Sensing gastric cancer via point-of-care sensor breath analyzer.
Adult
Aged
Aged, 80 and over
Area Under Curve
Biosensing Techniques
/ instrumentation
Breath Tests
/ instrumentation
Case-Control Studies
Discriminant Analysis
Female
Humans
Male
Middle Aged
Nanotechnology
Point-of-Care Systems
Precancerous Conditions
/ diagnosis
Sensitivity and Specificity
Stomach Neoplasms
/ diagnosis
breath analyzer
gastric cancer
personalized
precancerous lesion
screening
volatile organic compound
Journal
Cancer
ISSN: 1097-0142
Titre abrégé: Cancer
Pays: United States
ID NLM: 0374236
Informations de publication
Date de publication:
15 04 2021
15 04 2021
Historique:
revised:
14
12
2020
received:
25
09
2020
accepted:
16
12
2020
pubmed:
20
3
2021
medline:
12
11
2021
entrez:
19
3
2021
Statut:
ppublish
Résumé
Detection of disease by means of volatile organic compounds from breath samples using sensors is an attractive approach to fast, noninvasive and inexpensive diagnostics. However, these techniques are still limited to applications within the laboratory settings. Here, we report on the development and use of a fast, portable, and IoT-connected point-of-care device (so-called, SniffPhone) to detect and classify gastric cancer to potentially provide new qualitative solutions for cancer screening. A validation study of patients with gastric cancer, patients with high-risk precancerous gastric lesions, and controls was conducted with 2 SniffPhone devices. Linear discriminant analysis (LDA) was used as a classifying model of the sensing signals obatined from the examined groups. For the testing step, an additional device was added. The study group included 274 patients: 94 with gastric cancer, 67 who were in the high-risk group, and 113 controls. The results of the test set showed a clear discrimination between patients with gastric cancer and controls using the 2-device LDA model (area under the curve, 93.8%; sensitivity, 100%; specificity, 87.5%; overall accuracy, 91.1%), and acceptable results were also achieved for patients with high-risk lesions (the corresponding values for dysplasia were 84.9%, 45.2%, 87.5%, and 65.9%, respectively). The test-phase analysis showed lower accuracies, though still clinically useful. Our results demonstrate that a portable breath sensor device could be useful in point-of-care settings. It shows a promise for detection of gastric cancer as well as for other types of disease. A portable sensor-based breath analyzer for detection of gastric cancer can be used in point-of-care settings. The results are transferrable between devices via advanced IoT technology. Both the hardware and software of the reported breath analyzer could be easily modified to enable detection and monitirng of other disease states.
Sections du résumé
BACKGROUND
Detection of disease by means of volatile organic compounds from breath samples using sensors is an attractive approach to fast, noninvasive and inexpensive diagnostics. However, these techniques are still limited to applications within the laboratory settings. Here, we report on the development and use of a fast, portable, and IoT-connected point-of-care device (so-called, SniffPhone) to detect and classify gastric cancer to potentially provide new qualitative solutions for cancer screening.
METHODS
A validation study of patients with gastric cancer, patients with high-risk precancerous gastric lesions, and controls was conducted with 2 SniffPhone devices. Linear discriminant analysis (LDA) was used as a classifying model of the sensing signals obatined from the examined groups. For the testing step, an additional device was added. The study group included 274 patients: 94 with gastric cancer, 67 who were in the high-risk group, and 113 controls.
RESULTS
The results of the test set showed a clear discrimination between patients with gastric cancer and controls using the 2-device LDA model (area under the curve, 93.8%; sensitivity, 100%; specificity, 87.5%; overall accuracy, 91.1%), and acceptable results were also achieved for patients with high-risk lesions (the corresponding values for dysplasia were 84.9%, 45.2%, 87.5%, and 65.9%, respectively). The test-phase analysis showed lower accuracies, though still clinically useful.
CONCLUSION
Our results demonstrate that a portable breath sensor device could be useful in point-of-care settings. It shows a promise for detection of gastric cancer as well as for other types of disease.
LAY SUMMARY
A portable sensor-based breath analyzer for detection of gastric cancer can be used in point-of-care settings. The results are transferrable between devices via advanced IoT technology. Both the hardware and software of the reported breath analyzer could be easily modified to enable detection and monitirng of other disease states.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
1286-1292Subventions
Organisme : European Union's Horizon 2020 Research and Innovation Programme
ID : VOGAS project grant No. 824986
Organisme : European Union's Horizon 2020 Research and Innovation Programme
ID : VOGAS SNIFFPHONE project grant No. 644031
Investigateurs
Viki Kloper
(V)
Yana Milyutin
(Y)
Manal Abboud
(M)
Walaa Saliba
(W)
Shifaa Bdarneh
(S)
Salam Khateb
(S)
Alaa Gharra
(A)
Liat Zuri
(L)
Edgars Vasiljevs
(E)
Lelde Lauka
(L)
Evita Gasenko
(E)
Roberts Skapars
(R)
Armands Sivins
(A)
Inga Bogdanova
(I)
Sergejs Isajevs
(S)
Ilze Kikuste
(I)
Aigars Vanags
(A)
Ivars Tolmanis
(I)
Ilona Kojalo
(I)
Viktors Veliks
(V)
Carsten Jaeschke
(C)
Max Fleischer
(M)
Maria Sramek
(M)
Mark Nav Gils
(M)
Minna Kulju
(M)
Janika Miettinen
(J)
Informations de copyright
© 2021 American Cancer Society.
Références
Council of the European Union. Council recommendation of 2 December 2003 on cancer screening. Official J Europ Union. 2003;327:16.12.2003.
