Detection of differentiated thyroid carcinoma in exhaled breath with an electronic nose

Max H. M. C. Scheepers, Zaid J. J. Al-Difaie, Anne G. W. E. Wintjens, Sanne M. E. Engelen, Bas Havekes, Tim Lubbers, Marielle M. E. Coolsen, Job van der Palen, Tessa M. van Ginhoven, Menno Vriens, Nicole D. Bouvy

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Abstract

This proof-of-principle study investigates the diagnostic performance of the Aeonose in
differentiating malignant from benign thyroid diseases based on volatile organic compound
analysis in exhaled breath. All patients with a suspicious thyroid nodule planned for surgery,
exhaled in the Aeonose. Definitive diagnosis was provided by histopathological determination after
surgical resection. Breath samples were analyzed utilizing artificial neural networking. About 133
participants were included, 48 of whom were diagnosed with well-differentiated thyroid cancer. A
sensitivity of 0.73 and a negative predictive value (NPV) of 0.82 were found. The sensitivity and
NPV improved to 0.94 and 0.95 respectively after adding clinical variables via multivariate logistic
regression analysis. This study demonstrates the feasibility of the Aeonose to discriminate between
malignant and benign thyroid disease. With a high NPV, low cost, and non-invasive nature, the
Aeonose may be a promising diagnostic tool in the detection of thyroid cancer.
Original languageEnglish
Article number036008
JournalJOURNAL OF BREATH RESEARCH
Volume16
Issue number3
DOIs
Publication statusPublished - 21 Jun 2022

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