The Accuracy of Breath Analysis for Lung Cancer Detection Using a Portable Colorimetric Sensor Array System

Abstract

PURPOSE: A non-invasive test, capable of accurately identifying early stage lung cancer, has the potential to improve the clinical management of lung cancer. The pattern of volatile organic compounds in the breath has been shown to be able to distinguish between those with and those without lung cancer. We previously reported on the use of a colorimetric sensor array system for this purpose. This system uses sensors with chemically responsive colored dyes printed on a disposable cartridge. The dyes change their colors in response to the chemical mixture that passes over them. The pattern of color changes represents the output of the sensor. A crude portable version of this device, capable of being applied in an office setting, has been developed. The purpose of this study was to determine the accuracy of this portable system. METHODS: Subjects with biopsy proven lung cancer and controls with benign lung nodules or similar demographics were recruited to participate. Study subjects performed tidal breathing for 5 minutes. The exhaled breath was drawn across the sensor array. The sensor was imaged every 30 seconds. Color changes were converted to numerical values for changes in the red, green, and blue spectra. Logistic classification models were developed from this data and validated using boostrap validation techniques. RESULTS: 99 patients with lung cancer and 101 control subjects participated in the study. The mean age of the entire group was 64.2 years, 53% were male, and 82.5% had a smoking history. The model identified 19 significant variables with a combined p-value of 0.0087. The AUC of the ROC curve for the model was 0.82. The AUC for the model validation was 0.74 (e.g. specificity of 79% at a sensitivity of 70%). CONCLUSION: A portable version of a colorimetric sensor array system has moderate accuracy in identifying patients with lung cancer. CLINICAL IMPLICATIONS: Advances in the colorimetric sensor array technology and breath sampling methodology may allow this sensor system to be developed into a clinically useful tool.