Development of a novel computer-aided diagnosis system for automatic discrimination of malignant from benign solitary pulmonary nodules on thin-section dynamic computed tomography
As an application of the computer-aided diagnosis of solitary pulmonary nodules (SPNs), 3-dimensional contrast-enhanced (CE) dynamic helical computed tomography (HCT) was performed to evaluate temporal changes in the internal structure of nodules to differentiate between benign nodules (BNs) and mal...
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| Veröffentlicht in: | Journal of computer assisted tomography 2005-03, Vol.29 (2), p.215-222 |
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| container_title | Journal of computer assisted tomography |
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| creator | Mori, Kiyoshi Niki, Noboru Kondo, Teturo Kamiyama, Yukari Kodama, Teturo Kawada, Yoshiki Moriyama, Noriyuki |
| description | As an application of the computer-aided diagnosis of solitary pulmonary nodules (SPNs), 3-dimensional contrast-enhanced (CE) dynamic helical computed tomography (HCT) was performed to evaluate temporal changes in the internal structure of nodules to differentiate between benign nodules (BNs) and malignant nodules (MNs).
There were 62 SPNs (35 MNs and 27 BNs) included in this study. Scanning (2-mm collimation) was performed before and 2 and 4 minutes after CE dynamic HCT. The CT data were sent to a computer, and the pixels inside the nodule were characterized in terms of 3 parameters (attenuation, shape index, and curvedness value).
Based on the CT data at 4 (MN: 1.81-27.1, BN: -42.8 to -3.29) minutes after CE-dynamic HCT, a score of 0 or higher can be assumed to indicate an MN.
Three-dimensional computer-aided diagnosis of the internal structure of SPNs using CE dynamic HCT was found to be effective for differentiating between BNs and MNs. |
| doi_str_mv | 10.1097/01.rct.0000155668.28514.01 |
| format | Article |
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There were 62 SPNs (35 MNs and 27 BNs) included in this study. Scanning (2-mm collimation) was performed before and 2 and 4 minutes after CE dynamic HCT. The CT data were sent to a computer, and the pixels inside the nodule were characterized in terms of 3 parameters (attenuation, shape index, and curvedness value).
Based on the CT data at 4 (MN: 1.81-27.1, BN: -42.8 to -3.29) minutes after CE-dynamic HCT, a score of 0 or higher can be assumed to indicate an MN.
Three-dimensional computer-aided diagnosis of the internal structure of SPNs using CE dynamic HCT was found to be effective for differentiating between BNs and MNs.</description><identifier>ISSN: 0363-8715</identifier><identifier>DOI: 10.1097/01.rct.0000155668.28514.01</identifier><identifier>PMID: 15772540</identifier><language>eng</language><publisher>United States</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Child, Preschool ; Computer Graphics ; Contrast Media - administration & dosage ; Diagnosis, Computer-Assisted - methods ; Diagnosis, Differential ; Female ; Fourier Analysis ; Humans ; Image Enhancement - methods ; Image Processing, Computer-Assisted - methods ; Imaging, Three-Dimensional - methods ; Injections, Intravenous ; Iopamidol ; Linear Models ; Lung - diagnostic imaging ; Lung Diseases - diagnostic imaging ; Lung Neoplasms - diagnostic imaging ; Male ; Mathematical Computing ; Middle Aged ; ROC Curve ; Software ; Solitary Pulmonary Nodule - diagnostic imaging ; Solitary Pulmonary Nodule - etiology ; Tomography, Spiral Computed - methods</subject><ispartof>Journal of computer assisted tomography, 2005-03, Vol.29 (2), p.215-222</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c414t-257fc2b6d752e743f2850c0b197d9ea6937d97710d6e430b248ceeefd83ab71b3</citedby><cites>FETCH-LOGICAL-c414t-257fc2b6d752e743f2850c0b197d9ea6937d97710d6e430b248ceeefd83ab71b3</cites></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/15772540$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mori, Kiyoshi</creatorcontrib><creatorcontrib>Niki, Noboru</creatorcontrib><creatorcontrib>Kondo, Teturo</creatorcontrib><creatorcontrib>Kamiyama, Yukari</creatorcontrib><creatorcontrib>Kodama, Teturo</creatorcontrib><creatorcontrib>Kawada, Yoshiki</creatorcontrib><creatorcontrib>Moriyama, Noriyuki</creatorcontrib><title>Development of a novel computer-aided diagnosis system for automatic discrimination of malignant from benign solitary pulmonary nodules on thin-section dynamic computed tomography</title><title>Journal of computer assisted tomography</title><addtitle>J Comput Assist Tomogr</addtitle><description>As an application of the computer-aided diagnosis of solitary pulmonary nodules (SPNs), 3-dimensional contrast-enhanced (CE) dynamic helical computed tomography (HCT) was performed to evaluate temporal changes in the internal structure of nodules to differentiate between benign nodules (BNs) and malignant nodules (MNs).
There were 62 SPNs (35 MNs and 27 BNs) included in this study. Scanning (2-mm collimation) was performed before and 2 and 4 minutes after CE dynamic HCT. The CT data were sent to a computer, and the pixels inside the nodule were characterized in terms of 3 parameters (attenuation, shape index, and curvedness value).
