Electronic noses are accurately able to literally sniff out cancers by analysing our breath

September 2022 Health Innovation Nalinee Pandey
Close up visualization of a smell moving towards a human nose.

A systematic review and meta-analysis have found that electronic noses (e-noses) are highly efficient and accurate in detecting cancer using exhaled breath. This review was published in the journal JAMA network open.

Volatile organic compounds (VOCs) are produced from the biochemical degradation processes in the body. They are released outside the body through an exhaled breath. Therefore, any changes in their levels can be a good indicator of diseases such as cancer.

E-noses are electronic devices that have been designed to detect any odours or flavours. They are being tested for their ability to detect human diseases, including cancer, accurately. Max Scheepers, MD, a PhD candidate in the department of surgery at GROW School for Oncology and Developmental Biology at Maastricht University in the Netherlands and colleagues systematically reviewed the literature regarding the use of e-noses in cancer detection.  

Superior diagnostic ability

Their meta-analysis found that e-noses are highly sensitive (90%) and specific (87%) in detecting cancer. The superior diagnostic ability of e-noses was seen in malignancies such as lung cancer, head and neck cancer, and colorectal cancer. However, the researchers warn about interpreting these findings as there was much of heterogeneity among the studies, a high risk of bias and a lack of standardisation.

Thyroid cancer

To address these issues, researchers have planned a proof of concept study in thyroid cancer where e-noses will be used to analyse the breath of the patients. Hopefully, the findings of the proposed investigation will address standardisation and reproducibility issues associated with e-nose cancer research.

Reference

Scheepers MHMC, Al-Difaie Z, et al. Diagnostic Performance of Electronic Noses in Cancer Diagnoses Using Exhaled Breath: A Systematic Review and Meta-analysis. JAMA Netw Open. 2022;5(6):e2219372