Exhaled breath contains hundreds of volatile organic compounds (VOCs). Several independent researchers point out that the breath of lung cancer patients shows a characteristic VOC-profile which can be considered as lung cancer signature and, thus, used for diagnosis. In this regard, the analysis of exhaled breath with gas sensor arrays is a potential non-invasive, relatively low-cost and easy technique for the early detection of lung cancer. This clinical study evaluated the gas sensor array response for the identification of the exhaled breath of lung cancer patients. This study involved 146 individuals: 70 with lung cancer confirmed by computerized tomography (CT) or positron emission tomography-(PET) imaging techniques and histology (biopsy) or with clinical suspect of lung cancer and 76 healthy controls. Their exhaled breath was measured with a gas sensor array composed of a matrix of eight quartz microbalances (QMBs), each functionalized with a different metalloporphyrin. The instrument produces, for each analyzed sample, a vector of signals encoding the breath (breathprint). Breathprints were analyzed with multivariate analysis in order to correlate the sensor signals to the disease. Breathprints of the lung cancer patients were differentiated from those of the healthy controls with a sensitivity of 81% and specificity of 91%. Similar values were obtained in patients with and without metabolic comorbidities, such as diabetes, obesity and dyslipidemia (sensitivity 85%, specificity 88% and sensitivity 76%, specificity 94%, respectively). The device showed a large sensitivity to lung cancer at stage I with respect to stage II/III/IV (92% and 58% respectively). The sensitivity for stage I did not change for patients with or without metabolic comorbidities (90%, 94%, respectively). Results show that this electronic nose can discriminate the exhaled breath of the lung cancer patients from those of the healthy controls. Moreover, the largest sensitivity is observed for the subgroup of patients with a lung cancer at stage I.
Gasparri, R., Santonico, M., Valentini, C., Sedda, G., Borri, A., Petrella, F., et al. (2016). Volatile signature for the early diagnosis of lung cancer. JOURNAL OF BREATH RESEARCH, 10(1) [10.1088/1752-7155/10/1/016007].
|Tipologia:||Articolo su rivista|
|Citazione:||Gasparri, R., Santonico, M., Valentini, C., Sedda, G., Borri, A., Petrella, F., et al. (2016). Volatile signature for the early diagnosis of lung cancer. JOURNAL OF BREATH RESEARCH, 10(1) [10.1088/1752-7155/10/1/016007].|
|IF:||Con Impact Factor ISI|
|Settore Scientifico Disciplinare:||Settore CHIM/07 - Fondamenti Chimici delle Tecnologie|
Settore ING-INF/01 - Elettronica
|Revisione (peer review):||Esperti anonimi|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1088/1752-7155/10/1/016007|
|Stato di pubblicazione:||Pubblicato|
|Data di pubblicazione:||2016|
|Titolo:||Volatile signature for the early diagnosis of lung cancer|
|Autori:||Gasparri, R; Santonico, M; Valentini, C; Sedda, G; Borri, A; Petrella, F; Maisonneuve, P; Pennazza, G; D'AMICO, A; DI NATALE, C; PAOLESSE, R; Spaggiari, L|
|Appare nelle tipologie:||01 - Articolo su rivista|