scholarly journals Exhaled Breath Analysis with a Colorimetric Sensor Array for the Identification and Characterization of Lung Cancer

2012 ◽  
Vol 7 (1) ◽  
pp. 137-142 ◽  
Author(s):  
Peter J. Mazzone ◽  
Xiao-Feng Wang ◽  
Yaomin Xu ◽  
Tarek Mekhail ◽  
Mary C. Beukemann ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Sensor Array ◽  
Breath Analysis ◽  
Colorimetric Sensor ◽  
Exhaled Breath ◽  
Colorimetric Sensor Array ◽  
Exhaled Breath Analysis ◽  
Identification And Characterization

scholarly journals Exhaled Breath Analysis with a Colorimetric Sensor Array for the Identification and Characterization of Lung Cancer of People from Urban Area

2019 ◽  
Vol 8 (2) ◽  
pp. 4279-4283
Keyword(s):  
Lung Cancer ◽  
Urban Areas ◽  
Sensor Array ◽  
Breath Analysis ◽  
Colorimetric Sensor ◽  
Smoking History ◽  
Exhaled Breath ◽  
Malignant Growth ◽  
Colorimetric Sensor Array ◽  
Exhaled Breath Analysis

An endeavor to reproduce the Exhaled Breath Analysis with a colorimetric Sensor Array for the distinguishing proof and portrayal of lung Cancer by Peter J. Mazzone yet duplicated in urban situations, to survey the legitimacy of the etod of distinguishing biosignatures in the breath of individuals and furthermore including clinical hazard factors To be as true as possible to the original experiment by developing an breath biosignature of lung malignant growth utilizing a colorimetric sensor cluster and to decide the exactness of breath biosignatures of lung disease but this time concentrated only around sample concentrated from urban areas Comparative techniques were utilized as refered to unique analysis The breathed out breath of 200 investigation subjects, 80 with lung malignant growth and 120 controls, was strained over a colorimetric sensor cluster. Expectation copies were constructed and factually rechecked dependent on the shading deviations of the sensor. Age, sex, contamination introduction, zone of remain, smoking history, and interminable uncooperative pneumonic sickness were fused in the forecast representations. The conjecture model were first endorsed in real way,The show were made of the combined breath and clinical biosignature ; was similarly precise at perceiving lung sickness from control subjects (C-estimation 0.811). The precision improved when the model focused on only a solitary histology (C-estimation 0.825–0.890). Individuals with different histologists could be definitely perceived from one another (C-estimation 0.864 for adenocarcinoma versus squamous cell carcinoma). Moderate rightness were noted for affirmed breath biosignatures of stage and survival. Conclusions: A colorimetric sensor array offers a possible tool to detect any sings especially of lung cancer derived from biosignatures of exhaled breath. Though the extent of surety changes with optimizations, yet breath can be evaluated successfully by evaluating specific factors such as incorporating clinical risk factors.

scholarly journals The Accuracy of Breath Analysis for Lung Cancer Detection Using a Portable Colorimetric Sensor Array System

CHEST Journal ◽  
2010 ◽  
Vol 138 (4) ◽  
pp. 774A
Author(s):  
Peter J. Mazzone ◽  
Xiaofeng Wang ◽  
Yaomin Xu ◽  
Tarek Mekhail ◽  
Mary Beukemann ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Detection ◽  
Sensor Array ◽  
Breath Analysis ◽  
Colorimetric Sensor ◽  
Colorimetric Sensor Array ◽  
Lung Cancer Detection

scholarly journals Diagnosis of lung cancer by the analysis of exhaled breath with a colorimetric sensor array

Thorax ◽  
2007 ◽  
Vol 62 (7) ◽  
pp. 565-568 ◽  
Author(s):  
P. J Mazzone ◽  
J. Hammel ◽  
R. Dweik ◽  
J. Na ◽  
C. Czich ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Sensor Array ◽  
Colorimetric Sensor ◽  
Exhaled Breath ◽  
Colorimetric Sensor Array ◽  
Diagnosis Of Lung Cancer

Cancerous glucose metabolism in lung cancer—evidence from exhaled breath analysis

2016 ◽  
Vol 10 (2) ◽  
pp. 026012 ◽  
Author(s):  
Tali Feinberg ◽  
Layah Alkoby-Meshulam ◽  
Jens Herbig ◽  
John C Cancilla ◽  
Jose S Torrecilla ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Glucose Metabolism ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis

scholarly journals Sensor array optimization techniques for exhaled breath analysis to discriminate diabetics using an electronic nose