Car J, Sheikh A, Wicks P, Williams MS. Beyond the hype of big data and artificial intelligence: building foundations for knowledge and wisdom. BMC Medicine. 2019;17:143.
Einoch Amor R, Nakhleh MK, Barash O, Haick H. Breath analysis of cancer in the present and the future. Eur Respir Rev. 2019;28:190002.
Wilson, JM, Jungner, YG. Principles and practice of mass screening for disease. Bol Oficina Sanit Panam. 1968;65:281-393.
Palmieri B, Nardo B, Lippi G, Palmieri L, Vadalà M, Laurino C. Dogs' olfactory diagnostics applied on human species: state of the art and clinical perspectives. La Clinica Terap. 2016;167:e78-e84.
de Lacy Costello B, Amann A, Al-Kateb H, et al. A review of the volatiles from the healthy human body. J Breath Res. 2014;8:014001.
Sánchez C, Santos JP, Lozano J. Use of electronic noses for diagnosis of digestive and respiratory diseases through the breath. Biosensors (Basel). 2019;9:35.
Krilaviciute A, Stock C, Leja M, Brenner H. Potential of non-invasive breath tests for preselecting individuals for invasive gastric cancer screening endoscopy. J Breath Res. 2018;12:036009.
Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018;68:394-424.
Herrero R, Parsonnet J, Greenberg ER. Prevention of gastric cancer. JAMA. 2014;312:1197-1198.
Leja M, You W, Camargo MC, Saito H. Implementation of gastric cancer screening-the global experience. Best Pract Res Clin Gastroenterol. 2014;28:1093-1106.
Lonnberg S, Sekerija M, Malila N, et al. Cancer screening: policy recommendations on governance, organization and evaluation of cancer screening. In: European Guide on Quality Improvement in Comprehensive Cancer Control. National Institute of Public Health, Slovenia, Scientific Institute of Public Health, Belgium; 2017:39-76.
Malfertheiner P, Megraud F, O’Morain CA, et al. Management of Helicobacter pylori infection-the Maastricht V/Florence Consensus Report. Gut. 2017;66:6-30.
Huang YK, Yu JC, Kang WM, et al. Significance of serum pepsinogens as a biomarker for gastric cancer and atrophic gastritis screening: a systematic review and meta-analysis. PLoS One. 2015;10:e0142080.
Liu L, Lang J, Jin Y, et al. The value of pepsinogen in GC screening: a systematic review and meta-analysis. Gastroenterol Res Pract. 2019;2019:7087232.
Xu ZQ, Broza YY, Ionsecu R, et al. A nanomaterial-based breath test for distinguishing gastric cancer from benign gastric conditions. Br J Cancer. 2013;108:941-950.
Amal H, Leja M, Funka K, et al. Detection of precancerous gastric lesions and gastric cancer through exhaled breath. Gut. 2016;65:400-407.
Durán-Acevedo CM, Jaimes-Mogollón AL, Gualdrón-Guerrero OE, et al. Exhaled breath analysis for gastric cancer diagnosis in Colombian patients. Oncotarget. 2018;9:28805-28817.
Broza YY, Khatib S, Gharra A, et al. Screening for gastric cancer using exhaled breath samples. Br J Surg. 2019;106:1122-1125.
Schlemper RJ, Riddell RH, Kato Y, et al. The Vienna classification of gastrointestinal epithelial neoplasia. Gut. 2000;47:251-255.
Rugge M, Genta RM. Staging gastritis: an international proposal. Gastroenterology. 2005;129:1807-1808.
Capelle LG, de Vries AC, Haringsma J, et al. The staging of gastritis with the OLGA system by using intestinal metaplasia as an accurate alternative for atrophic gastritis. Gastrointest Endosc. 2010;71:1150-1158.
Krilaviciute A, Leja M, Kopp-Schneider A, et al. Associations of diet and lifestyle factors with common volatile organic compounds in exhaled breath of average-risk individuals. J Breath Res. 2019;13:026006.
Chen M, Zhao H. Next-generation sequencing in liquid biopsy: cancer screening and early detection. Hum Genomics. 2019;13:34.
Wormanns D, Kauczor HU, Antoch G, et al. Joint statement of the German Radiological Society and the German Respiratory Society on a quality-assured early detection program for lung cancer with low-dose CT [in German]. RoFo. 2019;191:993-997.
Areia M, Spaander MC, Kuipers EJ, Dinis-Ribeiro M. Endoscopic screening for gastric cancer: a cost-utility analysis for countries with an intermediate gastric cancer risk. United European Gastroenterol J. 2018;6:192-202.
Nakhleh MK, Amal H, Jeries R, et al. Diagnosis and classification of 17 diseases from 1404 subjects via pattern analysis of exhaled molecules. ACS Nano. 2017;11:112-125.
Yoon J-W, Lee J-H. Toward breath analysis on a chip for disease diagnosis using semiconductor-based chemiresistors: recent progress and future perspectives. Lab Chip. 2017;17.
Amal H, Funka K, Liepniece-Karele I, Skapars R, Leja M, Haick H. Sa1991 volatile markers can discriminate between gastric cancer and benign conditions. Gastroenterology. 2013;144:S-353.
Mochalski P, Leja M, Gasenko E, et al. Ex vivo emission of volatile organic compounds from gastric cancer and non-cancerous tissue. J Breath Res. 2018;12:046005.
Broza YY, Kremer R, Tisch U, et al. A nanomaterial-based breath test for short-term follow-up after lung tumor resection. Nanomedicine. 2013;9:15-21.