RESUMEN
Aim: Aim of this explorative pilot study was to evaluate the capability of an electronic nose (aeoNose, the eNose Company) to classify healthy individuals and patients with chondrosarcoma, based on their volatile organic compound profiles in exhaled breath. Materials & methods: Fifty-seven patients (25 healthy controls, 24 chondrosarcoma and 8 different benign lesions) were included in the study from 2018 to 2023. An artificial neural network was used as classifier. Results: The developed model had a sensitivity of 75%, and a specificity of 65% with an AUC of 0.66. Conclusion: Results show that there is not enough evidence to include the aeoNose as diagnostic biomarker for chondrosarcoma in daily practice. However, the aeoNose might play an additional role alongside MRI, in questionable chondrosarcoma cases.