9,011 research outputs found

    Advances in Electronic-Nose Technologies Developed for Biomedical Applications

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    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

    Volatile organic compounds in breath can serve as a non-invasive diagnostic biomarker for the detection of advanced adenomas and colorectal cancer

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    Contains fulltext : 220031.pdf (Publisher’s version ) (Open Access)BACKGROUND: Colorectal cancer (CRC) is the third most common cancer diagnosis in the Western world. AIM: To evaluate exhaled volatile organic compounds (VOCs) as a non-invasive biomarker for the detection of CRC and precursor lesions using an electronic nose. METHODS: In this multicentre study adult colonoscopy patients, without inflammatory bowel disease or (previous) malignancy, were invited for breath analysis. Two-thirds of the breath tests were randomly assigned to develop training models which were used to predict the diagnosis of the remaining patients (external validation). In the end, all data were used to develop final-disease models to further improve the discriminatory power of the algorithms. RESULTS: Five hundred and eleven breath samples were collected. Sixty-four patients were excluded due to an inadequate breath test (n = 51), incomplete colonoscopy (n = 8) or colitis (n = 5). Classification was based on the most advanced lesion found; CRC (n = 70), advanced adenomas (AAs) (n = 117), non-advanced adenoma (n = 117), hyperplastic polyp (n = 15), normal colonoscopy (n = 125). Training models for CRC and AAs had an area under the curve (AUC) of 0.76 and 0.71 and blind validation resulted in an AUC of 0.74 and 0.61 respectively. Final models for CRC and AAs yielded an AUC of 0.84 (sensitivity 95% and specificity 64%) and 0.73 (sensitivity and specificity 79% and 59%) respectively. CONCLUSIONS: This study suggests that exhaled VOCs could potentially serve as a non-invasive biomarker for the detection of CRC and AAs. Future studies including more patients could further improve the discriminatory potential of VOC analysis for the detection of (pre-)malignant colorectal lesions. (https://clinicaltrials.gov Identifier NCT03488537)

    analysis of exhaled breath fingerprints and volatile organic compounds in copd

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    Exhaled air contains many volatile organic compounds (VOCs) produced during human metabolic processes, in both healthy and pathological conditions. Analysis of breath allows studying the modifications of the profile of the exhaled VOCs due to different disease states, including chronic obstructive pulmonary disease (COPD). The early diagnosis of COPD is complicated and the identification of specific metabolic profiles of exhaled air may provide useful indication to better identify the disease. The aim of our study was to characterize the specific exhaled VOCs by means of the electronic nose and by solid phase micro-extraction associated to gas chromatography–mass spectrometry (SPME GC-MS). Exhaled air was collected and measured in 34 subjects, 7 healthy and 27 former smokers affected by COPD (GOLD 1–4). The signals of the electronic nose sensors were higher in COPD patients with respect to controls, and allowed to accurately classify the studied subjects in healthy or COPD. GC-MS analysis identified 37 VOCs, nine of which were significantly correlated with COPD. In particular the concentration of two of these were positively correlated whereas seven were negatively correlated with COPD. The partial least squares discriminant analysis (PLS-DA) carried out with these nine VOCs produced a significant predictive model of disease. This study shows that COPD patients exhibit qualitative and quantitative differences in the chemical compositions of exhale. These differences are detectable both by the GC-MS and the six-sensor e-nose. The use of electronic nose may represent a suitable, non-invasive diagnostic tool for characterization of COPD

    Using Volatile Organic Compounds In Exhaled Breath As A Biomarker For Early Lung Cancer Detection: A Systematic Review

