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Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review

Lung cancer has been studied for decades because of its high morbidity and high mortality. Traditional methods involving bronchoscopy and needle biopsy are invasive and expensive, which makes patients suffer more risks and costs. Various noninvasive lung cancer markers, such as medical imaging indic...

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Autores principales: Yu, Qiwen, Chen, Jing, Fu, Wei, Muhammad, Kanhar Ghulam, Li, Yi, Liu, Wenxin, Xu, Linxin, Dong, Hao, Wang, Di, Liu, Jun, Lu, Yanli, Chen, Xing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028493/
https://www.ncbi.nlm.nih.gov/pubmed/35448283
http://dx.doi.org/10.3390/bios12040223
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author Yu, Qiwen
Chen, Jing
Fu, Wei
Muhammad, Kanhar Ghulam
Li, Yi
Liu, Wenxin
Xu, Linxin
Dong, Hao
Wang, Di
Liu, Jun
Lu, Yanli
Chen, Xing
author_facet Yu, Qiwen
Chen, Jing
Fu, Wei
Muhammad, Kanhar Ghulam
Li, Yi
Liu, Wenxin
Xu, Linxin
Dong, Hao
Wang, Di
Liu, Jun
Lu, Yanli
Chen, Xing
author_sort Yu, Qiwen
collection PubMed
description Lung cancer has been studied for decades because of its high morbidity and high mortality. Traditional methods involving bronchoscopy and needle biopsy are invasive and expensive, which makes patients suffer more risks and costs. Various noninvasive lung cancer markers, such as medical imaging indices, volatile organic compounds (VOCs), and exhaled breath condensates (EBCs), have been discovered for application in screening, diagnosis, and prognosis. However, the detection of markers still relies on bulky and professional instruments, which are limited to training personnel or laboratories. This seriously hinders population screening for early diagnosis of lung cancer. Advanced smartphones integrated with powerful applications can provide easy operation and real-time monitoring for healthcare, which demonstrates tremendous application scenarios in the biomedical analysis region from medical institutions or laboratories to personalized medicine. In this review, we propose an overview of lung-cancer-related noninvasive markers from exhaled breath, focusing on the novel development of smartphone-based platforms for the detection of these biomarkers. Lastly, we discuss the current limitations and potential solutions.
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spelling pubmed-90284932022-04-23 Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review Yu, Qiwen Chen, Jing Fu, Wei Muhammad, Kanhar Ghulam Li, Yi Liu, Wenxin Xu, Linxin Dong, Hao Wang, Di Liu, Jun Lu, Yanli Chen, Xing Biosensors (Basel) Review Lung cancer has been studied for decades because of its high morbidity and high mortality. Traditional methods involving bronchoscopy and needle biopsy are invasive and expensive, which makes patients suffer more risks and costs. Various noninvasive lung cancer markers, such as medical imaging indices, volatile organic compounds (VOCs), and exhaled breath condensates (EBCs), have been discovered for application in screening, diagnosis, and prognosis. However, the detection of markers still relies on bulky and professional instruments, which are limited to training personnel or laboratories. This seriously hinders population screening for early diagnosis of lung cancer. Advanced smartphones integrated with powerful applications can provide easy operation and real-time monitoring for healthcare, which demonstrates tremendous application scenarios in the biomedical analysis region from medical institutions or laboratories to personalized medicine. In this review, we propose an overview of lung-cancer-related noninvasive markers from exhaled breath, focusing on the novel development of smartphone-based platforms for the detection of these biomarkers. Lastly, we discuss the current limitations and potential solutions. MDPI 2022-04-08 /pmc/articles/PMC9028493/ /pubmed/35448283 http://dx.doi.org/10.3390/bios12040223 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Yu, Qiwen
Chen, Jing
Fu, Wei
Muhammad, Kanhar Ghulam
Li, Yi
Liu, Wenxin
Xu, Linxin
Dong, Hao
Wang, Di
Liu, Jun
Lu, Yanli
Chen, Xing
Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review
title Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review
title_full Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review
title_fullStr Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review
title_full_unstemmed Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review
title_short Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review
title_sort smartphone-based platforms for clinical detections in lung-cancer-related exhaled breath biomarkers: a review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028493/
https://www.ncbi.nlm.nih.gov/pubmed/35448283
http://dx.doi.org/10.3390/bios12040223
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