亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

A review of exhaled breath: a key role in lung cancer diagnosis

医学 肺癌 重症监护医学 阶段(地层学) 人口 气体分析呼吸 呼出的空气 肺癌筛查 癌症 死亡率 医学物理学 肿瘤科 内科学 环境卫生 毒理 古生物学 解剖 生物
作者
Davide Marzorati,Luca Mainardi,Giulia Sedda,Roberto Gasparri,Lorenzo Spaggiari,Pietro Cerveri
出处
期刊:Journal of Breath Research [IOP Publishing]
卷期号:13 (3): 034001-034001 被引量:81
标识
DOI:10.1088/1752-7163/ab0684
摘要

One of the main causes of the high mortality rate in lung cancer is the late-stage tumor detection. Early diagnosis is therefore essential to increase the chances of obtaining an effective treatment quickly thus increasing the survival rate. Current screening techniques are based on imaging, with low-dose computed tomography (LDCT) as the pivotal approach. Even if LDCT has high accuracy, its invasiveness and high false positive rate limit its application to high-risk population screening. A non-invasive, cost-efficient, and easy-to-use test should instead be designed as an alternative. Exhaled breath contains thousands of volatile organic compounds (VOCs). Since ancient times, it has been understood that changes in the VOCs' mixture may be directly related to the presence of a disease, and recent studies have quantified the change in the compounds' concentration. Analyzing exhaled breath to achieve lung cancer early diagnosis represents a non-invasive, low-cost, and user-friendly approach, thus being a promising candidate for high-risk lung cancer population screening. This review discusses technological solutions that have been proposed in the literature as tools to analyze exhaled breath for lung cancer diagnosis, together with factors that potentially affect the outcome of the analysis. Even if research on this topic started many years ago, and many different technological approaches have since been adopted, there is still no validated clinical application of this technique. Standard guidelines and protocols should be defined by the medical community in order to translate exhaled breath analysis to clinical practice.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
dilli完成签到,获得积分10
3秒前
CodeCraft应助dilli采纳,获得10
5秒前
YifanWang应助科研通管家采纳,获得30
6秒前
10秒前
dilli发布了新的文献求助10
15秒前
18秒前
现代海发布了新的文献求助10
22秒前
27秒前
复杂妙海完成签到,获得积分10
30秒前
赘婿应助现代海采纳,获得10
42秒前
53秒前
EscX完成签到,获得积分10
57秒前
科研通AI6.3应助yxl采纳,获得10
1分钟前
1分钟前
科研小新发布了新的文献求助10
1分钟前
orixero应助guliguli采纳,获得10
1分钟前
危机的曼香完成签到,获得积分10
1分钟前
拿铁小笼包完成签到,获得积分10
1分钟前
Lucas应助科研小新采纳,获得10
1分钟前
1分钟前
Mr_老旭完成签到,获得积分10
1分钟前
yxl发布了新的文献求助10
1分钟前
bbband发布了新的文献求助10
1分钟前
1分钟前
1分钟前
541完成签到 ,获得积分10
1分钟前
早茶可口完成签到,获得积分10
1分钟前
现代海发布了新的文献求助10
2分钟前
所所应助糖冻采纳,获得10
2分钟前
2分钟前
成就书雪完成签到,获得积分0
2分钟前
小马甲应助科研通管家采纳,获得10
2分钟前
传奇3应助科研通管家采纳,获得10
2分钟前
彭于晏应助科研通管家采纳,获得10
2分钟前
852应助科研通管家采纳,获得10
2分钟前
努力的淼淼完成签到 ,获得积分10
2分钟前
xny发布了新的文献求助10
2分钟前
隐形曼青应助xny采纳,获得10
2分钟前
2分钟前
葛雯发布了新的文献求助10
2分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Quality by Design - An Indispensable Approach to Accelerate Biopharmaceutical Product Development 800
Pulse width control of a 3-phase inverter with non sinusoidal phase voltages 777
Signals, Systems, and Signal Processing 610
Research Methods for Applied Linguistics: A Practical Guide 600
Research Methods for Applied Linguistics 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6404250
求助须知:如何正确求助?哪些是违规求助? 8223471
关于积分的说明 17429639
捐赠科研通 5456615
什么是DOI,文献DOI怎么找? 2883591
邀请新用户注册赠送积分活动 1859842
关于科研通互助平台的介绍 1701261