- Division of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610041, P. R. China;
Early diagnosis of lung cancer is of great significance for reducing mortality and improving survival. Traditional methods of early diagnosis of lung cancer have their own limitations. The exhaled breath can reflect the disease state of the body, which has great potential in the early diagnosis of lung cancer. In this paper, the diagnosis of lung cancer and the application of exhaled breath detection technology in the diagnosis of lung cancer were reviewed.
Citation: XIE Shaohua, XIANG Run, XIE Tianpeng, LI Qiang. Research status and progress of exhaled gas analysis and diagnosis of lung cancer. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2022, 29(9): 1197-1209. doi: 10.7507/1007-4848.202112078 Copy
1. | Wild CP, Weiderpass E, Stewart BW. World cancer report: Cancer research for cancer prevention. Lyon: International Agency for Research on Cancer, 2020. |
2. | Feng RM, Zong YN, Cao SM, et al. Current cancer situation in China: Good or bad news from the 2018 Global Cancer Statistics? Cancer Commun (Lond), 2019, 39(1): 22. |
3. | Goldstraw P, Chansky K, Crowley J, et al. The IASLC Lung Cancer Staging Project: Proposals for revision of the TNM stage groupings in the forthcoming (eighth) edition of the TNM classification for lung cancer. J Thorac Oncol, 2016, 11(1): 39-51. |
4. | Khullar OV, Liu Y, Gillespie T, et al. Survival after sublobar resection versus lobectomy for clinical stage ⅠA lung cancer: An analysis from the national cancer data base. J Thorac Oncol, 2015, 10(11): 1625-1633. |
5. | Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin, 2016, 66(1): 7-30. |
6. | Krilaviciute A, Heiss JA, Leja M, et al. Detection of cancer through exhaled breath: A systematic review. Oncotarget, 2015, 6(36): 38643-38657. |
7. | Dent AG, Sutedja TG, Zimmerman PV. Exhaled breath analysis for lung cancer. J Thorac Dis, 2013, 5(Suppl 5): S540-S550. |
8. | Schreiber G, McCrory DC. Performance characteristics of different modalities for diagnosis of suspected lung cancer: Summary of published evidence. Chest, 2003, 123(1 Suppl): 115S-128S. |
9. | Yang DW, Zhang Y, Hong QY, et al. Role of a serum-based biomarker panel in the early diagnosis of lung cancer for a cohort of high-risk patients. Cancer, 2015, 121 Suppl 17: 3113-3121. |
10. | Fontana RS, Sanderson DR, Woolner LB, et al. Lung cancer screening: The Mayo program. J Occup Med, 1986, 28(8): 746-750. |
11. | Fontana RS, Sanderson DR, Woolner LB, et al. Screening for lung cancer. A critique of the Mayo Lung Project. Cancer, 1991, 67(4 Suppl): 1155-1164. |
12. | Oken MM, Hocking WG, Kvale PA, et al. Screening by chest radiograph and lung cancer mortality: The Prostate, Lung, Colorectal, and Ovarian (PLCO) randomized trial. JAMA, 2011, 306(17): 1865-1873. |
13. | 杨越清, 金梅, 罗春材, 等. 数字 X 线胸片对肺癌检查的漏诊分析. 解放军医学院学报, 2017, 38(1): 30-33. |
14. | Navani N, Spiro SG. PET scanning is important in lung cancer; but it has its limitations. Respirology, 2010, 15(8): 1149-1151. |
15. | National Lung Screening Trial Research Team, Aberle DR, Adams AM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med, 2011, 365(5): 395-409. |
16. | Christensen JD, Tong BC. Computed tomography screening for lung cancer: Where are we now? N C Med J, 2013, 74(5): 406-410. |
17. | Black WC, Gareen IF, Soneji SS, et al. Cost-effectiveness of CT screening in the National Lung Screening Trial. N Engl J Med, 2014, 371(19): 1793-1802. |
18. | Buszewski B, Kesy M, Ligor T, et al. Human exhaled air analytics: Biomarkers of diseases. Biomed Chromatogr, 2007, 21(6): 553-566. |
19. | Phillips M. Method for the collection and assay of volatile organic compounds in breath. Anal Biochem, 1997, 247(2): 272-278. |
20. | Pauling L, Robinson AB, Teranishi R, et al. Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. Proc Natl Acad Sci U S A, 1971, 68(10): 2374-2376. |
21. | Gordon SM, Szidon JP, Krotoszynski BK, et al. Volatile organic compounds in exhaled air from patients with Lung Cancer. Clin Chem, 1985, 31(8): 1278-1282. |
22. | Phillips M, Herrera J, Krishnan S, et al. Variation in volatile organic compounds in the breath of normal humans. J Chromatogr B Biomed Sci Appl, 1999, 729(1-2): 75-88. |
23. | Phillips M, Gleeson K, Hughes JM, et al. Volatile organic compounds in breath as markers of lung cancer: A cross-sectional study. Lancet, 1999, 353(9168): 1930-1933. |
24. | Phillips M, Altorki N, Austin JH, et al. Prediction of lung cancer using volatile biomarkers in breath. Cancer Biomark, 2007, 3(2): 95-109. |
25. | Rudnicka J, Kowalkowski T, Buszewski B. Searching for selected VOCs in human breath samples as potential markers of lung cancer. Lung Cancer, 2019, 135: 123-129. |
26. | Poli D, Carbognani P, Corradi M, et al. Exhaled volatile organic compounds in patients with non-small cell lung cancer: Cross sectional and nested short-term follow-up study. Respir Res, 2005, 6(1): 71. |
27. | Poli D, Goldoni M, Corradi M, et al. Determination of aldehydes in exhaled breath of patients with lung cancer by means of on-fiber-derivatisation SPME-GC/MS. J Chromatogr B Analyt Technol Biomed Life Sci, 2010, 878(27): 2643-2651. |
28. | Fuchs P, Loeseken C, Schubert JK, et al. Breath gas aldehydes as biomarkers of lung cancer. Int J Cancer, 2010, 126(11): 2663-2670. |
29. | Long Y, Wang C, Wang T, et al. High performance exhaled breath biomarkers for diagnosis of lung cancer and potential biomarkers for classification of lung cancer. J Breath Res, 2021, 15(1): 016017. |
