[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-332228-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-332228-en":131},{"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","multi-wavelength-raman-differentiation-of-malignant-skin-neoplasms","Multi-Wavelength Raman Differentiation of Malignant Skin Neoplasms","","Raman microspectroscopy serves as an effective approach to characterize biomarker-related molecular patterns in skin tissue. Healthy and malignant specimens—including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC)—were studied using 532 and 785 nm laser excitation across defined wavenumber ranges. Spectral features supporting class differentiation were identified via band intensity ratios, with 532 nm criteria based on bands near 1268, 1336, and 1445 cm−1 and higher-wavenumber bands reflecting protein/lipid changes. Merged 532+785 ratio selection improved three-class accuracy to 87%, reaching BCC+SCC specificity of 87% and sensitivities of 95% and 99% for relevant classes.",{"@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/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/multi-wavelength-raman-differentiation-of-malignant-skin-neoplasms/332228/",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/multi-wavelength-raman-differentiation-of-malignant-skin-neoplasms/332228.png","ImageObject",300,407,{"name":42,"@type":43},"Aria","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-29","2026-09-21",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",15,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What is the main goal of the Raman spectroscopy study?","Question",{"text":63,"@type":64},"To distinguish malignant skin neoplasms by analyzing spectral features in Raman microspectroscopy data from healthy and malignant tissues.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"Which Raman excitation wavelengths and wavenumber ranges were used?",{"text":68,"@type":64},"Spectra were acquired using 532 nm and 785 nm laser excitation, covering wavenumber ranges of 900–1800 cm−1 and 2800–3100 cm−1.",{"name":70,"@type":61,"acceptedAnswer":71},"How were spectral criteria selected to improve classification accuracy?",{"text":72,"@type":64},"The study used intensity ratios of characteristic Raman bands, and further improved results by selecting ratios from the merged 532+785 dataset.","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},332228,1790165343,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,115,120,123,127],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":112,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":113,"slug":114},8,30,"research-report",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":97,"slug":130},19,"General","general",{"code":4,"msg":82,"data":132},{"doc_id":79,"user_id":133,"nickname":42,"user_avatar":134,"doc_module":4,"category_id":112,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":140,"language":141,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":12,"update_tm":145,"read_time":146,"preview_page_count":4},2336464648322,"https://ap-avatar.wpscdn.com/avatar/2200025388227c56fec?_k=1778556882303663488","Article  \nMulti-Wavelength Raman Differentiation of Malignant Skin Neoplasms  \nElena Rimskaya 1, Alexey Gorevoy 1, Svetlana Shelygina 1, Elena Perevedentseva 1, Alina Timurzieva 1,2, Irina Saraeva 1, Nikolay Melnik 1, Sergey Kudryashov 1 and Aleksandr Kuchmizhak 3,4, *  \nCitation: Rimskaya, E.; Gorevoy, A.; Shelygina, S.; Perevedentseva, E.; Timurzieva, A.; Saraeva, I.; Melnik, N.; Kudryashov, S.; Kuchmizhak, A. Multi-Wavelength Raman Differentiation of Malignant Skin Neoplasms. Int. J. Mol. Sci. 2024, 25, 7422. [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)ijms25137422  \nAcademic Editor: Guendalina Lucarini  \nReceived: 23 May 2024  \nRevised: 3 July 2024  \nAccepted: 4 July 2024  \nPublished: 6 July 2024  \nCopyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \n1 Lebedev Physical Institute, 119991 Moscow, Russia; [rimskaya@lebedev.ru](rimskaya@lebedev.ru) (E.R.); [a.gorevoy@lebedev.ru](a.gorevoy@lebedev.ru) (A.G.); [shelyginasn@lebedev.ru](shelyginasn@lebedev.ru) (S.S.); [perevedencevaev@lebedev.ru](perevedencevaev@lebedev.ru) (E.P.); [a.timurzieva@lebedev.ru](a.timurzieva@lebedev.ru) (A.T.); [saraevain@lebedev.ru](saraevain@lebedev.ru) (I.S.); [melniknn@lebedev.ru](melniknn@lebedev.ru) (N.M.); [kudryashovsi@lebedev.ru](kudryashovsi@lebedev.ru) (S.K.)  \n2 Semashko National Research Institute of Public Health, 105064 Moscow, Russia  \n3 Institute of Automation and Control Processes, Far Eastern Branch, Russian Academy of Science,  \n690041 Vladivostok, Russia  \n4 Far Eastern Federal University, 690922 Vladivostok, Russia  \n* Correspondence: [alex.iacp.dvo@mail.ru](alex.iacp.dvo@mail.ru)  \nAbstract: Raman microspectroscopy has become an effective method for analyzing the molecular appearance of biomarkers in skin tissue. For the first time, we acquired in vitro Raman spectra of healthy and malignant skin tissues, including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), at 532 and 785 nm laser excitation wavelengths in the wavenumber ranges of 900–1800 cm−1 and 2800–3100 cm−1 and analyzed them to find spectral features for differentiation between the three classes of the samples. The intensity ratios of the bands at 1268, 1336, and 1445 cm−1 appeared tobe the most reliable criteria for the three-class differentiation at 532 nm excitation, whereas the bands from the higher wavenumber region (2850, 2880, and 2930 cm−1) were a robust measure of the increased protein/lipid ratio in the tumors at both excitation wavelengths. Selecting ratios of the three bands from the merged (532 + 785) dataset made it possible to increase the accuracy to 87% for the three classes and reach the specificities for BCC + SCC equal to 87% and 81% for the sensitivities of 95% and 99%, respectively. Development of multi-wavelength excitation Raman spectroscopic techniques provides a versatile non-invasive tool for research of the processes in malignant skin tumors, as well as other forms of cancer.  \nKeywords: basal cell carcinoma; squamous cell carcinoma; Raman microspectroscopy; multispectral analysis  \n1. Introduction  \nMalignant skin tumors are a serious health problem in all countries [1,2] . A reduction in the mortality of skin tumors has been achieved primarily through early detection and treatment. Currently, a biopsy is used to definitively diagnose and determine appropriate treatment; however, this requires tissue removal, which may itself alter the progression of the disease. The development of optical methods for noninvasive diagnosis can dramatically improve the detection of skin tumors and help with therapy [3,4] . Despite the huge amount of research, there is still no complete picture of the mechan","cbCaivG8EfDDNwp2","https://ap.wps.com/l/cbCaivG8EfDDNwp2","pdf",4996331,22,"English","# Abstract\n# Keywords\n# 1. Introduction","[{\"question\":\"What is the main goal of the Raman spectroscopy study?\",\"answer\":\"To distinguish malignant skin neoplasms by analyzing spectral features in Raman microspectroscopy data from healthy and malignant tissues.\"},{\"question\":\"Which Raman excitation wavelengths and wavenumber ranges were used?\",\"answer\":\"Spectra were acquired using 532 nm and 785 nm laser excitation, covering wavenumber ranges of 900–1800 cm−1 and 2800–3100 cm−1.\"},{\"question\":\"How were spectral criteria selected to improve classification accuracy?\",\"answer\":\"The study used intensity ratios of characteristic Raman bands, and further improved results by selecting ratios from the merged 532+785 dataset.\"}]","Multi-Wavelength Raman Differentiation of Malignant Skin Neoplasms | PDF",1789997441,55]