[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-379224-105":3,"doc-detail-379224-en":81,"detail-sidebar-cat-0-en-105":99},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","subsecond-lung-cancer-detection-within-a-heterogeneous-background-of-normal-and-benign-tissue-using-single-point-raman-spectroscopy","Subsecond lung cancer detection within a heterogeneous background of normal and benign tissue using single-point Raman spectroscopy","","Lung cancer remains the most frequently diagnosed cancer and the deadliest cause of cancer-related death in North America. Current bronchoscopy-based diagnosis is constrained by limited diagnostic yield and low specificity, especially for peripheral lesions. This study evaluates whether in situ single-point fingerprint Raman spectroscopy, in the 800–1700 cm−1 range, combined with machine learning can identify cancer within backgrounds of normal tissue and benign conditions, including emphysema and bronchiolitis. A Raman probe measured spectra from normal, benign, and cancer specimens across 10 patients, with histology determining cancer type.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/subsecond-lung-cancer-detection-within-a-heterogeneous-background-of-normal-and-benign-tissue-using-single-point-raman-spectroscopy/379224/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/subsecond-lung-cancer-detection-within-a-heterogeneous-background-of-normal-and-benign-tissue-using-single-point-raman-spectroscopy/379224.png","ImageObject",300,407,{"name":42,"@type":43},"Chumphorn","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-29","2026-09-24",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",9,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What problem does this study target in lung cancer diagnosis?","Question",{"text":63,"@type":64},"It targets the low diagnostic yield and low specificity of current bronchoscopy techniques, particularly for lesions in peripheral lung locations. The study also addresses the challenge of detecting cancer within a heterogeneous background that includes benign tissue conditions.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How was Raman spectroscopy used in the approach?",{"text":68,"@type":64},"A single-point Raman spectroscopy probe measured spectral fingerprints from normal, benign, and cancer lung tissue samples. The study focused on the 800–1700 cm−1 spectral range and extracted biomolecular information from the spectra.",{"name":70,"@type":61,"acceptedAnswer":71},"What performance did the machine learning models achieve?",{"text":72,"@type":64},"Supervised machine learning models were trained using leave-one-patient-out cross-validation. Lung cancer detection reached 94% sensitivity and 80% specificity in the reported results.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},379224,1790271496,{"code":4,"msg":82,"data":83},"success",{"doc_id":79,"user_id":84,"nickname":42,"user_avatar":85,"doc_module":4,"category_id":86,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":87,"file_id":88,"file_url":89,"file_type":90,"file_size":91,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":92,"language":93,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":94,"faqs":95,"seo_title":96,"seo_description":12,"update_tm":97,"read_time":98},2336475401981,"https://ap-avatar.wpscdn.com/avatar/22000c94efd8d5204d?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786935347598174694",7,"LETTER  \nSubsecond lung cancer detection within a heterogeneous background of normal and benign tissue using single-point Raman spectroscopy  \nFrédéric Leblond  ,a,b,c,* Frédérick Dallaire  ,a,b Trang Tran,a,b Rajeev Yadav,d Kelly Aubertin  ,e Eric Goudie  ,b,f Philippe Romeo,g Christopher Kent,d  \nCharles Leduc  ,g and Moishe Libermanb,c,f  \naPolytechnique Montréal, Department of Engineering Physics, Montreal, Québec, Canada bCentre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Quebec, Canada  \ncInstitut du cancer de Montréal, Montreal, Quebec, Canada  \ndReveal Surgical, Montreal, Quebec, Canada  \neINSERM UMR_S1109 and Université de Strasbourg, Institut d’immunologie et d’hématologie,  \nTeam Tumor Biomechanics, Strasbourg, France  \nfCentre Hospitalier de l’Université de Montréal, Division of Thoracic Surgery, Montreal, Quebec, Canada gCentre hospitalier de l’Université de Montréal, Department of Pathology, Montreal, Quebec, Canada  \nABSTRACT. Significance: Lung cancer is the most frequently diagnosed cancer overall and the deadliest cancer in North America. Early diagnosis through current bronchoscopy techniques is limited by poor diagnostic yield and low specificity, especially for lesions located in peripheral pulmonary locations. Even with the emergence of robotic-assisted platforms, bronchoscopy diagnostic yields remain below 80% . Aim: The aim of this study was to determine whether in situ single-point fingerprint (800 to 1700 cm−1) Raman spectroscopy coupled with machine learning could detect lung cancer within an otherwise heterogenous background composed of normal tissue and tissue associated with benign conditions, including emphysema and bronchiolitis.  \nApproach: A Raman spectroscopy probe was used to measure the spectral fingerprint of normal, benign, and cancer lung tissue in 10 patients. Each interrogated specimen was characterized by histology to determine cancer type, i.e., small cell carcinoma or non-small cell carcinoma (adenocarcinoma and squamous cell carcinoma) . Biomolecular information was extracted from the fingerprint spectra to identify biomolecular features that can be used for cancer detection.  \nResults: Supervised machine learning models were trained using leave-onepatient-out cross-validation, showing lung cancer could be detected with a sensitivity of 94% and a specificity of 80% .  \nConclusions: This proof of concept demonstrates fingerprint Raman spectroscopy is a promising tool for the detection of lung cancer during diagnostic procedures and can capture biomolecular changes associated with the presence of cancer among a complex heterogeneous background within less than 1 s.  \n© The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. [DOI: 10.1117/1.JBO.28.9.090501]  \nKeywords: Raman spectroscopy; lung cancer; bronchoscopy; biopsy; surgery; machine learning; tissue optics; biochemistry  \nPaper 230087LRR received Mar. 29, 2023; revised Aug. 9, 2023; accepted Aug. 10, 2023; published Sep.  \n9, 2023 .  \n*Address all correspondence to Frédéric Leblond, [Frederic.leblond@polymtl.ca](Frederic.leblond@polymtl.ca)  \nJournal of Biomedical Optics 090501-1 September 2023 • Vol. 28(9)  \nLeblond et al.: Subsecond lung cancer detection within a heterogeneous background. . .  \nLung cancer is the most prevalent form of cancer worldwide and the leading cause of cancerrelated deaths.1 Despite recent advances in treatment, the 5-year survival rate has remained largely unchanged under 20% .2,3 This is largely due to the fact most patients are diagnosed at advanced disease stages where treatments are often ineffective and prognosis is poor. Despite recent advances in treatment, surgical resection remains the mainstay of curative treatment for non-small cell lung carcinoma (NSCLC) and SCLC. Survival rate depends o","cbCairxubpvwnU4v","https://ap.wps.com/l/cbCairxubpvwnU4v","pdf",2890182,8,"English","# Abstract\n## Significance\n## Aim\n## Approach\n## Results\n## Conclusions","[{\"question\":\"What problem does this study target in lung cancer diagnosis?\",\"answer\":\"It targets the low diagnostic yield and low specificity of current bronchoscopy techniques, particularly for lesions in peripheral lung locations. The study also addresses the challenge of detecting cancer within a heterogeneous background that includes benign tissue conditions.\"},{\"question\":\"How was Raman spectroscopy used in the approach?\",\"answer\":\"A single-point Raman spectroscopy probe measured spectral fingerprints from normal, benign, and cancer lung tissue samples. The study focused on the 800–1700 cm−1 spectral range and extracted biomolecular information from the spectra.\"},{\"question\":\"What performance did the machine learning models achieve?\",\"answer\":\"Supervised machine learning models were trained using leave-one-patient-out cross-validation. Lung cancer detection reached 94% sensitivity and 80% specificity in the reported results.\"}]","Subsecond lung cancer detection within a heterogeneous background of normal and benign tissue using single-point Raman spectroscopy | PDF",1790234660,20,{"code":4,"msg":82,"data":100},[101,105,109,113,118,123,126,130,133,136,140],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":106,"show_sort_weight":107,"slug":108},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":110,"show_sort_weight":111,"slug":112},"Exam",70,"exam",{"id":114,"doc_module":4,"doc_module_name":25,"category_name":115,"show_sort_weight":116,"slug":117},5,"Comic",60,"comic",{"id":119,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":121,"slug":122},6,"Technology",50,"technology",{"id":86,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":124,"slug":125},40,"healthcare",{"id":92,"doc_module":4,"doc_module_name":25,"category_name":127,"show_sort_weight":128,"slug":129},"Research & Report",30,"research-report",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":131,"show_sort_weight":98,"slug":132},"Religion & Spirituality","religion-spirituality",{"id":98,"doc_module":4,"doc_module_name":25,"category_name":134,"show_sort_weight":98,"slug":135},"World Cup","world-cup",{"id":137,"doc_module":4,"doc_module_name":25,"category_name":138,"show_sort_weight":137,"slug":139},10,"Lifestyle","lifestyle",{"id":141,"doc_module":4,"doc_module_name":25,"category_name":142,"show_sort_weight":114,"slug":143},19,"General","general"]