30. | Koureas M, Kalompatsios D, Amoutzias GD, et al. Comparison of targeted and untargeted approaches in breath analysis for the discrimination of lung cancer from benign pulmonary diseases and healthy persons. Molecules, 2021, 26(9): 2609. |
31. | Hansel A, Jordan A, Holzinger R, et al. Proton transfer reaction mass spectrometry: On-line trace gas analysis at the ppb level. Int J Mass Spectrom Ion Processes, 1995, 149: 609-619. |
32. | Moser B, Bodrogi F, Eibl G, et al. Mass spectrometric profile of exhaled breath-field study by PTR-MS. Respir Physiol Neurobiol, 2005, 145(2-3): 295-300. |
33. | Feinberg T, Alkoby-Meshulam L, Herbig J, et al. Cancerous glucose metabolism in lung cancer-evidence from exhaled breath analysis. J Breath Res, 2016, 10(2): 026012. |
34. | Wehinger A, Schmid A, Mechtcheriakov S, et al. Lung cancer detection by proton transfer reaction mass-spectrometric analysis of human breath gas. Int J Mass Spectrom, 2007, 265(1): 49-59. |
35. | Bajtarevic A, Ager C, Pienz M, et al. Noninvasive detection of lung cancer by analysis of exhaled breath. BMC Cancer, 2009, 9: 348. |
36. | Slingers G, Goossens R, Janssens H, et al. Real-time selected ion flow tube mass spectrometry to assess short- and long-term variability in oral and nasal breath. J Breath Res, 2020, 14(3): 036006. |
37. | Spanĕl P, Smith D. Selected ion flow tube mass spectrometry for on-line trace gas analysis in biology and medicine. Eur J Mass Spectrom (Chichester), 2007, 13(1): 77-82. |
38. | Diskin AM, Spanel P, Smith D. Time variation of ammonia, acetone, isoprene and ethanol in breath: A quantitative SIFT-MS study over 30 days. Physiol Meas, 2003, 24(1): 107-119. |
39. | Smith D, Wang T, Sulé-Suso J, et al. Quantification of acetaldehyde released by lung cancer cells in vitro using selected ion flow tube mass spectrometry. Rapid Commun Mass Spectrom, 2003, 17(8): 845-850. |
40. | Sulé-Suso J, Pysanenko A, Spanel P, et al. Quantification of acetaldehyde and carbon dioxide in the headspace of malignant and non-malignant lung cells in vitro by SIFT-MS. Analyst, 2009, 134(12): 2419-2425. |
41. | Tsou PH, Lin ZL, Pan YC, et al. Exploring volatile organic compounds in breath for high-accuracy prediction of lung cancer. Cancers (Basel), 2021, 13(6): 1431. |
42. | Nikolaev EN, Kostyukevich YI, Vladimirov GN. Fourier transform ion cyclotron resonance (FT ICR) mass spectrometry: Theory and simulations. Mass Spectrom Rev, 2016, 35(2): 219-258. |
43. | Fu XA, Li M, Knipp RJ, et al. Noninvasive detection of lung cancer using exhaled breath. Cancer Med, 2014, 3(1): 174-181. |
44. | Li M, Yang D, Brock G, et al. Breath carbonyl compounds as biomarkers of lung cancer. Lung Cancer, 2015, 90(1): 92-97. |
45. | Monge ME, Harris GA, Dwivedi P, et al. Mass spectrometry: Recent advances in direct open air surface sampling/ionization. Chem Rev, 2013, 113(4): 2269-2308. |
46. | Zuo W, Bai W, Gan X, et al. Detection of lung cancer by analysis of exhaled gas utilizing extractive electrospray ionization-mass spectroscopy. J Biomed Nanotechnol, 2019, 15(4): 633-646. |
47. | Gardner JW, Bartlett PN. A brief history of electronic noses. Sens Actuators B Chem, 1994, 18(1-3): 210-211. |
48. | Yan J, Guo X, Duan S, et al. Electronic nose feature extraction methods: A review. Sensors (Basel), 2015, 15(11): 27804-27831. |
49. | Behera B, Joshi R, Anil Vishnu GK, et al. Electronic nose: A non-invasive technology for breath analysis of diabetes and lung cancer patients. J Breath Res, 2019, 13(2): 024001. |
50. | Wilson AD, Baietto M. Applications and advances in electronic-nose technologies. Sensors (Basel), 2009, 9(7): 5099-5148. |
51. | Machado RF, Laskowski D, Deffenderfer O, et al. Detection of lung cancer by sensor array analyses of exhaled breath. Am J Respir Crit Care Med, 2005, 171(11): 1286-1291. |
52. | McWilliams A, Beigi P, Srinidhi A, et al. Sex and smoking status effects on the early detection of early lung cancer in high-risk smokers using an electronic nose. IEEE Trans Biomed Eng, 2015, 62(8): 2044-2054. |
53. | Hubers AJ, Brinkman P, Boksem RJ, et al. Combined sputum hypermethylation and eNose analysis for lung cancer diagnosis. J Clin Pathol, 2014, 67(8): 707-711. |
54. | Tirzīte M, Bukovskis M, Strazda G, et al. Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis. J Breath Res, 2017, 11(3): 036009. |
55. | Bikov A, Hernadi M, Korosi BZ, et al. Expiratory flow rate, breath hold and anatomic dead space influence electronic nose ability to detect lung cancer. BMC Pulm Med, 2014, 14: 202. |
56. | Rodríguez-Aguilar M, Díaz de León-Martínez L, Gorocica-Rosete P, et al. Application of chemoresistive gas sensors and chemometric analysis to differentiate the fingerprints of global volatile organic compounds from diseases. Preliminary results of COPD, lung cancer and breast cancer. Clin Chim Acta, 2021, 518: 83-92. |
57. | Wang Z, Yang M, He J, et al. Progress of different sensing materials modified QCM gas sensors. Prog Chem, 2015, 27(2/3): 251-266. |
58. | Di Natale C, Paolesse R, D'Amico A. Metalloporphyrins based artificial olfactory receptors. Sens Actuators B Chem, 2007, 121(1): 238-246. |
59. | Di Natale C, Macagnano A, Martinelli E, et al. Lung cancer identification by the analysis of breath by means of an array of non-selective gas sensors. Biosens Bioelectron, 2003, 18(10): 1209-1218. |
60. | Gasparri R, Santonico M, Valentini C, et al. Volatile signature for the early diagnosis of lung cancer. J Breath Res, 2016, 10(1): 016007. |
61. | D'Amico A, Pennazza G, Santonico M, et al. An investigation on electronic nose diagnosis of lung cancer. Lung Cancer, 2010, 68(2): 170-176. |
