Detection of non-small cell lung cancer by an electronic nose

Introduction: Lung cancer occupies the first place in cancer-related deaths. 15% of lung cancer cases present timely with localized, potentially curable disease. Therefore, a sensitive, non-invasive tool to detect lung cancer earlier is desired. Exhaled breath analysis by electronic nose technology measures volatile organic compounds (VOC's), which reflect pathological processes in the body. We aimed to determine the diagnostic accuracy of exhaled breath analysis by the Aeonose™ in non-small cell lung cancer (NSCLC).

Methods: Subjects diagnosed with NSCLC and healthy subjects breathed into the Aeonose™ (The eNose Company, Zutphen, The Netherlands) during 5 minutes. 3 Aeonoses were used, producing repeatable and interchangeable results. The diagnostic accuracy was prospectively studied in a multicentre study in 107 subjects. 60 Had a histopathologically confirmed diagnosis of NSCLC. Their exhaled breath prints were compared with 47 subjects without lung cancer. Data compression and artificial neural networks were used for the analysis of VOC data.

Results: The subjects had a mean age of 64.4±8.8 years and 53 (50%) were male. The optimal threshold to rule out NSCLC resulted in a sensitivity of 90% (54/60) with a specificity of 74% (35/47), positive predictive value of 82% (54/66), negative predictive value of 85% (35/41) and an area under the curve of 0.80.

Conclusion: The data suggest that electronic nose technology with the Aeonose™ can have a substantial added value in the non-invasive diagnostic workup in NSCLC. Data collection is still ongoing. With more subjects added (N=350 expected), the model can in all likelihood be further improved to increase sensitivity and negative predictive value, so no patient is missed.