Noninvasive detection of soft tissue sarcoma using volatile organic compounds in exhaled breath: a pilot study

Abstract

Aim: The aim of this pilot study was to assess whether an electronic nose can detect patients with soft tissue sarcoma (STS) based on volatile organic compound profiles in exhaled breath. Patients & methods: In this cross-sectional pilot study, patients with primary STS and healthy controls, matched on sex and age, were included for breath analysis. Machine learning techniques were used to develop the best-fitting model. Results: Fifty-nine breath samples were collected (29 STS and 30 control) from March 2018 to March 2022. The final model yielded a c-statistic of 0.85 with a sensitivity of 83% and specificity of 60%. Conclusion: This study suggests that exhaled volatile organic compound analysis could serve as a noninvasive diagnostic biomarker for the detection of STS with a good performance.

Plain language summary

Diagnosing soft tissue sarcoma (STS) among the large number of benign soft tissue tumors is challenging. There is a serious need for a novel and easy tool that could accurately detect patients with STS. This study aimed to assess how well an easy-to-use electronic nose could differentiate between patients with STS and those without STS based on their exhaled breath. This is the first pilot study to reveal that an electronic nose could serve as a diagnostic tool for the detection of STS with a good performance. Future studies are needed to validate the findings in larger cohorts.

Keywords::

• breath analysis
• diagnostic test
• electronic nose
• soft tissue sarcoma
• volatile organic compounds

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.futuremedicine.com/doi/suppl/10.2217/fon-2022-1122

Author contributions

Conceptualization: V van Praag, C Mostert, R Neijenhuis and M van de Sande; methodology: I Acem, V van Praag, C Mostert, R Neijenhuis and M van de Sande; formal analysis: I Acem; investigation: I Acem, V van Praag, C Mostert, R Neijenhuis, C Verhoef, D Grünhagen and M van de Sande; data curation: I Acem; writing (original draft preparation): I Acem; writing (review and editing): I Acem, V van Praag, C Mostert, R van der Wal, R Neijenhuis, C Verhoef, D Grünhagen and M van de Sande; visualization: I Acem; supervision: C Verhoef, D Grünhagen and M van de Sande. All authors have read and agreed to the published version of the manuscript.

Acknowledgments

The electronic nose and proprietary software program were provided by The eNose Company, Zutphen, The Netherlands.

Financial & competing interests disclosure

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.

No writing assistance was utilized in the production of this manuscript.