Cancer diagnosis is typically delayed to the late stages of disease due to the asymptomatic nature of cancer in its early stages. Cancer screening offers the promise of early cancer detection, but most conventional diagnostic methods are invasive and remain ineffective at early detection. Breath analysis is, however, non-invasive and has the potential to detect cancer at an earlier stage by analyzing volatile biomarkers in exhaled breath. This paper summarizes breath sampling techniques and recent developments of various array-based sensor technologies for breath analysis. Significant advancements were made by a number of different research groups in the development of nanomaterial-based sensor arrays, and the ability to accurately distinguish cancer patients from healthy controls based on the volatile organic compounds (VOCs) in exhaled breath has been demonstrated. Optical sensors based on colorimetric sensor array technology are also discussed, where preliminary clinical studies suggest that metabolic VOC profiles could be used to accurately diagnose various forms of lung cancer. Recent studies have demonstrated the potential of using metabolic VOCs for cancer detection, but further standardization and validation is needed before breath analysis can be widely adopted as a clinically useful tool.
Sepsis is a medical emergency demanding early diagnosis and tailored antimicrobial therapy. Every hour of delay in initiating effective therapy measurably increases patient mortality. Blood culture is currently the reference standard for detecting bloodstream infection, a multistep process which may take one to several days. Here, we report a novel paradigm for earlier detection and the simultaneous identification of pathogens in spiked blood cultures by means of a metabolomic "fingerprint" of the volatile mixture outgassed by the organisms. The colorimetric sensor array provided significantly faster detection of positive blood cultures than a conventional blood culture system (12.1 h versus 14.9 h, P < 0.001) while allowing for the identification of 18 bacterial species with 91.9% overall accuracy within 2 h of growth detection. The colorimetric sensor array also allowed for discrimination between unrelated strains of methicillin-resistant Staphylococcus aureus, indicating that the metabolomic fingerprint has the potential to track nosocomial transmissions. Altogether, the colorimetric sensor array is a promising tool that offers a new paradigm for diagnosing bloodstream infections.
Clinical microbiology automation is currently limited by the lack of an in-plate culture identification system. Using an inexpensive, printed, disposable colorimetric sensor array (CSA) responsive to the volatiles emitted into plate headspace by microorganisms during growth, we report here that not only the presence but the species of bacteria growing in plate was identified before colonies are visible. In 1894 trials, 15 pathogenic bacterial species cultured on blood agar were identified with 91.0% sensitivity and 99.4% specificity within 3 hours of detection. The results indicate CSAs integrated into Petri dish lids present a novel paradigm to speciate microorganisms, well-suited to integration into automated plate handling systems.
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