated, which allows it to out-­perform artificial instruments. Though limited, artificial instruments can provide a lower cost option to specific problems and can be an alternative to the use of organoleptic panels. Most existing commercial electronic nose (e-­nose) instruments are expensive, bulky, desktop units, requiring a PC to operate. In addition, these instruments usually require a trained operator to gather and analyse the data. Motivated to improve the performance, size and cost of e-­nose instruments, this research aims to extract biological principles from the mammalian olfactory system to aid the implementation of a portable e-­nose instrument. This study has focused on several features of the biological system that may provide the key to its superior performance. Specifically, the large number of different olfactory receptors and the diversity of these receptors; the nasal chromatograph effect; stereo olfaction; sniff rate and odour conditioning. Based on these features, a novel, portable, cost effective instrument, called the Portable e-­Mucosa (PeM), has been designed, implemented and tested. The main components of the PeM are three sensor arrays each containing 200 carbon black composite chemoresistive sensors (totalling 600 sensors with 24 different tunings) mimicking the large number of olfactory receptors and two gas chromatographic columns (coated with non-­polar and polar compounds to maximise the discrimination) emulating the “nasal chromatograph” effect of the human mucus. A preconcentrator based on thermal desorption is also included as an odour collection system to further improve the instrument. The PeM provides USB and Multimedia Memory Card support for easy communication with a PC. The instrument weighs 700g and, with dimensions of 110 x 210 x 110 mm, is slightly larger than the commercial Cyranose 320 (produced by Smiths Detection). This novel instrument generates ‘spatio-­temporal’ data and when coupled with an appropriate pattern recognition algorithm, has shown an enhanced ability to discriminate between odours. The instrument successfully discriminates between simple odours (ethanol, ethyl acetate and acetone) and more complex odours (lavender, ylang ylang, cinnamon and lemon grass essential oils). This system can perhaps be seen as a foundation for a new generation of e-noses

Black box and mechanistic modelling of electronic nose systems

Electronic nose systems have been in existence for around 20 years or more. The ability to mimic the function of the mammalian olfactory system is a very tempting goal. Such devices would offer the possibility of rapid chemical screening of samples. To gain a detailed insight into the operation of such systems it is proposed to carry out a systems modelling analysis. This thesis reports such an analysis using black box and mechanistic models. The nature and construction of electronic nose systems are discussed. The challenges presented by these systems in order to produce a truly electronic nose are analysed as a prelude to systems modelling. These may be summarised as time and environmental dependent behaviour, information extraction and computer data handling. Model building in general is investigated. It is recognised that robust parameter estimation is necessary to build good models of electronic nose systems. A number of optimisation algorithms for parameter estimation are proposed and investigated, these being gradient search, genetic algorithms and the support vector method. It is concluded that the support vector method is most robust, although the genetic algorithm approach shows promise for initial parameter value estimation. A series of investigations are reported that involve the analysis of biomedical samples. These samples are of blood, urine and bacterial cultures. The findings demonstrate that the nature of such samples, such as bacterial content and type, may be accurately identified using an electronic nose system by careful modelling of the system. These findings also highlight the advantages of data set reduction and feature extraction. A mechanistic model embodying the operating principles of carbon black-polymer sensors is developed. This is validated experimentally and is used to investigate the environmental dependencies of electronic nose systems. These findings demonstrate a clear influence of environmental conditions on the behaviour of carbon black-polymer sensors and these should be considered when designing future electronic nose systems. The findings in this thesis demonstrate that careful systems modelling and analysis of electronic nose systems allows a greater understanding of such systems

Microbial and non-microbial volatile fingerprints : potential clinical applications of electronic nose for early diagnoses and detection of diseases

This is the first study to explore the potential applications of using qualitative volatile fingerprints (electronic nose) for early detection and diagnosis of diseases such as dermatophytosis, ventilator associated pneumonia and upper gastrointestinal cancer. The investigations included in vitro analysis of various dermatophyte species and strains, antifungal screening, bacterial cultures and associated clinical specimens and oesophageal cell lines. Mass spectrometric analyses were attempted to identify possible markers. The studies that involved e-nose comparisons indicated that the conducting polymer system was unable to differentiate between any of the treatments over the experimental period (120 hours). Metal oxide-based sensor arrays were better suited and differentiated between four dermatophyte species within 96 hours of growth using principal component analysis and cluster analysis (Euclidean distance and Ward’s linkage) based on their volatile profile patterns. Studies on the sensitivity of detection showed that for Trichophyton mentagrophytes and T. rubrum it was possible to differentiate between log3, log5 and log7 inoculum levels within 96 hours. The probabilistic neural network model had a high prediction accuracy of 88 to 96% depending on the number of sensors used. Temporal volatile production patterns studied at a species level for a Microsporum species, two Trichophyton species and at a strain level for the two Trichophyton species; showed possible discrimination between the species from controls after 120 hours. The predictive neural network model misclassified only one sample. Data analysis also indicated probable differentiation between the strains of T. rubrum while strains of T. mentagrophytes clustered together showing good similarity between them. Antifungal treatments with itraconazole on T. mentagrophytes and T. rubrum showed that the e-nose could differentiate between untreated fungal species from the treated fungal species at both temperatures (25 and 30°C). However, the different antifungal concentrations of 50% fungal inhibition and 2 ppm could not be separated from each other or the controls based on their volatiles. Headspace analysis of bacterial cultures in vitro indicated that the e-nose could differentiate between the microbial species and controls in 83% of samples (n=98) based on a four group model (gram-positive, gram-negative, fungi and no growth). Volatile fingerprint analysis of the bronchoalveolar lavage fluid accurately separated growth and no growth in 81% of samples (n=52); however only 63% classification accuracy was achieved with a four group model. 12/31 samples were classified as infected by the e-nose but had no microbiological growth, further analysis suggested that the traditional clinical pulmonary infection score (CPIS) system correlated with the e-nose prediction of infection in 68% of samples (n=31). No clear distinction was observed between various human cell lines (oesophageal and colorectal) based on volatile fingerprints within one to four hours of incubation, although they were clearly separate from the blank media. However, after 24 hours one of the cell lines could be clearly differentiated from the others and the controls. The different gastrointestinal pathologies (forming the clinical samples) did not show any specific pattern and thus could not be distinguished. Mass spectrometric analysis did not detect distinct markers within the fungal and cell line samples, but potential identifiers in the fungal species such as 3-Octanone, 1-Octen-3-ol and methoxybenzene including high concentration of ammonia, the latter mostly in T. mentagrophytes, followed by T. rubrum and Microsporum canis, were found. These detailed studies suggest that the approach of qualitative volatile fingerprinting shows promise for use in clinical settings, enabling rapid detection/diagnoses of diseases thus eventually reducing the time to treatment significantly.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Development of new analytical strategies for the determination of compounds of biological and environmental interest

[ES] La Tesis Doctoral que se presenta se centra en el desarrollo de metodologías analíticas basadas en la utilización de la cromatografía de gases (GC) como técnica de separación y encaminadas a conseguir una reducción significativa del esfuerzo necesario para llevar a cabo la etapa de tratamiento de muestra con el fin de minimizar costes y tiempo y reducir los errores asociados a esta etapa del proceso analítico. La Tesis consta de dos partes dedicadas ambas a la puesta a punto de metodologías que cumplan las características anteriormente descritas pero que difieren en el tipo de matriz de estudio, dedicándose la primera parte a muestras de suelo y la segunda a matrices biológicas. En todas las metodologías propuestas se utiliza un inyector de temperatura programada (PTV) para la transferencia de la muestra al sistema cromatográfico