Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2025
Feasibility of an Electronic Nose to Aid Biochemical Assessment of Adrenal Lesions.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Viëtor Charlotte L, Sosef Odin V, van Dijk Sam P J, Holscher Isabelle, Chen Jeffrey W, Al-Difaie Zaid, Scheepers Max H M C, Feelders Richard A, Dreijerink Koen M A, Engelsman Anton F, van Ginhoven Tessa M
Аннотация
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.
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.