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.

We report the successful use of colorimetric arrays to identify chemical warfare agents (CWAs). Methods were developed to interpret and analyze a 73-indicator array with an entirely automated workflow. Using a cross-validated first-nearest-neighbor algorithm for assessing detection and identification performances on 632 exposures, at 30 min postexposure we report, on average, 78% correct chemical identification, 86% correct class-level identification, and 96% correct red light/green light (agent versus non-agent) detection. Of 174 total independent agent test exposures, 164 were correctly identified from a 30 min exposure in the red light/green light context, yielding a 94% correct identification of CWAs. Of 149 independent non-agent exposures, 139 were correctly identified at 30 min in the red light/green light context, yielding a 7% false alarm rate. We find that this is a promising approach for the development of a miniaturized, field-portable analytical equipment suitable for soldiers and first responders.

A colorimetric sensor array is a high-dimensional chemical sensor that is cheap, compact, disposable, robust, and easy to operate, making it a good candidate technology to detect pathogenic bacteria, especially potential bioterrorism agents like Yersinia pestis and Bacillus anthracis which feature on the Center for Disease Control and Prevention’s list of potential biothreats. Here, a colorimetric sensor array was used to continuously monitor the volatile metabolites released by bacteria in solid media culture in an Advisory Committee on Dangerous Pathogen Containment Level 3 laboratory. At inoculum concentrations as low as 8 colony-forming units per plate, 4 different bacterial species were identified with 100% accuracy using logistic regression to classify the kinetic profile of sensor responses to culture headspace gas. The sensor array was able to further discriminate between different strains of the same species, including 5 strains of Yersinia pestis and Bacillus anthracis. These preliminary results suggest that disposable colorimetric sensor arrays can be an effective, low-cost tool to identify pathogenic bacteria.

The World Health Organization has called for simple, sensitive, and non-sputum diagnostics for tuberculosis. We report development of a urine tuberculosis test using a colorimetric sensor array (CSA). The sensor comprised of 73 different indicators captures high-dimensional, spatiotemporal signatures of volatile chemicals emitted by human urine samples. The sensor responses to 63 urine samples collected from 22 tuberculosis cases and 41 symptomatic controls were measured under five different urine test conditions. Basified testing condition yielded the best accuracy with 85.5% sensitivity and 79.5% specificity. The CSA urine assay offers desired features needed for tuberculosis diagnosis in endemic settings.