Oral cancer screening: serum Raman spectroscopic approach
Serum Raman spectroscopy (RS) has previously shown potential in oral cancer diagnosis and recurrence prediction. To evaluate the potential of serum RS in oral cancer screening, premalignant and cancer-specific detection was explored in the present study using 328 subjects belonging to healthy contro...
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Veröffentlicht in: | Journal of biomedical optics 2015-11, Vol.20 (11), p.115006-115006 |
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creator | Sahu, Aditi K Dhoot, Suyash Singh, Amandeep Sawant, Sharada S Nandakumar, Nikhila Talathi-Desai, Sneha Garud, Mandavi Pagare, Sandeep Srivastava, Sanjeeva Nair, Sudhir Chaturvedi, Pankaj Murali Krishna, C |
description | Serum Raman spectroscopy (RS) has previously shown potential in oral cancer diagnosis and recurrence prediction. To evaluate the potential of serum RS in oral cancer screening, premalignant and cancer-specific detection was explored in the present study using 328 subjects belonging to healthy controls, premalignant, disease controls, and oral cancer groups. Spectra were acquired using a Raman microprobe. Spectral findings suggest changes in amino acids, lipids, protein, DNA, and β-carotene across the groups. A patient-wise approach was employed for data analysis using principal component linear discriminant analysis. In the first step, the classification among premalignant, disease control (nonoral cancer), oral cancer, and normal samples was evaluated in binary classification models. Thereafter, two screening-friendly classification approaches were explored to further evaluate the clinical utility of serum RS: a single four-group model and normal versus abnormal followed by determining the type of abnormality model. Results demonstrate the feasibility of premalignant and specific cancer detection. The normal versus abnormal model yields better sensitivity and specificity rates of 64 and 80%; these rates are comparable to standard screening approaches. Prospectively, as the current screening procedure of visual inspection is useful mainly for high-risk populations, serum RS may serve as a useful adjunct for early and specific detection of oral precancers and cancer. |
doi_str_mv | 10.1117/1.JBO.20.11.115006 |
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To evaluate the potential of serum RS in oral cancer screening, premalignant and cancer-specific detection was explored in the present study using 328 subjects belonging to healthy controls, premalignant, disease controls, and oral cancer groups. Spectra were acquired using a Raman microprobe. Spectral findings suggest changes in amino acids, lipids, protein, DNA, and β-carotene across the groups. A patient-wise approach was employed for data analysis using principal component linear discriminant analysis. In the first step, the classification among premalignant, disease control (nonoral cancer), oral cancer, and normal samples was evaluated in binary classification models. Thereafter, two screening-friendly classification approaches were explored to further evaluate the clinical utility of serum RS: a single four-group model and normal versus abnormal followed by determining the type of abnormality model. Results demonstrate the feasibility of premalignant and specific cancer detection. The normal versus abnormal model yields better sensitivity and specificity rates of 64 and 80%; these rates are comparable to standard screening approaches. Prospectively, as the current screening procedure of visual inspection is useful mainly for high-risk populations, serum RS may serve as a useful adjunct for early and specific detection of oral precancers and cancer.