Debora Brascia, Giulia De Iaco, Teodora Panza, Francesca Signore, Graziana Carleo, Wenzhe Zang, Ruchi Sharma, Pamela Riahi, Jared Scott, Xudong Fan, Giuseppe Marulli
{"title":"呼吸组学:它能否成为非小细胞肺癌早期诊断的经济实惠的新工具?一项针对 60 名患者的探索性研究。","authors":"Debora Brascia, Giulia De Iaco, Teodora Panza, Francesca Signore, Graziana Carleo, Wenzhe Zang, Ruchi Sharma, Pamela Riahi, Jared Scott, Xudong Fan, Giuseppe Marulli","doi":"10.1093/icvts/ivae149","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Analysis of breath, specifically the patterns of volatile organic compounds (VOCs), has shown the potential to distinguish between patients with lung cancer (LC) and healthy individuals (HC). However, the current technology relies on complex, expensive and low throughput analytical platforms, which provide an offline response, making it unsuitable for mass screening. A new portable device has been developed to enable fast and on-site LC diagnosis, and its reliability is being tested.</p><p><strong>Methods: </strong>Breath samples were collected from patients with histologically proven non-small-cell lung cancer (NSCLC) and healthy controls using Tedlar bags and a Nafion filter attached to a one-way mouthpiece. These samples were then analysed using an automated micro portable gas chromatography device that was developed in-house. The device consisted of a thermal desorption tube, thermal injector, separation column, photoionization detector, as well as other accessories such as pumps, valves and a helium cartridge. The resulting chromatograms were analysed using both chemometrics and machine learning techniques.</p><p><strong>Results: </strong>Thirty NSCLC patients and 30 HC entered the study. After a training set (20 NSCLC and 20 HC) and a testing set (10 NSCLC and 10 HC), an overall specificity of 83.3%, a sensitivity of 86.7% and an accuracy of 85.0% to identify NSCLC patients were found based on 3 VOCs.</p><p><strong>Conclusions: </strong>These results are a significant step towards creating a low-cost, user-friendly and accessible tool for rapid on-site LC screening.</p><p><strong>Clinical registration number: </strong>ClinicalTrials.gov Identifier: NCT06034730.</p>","PeriodicalId":73406,"journal":{"name":"Interdisciplinary cardiovascular and thoracic surgery","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11379464/pdf/","citationCount":"0","resultStr":"{\"title\":\"Breathomics: may it become an affordable, new tool for early diagnosis of non-small-cell lung cancer? An exploratory study on a cohort of 60 patients.\",\"authors\":\"Debora Brascia, Giulia De Iaco, Teodora Panza, Francesca Signore, Graziana Carleo, Wenzhe Zang, Ruchi Sharma, Pamela Riahi, Jared Scott, Xudong Fan, Giuseppe Marulli\",\"doi\":\"10.1093/icvts/ivae149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>Analysis of breath, specifically the patterns of volatile organic compounds (VOCs), has shown the potential to distinguish between patients with lung cancer (LC) and healthy individuals (HC). However, the current technology relies on complex, expensive and low throughput analytical platforms, which provide an offline response, making it unsuitable for mass screening. A new portable device has been developed to enable fast and on-site LC diagnosis, and its reliability is being tested.</p><p><strong>Methods: </strong>Breath samples were collected from patients with histologically proven non-small-cell lung cancer (NSCLC) and healthy controls using Tedlar bags and a Nafion filter attached to a one-way mouthpiece. These samples were then analysed using an automated micro portable gas chromatography device that was developed in-house. The device consisted of a thermal desorption tube, thermal injector, separation column, photoionization detector, as well as other accessories such as pumps, valves and a helium cartridge. The resulting chromatograms were analysed using both chemometrics and machine learning techniques.</p><p><strong>Results: </strong>Thirty NSCLC patients and 30 HC entered the study. After a training set (20 NSCLC and 20 HC) and a testing set (10 NSCLC and 10 HC), an overall specificity of 83.3%, a sensitivity of 86.7% and an accuracy of 85.0% to identify NSCLC patients were found based on 3 VOCs.</p><p><strong>Conclusions: </strong>These results are a significant step towards creating a low-cost, user-friendly and accessible tool for rapid on-site LC screening.</p><p><strong>Clinical registration number: </strong>ClinicalTrials.gov Identifier: NCT06034730.</p>\",\"PeriodicalId\":73406,\"journal\":{\"name\":\"Interdisciplinary cardiovascular and thoracic surgery\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11379464/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Interdisciplinary cardiovascular and thoracic surgery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/icvts/ivae149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interdisciplinary cardiovascular and thoracic surgery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/icvts/ivae149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Breathomics: may it become an affordable, new tool for early diagnosis of non-small-cell lung cancer? An exploratory study on a cohort of 60 patients.
Objectives: Analysis of breath, specifically the patterns of volatile organic compounds (VOCs), has shown the potential to distinguish between patients with lung cancer (LC) and healthy individuals (HC). However, the current technology relies on complex, expensive and low throughput analytical platforms, which provide an offline response, making it unsuitable for mass screening. A new portable device has been developed to enable fast and on-site LC diagnosis, and its reliability is being tested.
Methods: Breath samples were collected from patients with histologically proven non-small-cell lung cancer (NSCLC) and healthy controls using Tedlar bags and a Nafion filter attached to a one-way mouthpiece. These samples were then analysed using an automated micro portable gas chromatography device that was developed in-house. The device consisted of a thermal desorption tube, thermal injector, separation column, photoionization detector, as well as other accessories such as pumps, valves and a helium cartridge. The resulting chromatograms were analysed using both chemometrics and machine learning techniques.
Results: Thirty NSCLC patients and 30 HC entered the study. After a training set (20 NSCLC and 20 HC) and a testing set (10 NSCLC and 10 HC), an overall specificity of 83.3%, a sensitivity of 86.7% and an accuracy of 85.0% to identify NSCLC patients were found based on 3 VOCs.
Conclusions: These results are a significant step towards creating a low-cost, user-friendly and accessible tool for rapid on-site LC screening.