62. | Rocco R, Incalzi RA, Pennazza G, et al. BIONOTE E-nose technology may reduce false positives in lung cancer screening programmes. Eur J Cardiothorac Surg, 2016, 49(4): 1112-1117. |
63. | Jakubik WP. Surface acoustic wave-based gas sensors. Thin Solid Films, 2011, 520(3): 986-993. |
64. | Chen X, Cao M, Hao Y, et al. A Non-invasive detection of lung cancer combined virtual gas sensors array with imaging recognition technique. Conf Proc IEEE Eng Med Biol Soc, 2005, 2005: 5873-5876. |
65. | de Vries R, Brinkman P, van der Schee MP, et al. Integration of electronic nose technology with spirometry: Validation of a new approach for exhaled breath analysis. J Breath Res, 2015, 9(4): 046001. |
66. | de Vries R, Muller M, van der Noort V, et al. Prediction of response to anti-PD-1 therapy in patients with non-small-cell lung cancer by electronic nose analysis of exhaled breath. Ann Oncol, 2019, 30(10): 1660-1666. |
67. | Kort S, Tiggeloven MM, Brusse-Keizer M, et al. Multi-centre prospective study on diagnosing subtypes of lung cancer by exhaled-breath analysis. Lung Cancer, 2018, 125: 223-229. |
68. | Marzorati D, Mainardi L, Sedda G, et al. A metal oxide gas sensors array for lung cancer diagnosis through exhaled breath analysis. Annu Int Conf IEEE Eng Med Biol Soc, 2019, 2019: 1584-1587. |
69. | Mazzone PJ, Hammel J, Dweik R, et al. Diagnosis of lung cancer by the analysis of exhaled breath with a colorimetric sensor array. Thorax, 2007, 62(7): 565-568. |
70. | Mazzone PJ, Wang XF, Xu Y, et al. Exhaled breath analysis with a colorimetric sensor array for the identification and characterization of lung cancer. J Thorac Oncol, 2012, 7(1): 137-142. |
71. | Huo D, Xu Y, Hou C, et al. A novel optical chemical sensor based AuNR-MTPP and dyes for lung cancer biomarkers in exhaled breath identification. Sens Actuators B Chem, 2014, 199: 446-456. |
72. | Zhong X, Li D, Du W, et al. Rapid recognition of volatile organic compounds with colorimetric sensor arrays for lung cancer screening. Anal Bioanal Chem, 2018, 410(16): 3671-3681. |
73. | Peng G, Tisch U, Adams O, et al. Diagnosing lung cancer in exhaled breath using gold nanoparticles. Nat Nanotechnol, 2009, 4(10): 669-673. |
74. | Shlomi D, Abud M, Liran O, et al. Detection of lung cancer and EGFR mutation by electronic nose system. J Thorac Oncol, 2017, 12(10): 1544-1551. |
75. | Barash O, Peled N, Tisch U, et al. Classification of lung cancer histology by gold nanoparticle sensors. Nanomedicine, 2012, 8(5): 580-589. |
76. | Peled N, Barash O, Tisch U, et al. Volatile fingerprints of cancer specific genetic mutations. Nanomedicine, 2013, 9(6): 758-766. |
77. | Chen Q, Chen Z, Liu D, et al. Constructing an E-nose using metal-ion-induced assembly of graphene oxide for diagnosis of lung cancer via exhaled breath. ACS Appl Mater Interfaces, 2020, 12(15): 17713-17724. |
78. | Huang CH, Zeng C, Wang YC, et al. A study of diagnostic accuracy using a chemical sensor array and a machine learning technique to detect lung cancer. Sensors (Basel), 2018, 18(9): 2845. |
79. | Davies MP, Barash O, Jeries R, et al. Unique volatolomic signatures of TP53 and KRAS in lung cells. Br J Cancer, 2014, 111(6): 1213-1221. |
80. | Chen K, Liu L, Nie B, et al. Recognizing lung cancer and stages using a self-developed electronic nose system. Comput Biol Med, 2021, 131: 104294. |
81. | Williams H, Pembroke A. Sniffer dogs in the melanoma clinic? Lancet, 1989, 1(8640): 734. |
82. | Church J, Williams H. Another sniffer dog for the clinic? Lancet, 2001, 358(9285): 930. |
83. | McCulloch M, Jezierski T, Broffman M, et al. Diagnostic accuracy of canine scent detection in early- and late-stage lung and breast cancers. Integr Cancer Ther, 2006, 5(1): 30-39. |
84. | Ehmann R, Boedeker E, Friedrich U, et al. Canine scent detection in the diagnosis of lung cancer: Revisiting a puzzling phenomenon. Eur Respir J, 2012, 39(3): 669-676. |
85. | Guirao A, Molins L, Ramón I, et al. Trained dogs can identify malignant solitary pulmonary nodules in exhaled gas. Lung Cancer, 2019, 135: 230-233. |
86. | Buszewski B, Ligor T, Jezierski T, et al. Identification of volatile lung cancer markers by gas chromatography-mass spectrometry: Comparison with discrimination by canines. Anal Bioanal Chem, 2012, 404(1): 141-146. |
87. | Mazzola SM, Pirrone F, Sedda G, et al. Two-step investigation of lung cancer detection by sniffer dogs. J Breath Res, 2020, 14(2): 026011. |
88. | Biehl W, Hattesohl A, Jörres RA, et al. VOC pattern recognition of lung cancer: A comparative evaluation of different dog- and eNose-based strategies using different sampling materials. Acta Oncol, 2019, 58(9): 1216-1224. |
89. | Baumbach JI. Ion mobility spectrometry coupled with multi-capillary columns for metabolic profiling of human breath. J Breath Res, 2009, 3(3): 034001. |
90. | Westhoff M, Litterst P, Freitag L, et al. Ion mobility spectrometry for the detection of volatile organic compounds in exhaled breath of patients with lung cancer: results of a pilot study. Thorax, 2009, 64(9): 744-748. |
91. | Handa H, Usuba A, Maddula S, et al. Exhaled breath analysis for lung cancer detection using ion mobility spectrometry. PLoS One, 2014, 9(12): e114555. |
92. | Darwiche K, Baumbach JI, Sommerwerck U, et al. Bronchoscopically obtained volatile biomarkers in lung cancer. Lung, 2011, 189(6): 445-452. |
93. | Xia Z, Li D, Deng W. Identification and detection of volatile aldehydes as lung cancer biomarkers by vapor generation combined with paper-based thin-film microextraction. Anal Chem, 2021, 93(11): 4924-4931. |
94. | Li Z, Li Y, Zhan L, et al. Point-of-care test paper for exhaled breath aldehyde analysis via mass spectrometry. Anal Chem, 2021, 93(26): 9158-9165. |
