Dragonieri Silvano, Quaranta Vitaliano Nicola, Portacci Andrea, Ranieri Teresa, Carpagnano Giovanna Elisiana
Respiratory Diseases, University of Bari "Aldo Moro", 70121 Bari, Italy.
Sensors (Basel). 2025 Apr 20;25(8):2610. doi: 10.3390/s25082610.
Exhaled breath analysis using electronic noses (e-noses) is a promising non-invasive diagnostic tool. However, a lack of standardized protocols limits clinical implementation. This study evaluates the consistency of breathprints in healthy subjects using the Cyranose 320 e-nose to support standardization efforts. Breath samples from 139 healthy non-smoking subjects (age range 18-65 years) were collected using a standardized protocol. Participants exhaled into a Tedlar bag for immediate analysis with the Cyranose 320. Principal Component Analysis (PCA) was used to reduce data dimensionality, and K-means clustering grouped subjects based on breathprints. PCA identified four principal components explaining 97.15% of variance. K-means clustering revealed two clusters: 1 outlier and 138 subjects with highly similar breathprints. The median distance from the cluster center was 0.21 (IQR: 0.18-0.24), indicating low variability. Box plots confirmed breathprint consistency across subjects. The high consistency of breathprints in healthy subjects supports the feasibility of standardizing e-nose protocols. These findings highlight the potential of e-noses for clinical diagnostics, warranting further research in diverse populations and disease cohorts.
使用电子鼻进行呼气分析是一种很有前景的非侵入性诊断工具。然而,缺乏标准化方案限制了其临床应用。本研究使用Cyranose 320电子鼻评估健康受试者呼吸指纹的一致性,以支持标准化工作。采用标准化方案收集了139名健康非吸烟受试者(年龄范围18 - 65岁)的呼吸样本。参与者向Tedlar袋中呼气,以便立即用Cyranose 320进行分析。主成分分析(PCA)用于降低数据维度,K均值聚类根据呼吸指纹对受试者进行分组。PCA确定了四个主成分,解释了97.15%的方差。K均值聚类揭示了两个簇:1个离群值和138名呼吸指纹高度相似的受试者。到簇中心的中位数距离为0.21(四分位距:0.18 - 0.24),表明变异性较低。箱线图证实了受试者间呼吸指纹的一致性。健康受试者呼吸指纹的高度一致性支持了电子鼻方案标准化的可行性。这些发现凸显了电子鼻在临床诊断中的潜力,值得在不同人群和疾病队列中进一步研究。