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    Lung cancer has become the most commonly diagnosed cancer and the leading cause of cancer deaths globally. The major problem of the high mortality rate is the late diagnosis. Conventional methods utilized for clinical detection of lung cancer have employed expensive and invasive medical procedures that cause stress, discomfort, and pain to patients, and have demonstrated low sensitivity, substantial false negatives, and risk of radiation exposure. The drawbacks obviate their applicability to large-scale, population-wide screening efforts. This paper reviews the applications of using volatile organic compounds (VOCs) in exhaled breath as a potential approach for early lung cancer detection. An electronic search was conducted in PubMed and Scopus. A total of 41 studies were included in this review. The sampling method of exhaled breath employed in most of the included studies were leak-proof Tedlar bags. Mass spectrometry and electronic noses were two main techniques used in breath sample detection. In the recent years, electronic noses gained more popularity due to their portability and cost-effectiveness. In this review, a total of 40 VOCs, originated from both endogenous and exogenous sources, were found to be significant in discriminating between lung cancer patients and healthy controls in two or more of the included studies. The included studies demonstrated substantial sensitivity, specificity, and accuracy of the method. Overall, the results showed that VOCs in exhaled breath is a promising biomarker for early detection of lung cancer. However, the large-scale practice of this method is constrained by the lack of standardized breath collection and analysis system and putative exhaled VOC biomarkers. Further studies with consistent sampling protocols should be used to demonstrate the reproducibility and repeatability of the detection tool before they are applied in clinical practice

    Alteration of the Exhaled Volatile Organic Compound Pattern in Colorectal Cancer Patients after Intentional Curative Surgery—A Prospective Pilot Study

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    As current follow-up modalities for colorectal carcinoma (CRC) have restricted sensitivity, novel diagnostic tools are needed. The presence of CRC changes the endogenous metabolism, resulting in the release of a specific volatile organic compounds (VOC) pattern that can be detected with an electronic nose or AeonoseTM. To evaluate the use of an electronic nose in the follow-up of CRC, we studied the effect of curative surgery on the VOC pattern recognition using AeonoseTM. A prospective cohort study was performed, in which 47 patients diagnosed with CRC were included, all of whom underwent curative surgical resection. Breath testing was performed before and after surgery using the AeonoseTM. A machine learning model was developed by discerning between the 94 pre-and postoperative breath samples. The training model differentiated between the pre-and postoperative CRC breath samples with a sensitivity and specificity of 0.78 (95%CI 0.61–0.90) and 0.73 (95%CI 0.56–0.86), respectively, with an accuracy of 0.76 (95%CI 0.66–0.85), and an area under the curve of 0.79 (95%CI 0.68–0.89). The internal validation of the test set resulted in an accuracy of 0.75 (95%CI 0.51–0.91) and AUC of 0.82 (95%CI 0.61–1). In conclusion, our results suggest that the VOC pattern of CRC patients is altered by curative surgery in a short period, indicating that the exhaled VOCs might be closely related to the presence of CRC. However, to use AeonoseTM as a potential diagnostic tool in the clinical follow-up of CRC patients, the performance of the models needs to be improved through further large-scale prospective research.</p

    Sensor Technology for Opening New Pathways in Diagnosis and Therapeutics of Breast, Lung, Colorectal and Prostate Cancer

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    This study analyzes the interaction between sensor research and technology and different types of cancer (breast, lung, colorectal, and prostate) with the goal of detecting new directions for improving diagnosis and therapeutics in medicine. This study develops an approach to computational scientometrics based on data from the Web of Science from the 1991 to 2021 period. The results of this analysis show the vital role of biosensors and electrochemical biosensors applied in breast cancer, lung cancer, and prostate cancer research. Instead, scientific research of optical sensors is developing main technological trajectories in breast, prostate, and colorectal cancer for improving diagnostics. Finally, oxygen sensor research has a main technological development in breast and lung cancer for new applications in breath analysis directed to treatment processes. Preliminary results presented here clearly illustrate the evolutionary paths of sensor research and technologies that have great potential for developing incremental and radical innovations in cancer diagnosis and therapies. These conclusions are, of course, tentative. There is a need for much more detailed research based on other aspects and factors for detecting stable technological trajectories that can foster the technology transfer of new sensor in cancer research for improving diagnosis and therapeutics, reducing, whenever possible, world-wide mortality of cancer in society.JEL Classification: I10, O30, O31, O32; O33. Doi: 10.28991/HIJ-2022-03-03-010 Full Text: PD
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