95. | Scheideler L, Manke HG, Schwulera U, et al. Detection of nonvolatile macromolecules in breath. A possible diagnostic tool? Am Rev Respir Dis, 1993, 148(3): 778-784. |
96. | Carpagnano GE, Resta O, Foschino-Barbaro MP, et al. Interleukin-6 is increased in breath condensate of patients with non-small cell lung cancer. Int J Biol Markers, 2002, 17(2): 141-145. |
97. | Carpagnano GE, Foschino-Barbaro MP, Resta O, et al. Endothelin-1 is increased in the breath condensate of patients with non-small-cell lung cancer. Oncology, 2004, 66(3): 180-184. |
98. | 陈琳, 朱惠莉, 张新. 非小细胞肺癌患者呼出气冷凝液ET-1测定的意义. 西安交通大学学报(医学版), 2011, 32(4): 458-461. |
99. | Carpagnano GE, Spanevello A, Curci C, et al. IL-2, TNF-alpha, and leptin: Local versus systemic concentrations in NSCLC patients. Oncol Res, 2007, 16(8): 375-381. |
100. | 秦娥, 沈巨信, 孙健, 等. 非小细胞肺癌患者血和呼出气冷凝液转移生长因子β1的检测及诊断价值. 中国卫生检验杂志, 2019, 29(1): 61-63. |
101. | 董敬军, 陶一江, 陈建荣, 等. 非小细胞肺癌患者呼出气冷凝液中CEA检测的临床意义. 临床肺科杂志, 2008, 13(7): 828-830. |
102. | 陈琳. 非小细胞肺癌患者呼出气冷凝液CEA、ET-1测定的意义. 复旦大学, 2009. |
103. | 邹莹畅. 基于呼出气体及其冷凝物检测的肺癌早期诊断方法及仪器研究. 浙江大学, 2016. |
104. | Carpagnano GE, Foschino-Barbaro MP, Mulé G, et al. 3p microsatellite alterations in exhaled breath condensate from patients with non-small cell lung cancer. Am J Respir Crit Care Med, 2005, 172(6): 738-744. |
105. | Carpagnano GE, Foschino-Barbaro MP, Spanevello A, et al. 3p microsatellite signature in exhaled breath condensate and tumor tissue of patients with lung cancer. Am J Respir Crit Care Med, 2008, 177(3): 337-341. |
106. | Gessner C, Kuhn H, Toepfer K, et al. Detection of p53 gene mutations in exhaled breath condensate of non-small cell lung cancer patients. Lung Cancer, 2004, 43(2): 215-222. |
107. | 黄芬芬, 陈金亮, 陈建荣. 非小细胞肺癌呼出气冷凝液中p16基因突变及表达分析. 临床军医杂志, 2019, 47(11): 1254-1256. |
108. | Faist J, Capasso F, Sivco DL, et al. Quantum cascade laser. Science, 1994, 264(5158): 553-556. |
109. | 刘峰奇, 张锦川, 刘俊岐, 等. 量子级联激光器研究进展. 中国激光, 2020, 47(7): 79-91. |
110. | Weidmann D, Wysocki G, Oppenheimer C, et al. Development of a compact quantum cascade laser spectrometer for field measurements of CO2 isotopes. Appl Phys B, 2005, 80: 255-260. |
111. | Rubin T, von Haimberger T, Helmke A, et al. Quantitative determination of metabolization dynamics by a real-time 13CO2 breath test. J Breath Res, 2011, 5(2): 027102. |
112. | Ghorbani R, Schmidt FM. Real-time breath gas analysis of CO and CO2 using an EC-QCL. Appl Phys B, 2017, 123: 144. |
113. | Gaston B, Drazen JM, Loscalzo J, et al. The biology of nitrogen oxides in the airways. Am J Respir Crit Care Med, 1994, 149(2 Pt 1): 538-551. |
114. | McCurdy MR, Bakhirkin Y, Wysocki G, et al. Performance of an exhaled nitric oxide and carbon dioxide sensor using quantum cascade laser-based integrated cavity output spectroscopy. J Biomed Opt, 2007, 12(3): 034034. |
115. | Manne J, Sukhorukov O, Jäger W, et al. Pulsed quantum cascade laser-based cavity ring-down spectroscopy for ammonia detection in breath. Appl Opt, 2006, 45(36): 9230-9237. |
116. | Owen K, Farooq A. A calibration-free ammonia breath sensor using a quantum cascade laser with WMS 2f/1f. Applied Physics B, 2014, 116(2): 371-383. |
117. | Risby TH, Tittel FK. Current status of midinfrared quantum and interband cascade lasers for clinical breath analysis. Optical Engineering, 2010, 49(11): 111123. |
118. | Wang C, Sahay P. Breath analysis using laser spectroscopic techniques: Breath biomarkers, spectral fingerprints, and detection limits. Sensors (Basel), 2009, 9(10): 8230-8262. |
119. | Wang Z, Wang C. Is breath acetone a biomarker of diabetes? A historical review on breath acetone measurements. J Breath Res, 2013, 7(3): 037109. |
120. | Ciaffoni L, Hancock G, Harrison JJ, et al. Demonstration of a mid-infrared cavity enhanced absorption spectrometer for breath acetone detection. Anal Chem, 2013, 85(2): 846-850. |
121. | Reyes-Reyes A, Horsten RC, Urbach HP, et al. Study of the exhaled acetone in type 1 diabetes using quantum cascade laser spectroscopy. Anal Chem, 2015, 87(1): 507-512. |
122. | Shorter JH, Nelson DD, McManus JB, et al. Clinical study of multiple breath biomarkers of asthma and COPD (NO, CO(2), CO and N(2)O) by infrared laser spectroscopy. J Breath Res, 2011, 5(3): 037108. |
123. | Shorter JH, Nelson DD, Barry McManus J, et al. Multicomponent breath analysis with infrared absorption using room-temperature quantum cascade lasers. IEEE Sens J, 2009, 10(1): 76-84. |
124. | Martínez-Lozano P, de la Mora JF. Electrospray ionization of volatiles in breath. Int J Mass Spectrom, 2007, 265(1): 68-72. |
125. | Li X, Huang L, Zhu H, et al. Direct human breath analysis by secondary nano-electrospray ionization ultrahigh-resolution mass spectrometry: Importance of high mass resolution and mass accuracy. Rapid Commun Mass Spectrom, 2017, 31(3): 301-308. |
126. | Sinues PM, Kohler M, Zenobi R. Monitoring diurnal changes in exhaled human breath. Anal Chem, 2013, 85(1): 369-373. |
127. | Martinez-Lozano Sinues P, Landoni E, Miceli R, et al. Secondary electrospray ionization-mass spectrometry and a novel statistical bioinformatic approach identifies a cancer-related profile in exhaled breath of breast cancer patients: A pilot study. J Breath Res, 2015, 9(3): 031001. |
128. | Rizzo S, Del Grande F, Wannesson L, et al. Recent developments and advances in secondary prevention of lung cancer. Eur J Cancer Prev, 2020, 29(4): 321-328. |
- 1. Wild CP, Weiderpass E, Stewart BW. World cancer report: Cancer research for cancer prevention. Lyon: International Agency for Research on Cancer, 2020.
