| Autor: |
Company Se, Georgina, Nescolarde Selva, Lexa Digna, Pajares Ruiz, Virginia, Torrego Fernández, Alfons, Riu Costa, Pere Joan, Rosell Ferrer, Francisco Javier, Bragós Bardia, Ramon |
| Přispěvatelé: |
Universitat Politècnica de Catalunya. Doctorat en Enginyeria Biomèdica, Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica, Universitat Politècnica de Catalunya. IEB - Instrumentació Electrònica i Biomèdica |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Frontiers in Medicine. 10 |
| ISSN: |
2296-858X |
| Popis: |
PurposeTo use minimally-invasive transcatheter electrical impedance spectroscopy measurements for tissue differentiation among healthy lung tissue and pathologic lung tissue from patients with different respiratory diseases (neoplasm, fibrosis, pneumonia and emphysema) to complement the diagnosis at real time during bronchoscopic procedures.MethodsMulti-frequency bioimpedance measurements were performed in 102 patients. The two most discriminative frequencies for impedance modulus (|Z|), phase angle (PA), resistance (R) and reactance (Xc) were selected based on the maximum mean pair-wise Euclidean distances between paired groups. One-way ANOVA for parametric variables and Kruskal–Wallis for non-parametric data tests have been performed with post-hoc tests. Discriminant analysis has also been performed to find a linear combination of features to separate among tissue groups.ResultsWe found statistically significant differences for all the parameters between: neoplasm and pneumonia (p p p ≤ 0.001) and pneumonia and healthy lung tissue (p p p p > 0.05) are found between neoplasm and fibrosis; fibrosis and pneumonia; and between healthy lung tissue and emphysema.ConclusionThe application of minimally-invasive electrical impedance spectroscopy measurements in lung tissue have proven to be useful for tissue differentiation between those pathologies that leads increased tissue and inflammatory cells and those ones that contain more air and destruction of alveolar septa, which could help clinicians to improve diagnosis. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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