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A comparison of methods using optical coherence tomography to detect demineralized regions in teeth
Optical coherence tomography (OCT) is a three‐ dimensional optical imaging technique that can be used to identify areas of early caries formation in dental enamel. The OCT signal at 850 nm back‐reflected from sound enamel is attenuated stronger than the signal back‐reflected from demineralized regio...
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Published in: | Journal of biophotonics 2011-11, Vol.4 (11-12), p.814-823 |
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description | Optical coherence tomography (OCT) is a three‐ dimensional optical imaging technique that can be used to identify areas of early caries formation in dental enamel. The OCT signal at 850 nm back‐reflected from sound enamel is attenuated stronger than the signal back‐reflected from demineralized regions. To quantify this observation, the OCT signal as a function of depth into the enamel (also known as the A‐scan intensity), the histogram of the A‐scan intensities and three summary parameters derived from the A‐scan are defined and their diagnostic potential compared. A total of 754 OCT A‐scans were analyzed. The three summary parameters derived from the A‐scans, the OCT attenuation coefficient as well as the mean and standard deviation of the lognormal fit to the histogram of the A‐scan ensemble show statistically significant differences (p < 0.01) when comparing parameters from sound enamel and caries. Furthermore, these parameters only show a modest correlation. Based on the area under the curve (AUC) of the receiver operating characteristics (ROC) plot, the OCT attenuation coefficient shows higher discriminatory capacity (AUC = 0.98) compared to the parameters derived from the lognormal fit to the histogram of the A‐scan. However, direct analysis of the A‐scans or the histogram of A‐scan intensities using linear support vector machine classification shows diagnostic discrimination (AUC = 0.96) comparable to that achieved using the attenuation coefficient. These findings suggest that either direct analysis of the A‐scan, its intensity histogram or the attenuation coefficient derived from the descending slope of the OCT A‐scan have high capacity to discriminate between regions of caries and sound enamel. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim) |
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The OCT signal at 850 nm back‐reflected from sound enamel is attenuated stronger than the signal back‐reflected from demineralized regions. To quantify this observation, the OCT signal as a function of depth into the enamel (also known as the A‐scan intensity), the histogram of the A‐scan intensities and three summary parameters derived from the A‐scan are defined and their diagnostic potential compared. A total of 754 OCT A‐scans were analyzed. The three summary parameters derived from the A‐scans, the OCT attenuation coefficient as well as the mean and standard deviation of the lognormal fit to the histogram of the A‐scan ensemble show statistically significant differences (p < 0.01) when comparing parameters from sound enamel and caries. Furthermore, these parameters only show a modest correlation. Based on the area under the curve (AUC) of the receiver operating characteristics (ROC) plot, the OCT attenuation coefficient shows higher discriminatory capacity (AUC = 0.98) compared to the parameters derived from the lognormal fit to the histogram of the A‐scan. However, direct analysis of the A‐scans or the histogram of A‐scan intensities using linear support vector machine classification shows diagnostic discrimination (AUC = 0.96) comparable to that achieved using the attenuation coefficient. These findings suggest that either direct analysis of the A‐scan, its intensity histogram or the attenuation coefficient derived from the descending slope of the OCT A‐scan have high capacity to discriminate between regions of caries and sound enamel. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)</description><identifier>ISSN: 1864-063X</identifier><identifier>ISSN: 1864-0648</identifier><identifier>EISSN: 1864-0648</identifier><identifier>DOI: 10.1002/jbio.201100014</identifier><identifier>PMID: 22052833</identifier><language>eng</language><publisher>Berlin: WILEY-VCH Verlag</publisher><subject>Area Under Curve ; Bicuspid - pathology ; Computer Simulation ; Dental Caries - diagnosis ; Dental Caries - pathology ; Dental Enamel - pathology ; diagnostic discrimination ; Enamel demineralization ; Humans ; Image Interpretation, Computer-Assisted - methods ; incipient caries detection ; lognormal fit ; Models, Statistical ; Molar - pathology ; Monte Carlo Method ; optical coherence tomography ; ROC Curve ; Sensitivity and Specificity ; Statistical Distributions ; Statistics, Nonparametric ; Support Vector Machine ; support vector machine classification ; Tomography, Optical Coherence - methods ; Tooth Demineralization - diagnosis ; Tooth Demineralization - pathology</subject><ispartof>Journal of biophotonics, 2011-11, Vol.4 (11-12), p.814-823</ispartof><rights>Copyright © 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim</rights><rights>Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c6414-e6c14aee01ce1320c4b5b49ba2fcb2728d82bbc29695a73d43226ecb68ebd893</citedby><cites>FETCH-LOGICAL-c6414-e6c14aee01ce1320c4b5b49ba2fcb2728d82bbc29695a73d43226ecb68ebd893</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22052833$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sowa, Michael G.