Institute of Clinical and Preventive Medicine & Faculty of Medicine, University of Latvia, Riga, Latvia.
Riga East University Hospital, Riga, Latvia.
Cancer. 2021 Apr 15;127(8):1286-1292. doi: 10.1002/cncr.33437. Epub 2021 Mar 19.
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.
利用传感器从呼吸样本中检测疾病的挥发性有机化合物是一种快速、非侵入性和廉价的诊断方法。然而，这些技术仍然仅限于实验室环境中的应用。在这里，我们报告了一种快速、便携、物联网连接的即时护理设备（所谓的 SniffPhone）的开发和使用，以检测和分类胃癌，从而为癌症筛查提供新的定性解决方案。
对 274 名患者（胃癌患者 94 例，高危癌前胃病变患者 67 例，对照组 113 例）进行了使用 2 台 SniffPhone 设备的验证研究。线性判别分析（LDA）被用作从受检组获得的传感信号的分类模型。在测试步骤中，增加了一台额外的设备。研究组包括 274 名患者：94 名胃癌患者，67 名高危组患者和 113 名对照组患者。
使用 2 台设备的 LDA 模型，测试集的结果显示出胃癌患者与对照组之间的明显区分（曲线下面积为 93.8%；敏感性为 100%；特异性为 87.5%；总体准确率为 91.1%），对于高危病变患者也获得了可接受的结果（相应的异型增生值分别为 84.9%、45.2%、87.5%和 65.9%）。测试阶段的分析显示出较低的准确性，但仍然具有临床意义。
我们的结果表明，一种便携式基于传感器的呼吸分析仪可用于即时护理环境。它有望用于检测胃癌以及其他类型的疾病。
一种用于检测胃癌的基于传感器的便携式呼吸分析仪可用于即时护理环境。通过先进的物联网技术，结果可以在设备之间传输。报告的呼吸分析仪的硬件和软件都可以轻松修改，以实现对其他疾病状态的检测和监测。
