Sensing gastric cancer via point‐of‐care sensor breath analyzer. Issue 8 (19th March 2021)
- Record Type:
- Journal Article
- Title:
- Sensing gastric cancer via point‐of‐care sensor breath analyzer. Issue 8 (19th March 2021)
- Main Title:
- Sensing gastric cancer via point‐of‐care sensor breath analyzer
- Authors:
- Leja, Marcis
Kortelainen, Juha M.
Polaka, Inese
Turppa, Emmi
Mitrovics, Jan
Padilla, Marta
Mochalski, Pawel
Shuster, Gregory
Pohle, Roland
Kashanin, Dmitry
Klemm, Richard
Ikonen, Veikko
Mezmale, Linda
Broza, Yoav Y.
Shani, Gidi
Haick, Hossam - Other Names:
- Kloper Viki investigator.
Milyutin Yana investigator.
Abboud Manal investigator.
Saliba Walaa investigator.
Bdarneh Shifaa investigator.
Khateb Salam investigator.
Gharra Alaa investigator.
Zuri Liat investigator.
Vasiljevs Edgars investigator.
Lauka Lelde investigator.
Gasenko Evita investigator.
Skapars Roberts investigator.
Sivins Armands investigator.
Bogdanova Inga investigator.
Isajevs Sergejs investigator.
Kikuste Ilze investigator.
Vanags Aigars investigator.
Tolmanis Ivars investigator.
Kojalo Ilona investigator.
Veliks Viktors investigator.
Jaeschke Carsten investigator.
Fleischer Max investigator.
Sramek Maria investigator.
nav Gils Mark investigator.
Kulju Minna investigator.
Miettinen Janika investigator. - Abstract:
- Abstract : 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: OurAbstract : 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. Abstract : A sensor‐based breath analyzer for volatile organic markers can be used in a personal‐use device and in point‐of‐care settings. Promising results have been achieved for gastric cancer, and this method has other potential applications, including cancer screening. … (more)
- Is Part Of:
- Cancer. Volume 127:Issue 8(2021)
- Journal:
- Cancer
- Issue:
- Volume 127:Issue 8(2021)
- Issue Display:
- Volume 127, Issue 8 (2021)
- Year:
- 2021
- Volume:
- 127
- Issue:
- 8
- Issue Sort Value:
- 2021-0127-0008-0000
- Page Start:
- 1286
- Page End:
- 1292
- Publication Date:
- 2021-03-19
- Subjects:
- breath analyzer -- gastric cancer -- personalized -- precancerous lesion -- screening -- volatile organic compound
Cancer -- Periodicals
Cancer -- Cytopathology -- Periodicals
616.99405 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0142 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/cncr.33437 ↗
- Languages:
- English
- ISSNs:
- 0008-543X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3046.450000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 23398.xml