- 2. Feng RM, Zong YN, Cao SM, et al. Current cancer situation in China: Good or bad news from the 2018 Global Cancer Statistics? Cancer Commun (Lond), 2019, 39(1): 22.
- 3. Goldstraw P, Chansky K, Crowley J, et al. The IASLC Lung Cancer Staging Project: Proposals for revision of the TNM stage groupings in the forthcoming (eighth) edition of the TNM classification for lung cancer. J Thorac Oncol, 2016, 11(1): 39-51.
- 4. Khullar OV, Liu Y, Gillespie T, et al. Survival after sublobar resection versus lobectomy for clinical stage ⅠA lung cancer: An analysis from the national cancer data base. J Thorac Oncol, 2015, 10(11): 1625-1633.
- 5. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin, 2016, 66(1): 7-30.
- 6. Krilaviciute A, Heiss JA, Leja M, et al. Detection of cancer through exhaled breath: A systematic review. Oncotarget, 2015, 6(36): 38643-38657.
- 7. Dent AG, Sutedja TG, Zimmerman PV. Exhaled breath analysis for lung cancer. J Thorac Dis, 2013, 5(Suppl 5): S540-S550.
- 8. Schreiber G, McCrory DC. Performance characteristics of different modalities for diagnosis of suspected lung cancer: Summary of published evidence. Chest, 2003, 123(1 Suppl): 115S-128S.
- 9. Yang DW, Zhang Y, Hong QY, et al. Role of a serum-based biomarker panel in the early diagnosis of lung cancer for a cohort of high-risk patients. Cancer, 2015, 121 Suppl 17: 3113-3121.
- 10. Fontana RS, Sanderson DR, Woolner LB, et al. Lung cancer screening: The Mayo program. J Occup Med, 1986, 28(8): 746-750.
- 11. Fontana RS, Sanderson DR, Woolner LB, et al. Screening for lung cancer. A critique of the Mayo Lung Project. Cancer, 1991, 67(4 Suppl): 1155-1164.
- 12. Oken MM, Hocking WG, Kvale PA, et al. Screening by chest radiograph and lung cancer mortality: The Prostate, Lung, Colorectal, and Ovarian (PLCO) randomized trial. JAMA, 2011, 306(17): 1865-1873.
- 13. 杨越清, 金梅, 罗春材, 等. 数字 X 线胸片对肺癌检查的漏诊分析. 解放军医学院学报, 2017, 38(1): 30-33.
- 14. Navani N, Spiro SG. PET scanning is important in lung cancer; but it has its limitations. Respirology, 2010, 15(8): 1149-1151.
- 15. National Lung Screening Trial Research Team, Aberle DR, Adams AM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med, 2011, 365(5): 395-409.
- 16. Christensen JD, Tong BC. Computed tomography screening for lung cancer: Where are we now? N C Med J, 2013, 74(5): 406-410.
- 17. Black WC, Gareen IF, Soneji SS, et al. Cost-effectiveness of CT screening in the National Lung Screening Trial. N Engl J Med, 2014, 371(19): 1793-1802.
- 18. Buszewski B, Kesy M, Ligor T, et al. Human exhaled air analytics: Biomarkers of diseases. Biomed Chromatogr, 2007, 21(6): 553-566.
- 19. Phillips M. Method for the collection and assay of volatile organic compounds in breath. Anal Biochem, 1997, 247(2): 272-278.
- 20. Pauling L, Robinson AB, Teranishi R, et al. Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. Proc Natl Acad Sci U S A, 1971, 68(10): 2374-2376.
- 21. Gordon SM, Szidon JP, Krotoszynski BK, et al. Volatile organic compounds in exhaled air from patients with Lung Cancer. Clin Chem, 1985, 31(8): 1278-1282.
- 22. Phillips M, Herrera J, Krishnan S, et al. Variation in volatile organic compounds in the breath of normal humans. J Chromatogr B Biomed Sci Appl, 1999, 729(1-2): 75-88.
- 23. Phillips M, Gleeson K, Hughes JM, et al. Volatile organic compounds in breath as markers of lung cancer: A cross-sectional study. Lancet, 1999, 353(9168): 1930-1933.
- 24. Phillips M, Altorki N, Austin JH, et al. Prediction of lung cancer using volatile biomarkers in breath. Cancer Biomark, 2007, 3(2): 95-109.
- 25. Rudnicka J, Kowalkowski T, Buszewski B. Searching for selected VOCs in human breath samples as potential markers of lung cancer. Lung Cancer, 2019, 135: 123-129.
- 26. Poli D, Carbognani P, Corradi M, et al. Exhaled volatile organic compounds in patients with non-small cell lung cancer: Cross sectional and nested short-term follow-up study. Respir Res, 2005, 6(1): 71.
- 27. Poli D, Goldoni M, Corradi M, et al. Determination of aldehydes in exhaled breath of patients with lung cancer by means of on-fiber-derivatisation SPME-GC/MS. J Chromatogr B Analyt Technol Biomed Life Sci, 2010, 878(27): 2643-2651.
- 28. Fuchs P, Loeseken C, Schubert JK, et al. Breath gas aldehydes as biomarkers of lung cancer. Int J Cancer, 2010, 126(11): 2663-2670.
- 29. Long Y, Wang C, Wang T, et al. High performance exhaled breath biomarkers for diagnosis of lung cancer and potential biomarkers for classification of lung cancer. J Breath Res, 2021, 15(1): 016017.
- 30. Koureas M, Kalompatsios D, Amoutzias GD, et al. Comparison of targeted and untargeted approaches in breath analysis for the discrimination of lung cancer from benign pulmonary diseases and healthy persons. Molecules, 2021, 26(9): 2609.
- 31. Hansel A, Jordan A, Holzinger R, et al. Proton transfer reaction mass spectrometry: On-line trace gas analysis at the ppb level. Int J Mass Spectrom Ion Processes, 1995, 149: 609-619.
- 32. Moser B, Bodrogi F, Eibl G, et al. Mass spectrometric profile of exhaled breath-field study by PTR-MS. Respir Physiol Neurobiol, 2005, 145(2-3): 295-300.