</description><identifier>ISSN: 1083-3668</identifier><identifier>EISSN: 1560-2281</identifier><identifier>DOI: 10.1117/1.JBO.20.11.115006</identifier><identifier>PMID: 26580700</identifier><language>eng</language><publisher>United States: Society of Photo-Optical Instrumentation Engineers</publisher><subject>Algorithms ; Biomarkers, Tumor - blood ; Data Interpretation, Statistical ; Diagnosis, Computer-Assisted - methods ; Early Detection of Cancer - methods ; Humans ; Mouth Neoplasms - blood ; Mouth Neoplasms - diagnosis ; Pattern Recognition, Automated - methods ; Reproducibility of Results ; Sensitivity and Specificity ; Spectrum Analysis, Raman - methods</subject><ispartof>Journal of biomedical optics, 2015-11, Vol.20 (11), p.115006-115006</ispartof><rights>2015 Society of Photo-Optical Instrumentation Engineers (SPIE)</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c582t-fdb21229192bb0526d61bd5eafb0d9204fa78acb551c79a4bbbd31d602c6c07e3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26580700$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sahu, Aditi K</creatorcontrib><creatorcontrib>Dhoot, Suyash</creatorcontrib><creatorcontrib>Singh, Amandeep</creatorcontrib><creatorcontrib>Sawant, Sharada S</creatorcontrib><creatorcontrib>Nandakumar, Nikhila</creatorcontrib><creatorcontrib>Talathi-Desai, Sneha</creatorcontrib><creatorcontrib>Garud, Mandavi</creatorcontrib><creatorcontrib>Pagare, Sandeep</creatorcontrib><creatorcontrib>Srivastava, Sanjeeva</creatorcontrib><creatorcontrib>Nair, Sudhir</creatorcontrib><creatorcontrib>Chaturvedi, Pankaj</creatorcontrib><creatorcontrib>Murali Krishna, C</creatorcontrib><title>Oral cancer screening: serum Raman spectroscopic approach</title><title>Journal of biomedical optics</title><addtitle>J. Biomed. Opt</addtitle><description>Serum Raman spectroscopy (RS) has previously shown potential in oral cancer diagnosis and recurrence prediction. To evaluate the potential of serum RS in oral cancer screening, premalignant and cancer-specific detection was explored in the present study using 328 subjects belonging to healthy controls, premalignant, disease controls, and oral cancer groups. Spectra were acquired using a Raman microprobe. Spectral findings suggest changes in amino acids, lipids, protein, DNA, and β-carotene across the groups. A patient-wise approach was employed for data analysis using principal component linear discriminant analysis. In the first step, the classification among premalignant, disease control (nonoral cancer), oral cancer, and normal samples was evaluated in binary classification models. Thereafter, two screening-friendly classification approaches were explored to further evaluate the clinical utility of serum RS: a single four-group model and normal versus abnormal followed by determining the type of abnormality model. Results demonstrate the feasibility of premalignant and specific cancer detection. The normal versus abnormal model yields better sensitivity and specificity rates of 64 and 80%; these rates are comparable to standard screening approaches. Prospectively, as the current screening procedure of visual inspection is useful mainly for high-risk populations, serum RS may serve as a useful adjunct for early and specific detection of oral precancers and cancer.</description><subject>Algorithms</subject><subject>Biomarkers, Tumor - blood</subject><subject>Data Interpretation, Statistical</subject><subject>Diagnosis, Computer-Assisted - methods</subject><subject>Early Detection of Cancer - methods</subject><subject>Humans</subject><subject>Mouth Neoplasms - blood</subject><subject>Mouth Neoplasms - diagnosis</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Spectrum Analysis, Raman - methods</subject><issn>1083-3668</issn><issn>1560-2281</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1LAzEQhoMotlb_gAfZo5dtJ9kmu_FWq_UDoSKKx5Bks7plv0x2D_rrTd0qQkUIJJN555mZF6FjDGOMcTzB49vz5ZisI38oANtBQ0wZhIQkeNe_IYnCiLFkgA6cWwFAwjjbRwPCaAIxwBDxpZVFoGWljQ2ctsZUefVyFjhjuzJ4kKWsAtcY3dra6brJdSCbxtZSvx6ivUwWzhxt7hF6Wlw-zq_Du-XVzXx2F2qakDbMUkUwIRxzohRQwlKGVUqNzBSknMA0k3EitaIU65jLqVIqjXDKgGimITbRCJ32XN_2rTOuFWXutCkKWZm6cwLHEeUQ8Qh7Keml2k_rrMlEY_NS2neBQawtE1h4ywRZR6K3zBedbPidKk36U_LtkRc89wLX5Eas6s5Wft9foI-82cJ-fc5sm-vC3F8stvNNmnny5C_yP8N-AiLtkPs</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Sahu, Aditi K</creator><creator>Dhoot, Suyash</creator><creator>Singh, Amandeep</creator><creator>Sawant, Sharada S</creator><creator>Nandakumar, Nikhila</creator><creator>Talathi-Desai, Sneha</creator><creator>Garud, Mandavi</creator><creator>Pagare, Sandeep</creator><creator>Srivastava, Sanjeeva</creator><creator>Nair, Sudhir</creator><creator>Chaturvedi, Pankaj</creator><creator>Murali Krishna, C</creator><general>Society of Photo-Optical Instrumentation Engineers</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20151101</creationdate><title>Oral cancer screening: serum Raman spectroscopic approach</title><author>Sahu, Aditi