</creatorcontrib><creatorcontrib>Popescu, Dan P.</creatorcontrib><creatorcontrib>Friesen, Jeri R.</creatorcontrib><creatorcontrib>Hewko, Mark D.</creatorcontrib><creatorcontrib>Choo-Smith, and Lin-P'ing</creatorcontrib><title>A comparison of methods using optical coherence tomography to detect demineralized regions in teeth</title><title>Journal of biophotonics</title><addtitle>J. Biophoton</addtitle><description>Optical coherence tomography (OCT) is a three‐ dimensional optical imaging technique that can be used to identify areas of early caries formation in dental enamel. The OCT signal at 850 nm back‐reflected from sound enamel is attenuated stronger than the signal back‐reflected from demineralized regions. To quantify this observation, the OCT signal as a function of depth into the enamel (also known as the A‐scan intensity), the histogram of the A‐scan intensities and three summary parameters derived from the A‐scan are defined and their diagnostic potential compared. A total of 754 OCT A‐scans were analyzed. The three summary parameters derived from the A‐scans, the OCT attenuation coefficient as well as the mean and standard deviation of the lognormal fit to the histogram of the A‐scan ensemble show statistically significant differences (p < 0.01) when comparing parameters from sound enamel and caries. Furthermore, these parameters only show a modest correlation. Based on the area under the curve (AUC) of the receiver operating characteristics (ROC) plot, the OCT attenuation coefficient shows higher discriminatory capacity (AUC = 0.98) compared to the parameters derived from the lognormal fit to the histogram of the A‐scan. However, direct analysis of the A‐scans or the histogram of A‐scan intensities using linear support vector machine classification shows diagnostic discrimination (AUC = 0.96) comparable to that achieved using the attenuation coefficient. These findings suggest that either direct analysis of the A‐scan, its intensity histogram or the attenuation coefficient derived from the descending slope of the OCT A‐scan have high capacity to discriminate between regions of caries and sound enamel. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)</description><subject>Area Under Curve</subject><subject>Bicuspid - pathology</subject><subject>Computer Simulation</subject><subject>Dental Caries - diagnosis</subject><subject>Dental Caries - pathology</subject><subject>Dental Enamel - pathology</subject><subject>diagnostic discrimination</subject><subject>Enamel demineralization</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>incipient caries detection</subject><subject>lognormal fit</subject><subject>Models, Statistical</subject><subject>Molar - pathology</subject><subject>Monte Carlo Method</subject><subject>optical coherence tomography</subject><subject>ROC Curve</subject><subject>Sensitivity and Specificity</subject><subject>Statistical Distributions</subject><subject>Statistics, Nonparametric</subject><subject>Support Vector Machine</subject><subject>support vector machine classification</subject><subject>Tomography, Optical Coherence - methods</subject><subject>Tooth Demineralization - diagnosis</subject><subject>Tooth Demineralization - pathology</subject><issn>1864-063X</issn><issn>1864-0648</issn><issn>1864-0648</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqFkc1v1DAQxSMEoh9w5Yh85JLFX3GcC1IptBRVVEIr4GbZzuyuS2KnthdY_nq82hKVE6cZa9783livql4QvCAY09e3xoUFxaQ8MOGPqmMiBa-x4PLx3LNvR9VJSrcYC8wa9rQ6ohQ3VDJ2XNkzZMM46ehS8Cis0Ah5E_qEtsn5NQpTdlYPRbOBCN4CymEM66inza60qIcMNpcyOg9RD-439CjC2gWfkPMoQ8E9q56s9JDg-X09rZYX75fnH-rrm8ur87Pr2gpOeA3CEq4BMLFAGMWWm8bwzmi6soa2VPaSGmNpJ7pGt6znjFIB1ggJppcdO63eHLDT1ozQW_C5XKSm6EYddypop_6deLdR6_BDsbYRsmsK4NU9IIa7LaSsRpcsDIP2ELZJEUzaYs7o3mtxkNoYUoqwmm0IVvtg1D4YNQdTFl4-PG6W_02iCLqD4KcbYPcfnPr49urmIbw-7LqU4de8q-N3JdryO_X106XidCm_NPSd-sz-AN3zrI8</recordid><startdate>201111</startdate><enddate>201111</enddate><creator>Sowa, Michael G.</creator><creator>Popescu, Dan P.</creator><creator>Friesen, Jeri R.</creator><creator>Hewko, Mark D.