Metabolic processes are different in those with and without lung cancer. Cleveland Clinic researchers have developed a colorimetric sensor that analyzes breath to identify lung cancer and characterize cancer histology. The sensor evaluates the activity of antioxidant pathways, the handling of energy stress, and the metabolism of specific volatile organic compounds.
The technology used included nanoporous matrix for chemically reactive colorants. The study involved patients with biopsy-proven untreated lung cancer, patients with a high clinical suspicion for lung cancer, and control subjects. Samples were obtained while subjects performed tidal breathing through a volatile organic compound filter. The end tidal carbon dioxide level triggered the collection of the alveolar portion of the breath. Data were log-transformed to provide color values. The entire dataset was then reduced using univariate logistic regression. The sensor was optimized with samples from 288 subjects. Accuracy was then tested with samples from 236 patients.
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