Non-invasive breath analysis of pulmonary nodules.

Non-invasive breath analysis of pulmonary nodules.
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DOI:
10.1097/jto.0b013e3182637d5f
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发表时间:
2012-10
期刊:
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
影响因子:
--
通讯作者:
Haick H
Haick H
中科院分区:
其他
文献类型:
--
作者:
Peled N;Hakim M;Bunn PA Jr;Miller YE;Kennedy TC;Mattei J;Mitchell JD;Hirsch FR;Haick H

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对肺癌非侵入性诊断方法的探索已经带来了新的研究途径,包括对呼出气体的探索。以前的研究表明,肺癌原则上可以通过呼出气体分析来检测。本研究评估呼出气分析用于区分良性和恶性肺结节(PN)的潜力。在一项前瞻性试验中,从72名PN患者中采集呼吸样本。挥发性有机化合物(VOCs)的配置文件确定(i)气相色谱/质谱(GC-MS)结合固相微萃取(SPME)和(ii)化学纳米阵列。53例PN为恶性,19例为良性,具有相似的吸烟史和合并症。病灶大小(平均值+/− SD)分别为2.7±1.7和1.6±1.3 cm(p=0.004)。在恶性组中,47例为NSCLC,6例为SCLC。30例为早期疾病,23例为晚期疾病。GC-MS分析鉴定了肺癌的呼吸中显著更高浓度的1-辛烯,并且纳米阵列在良性与恶性PN之间(p<0.0001;准确度88±3%)、在腺细胞癌与鳞状细胞癌之间(p<0.0001; 88±3%)以及在早期阶段与晚期疾病之间(p<0.0001; 88±2%)显著区分。在该初步研究中,呼吸分析基于肺癌相关VOC特征在高风险队列中区分良性和恶性PN。此外,它区分了腺细胞癌和鳞状细胞癌以及早期与晚期疾病。需要进一步的研究来验证这种非侵入性的方法,使用更大的患者队列,通过CT检测PN。
The search for non-invasive diagnostic methods of lung cancer has led to new avenues of research, including the exploration of the exhaled breath. Previous studies have shown that lung cancer can in principle be detected through exhaled breath analysis. This study evaluated the potential of exhaled breath analysis for the distinction of benign and malignant pulmonary nodules (PNs). Breath samples were taken from 72 patients with PNs in a prospective trial. Profiles of volatile organic compounds (VOCs) were determined by (i) gas chromatography/mass spectrometry (GC-MS) combined with solid phase microextraction (SPME) and by (ii) a chemical nanoarray. 53 PNs were malignant and 19 were benign with similar smoking histories and co-morbidities. Nodule size (mean +/− SD) was 2.7±1.7 vs. 1.6±1.3 cm (p=0.004) respectively. Within the malignant group, 47 were NSCLC and 6 were SCLC. Thirty had early stage disease and 23 had advanced disease. GC-MS analysis identified a significantly higher concentration of 1-octene in the breath of lung cancer, and the nanoarray distinguished significantly between benign vs. malignant PNs (p<0.0001; accuracy 88±3%), between adeno- and squamous- cell carcinomas (p<0.0001; 88±3%) and between early stage and advanced disease (p<0.0001; 88±2%). In this pilot study, breath analysis discriminated benign from malignant PNs in a high-risk cohort based on lung cancer related VOC profiles. Further, it discriminated adeno-and squamous- cell carcinoma and between early vs. advanced disease. Further studies are required to validate this non-invasive approach, using a larger cohort of patients with PNs detected by CT.