Back to Search Start Over

Chemiresistive Sensor Array with Nanostructured Interfaces for Detection of Human Breaths with Simulated Lung Cancer Breath VOCs.

Authors :
Shang G
Dinh D
Mercer T
Yan S
Wang S
Malaei B
Luo J
Lu S
Zhong CJ
Source :
ACS sensors [ACS Sens] 2023 Mar 24; Vol. 8 (3), pp. 1328-1338. Date of Electronic Publication: 2023 Mar 08.
Publication Year :
2023

Abstract

Timely screening of lung cancer represents a challenging task for early diagnosis and treatment, which calls for reliable, low-cost, and noninvasive detection tools. One type of promising tools for early-stage cancer detection is breath analyzers or sensors that detect breath volatile organic compounds (VOCs) as biomarkers in exhaled breaths. However, a major challenge is the lack of effective integration of the different sensor system components toward the desired portability, sensitivity, selectivity, and durability for many of the current breath sensors. In this report, we demonstrate herein a portable and wireless breath sensor testing system integrated with sensor electronics, breath sampling, data processing, and sensor arrays derived from nanoparticle-structured chemiresistive sensing interfaces for detection of VOCs relevant to lung cancer biomarkers in human breaths. In addition to showing the sensor viability for the targeted application by theoretical simulations of chemiresistive sensor array responses to the simulated VOCs in human breaths, the sensor system was tested experimentally with different combinations of VOCs and human breath samples spiked with lung cancer-specific VOCs. The sensor array exhibits high sensitivity to lung cancer VOC biomarkers and mixtures, with a limit of detection as low as 6 ppb. The results from testing the sensor array system in detecting breath samples with simulated lung cancer VOC constituents have demonstrated an excellent recognition rate in discriminating healthy human breath samples and those with lung cancer VOCs. The recognition statistics were analyzed, showing the potential viability and optimization toward achieving the desired sensitivity, selectivity, and accuracy in the breath screening of lung cancer.

Details

Language :
English
ISSN :
2379-3694
Volume :
8
Issue :
3
Database :
MEDLINE
Journal :
ACS sensors
Publication Type :
Academic Journal
Accession number :
36883832
Full Text :
https://doi.org/10.1021/acssensors.2c02839