- 33. Feinberg T, Alkoby-Meshulam L, Herbig J, et al. Cancerous glucose metabolism in lung cancer-evidence from exhaled breath analysis. J Breath Res, 2016, 10(2): 026012.
- 34. Wehinger A, Schmid A, Mechtcheriakov S, et al. Lung cancer detection by proton transfer reaction mass-spectrometric analysis of human breath gas. Int J Mass Spectrom, 2007, 265(1): 49-59.
- 35. Bajtarevic A, Ager C, Pienz M, et al. Noninvasive detection of lung cancer by analysis of exhaled breath. BMC Cancer, 2009, 9: 348.
- 36. Slingers G, Goossens R, Janssens H, et al. Real-time selected ion flow tube mass spectrometry to assess short- and long-term variability in oral and nasal breath. J Breath Res, 2020, 14(3): 036006.
- 37. Spanĕl P, Smith D. Selected ion flow tube mass spectrometry for on-line trace gas analysis in biology and medicine. Eur J Mass Spectrom (Chichester), 2007, 13(1): 77-82.
- 38. Diskin AM, Spanel P, Smith D. Time variation of ammonia, acetone, isoprene and ethanol in breath: A quantitative SIFT-MS study over 30 days. Physiol Meas, 2003, 24(1): 107-119.
- 39. Smith D, Wang T, Sulé-Suso J, et al. Quantification of acetaldehyde released by lung cancer cells in vitro using selected ion flow tube mass spectrometry. Rapid Commun Mass Spectrom, 2003, 17(8): 845-850.
- 40. Sulé-Suso J, Pysanenko A, Spanel P, et al. Quantification of acetaldehyde and carbon dioxide in the headspace of malignant and non-malignant lung cells in vitro by SIFT-MS. Analyst, 2009, 134(12): 2419-2425.
- 41. Tsou PH, Lin ZL, Pan YC, et al. Exploring volatile organic compounds in breath for high-accuracy prediction of lung cancer. Cancers (Basel), 2021, 13(6): 1431.
- 42. Nikolaev EN, Kostyukevich YI, Vladimirov GN. Fourier transform ion cyclotron resonance (FT ICR) mass spectrometry: Theory and simulations. Mass Spectrom Rev, 2016, 35(2): 219-258.
- 43. Fu XA, Li M, Knipp RJ, et al. Noninvasive detection of lung cancer using exhaled breath. Cancer Med, 2014, 3(1): 174-181.
- 44. Li M, Yang D, Brock G, et al. Breath carbonyl compounds as biomarkers of lung cancer. Lung Cancer, 2015, 90(1): 92-97.
- 45. Monge ME, Harris GA, Dwivedi P, et al. Mass spectrometry: Recent advances in direct open air surface sampling/ionization. Chem Rev, 2013, 113(4): 2269-2308.
- 46. Zuo W, Bai W, Gan X, et al. Detection of lung cancer by analysis of exhaled gas utilizing extractive electrospray ionization-mass spectroscopy. J Biomed Nanotechnol, 2019, 15(4): 633-646.
- 47. Gardner JW, Bartlett PN. A brief history of electronic noses. Sens Actuators B Chem, 1994, 18(1-3): 210-211.
- 48. Yan J, Guo X, Duan S, et al. Electronic nose feature extraction methods: A review. Sensors (Basel), 2015, 15(11): 27804-27831.
- 49. Behera B, Joshi R, Anil Vishnu GK, et al. Electronic nose: A non-invasive technology for breath analysis of diabetes and lung cancer patients. J Breath Res, 2019, 13(2): 024001.
- 50. Wilson AD, Baietto M. Applications and advances in electronic-nose technologies. Sensors (Basel), 2009, 9(7): 5099-5148.
- 51. Machado RF, Laskowski D, Deffenderfer O, et al. Detection of lung cancer by sensor array analyses of exhaled breath. Am J Respir Crit Care Med, 2005, 171(11): 1286-1291.
- 52. McWilliams A, Beigi P, Srinidhi A, et al. Sex and smoking status effects on the early detection of early lung cancer in high-risk smokers using an electronic nose. IEEE Trans Biomed Eng, 2015, 62(8): 2044-2054.
- 53. Hubers AJ, Brinkman P, Boksem RJ, et al. Combined sputum hypermethylation and eNose analysis for lung cancer diagnosis. J Clin Pathol, 2014, 67(8): 707-711.
- 54. Tirzīte M, Bukovskis M, Strazda G, et al. Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis. J Breath Res, 2017, 11(3): 036009.
- 55. Bikov A, Hernadi M, Korosi BZ, et al. Expiratory flow rate, breath hold and anatomic dead space influence electronic nose ability to detect lung cancer. BMC Pulm Med, 2014, 14: 202.
- 56. Rodríguez-Aguilar M, Díaz de León-Martínez L, Gorocica-Rosete P, et al. Application of chemoresistive gas sensors and chemometric analysis to differentiate the fingerprints of global volatile organic compounds from diseases. Preliminary results of COPD, lung cancer and breast cancer. Clin Chim Acta, 2021, 518: 83-92.
- 57. Wang Z, Yang M, He J, et al. Progress of different sensing materials modified QCM gas sensors. Prog Chem, 2015, 27(2/3): 251-266.
- 58. Di Natale C, Paolesse R, D'Amico A. Metalloporphyrins based artificial olfactory receptors. Sens Actuators B Chem, 2007, 121(1): 238-246.
- 59. Di Natale C, Macagnano A, Martinelli E, et al. Lung cancer identification by the analysis of breath by means of an array of non-selective gas sensors. Biosens Bioelectron, 2003, 18(10): 1209-1218.
- 60. Gasparri R, Santonico M, Valentini C, et al. Volatile signature for the early diagnosis of lung cancer. J Breath Res, 2016, 10(1): 016007.
- 61. D'Amico A, Pennazza G, Santonico M, et al. An investigation on electronic nose diagnosis of lung cancer. Lung Cancer, 2010, 68(2): 170-176.
- 62. Rocco R, Incalzi RA, Pennazza G, et al. BIONOTE E-nose technology may reduce false positives in lung cancer screening programmes. Eur J Cardiothorac Surg, 2016, 49(4): 1112-1117.
- 63. Jakubik WP. Surface acoustic wave-based gas sensors. Thin Solid Films, 2011, 520(3): 986-993.
- 64. Chen X, Cao M, Hao Y, et al. A Non-invasive detection of lung cancer combined virtual gas sensors array with imaging recognition technique. Conf Proc IEEE Eng Med Biol Soc, 2005, 2005: 5873-5876.
