Sensoru izelpas analizatora pielietojums kuņģa vēža diagnostikā
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Latvijas Universitāte
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lav
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Ievads. Kuņģa vēzis ir viens no biežāk sastopamajiem un viens no nāvējošākajiem audzējiem pasaulē. Lai nodrošinātu veiksmīgu ārstēšanu, ir svarīgi kuņģa vēzi diagnosticēt agrīnās stadijās. Daudzsološa un neinvazīva kuņģa vēža skrīninga metode ir izelpas analīze, kas balstās uz gaistošo organisko savienojumu (GOS) noteikšanu izelpā, pielietojot sensorus. Darba mērķis. Izvērtēt sensoru izelpas analizatora spēju diferencēt kuņģa vēža pacientus un indivīdus bez vēža. Materiāli un metodes. Pētījumā tika iekļauti kuņģa vēža pacienti un indivīdi bez kuņģa vēža, kuri fiziski spēja ziedot savas izelpas paraugu. Izelpa tika veikta sensoru izelpas analizatorā, kurš saturēja divu veidu sensorus – astoņus zelta nanodaļiņu (GNP) sensorus un 22 metāla oksīda (MOX) sensorus. Datu statistiskā analīze tika veikta, izmantojot IBM SPSS 22.0. Darbā tika izmantotas aprakstošās un secinošās statistikas metodes. Darbā tika noteikta sensoru spēja diferencēt kuņģa vēža pacientus no indivīdiem bez kuņģa vēža. Par statistiski nozīmīgu atšķirību starp grupām tika uzskatīts, ja p<0,05. Tika novērtēta sensoru jutība, specifiskums un precizitāte, kā arī jaucējfaktoru ietekme uz sensoru darbību, kur par statistiski nozīmīgu jaucējfaktoru ietekmi tika uzskatīts, ja p<0,05. Lai noteiktu izelpas sensoru analizatora precizitāti noteikt kuņģa vēzi, tika konstruēta ROC līkne un noteikts AUC. Rezultāti. Pētījumā tika iekļauti 139 dalībnieki – 51,08% vīriešu un 48,92% sieviešu. Dalībnieki tika iedalīti divās grupās – kuņģa vēža grupa, kurā bija 55,40% dalībnieku un kontroles grupa, kurā bija 44,60% dalībnieku. Visi sensoru izelpas analizatorā izmantotie GNP sensori un 68,18% no MOX sensoriem uzrādīja statistiski nozīmīgu atšķirību starp pētījuma grupām. Tika konstatēta dzimuma, smēķēšanas statusa, alkohola lietošanas un kuņģa čūlas anamnēzē kā jaucējfaktoru ietekme uz sensoru darbību (p<0,05). Balstoties uz histoloģiskajiem datiem, tika noteikti sensoru jutīgums, specifiskums un precizitāte: GNP sensoriem – 67,53%, 90,32%, 77,70%; MOX sensoriem – 83,33%, 72,73%, 79,31%; sensoru kombinācijai – 91,67%, 95,45%, 93,10%. Secinājumi. GNP un MOX sensori spēj diferencēt kuņģa vēža pacientus no indivīdiem bez kuņģa vēža ar augstu jutīgumu, specifiskumu un precizitāti. Jaucējfaktori ietekmē GNP un MOX sensoru darbību. Atslēgvārdi. Kuņģa vēzis, gaistošie organiskie savienojumi, sensoru izelpas analizators, neinvazīvs diagnostiskais tests, kuņģa vēža skrīnings.
