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Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath

Machado, Roberto F ; Laskowski, Daniel ; Deffenderfer, Olivia ; Burch, Timothy ; Zheng, Shuo ; Mazzone, Peter J ; Mekhail, Tarek ; Jennings, Constance ; Stoller, James K ; Pyle, Jacqueline ; Duncan, Jennifer ; Dweik, Raed A ; Erzurum, Serpil C

American journal of respiratory and critical care medicine, 2005-06, Vol.171 (11), p.1286-1291 [Revista revisada por pares]

New York, NY: Am Thoracic Soc

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  • Título:
    Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath
  • Autor: Machado, Roberto F ; Laskowski, Daniel ; Deffenderfer, Olivia ; Burch, Timothy ; Zheng, Shuo ; Mazzone, Peter J ; Mekhail, Tarek ; Jennings, Constance ; Stoller, James K ; Pyle, Jacqueline ; Duncan, Jennifer ; Dweik, Raed A ; Erzurum, Serpil C
  • Materias: Adult ; Aged ; Aged, 80 and over ; Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy ; Biological and medical sciences ; Breath Tests - methods ; Chromatography, Gas ; Clinical death. Palliative care. Organ gift and preservation ; Cross-Sectional Studies ; F. Lung Cancer and Oncologic Disorders ; False Negative Reactions ; Female ; Humans ; Intensive care medicine ; Lung Neoplasms - diagnosis ; Male ; Mass Spectrometry ; Medical sciences ; Middle Aged ; Pneumology ; Principal Component Analysis ; Reproducibility of Results ; Sensitivity and Specificity ; Tumors of the respiratory system and mediastinum
  • Es parte de: American journal of respiratory and critical care medicine, 2005-06, Vol.171 (11), p.1286-1291
  • Notas: ObjectType-Article-2
    SourceType-Scholarly Journals-1
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    This article has an online supplement, which is accessible from this issue's table of contents at www.atsjournals.org
    Correspondence and requests for reprints should be addressed to Serpil C. Erzurum, M.D., Cleveland Clinic Foundation, 9500 Euclid Avenue/NB40, Cleveland, OH 44195. E-mail: erzurus@ccf.org
    Conflict of Interest Statement: R.F.M. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; D.L. is the owner of Physiologic Measurement Systems LLC, which builds gas-sampling systems; O.D. is employed by Smiths Detection, which sponsored the study through the loan of the electronic nose detection device; T.B. is employed by Smiths Detection, which sponsored the study through loan of the electronic nose detection device; S.Z. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; P.J.M. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; T.M. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; C.J. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; J.K.S. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; J.P. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; J.D. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; R.A.D. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; S.C.E. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript.
    Supported by the National Institutes of Health grant NIH HL04265 and Smiths Detection, Inc., through donation of the electronic nose instrument and partial financial support for research supplies.
  • Descripción: Electronic noses are successfully used in commercial applications, including detection and analysis of volatile organic compounds in the food industry. We hypothesized that the electronic nose could identify and discriminate between lung diseases, especially bronchogenic carcinoma. In a discovery and training phase, exhaled breath of 14 individuals with bronchogenic carcinoma and 45 healthy control subjects or control subjects without cancer was analyzed. Principal components and canonic discriminant analysis of the sensor data was used to determine whether exhaled gases could discriminate between cancer and noncancer. Discrimination between classes was performed using Mahalanobis distance. Support vector machine analysis was used to create and apply a cancer prediction model prospectively in a separate group of 76 individuals, 14 with and 62 without cancer. Principal components and canonic discriminant analysis demonstrated discrimination between samples from patients with lung cancer and those from other groups. In the validation study, the electronic nose had 71.4% sensitivity and 91.9% specificity for detecting lung cancer; positive and negative predictive values were 66.6 and 93.4%, respectively. In this population with a lung cancer prevalence of 18%, positive and negative predictive values were 66.6 and 94.5%, respectively. The exhaled breath of patients with lung cancer has distinct characteristics that can be identified with an electronic nose. The results provide feasibility to the concept of using the electronic nose for managing and detecting lung cancer.
  • Editor: New York, NY: Am Thoracic Soc
  • Idioma: Inglés
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