Exhaled volatile organic compounds analysis by e-nose can detect idiopathic pulmonary fibrosis
The current diagnostic work-up and monitoring of idiopathic pulmonary fibrosis (IPF) is often invasive and time consuming. Breath analysis by e-nose technology has shown potential in the diagnosis of numerous respiratory diseases. In this pilot study, we investigated whether exhaled breath analysis by an e-nose could discriminate among patients with IPF, healthy controls and COPD. Second, we verified whether these classification could be repeated in a set of newly recruited patients as external validation. Third, we evaluated any significant relationships between exhaled VOCs and Bronchoalveolar lavage fluid (BALF) in IPF patients. We enrolled 32 patients with well-characterized IPF, 33 individuals with COPD and 36 healthy controls. An electronic nose (Cyranose 320) was used to analyze exhaled breath samples. Raw data were processed by Principal component reduction and linear discriminant analysis. External validation in newly recruited patients (10 IPF, 10 COPD and 10 controls) was tested using the previous training set. Exhaled VOC-profiles of patients with IPF were distinct from those of healthy controls (CVA = 98.5%) as well as those with COPD (CVA = 80.0%). External validation confirmed the above findings (IPF vs COPD vs healthy controls, CVA 96.7%). Moreover, a significant inversely proportional correlation was shown between BALF total cell count and both Principal Components 1 and 2 (r = 0.543, r2 = 0.295, p < 0.01; r = 0.501, r2 = 0.251; p < 0.01, respectively). The exhaled breath Volatile Organic Compounds- profile of patients with IPF can be detected by an electronic nose. This suggests that breath analysis has potential for diagnosis and/or monitoring of IPF.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2020 |
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Erschienen: |
2020 |
Enthalten in: |
Zur Gesamtaufnahme - volume:14 |
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Enthalten in: |
Journal of breath research - 14(2020), 4 vom: 21. Juli, Seite 047101 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Dragonieri, Silvano [VerfasserIn] |
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Links: |
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Themen: |
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Anmerkungen: |
Date Completed 01.10.2020 Date Revised 01.10.2020 published: Electronic Citation Status MEDLINE |
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doi: |
10.1088/1752-7163/ab8c2e |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM309053609 |
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520 | |a The current diagnostic work-up and monitoring of idiopathic pulmonary fibrosis (IPF) is often invasive and time consuming. Breath analysis by e-nose technology has shown potential in the diagnosis of numerous respiratory diseases. In this pilot study, we investigated whether exhaled breath analysis by an e-nose could discriminate among patients with IPF, healthy controls and COPD. Second, we verified whether these classification could be repeated in a set of newly recruited patients as external validation. Third, we evaluated any significant relationships between exhaled VOCs and Bronchoalveolar lavage fluid (BALF) in IPF patients. We enrolled 32 patients with well-characterized IPF, 33 individuals with COPD and 36 healthy controls. An electronic nose (Cyranose 320) was used to analyze exhaled breath samples. Raw data were processed by Principal component reduction and linear discriminant analysis. External validation in newly recruited patients (10 IPF, 10 COPD and 10 controls) was tested using the previous training set. Exhaled VOC-profiles of patients with IPF were distinct from those of healthy controls (CVA = 98.5%) as well as those with COPD (CVA = 80.0%). External validation confirmed the above findings (IPF vs COPD vs healthy controls, CVA 96.7%). Moreover, a significant inversely proportional correlation was shown between BALF total cell count and both Principal Components 1 and 2 (r = 0.543, r2 = 0.295, p < 0.01; r = 0.501, r2 = 0.251; p < 0.01, respectively). The exhaled breath Volatile Organic Compounds- profile of patients with IPF can be detected by an electronic nose. This suggests that breath analysis has potential for diagnosis and/or monitoring of IPF | ||
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700 | 1 | |a Lacedonia, Donato |e verfasserin |4 aut | |
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