Introduction. Gastric cancer is one of the most common and deadliest cancers worldwide. It is important to detect gastric cancer in early stages to provide successful treatment. A promising and non-invasive gastric cancer screening method is exhaled breath analysis. It is based on the detection of volatile organic compounds in exhaled breath using the sensors. Objective. To evaluate the ability of sensor breath analyser to differentiate between gastric cancer patients and subjects without cancer. Materials und methods. The study included patients with gastric cancer and subjects without gastric cancer who were physically able to perform breath test. The breath samples were collected by study subjects breathing into the aperture of the sensor breath analyser which contained two types of sensors – eight gold nanoparticle (GNP) sensors and 22 metal oxide (MOX) sensors. Statistical analysis was performed with IBM SPSS 22.0. Descriptive and inferential statistical methods were used in the study. The ability of sensors to differentiate gastric cancer patients from subjects without gastric cancer was determined. The difference was considered statistically significant at p<0,05. Sensitivity, specifity and accuracy of the sensors, as well as the influence of the confounding factors on the sensors were evaluated. Influence of the confounding factors was considered statistically significant at p<0,05. To determine the accuracy of the sensor breath analyser to detect gastric cancer, an ROC curve was constructed and AUC was determined. Results. The study group included 139 participants – 51,08% were males and 48,60% were females. Participants were divided in two groups – 55,40% gastric cancer patients and 44,60% subjects without gastric cancer. All of GNP sensors and 68,18% of MOX sensors used in the sensor breath analyser showed statistically significant difference between study groups. Gender, smoking status, alcohol consumption and gastric ulcer in medical history as the confounding factors were found to influence sensor performance (p<0,05). Based on histological data, sensitivity, specificity and accuracy of the sensors were determined: for GNP sensors – 67,53%, 90,32%, 77,70%; for MOX sensors – 83,33%, 72,73%, 79,31%; for combination of both of the sensors – 91,67%, 95,45%, 93,10%. Conclusions. GNP and MOX sensors showed the ability to differentiate gastric cancer patients from subjects without gastric cancer with high sensitivity, specificity and accuracy. The confounding factors affect GNP and MOX sensors performance. Keywords. Gastric cancer, volatile organic compounds, sensor breath analyser, non-invasive diagnostic test, gastric cancer screening.
Introduction. Gastric cancer is one of the most common and deadliest cancers worldwide. It is important to detect gastric cancer in early stages to provide successful treatment. A promising and non-invasive gastric cancer screening method is exhaled breath analysis. It is based on the detection of volatile organic compounds in exhaled breath using the sensors. Objective. To evaluate the ability of sensor breath analyser to differentiate between gastric cancer patients and subjects without cancer. Materials und methods. The study included patients with gastric cancer and subjects without gastric cancer who were physically able to perform breath test. The breath samples were collected by study subjects breathing into the aperture of the sensor breath analyser which contained two types of sensors – eight gold nanoparticle (GNP) sensors and 22 metal oxide (MOX) sensors. Statistical analysis was performed with IBM SPSS 22.0. Descriptive and inferential statistical methods were used in the study. The ability of sensors to differentiate gastric cancer patients from subjects without gastric cancer was determined. The difference was considered statistically significant at p<0,05. Sensitivity, specifity and accuracy of the sensors, as well as the influence of the confounding factors on the sensors were evaluated. Influence of the confounding factors was considered statistically significant at p<0,05. To determine the accuracy of the sensor breath analyser to detect gastric cancer, an ROC curve was constructed and AUC was determined. Results. The study group included 139 participants – 51,08% were males and 48,60% were females. Participants were divided in two groups – 55,40% gastric cancer patients and 44,60% subjects without gastric cancer. All of GNP sensors and 68,18% of MOX sensors used in the sensor breath analyser showed statistically significant difference between study groups. Gender, smoking status, alcohol consumption and gastric ulcer in medical history as the confounding factors were found to influence sensor performance (p<0,05). Based on histological data, sensitivity, specificity and accuracy of the sensors were determined: for GNP sensors – 67,53%, 90,32%, 77,70%; for MOX sensors – 83,33%, 72,73%, 79,31%; for combination of both of the sensors – 91,67%, 95,45%, 93,10%. Conclusions. GNP and MOX sensors showed the ability to differentiate gastric cancer patients from subjects without gastric cancer with high sensitivity, specificity and accuracy. The confounding factors affect GNP and MOX sensors performance. Keywords. Gastric cancer, volatile organic compounds, sensor breath analyser, non-invasive diagnostic test, gastric cancer screening.