Feasibility of an Electronic Nose to Aid Biochemical Assessment of Adrenal Lesions.

Objectives: Analysis of volatile organic compounds (VOCs) in exhaled breath has emerged as a promising noninvasive diagnostic tool for various diseases. The aim of this study was to evaluate the potential of an electronic nose to differentiate between functional adrenal lesions - pheochromocytoma (PHEO), primary hyperaldosteronism (PHA), and hypercortisolism (CS) - and nonfunctional adrenal lesions.

Methods: A pilot study was conducted at 2 tertiary hospitals within the Netherlands. Patients with PHEO, PHA, CS, and nonfunctional adrenal lesions underwent breath testing with an electronic nose between May 2021 and June 2024. Each center employed a distinct electronic nose (device A and B). Comparability of data between the devices was assessed in a t-distributed stochastic neighbor embedding plot, and an artificial neural network was trained to classify breath patterns.

Results: Data obtained from the 2 electronic noses were too heterogeneous for pooling and device B had an insufficient sample size for further analysis. Therefore, VOC patterns of 76 functional lesions (27 PHEO, 33 PHA, 16 CS) and 29 nonfunctional adrenal lesions measured exclusively with device A were analyzed. Moderate discriminative performance was observed in the training data: pooled functional lesions (area under the curve [AUC] 0.76), PHEO [AUC 0.76], PHA [AUC 0.72] and CS [AUC 0.58] versus nonfunctional lesions. However, model performance declined significantly when applying the model developed with training data on test data, with wide confidence intervals across all comparisons.

Conclusions: While slight differences in VOC patterns were detected between functional and nonfunctional adrenal lesions, the electronic nose demonstrated limited discriminative value for clinical practice.