ETRI Journal ◽  
2018 ◽  
Vol 40 (6) ◽  
pp. 802-812 ◽  
Author(s):  
Jin-Young Jeon ◽  
Jang-Sik Choi ◽  
Joon-Boo Yu ◽  
Hae-Ryong Lee ◽  
Byoung Kuk Jang ◽  
...  
Keyword(s):  
Electronic Nose ◽  
Sensor Array ◽  
Breath Analysis ◽  
Optimization Techniques ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis ◽  
Array Optimization

scholarly journals MOS Sensors Array for the Discrimination of Lung Cancer and At-Risk Subjects with Exhaled Breath Analysis

Chemosensors ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 209
Author(s):  
Davide Marzorati ◽  
Luca Mainardi ◽  
Giulia Sedda ◽  
Roberto Gasparri ◽  
Lorenzo Spaggiari ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Mortality Rate ◽  
Early Diagnosis ◽  
Gas Sensor ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis

Lung cancer is characterized by a tremendously high mortality rate and a low 5-year survival rate when diagnosed at a late stage. Early diagnosis of lung cancer drastically reduces its mortality rate and improves survival. Exhaled breath analysis could offer a tool to clinicians to improve the ability to detect lung cancer at an early stage, thus leading to a reduction in the associated survival rate. In this paper, we present an electronic nose for the automatic analysis of exhaled breath. A total of five a-specific gas sensors were embedded in the electronic nose, making it sensitive to different volatile organic compounds (VOCs) contained in exhaled breath. Nine features were extracted from each gas sensor response to exhaled breath, identifying the subject breathprint. We tested the electronic nose on a cohort of 80 subjects, equally split between lung cancer and at-risk control subjects. Including gas sensor features and clinical features in a classification model, recall, precision, and accuracy of 78%, 80%, and 77% were reached using a fourfold cross-validation approach. The addition of other a-specific gas sensors, or of sensors specific to certain compounds, could improve the classification accuracy, therefore allowing for the development of a clinical tool to be integrated in the clinical pipeline for exhaled breath analysis and lung cancer early diagnosis.

scholarly journals Exhaled Breath Analysis for Monitoring Response to Treatment in Advanced Lung Cancer

2016 ◽  
Vol 11 (6) ◽  
pp. 827-837 ◽  
Author(s):  
Inbar Nardi-Agmon ◽  
Manal Abud-Hawa ◽  
Ori Liran ◽  
Naomi Gai-Mor ◽  
Maya Ilouze ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Breath Analysis ◽  
Response To Treatment ◽  
Advanced Lung Cancer ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis ◽  
Monitoring Response

scholarly journals An Update on the Use of Exhaled Breath Analysis for the Early Detection of Lung Cancer

2021 ◽  
Vol Volume 12 ◽  
pp. 81-92
Author(s):  
Nir Peled ◽  
Vered Fuchs ◽  
Emily H Kestenbaum ◽  
Elron Oscar ◽  
Raul Bitran
Keyword(s):  
Lung Cancer ◽  
Early Detection ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis

scholarly journals COMBINED DIAGNOSTICS OF LUNG CANCER USING EXHALED BREATH ANALSYSIS AND SPUTUM CYTOLOGY

2020 ◽  
Vol 66 (4) ◽  
pp. 381-384
Author(s):  
A. Arseniev ◽  
A. Nefedova ◽  
A. Ganeeva ◽  
A. Nefedov ◽  
S. Novikov ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Breath Test ◽  
Early Stage ◽  
Breath Analysis ◽  
Diagnostic Techniques ◽  
Cancer Diagnostics ◽  
Exhaled Breath ◽  
Sputum Cytology ◽  
Exhaled Breath Analysis ◽  
Sensitivity Specificity

In this article we summarize our own experience of lung cancer diagnostics using exhaled breath analysis with a non-selective method using metal oxide chemoresistor gas sensors with cross-sensitivity combined with the sputum cytology. Volatile organic compounds of exhaled breath change the conductivity of the sensor, the resulting pulse is displayed as a peak on the graph, the area of which is used as test results. The combination of two diagnostic techniques in 204 participants demonstrated the possibility of non-invasively detecting the disease at an early stage. The sensitivity, specificity and accuracy of the breath analysis was 91.2%, 100% and 93.4%, respectively. The combination of the breath test and the sputum cytology compared to the breath test alone showed statistically significant (p = 0.03) increase in sensitivity to 96.8% (95% CI: 80.9% -99%) with acceptable decrease in specificity to 93.4% (95% CI: 88% -96%). The convenience of analysis and realtime measurements show some promise for the early detection.

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