由于临床表现重叠，间质性肺疾病（ILD）可能难以与其他呼吸系统疾病区分开。 ILD 的识别往往很晚，导致延误，从而导致较差的临床结果。电子鼻 (eNose) 传感器技术可分析呼出气体中的挥发性有机化合物，并具有非侵入性检测 ILD 的潜力。我们使用 eNose 技术评估了区分 ILD 患者与哮喘、慢性阻塞性肺病 (COPD) 和肺癌患者呼吸特征的准确性。 ILD、哮喘、COPD 和肺癌患者，无论分期或治疗情况如何，被纳入两家医院的横断面研究中。使用 eNose (SpiroNose) 分析呼出气体并收集临床数据。数据集分为训练集和测试集，以独立验证模型。采用偏最小二乘判别法和接受者操作特征分析对数据进行分析。纳入了 161 名 ILD 患者和 161 名哮喘患者 (n = 65)、COPD (n = 50) 或肺癌 (n = 46) 患者。 ILD 患者的呼吸曲线与所有其他疾病不同，测试集中的曲线下面积 (AUC) 为 0.99 (95% CI 0.97-1.00)。此外，ILD患者的呼吸曲线可以准确地区分哮喘的AUC为1.00（95％CI 1.00-1.00），COPD的AUC为0.96（95％CI 0.90-1.00），AUC为0.98的个体疾病。 (95% CI 0.94-1.00) 测试集中肺癌。排除从不吸烟的患者后，结果相似。使用eNose技术可以准确地区分ILD患者的呼出气与其他呼吸系统疾病患者。 eNose 具有很大的潜力，可以作为一种易于使用的即时医疗测试，用于在有呼吸道症状的患者中识别 ILD，并且可能有助于早期转诊和诊断疑似 ILD 的患者。© 2023。作者。

Interstitial lung disease (ILD) may be difficult to distinguish from other respiratory diseases due to overlapping clinical presentation. Recognition of ILD is often late, causing delay which has been associated with worse clinical outcome. Electronic nose (eNose) sensor technology profiles volatile organic compounds in exhaled breath and has potential to detect ILD non-invasively. We assessed the accuracy of differentiating breath profiles of patients with ILD from patients with asthma, chronic obstructive pulmonary disease (COPD), and lung cancer using eNose technology.Patients with ILD, asthma, COPD, and lung cancer, regardless of stage or treatment, were included in a cross-sectional study in two hospitals. Exhaled breath was analysed using an eNose (SpiroNose) and clinical data were collected. Datasets were split in training and test sets for independent validation of the model. Data were analyzed with partial least squares discriminant and receiver operating characteristic analyses.161 patients with ILD and 161 patients with asthma (n = 65), COPD (n = 50) or lung cancer (n = 46) were included. Breath profiles of patients with ILD differed from all other diseases with an area under the curve (AUC) of 0.99 (95% CI 0.97-1.00) in the test set. Moreover, breath profiles of patients with ILD could be accurately distinguished from the individual diseases with an AUC of 1.00 (95% CI 1.00-1.00) for asthma, AUC of 0.96 (95% CI 0.90-1.00) for COPD, and AUC of 0.98 (95% CI 0.94-1.00) for lung cancer in test sets. Results were similar after excluding patients who never smoked.Exhaled breath of patients with ILD can be distinguished accurately from patients with other respiratory diseases using eNose technology. eNose has high potential as an easily accessible point-of-care medical test for identification of ILD amongst patients with respiratory symptoms, and could possibly facilitate earlier referral and diagnosis of patients suspected of ILD.© 2023. The Author(s).