Exhaled Breath Analysis Using a Novel Electronic Nose for Different Respiratory Disease Entities with Gas Chromatography Mass Spectrometry Validation: Prospective Study (Preprint)

Abstract

Electronic nose (eNose) can differentiate between healthy individuals and patients with specific respiratory diseases. However, its application in discriminating among various respiratory diseases is limited.

We aimed to investigate the feasibility of using a novel eNose to differentiate between patients with three respiratory disease entities, including lung cancer, pneumonia, and structural lung disease, and healthy control group. Additionally, we validated the results using gas chromatography mass spectrometry validation (GC-MS) quantitative analysis.

Patients with lung cancer, pneumonia, and structural lung diseases, along with healthy participants were recruited between May 2019 to July 2022. Exhaled breath samples were collected for eNose and GC-MS analysis. Breathprint features from eNose were analyzed using support vector machine model and leave-one-out cross-validation was performed.

A total of 263 participants (including 95 lung cancer, 59 pneumonia, 71 structural lung disease, and 38 healthy participants) were included. Three-dimensional linear discriminant analysis (LDA) showed a clear distribution of breathprints. The overall accuracy of eNose for four groups was 0.738 (194/263). The accuracy was 0.86 (61/71), 0.81 (77/95), 0.53 (31/59), and 0.66 (25/38) for structural lung disease, lung cancer, pneumonia, and control groups respectively. Pair-wise diagnostic performance comparison revealed excellent discriminant power (AUC:1-0.813) among four groups. The best performance was between structural lung disease and healthy controls (AUC:1), followed by lung cancer and structural lung disease (AUC:0.958). Volatile organic compounds revealed a high individual occurrence rate of cyclohexanone and N,N-dimethylacetamide in pneumonic patients, ethyl acetate in structural lung disease, and 2,3,4-trimethylhexane in lung cancer patients.

Our study demonstrated that the novel eNose can differentiate different respiratory diseases. The convenience, short turn-around time, and noninvasiveness of eNose make it a potential point-of-care test in clinical practice.