Noninvasive detection of COPD and Lung Cancer through breath analysis using MOS Sensor array based e-nose

ABSTRACT

Introduction

This paper describes the research work done toward the development of a breath analyzing electronic nose (e-nose), and the results obtained from testing patients with lung cancer, patients with chronic obstructive pulmonary disease (COPD), and healthy controls. Pulmonary diseases like COPD and lung cancer are detected with MOS sensor array-based e-noses. The e-nose device with the sensor array, data acquisition system, and pattern recognition can detect the variations of volatile organic compounds (VOC) present in the expelled breath of patients and healthy controls.

Materials and methods

This work presents the e-nose equipment design, study subjects selection, breath sampling procedures, and various data analysis tools. The developed e-nose system is tested in 40 patients with lung cancer, 48 patients with COPD, and 90 healthy controls.

Results

In differentiating lung cancer and COPD from controls, support vector machine (SVM) with 3-fold cross-validation outperformed all other classifiers with an accuracy of 92.3% in cross-validation. In external validation, the same discrimination was achieved by k-nearest neighbors (k-NN) with 75.0% accuracy.

Conclusion

The reported results show that the VOC analysis with an e-nose system holds exceptional possibilities in noninvasive disease diagnosis applications.

KEYWORDS:

• COPD
• lung cancer
• breath analysis
• volatile organic compounds
• electronic nose

Acknowledgments

The authors are thankful to all the participants enrolled in this study. We thank Dr. Youhan Sunny (Saintgits College of Engineering, Kerala) for his kind help in revising the manuscript. We also thank Dr. Philip Mathew, Ms. Linta Babu, and Ms. Nisha Oommen (Believers Church Medical College Hospital, Kerala) for their kind help in the breath sample collection.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.