K ; Dhoot, Suyash ; Singh, Amandeep ; Sawant, Sharada S ; Nandakumar, Nikhila ; Talathi-Desai, Sneha ; Garud, Mandavi ; Pagare, Sandeep ; Srivastava, Sanjeeva ; Nair, Sudhir ; Chaturvedi, Pankaj ; Murali Krishna, C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c582t-fdb21229192bb0526d61bd5eafb0d9204fa78acb551c79a4bbbd31d602c6c07e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithms</topic><topic>Biomarkers, Tumor - blood</topic><topic>Data Interpretation, Statistical</topic><topic>Diagnosis, Computer-Assisted - methods</topic><topic>Early Detection of Cancer - methods</topic><topic>Humans</topic><topic>Mouth Neoplasms - blood</topic><topic>Mouth Neoplasms - diagnosis</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Spectrum Analysis, Raman - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sahu, Aditi K</creatorcontrib><creatorcontrib>Dhoot, Suyash</creatorcontrib><creatorcontrib>Singh, Amandeep</creatorcontrib><creatorcontrib>Sawant, Sharada S</creatorcontrib><creatorcontrib>Nandakumar, Nikhila</creatorcontrib><creatorcontrib>Talathi-Desai, Sneha</creatorcontrib><creatorcontrib>Garud, Mandavi</creatorcontrib><creatorcontrib>Pagare, Sandeep</creatorcontrib><creatorcontrib>Srivastava, Sanjeeva</creatorcontrib><creatorcontrib>Nair, Sudhir</creatorcontrib><creatorcontrib>Chaturvedi, Pankaj</creatorcontrib><creatorcontrib>Murali Krishna, C</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of biomedical optics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sahu, Aditi K</au><au>Dhoot, Suyash</au><au>Singh, Amandeep</au><au>Sawant, Sharada S</au><au>Nandakumar, Nikhila</au><au>Talathi-Desai, Sneha</au><au>Garud, Mandavi</au><au>Pagare, Sandeep</au><au>Srivastava, Sanjeeva</au><au>Nair, Sudhir</au><au>Chaturvedi, Pankaj</au><au>Murali Krishna, C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Oral cancer screening: serum Raman spectroscopic approach</atitle><jtitle>Journal of biomedical optics</jtitle><addtitle>J. Biomed. Opt</addtitle><date>2015-11-01</date><risdate>2015</risdate><volume>20</volume><issue>11</issue><spage>115006</spage><epage>115006</epage><pages>115006-115006</pages><issn>1083-3668</issn><eissn>1560-2281</eissn><abstract>Serum Raman spectroscopy (RS) has previously shown potential in oral cancer diagnosis and recurrence prediction. To evaluate the potential of serum RS in oral cancer screening, premalignant and cancer-specific detection was explored in the present study using 328 subjects belonging to healthy controls, premalignant, disease controls, and oral cancer groups. Spectra were acquired using a Raman microprobe. Spectral findings suggest changes in amino acids, lipids, protein, DNA, and β-carotene across the groups. A patient-wise approach was employed for data analysis using principal component linear discriminant analysis. In the first step, the classification among premalignant, disease control (nonoral cancer), oral cancer, and normal samples was evaluated in binary classification models. Thereafter, two screening-friendly classification approaches were explored to further evaluate the clinical utility of serum RS: a single four-group model and normal versus abnormal followed by determining the type of abnormality model. Results demonstrate the feasibility of premalignant and specific cancer detection. The normal versus abnormal model yields better sensitivity and specificity rates of 64 and 80%; these rates are comparable to standard screening approaches. Prospectively, as the current screening procedure of visual inspection is useful mainly for high-risk populations, serum RS may serve as a useful adjunct for early and specific detection of oral precancers and cancer.</abstract><cop>United States</cop><pub>Society of Photo-Optical Instrumentation Engineers</pub><pmid>26580700</pmid><doi>10.1117/1.JBO.20.11.115006</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Biomarkers, Tumor - blood Data Interpretation, Statistical Diagnosis, Computer-Assisted - methods Early Detection of Cancer - methods Humans Mouth Neoplasms - blood Mouth Neoplasms - diagnosis Pattern Recognition, Automated - methods Reproducibility of Results Sensitivity and Specificity Spectrum Analysis, Raman - methods |
title | Oral cancer screening: serum Raman spectroscopic approach |
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