- 65. de Vries R, Brinkman P, van der Schee MP, et al. Integration of electronic nose technology with spirometry: Validation of a new approach for exhaled breath analysis. J Breath Res, 2015, 9(4): 046001.
- 66. de Vries R, Muller M, van der Noort V, et al. Prediction of response to anti-PD-1 therapy in patients with non-small-cell lung cancer by electronic nose analysis of exhaled breath. Ann Oncol, 2019, 30(10): 1660-1666.
- 67. Kort S, Tiggeloven MM, Brusse-Keizer M, et al. Multi-centre prospective study on diagnosing subtypes of lung cancer by exhaled-breath analysis. Lung Cancer, 2018, 125: 223-229.
- 68. Marzorati D, Mainardi L, Sedda G, et al. A metal oxide gas sensors array for lung cancer diagnosis through exhaled breath analysis. Annu Int Conf IEEE Eng Med Biol Soc, 2019, 2019: 1584-1587.
- 69. Mazzone PJ, Hammel J, Dweik R, et al. Diagnosis of lung cancer by the analysis of exhaled breath with a colorimetric sensor array. Thorax, 2007, 62(7): 565-568.
- 70. Mazzone PJ, Wang XF, Xu Y, et al. Exhaled breath analysis with a colorimetric sensor array for the identification and characterization of lung cancer. J Thorac Oncol, 2012, 7(1): 137-142.
- 71. Huo D, Xu Y, Hou C, et al. A novel optical chemical sensor based AuNR-MTPP and dyes for lung cancer biomarkers in exhaled breath identification. Sens Actuators B Chem, 2014, 199: 446-456.
- 72. Zhong X, Li D, Du W, et al. Rapid recognition of volatile organic compounds with colorimetric sensor arrays for lung cancer screening. Anal Bioanal Chem, 2018, 410(16): 3671-3681.
- 73. Peng G, Tisch U, Adams O, et al. Diagnosing lung cancer in exhaled breath using gold nanoparticles. Nat Nanotechnol, 2009, 4(10): 669-673.
- 74. Shlomi D, Abud M, Liran O, et al. Detection of lung cancer and EGFR mutation by electronic nose system. J Thorac Oncol, 2017, 12(10): 1544-1551.
- 75. Barash O, Peled N, Tisch U, et al. Classification of lung cancer histology by gold nanoparticle sensors. Nanomedicine, 2012, 8(5): 580-589.
- 76. Peled N, Barash O, Tisch U, et al. Volatile fingerprints of cancer specific genetic mutations. Nanomedicine, 2013, 9(6): 758-766.
- 77. Chen Q, Chen Z, Liu D, et al. Constructing an E-nose using metal-ion-induced assembly of graphene oxide for diagnosis of lung cancer via exhaled breath. ACS Appl Mater Interfaces, 2020, 12(15): 17713-17724.
- 78. Huang CH, Zeng C, Wang YC, et al. A study of diagnostic accuracy using a chemical sensor array and a machine learning technique to detect lung cancer. Sensors (Basel), 2018, 18(9): 2845.
- 79. Davies MP, Barash O, Jeries R, et al. Unique volatolomic signatures of TP53 and KRAS in lung cells. Br J Cancer, 2014, 111(6): 1213-1221.
- 80. Chen K, Liu L, Nie B, et al. Recognizing lung cancer and stages using a self-developed electronic nose system. Comput Biol Med, 2021, 131: 104294.
- 81. Williams H, Pembroke A. Sniffer dogs in the melanoma clinic? Lancet, 1989, 1(8640): 734.
- 82. Church J, Williams H. Another sniffer dog for the clinic? Lancet, 2001, 358(9285): 930.
- 83. McCulloch M, Jezierski T, Broffman M, et al. Diagnostic accuracy of canine scent detection in early- and late-stage lung and breast cancers. Integr Cancer Ther, 2006, 5(1): 30-39.
- 84. Ehmann R, Boedeker E, Friedrich U, et al. Canine scent detection in the diagnosis of lung cancer: Revisiting a puzzling phenomenon. Eur Respir J, 2012, 39(3): 669-676.
- 85. Guirao A, Molins L, Ramón I, et al. Trained dogs can identify malignant solitary pulmonary nodules in exhaled gas. Lung Cancer, 2019, 135: 230-233.
- 86. Buszewski B, Ligor T, Jezierski T, et al. Identification of volatile lung cancer markers by gas chromatography-mass spectrometry: Comparison with discrimination by canines. Anal Bioanal Chem, 2012, 404(1): 141-146.
- 87. Mazzola SM, Pirrone F, Sedda G, et al. Two-step investigation of lung cancer detection by sniffer dogs. J Breath Res, 2020, 14(2): 026011.
- 88. Biehl W, Hattesohl A, Jörres RA, et al. VOC pattern recognition of lung cancer: A comparative evaluation of different dog- and eNose-based strategies using different sampling materials. Acta Oncol, 2019, 58(9): 1216-1224.
- 89. Baumbach JI. Ion mobility spectrometry coupled with multi-capillary columns for metabolic profiling of human breath. J Breath Res, 2009, 3(3): 034001.
- 90. Westhoff M, Litterst P, Freitag L, et al. Ion mobility spectrometry for the detection of volatile organic compounds in exhaled breath of patients with lung cancer: results of a pilot study. Thorax, 2009, 64(9): 744-748.
- 91. Handa H, Usuba A, Maddula S, et al. Exhaled breath analysis for lung cancer detection using ion mobility spectrometry. PLoS One, 2014, 9(12): e114555.
- 92. Darwiche K, Baumbach JI, Sommerwerck U, et al. Bronchoscopically obtained volatile biomarkers in lung cancer. Lung, 2011, 189(6): 445-452.
- 93. Xia Z, Li D, Deng W. Identification and detection of volatile aldehydes as lung cancer biomarkers by vapor generation combined with paper-based thin-film microextraction. Anal Chem, 2021, 93(11): 4924-4931.
- 94. Li Z, Li Y, Zhan L, et al. Point-of-care test paper for exhaled breath aldehyde analysis via mass spectrometry. Anal Chem, 2021, 93(26): 9158-9165.
- 95. Scheideler L, Manke HG, Schwulera U, et al. Detection of nonvolatile macromolecules in breath. A possible diagnostic tool? Am Rev Respir Dis, 1993, 148(3): 778-784.
- 96. Carpagnano GE, Resta O, Foschino-Barbaro MP, et al. Interleukin-6 is increased in breath condensate of patients with non-small cell lung cancer. Int J Biol Markers, 2002, 17(2): 141-145.
