Detection of lung cancer by sensor array analyses of exhaled breath

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

Research output: Contribution to journalArticle

398 Citations (Scopus)

Abstract

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 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. Main Results: 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. Conclusion: 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.

Original languageEnglish (US)
Pages (from-to)1286-1291
Number of pages6
JournalAmerican Journal of Respiratory and Critical Care Medicine
Volume171
Issue number11
DOIs
StatePublished - Jun 1 2005
Externally publishedYes

Fingerprint

Electronic Nose
Lung Neoplasms
Bronchogenic Carcinoma
Discriminant Analysis
Neoplasms
Volatile Organic Compounds
Validation Studies
Food Industry
Lung Diseases
Healthy Volunteers
Gases
Sensitivity and Specificity
Population

Keywords

  • Breath tests
  • Bronchogenic cancer
  • Electronic nose
  • Volatile organic compounds

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine

Cite this

Machado, R., Laskowski, D., Deffenderfer, O., Burch, T., Zheng, S., Mazzone, P. J., ... Erzurum, S. C. (2005). Detection of lung cancer by sensor array analyses of exhaled breath. American Journal of Respiratory and Critical Care Medicine, 171(11), 1286-1291. https://doi.org/10.1164/rccm.200409-1184OC

Detection of lung cancer by sensor array analyses of exhaled breath. / Machado, Roberto; 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.

In: American Journal of Respiratory and Critical Care Medicine, Vol. 171, No. 11, 01.06.2005, p. 1286-1291.

Research output: Contribution to journalArticle

Machado, R, Laskowski, D, Deffenderfer, O, Burch, T, Zheng, S, Mazzone, PJ, Mekhail, T, Jennings, C, Stoller, JK, Pyle, J, Duncan, J, Dweik, RA & Erzurum, SC 2005, 'Detection of lung cancer by sensor array analyses of exhaled breath', American Journal of Respiratory and Critical Care Medicine, vol. 171, no. 11, pp. 1286-1291. https://doi.org/10.1164/rccm.200409-1184OC
Machado, Roberto ; 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. / Detection of lung cancer by sensor array analyses of exhaled breath. In: American Journal of Respiratory and Critical Care Medicine. 2005 ; Vol. 171, No. 11. pp. 1286-1291.
@article{226e64a7886147bca284fbd8f2fc2925,
title = "Detection of lung cancer by sensor array analyses of exhaled breath",
abstract = "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 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. Main Results: 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. Conclusion: 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.",
keywords = "Breath tests, Bronchogenic cancer, Electronic nose, Volatile organic compounds",
author = "Roberto Machado and Daniel Laskowski and Olivia Deffenderfer and Timothy Burch and Shuo Zheng and Mazzone, {Peter J.} and Tarek Mekhail and Constance Jennings and Stoller, {James K.} and Jacqueline Pyle and Jennifer Duncan and Dweik, {Raed A.} and Erzurum, {Serpil C.}",
year = "2005",
month = "6",
day = "1",
doi = "10.1164/rccm.200409-1184OC",
language = "English (US)",
volume = "171",
pages = "1286--1291",
journal = "American Journal of Respiratory and Critical Care Medicine",
issn = "1073-449X",
publisher = "American Thoracic Society",
number = "11",

}

TY - JOUR

T1 - Detection of lung cancer by sensor array analyses of exhaled breath

AU - Machado, Roberto

AU - Laskowski, Daniel

AU - Deffenderfer, Olivia

AU - Burch, Timothy

AU - Zheng, Shuo

AU - Mazzone, Peter J.

AU - Mekhail, Tarek

AU - Jennings, Constance

AU - Stoller, James K.

AU - Pyle, Jacqueline

AU - Duncan, Jennifer

AU - Dweik, Raed A.

AU - Erzurum, Serpil C.

PY - 2005/6/1

Y1 - 2005/6/1

N2 - 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 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. Main Results: 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. Conclusion: 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.

AB - 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 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. Main Results: 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. Conclusion: 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.

KW - Breath tests

KW - Bronchogenic cancer

KW - Electronic nose

KW - Volatile organic compounds

UR - http://www.scopus.com/inward/record.url?scp=21144450472&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=21144450472&partnerID=8YFLogxK

U2 - 10.1164/rccm.200409-1184OC

DO - 10.1164/rccm.200409-1184OC

M3 - Article

C2 - 15750044

AN - SCOPUS:21144450472

VL - 171

SP - 1286

EP - 1291

JO - American Journal of Respiratory and Critical Care Medicine

JF - American Journal of Respiratory and Critical Care Medicine

SN - 1073-449X

IS - 11

ER -