</creator><creator>Choo-Smith, and Lin-P'ing</creator><general>WILEY-VCH Verlag</general><general>WILEY‐VCH Verlag</general><scope>BSCLL</scope><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>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>5PM</scope></search><sort><creationdate>201111</creationdate><title>A comparison of methods using optical coherence tomography to detect demineralized regions in teeth</title><author>Sowa, Michael G. ; Popescu, Dan P. ; Friesen, Jeri R. ; Hewko, Mark D. ; Choo-Smith, and Lin-P'ing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c6414-e6c14aee01ce1320c4b5b49ba2fcb2728d82bbc29695a73d43226ecb68ebd893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Area Under Curve</topic><topic>Bicuspid - pathology</topic><topic>Computer Simulation</topic><topic>Dental Caries - diagnosis</topic><topic>Dental Caries - pathology</topic><topic>Dental Enamel - pathology</topic><topic>diagnostic discrimination</topic><topic>Enamel demineralization</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>incipient caries detection</topic><topic>lognormal fit</topic><topic>Models, Statistical</topic><topic>Molar - pathology</topic><topic>Monte Carlo Method</topic><topic>optical coherence tomography</topic><topic>ROC Curve</topic><topic>Sensitivity and Specificity</topic><topic>Statistical Distributions</topic><topic>Statistics, Nonparametric</topic><topic>Support Vector Machine</topic><topic>support vector machine classification</topic><topic>Tomography, Optical Coherence - methods</topic><topic>Tooth Demineralization - diagnosis</topic><topic>Tooth Demineralization - pathology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sowa, Michael G.</creatorcontrib><creatorcontrib>Popescu, Dan P.</creatorcontrib><creatorcontrib>Friesen, Jeri R.</creatorcontrib><creatorcontrib>Hewko, Mark D.</creatorcontrib><creatorcontrib>Choo-Smith, and Lin-P'ing</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of biophotonics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sowa, Michael G.</au><au>Popescu, Dan P.</au><au>Friesen, Jeri R.</au><au>Hewko, Mark D.</au><au>Choo-Smith, and Lin-P'ing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A comparison of methods using optical coherence tomography to detect demineralized regions in teeth</atitle><jtitle>Journal of biophotonics</jtitle><addtitle>J. Biophoton</addtitle><date>2011-11</date><risdate>2011</risdate><volume>4</volume><issue>11-12</issue><spage>814</spage><epage>823</epage><pages>814-823</pages><issn>1864-063X</issn><issn>1864-0648</issn><eissn>1864-0648</eissn><abstract>Optical coherence tomography (OCT) is a three‐ dimensional optical imaging technique that can be used to identify areas of early caries formation in dental enamel. The OCT signal at 850 nm back‐reflected from sound enamel is attenuated stronger than the signal back‐reflected from demineralized regions. To quantify this observation, the OCT signal as a function of depth into the enamel (also known as the A‐scan intensity), the histogram of the A‐scan intensities and three summary parameters derived from the A‐scan are defined and their diagnostic potential compared. A total of 754 OCT A‐scans were analyzed. The three summary parameters derived from the A‐scans, the OCT attenuation coefficient as well as the mean and standard deviation of the lognormal fit to the histogram of the A‐scan ensemble show statistically significant differences (p < 0.01) when comparing parameters from sound enamel and caries. Furthermore, these parameters only show a modest correlation. Based on the area under the curve (AUC) of the receiver operating characteristics (ROC) plot, the OCT attenuation coefficient shows higher discriminatory capacity (AUC = 0.98) compared to the parameters derived from the lognormal fit to the histogram of the A‐scan. However, direct analysis of the A‐scans or the histogram of A‐scan intensities using linear support vector machine classification shows diagnostic discrimination (AUC = 0.96) comparable to that achieved using the attenuation coefficient. These findings suggest that either direct analysis of the A‐scan, its intensity histogram or the attenuation coefficient derived from the descending slope of the OCT A‐scan have high capacity to discriminate between regions of caries and sound enamel. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)</abstract><cop>Berlin</cop><pub>WILEY-VCH Verlag</pub><pmid>22052833</pmid><doi>10.1002/jbio.201100014</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Area Under Curve Bicuspid - pathology Computer Simulation Dental Caries - diagnosis Dental Caries - pathology Dental Enamel - pathology diagnostic discrimination Enamel demineralization Humans Image Interpretation, Computer-Assisted - methods incipient caries detection lognormal fit Models, Statistical Molar - pathology Monte Carlo Method optical coherence tomography ROC Curve Sensitivity and Specificity Statistical Distributions Statistics, Nonparametric Support Vector Machine support vector machine classification Tomography, Optical Coherence - methods Tooth Demineralization - diagnosis Tooth Demineralization - pathology |
title | A comparison of methods using optical coherence tomography to detect demineralized regions in teeth |
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