- 97. Carpagnano GE, Foschino-Barbaro MP, Resta O, et al. Endothelin-1 is increased in the breath condensate of patients with non-small-cell lung cancer. Oncology, 2004, 66(3): 180-184.
- 98. 陈琳, 朱惠莉, 张新. 非小细胞肺癌患者呼出气冷凝液ET-1测定的意义. 西安交通大学学报(医学版), 2011, 32(4): 458-461.
- 99. Carpagnano GE, Spanevello A, Curci C, et al. IL-2, TNF-alpha, and leptin: Local versus systemic concentrations in NSCLC patients. Oncol Res, 2007, 16(8): 375-381.
- 100. 秦娥, 沈巨信, 孙健, 等. 非小细胞肺癌患者血和呼出气冷凝液转移生长因子β1的检测及诊断价值. 中国卫生检验杂志, 2019, 29(1): 61-63.
- 101. 董敬军, 陶一江, 陈建荣, 等. 非小细胞肺癌患者呼出气冷凝液中CEA检测的临床意义. 临床肺科杂志, 2008, 13(7): 828-830.
- 102. 陈琳. 非小细胞肺癌患者呼出气冷凝液CEA、ET-1测定的意义. 复旦大学, 2009.
- 103. 邹莹畅. 基于呼出气体及其冷凝物检测的肺癌早期诊断方法及仪器研究. 浙江大学, 2016.
- 104. Carpagnano GE, Foschino-Barbaro MP, Mulé G, et al. 3p microsatellite alterations in exhaled breath condensate from patients with non-small cell lung cancer. Am J Respir Crit Care Med, 2005, 172(6): 738-744.
- 105. Carpagnano GE, Foschino-Barbaro MP, Spanevello A, et al. 3p microsatellite signature in exhaled breath condensate and tumor tissue of patients with lung cancer. Am J Respir Crit Care Med, 2008, 177(3): 337-341.
- 106. Gessner C, Kuhn H, Toepfer K, et al. Detection of p53 gene mutations in exhaled breath condensate of non-small cell lung cancer patients. Lung Cancer, 2004, 43(2): 215-222.
- 107. 黄芬芬, 陈金亮, 陈建荣. 非小细胞肺癌呼出气冷凝液中p16基因突变及表达分析. 临床军医杂志, 2019, 47(11): 1254-1256.
- 108. Faist J, Capasso F, Sivco DL, et al. Quantum cascade laser. Science, 1994, 264(5158): 553-556.
- 109. 刘峰奇, 张锦川, 刘俊岐, 等. 量子级联激光器研究进展. 中国激光, 2020, 47(7): 79-91.
- 110. Weidmann D, Wysocki G, Oppenheimer C, et al. Development of a compact quantum cascade laser spectrometer for field measurements of CO2 isotopes. Appl Phys B, 2005, 80: 255-260.
- 111. Rubin T, von Haimberger T, Helmke A, et al. Quantitative determination of metabolization dynamics by a real-time 13CO2 breath test. J Breath Res, 2011, 5(2): 027102.
- 112. Ghorbani R, Schmidt FM. Real-time breath gas analysis of CO and CO2 using an EC-QCL. Appl Phys B, 2017, 123: 144.
- 113. Gaston B, Drazen JM, Loscalzo J, et al. The biology of nitrogen oxides in the airways. Am J Respir Crit Care Med, 1994, 149(2 Pt 1): 538-551.
- 114. McCurdy MR, Bakhirkin Y, Wysocki G, et al. Performance of an exhaled nitric oxide and carbon dioxide sensor using quantum cascade laser-based integrated cavity output spectroscopy. J Biomed Opt, 2007, 12(3): 034034.
- 115. Manne J, Sukhorukov O, Jäger W, et al. Pulsed quantum cascade laser-based cavity ring-down spectroscopy for ammonia detection in breath. Appl Opt, 2006, 45(36): 9230-9237.
- 116. Owen K, Farooq A. A calibration-free ammonia breath sensor using a quantum cascade laser with WMS 2f/1f. Applied Physics B, 2014, 116(2): 371-383.
- 117. Risby TH, Tittel FK. Current status of midinfrared quantum and interband cascade lasers for clinical breath analysis. Optical Engineering, 2010, 49(11): 111123.
- 118. Wang C, Sahay P. Breath analysis using laser spectroscopic techniques: Breath biomarkers, spectral fingerprints, and detection limits. Sensors (Basel), 2009, 9(10): 8230-8262.
- 119. Wang Z, Wang C. Is breath acetone a biomarker of diabetes? A historical review on breath acetone measurements. J Breath Res, 2013, 7(3): 037109.
- 120. Ciaffoni L, Hancock G, Harrison JJ, et al. Demonstration of a mid-infrared cavity enhanced absorption spectrometer for breath acetone detection. Anal Chem, 2013, 85(2): 846-850.
- 121. Reyes-Reyes A, Horsten RC, Urbach HP, et al. Study of the exhaled acetone in type 1 diabetes using quantum cascade laser spectroscopy. Anal Chem, 2015, 87(1): 507-512.
- 122. Shorter JH, Nelson DD, McManus JB, et al. Clinical study of multiple breath biomarkers of asthma and COPD (NO, CO(2), CO and N(2)O) by infrared laser spectroscopy. J Breath Res, 2011, 5(3): 037108.
- 123. Shorter JH, Nelson DD, Barry McManus J, et al. Multicomponent breath analysis with infrared absorption using room-temperature quantum cascade lasers. IEEE Sens J, 2009, 10(1): 76-84.
- 124. Martínez-Lozano P, de la Mora JF. Electrospray ionization of volatiles in breath. Int J Mass Spectrom, 2007, 265(1): 68-72.
- 125. Li X, Huang L, Zhu H, et al. Direct human breath analysis by secondary nano-electrospray ionization ultrahigh-resolution mass spectrometry: Importance of high mass resolution and mass accuracy. Rapid Commun Mass Spectrom, 2017, 31(3): 301-308.
- 126. Sinues PM, Kohler M, Zenobi R. Monitoring diurnal changes in exhaled human breath. Anal Chem, 2013, 85(1): 369-373.
- 127. Martinez-Lozano Sinues P, Landoni E, Miceli R, et al. Secondary electrospray ionization-mass spectrometry and a novel statistical bioinformatic approach identifies a cancer-related profile in exhaled breath of breast cancer patients: A pilot study. J Breath Res, 2015, 9(3): 031001.
- 128. Rizzo S, Del Grande F, Wannesson L, et al. Recent developments and advances in secondary prevention of lung cancer. Eur J Cancer Prev, 2020, 29(4): 321-328.