Published ahead of print on March 4, 2005, doi:10.1164/rccm.200409-1184OC Am. J. Respir. Crit. Care Med., Volume 171, Number 11, June 2005, 1286-1291 A more recent version of this article appeared on June 1, 2005
Submitted on September 8, 2004 Detection of Lung Cancer by Sensor Array Analyses of Exhaled BreathRoberto F Machado1,1 Department of Pulmonary, Allergy and Critical Care Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA, 2 Smiths Detection, Inc., Pasadena, CA, USA, 3 Department of Pathobiology, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA, 4 Department of Hematology and Medical Oncology, Cleveland Clinic Foundation, Cleveland, OH, USA, 5 Department of Pulmonary, Allergy and Critical Care Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Pathobiology, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA, 6 Department of Pathobiology, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Pulmonary, Allergy and Critical Care Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA * To whom correspondence should be addressed. E-mail: erzurus{at}ccf.org.
Rationale: Electronic noses are successfully used in commercial applications, including detection and analysis of volatile organic compounds in the food industry. Objectives: We hypothesized that the electronic nose could identify and discriminate between lung diseases, especially bronchogenic carcinoma. Methods: In a discovery and training phase, exhaled breath of 14 individuals with bronchogenic carcinoma, and 45 healthy or non-cancer disease controls was analyzed. Principal component and canonical discriminant analysis of the sensor data were used to determine whether exhaled gases could discriminate between cancer and non-cancer. 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 66 individuals, 14 with and 62 without cancer. Main Results: Principal component and canonical 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. Conclusion: The exhaled breath of lung cancer patients 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. Some of the results of these studies have been previously reported in the form of an abstract (16). Key words: exhaled breath analysis, lung cancer, volatile organic compounds
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