Based on the CT data at 4 (MN: 1.81-27.1, BN: -42.8 to -3.29) minutes after CE-dynamic HCT, a score of 0 or higher can be assumed to indicate an MN.
Three-dimensional computer-aided diagnosis of the internal structure of SPNs using CE dynamic HCT was found to be effective for differentiating between BNs and MNs.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Child, Preschool</subject><subject>Computer Graphics</subject><subject>Contrast Media - administration & dosage</subject><subject>Diagnosis, Computer-Assisted - methods</subject><subject>Diagnosis, Differential</subject><subject>Female</subject><subject>Fourier Analysis</subject><subject>Humans</subject><subject>Image Enhancement - methods</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Injections, Intravenous</subject><subject>Iopamidol</subject><subject>Linear Models</subject><subject>Lung - diagnostic imaging</subject><subject>Lung Diseases - diagnostic imaging</subject><subject>Lung Neoplasms - diagnostic imaging</subject><subject>Male</subject><subject>Mathematical Computing</subject><subject>Middle Aged</subject><subject>ROC Curve</subject><subject>Software</subject><subject>Solitary Pulmonary Nodule - diagnostic imaging</subject><subject>Solitary Pulmonary Nodule - etiology</subject><subject>Tomography, Spiral Computed - methods</subject><issn>0363-8715</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUcFu3CAQ9aFVkib9hQr10JtdMGC8vVVp2kaK1Et7RhjGGyoDLuBK-135wcwmK-UYLsMMb94M7zXNR0Y7RnfqM2VdtrWjeJiUwzB2_SiZ6Ch701xQPvB2VEyeN-9K-YsQxbk4a86ZVKqXgl40D9_gPyxpDRArSTMxJCYsEJvCulXIrfEOHHHe7GMqvpByKBUCmVMmZqspmOotPhebffARsxSPPMEsfh8Nks45BTJBxJSUtPhq8oGs2xJSPN5ictsChWBbvfexLWCfONwhmoDUp0UcwVlpn816f7hq3s5mKfD-FC-bP99vfl__bO9-_bi9_nrXWsFEbXupZttPg1OyByX4jMpQSye2U24HZthxjEox6gYQnE69GC0AzG7kZlJs4pfNp2feNad_G5SqA_4TlsVESFvRAxJzhRq_BuypVIMUPQK_PANtTqVkmPWKsqEMmlF99FNTptFP_eKnfvIT69j84TRlmwK4l9aTmfwRLv6lFw</recordid><startdate>20050301</startdate><enddate>20050301</enddate><creator>Mori, Kiyoshi</creator><creator>Niki, Noboru</creator><creator>Kondo, Teturo</creator><creator>Kamiyama, Yukari</creator><creator>Kodama, Teturo</creator><creator>Kawada, Yoshiki</creator><creator>Moriyama, Noriyuki</creator><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>7X8</scope></search><sort><creationdate>20050301</creationdate><title>Development of a novel computer-aided diagnosis system for automatic discrimination of malignant from benign solitary pulmonary nodules on thin-section dynamic computed tomography</title><author>Mori, Kiyoshi ; Niki, Noboru ; Kondo, Teturo ; Kamiyama, Yukari ; Kodama, Teturo ; Kawada, Yoshiki ; Moriyama, Noriyuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c414t-257fc2b6d752e743f2850c0b197d9ea6937d97710d6e430b248ceeefd83ab71b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Child, Preschool</topic><topic>Computer Graphics</topic><topic>Contrast Media - administration & dosage</topic><topic>Diagnosis, Computer-Assisted - methods</topic><topic>Diagnosis, Differential</topic><topic>Female</topic><topic>Fourier Analysis</topic><topic>Humans</topic><topic>Image Enhancement - methods</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Injections, Intravenous</topic><topic>Iopamidol</topic><topic>Linear Models</topic><topic>Lung - diagnostic imaging</topic><topic>Lung Diseases - diagnostic imaging</topic><topic>Lung Neoplasms - diagnostic imaging</topic><topic>Male</topic><topic>Mathematical Computing</topic><topic>Middle Aged</topic><topic>ROC Curve</topic><topic>Software</topic><topic>Solitary Pulmonary Nodule - diagnostic imaging</topic><topic>Solitary Pulmonary Nodule - etiology</topic><topic>Tomography, Spiral Computed - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mori, Kiyoshi</creatorcontrib><creatorcontrib>Niki, Noboru</creatorcontrib><creatorcontrib>Kondo, Teturo</creatorcontrib><creatorcontrib>Kamiyama, Yukari</creatorcontrib><creatorcontrib>Kodama, Teturo</creatorcontrib><creatorcontrib>Kawada, Yoshiki</creatorcontrib><creatorcontrib>Moriyama, Noriyuki</creatorcontrib><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>MEDLINE - Academic</collection><jtitle>Journal of computer assisted tomography</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mori, Kiyoshi</au><au>Niki, Noboru</au><au>Kondo, Teturo</au><au>Kamiyama, Yukari</au><au>Kodama, Teturo</au><au>Kawada, Yoshiki</au><au>Moriyama, Noriyuki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of a novel computer-aided diagnosis system for automatic discrimination of malignant from benign solitary pulmonary nodules on thin-section dynamic computed tomography</atitle><jtitle>Journal of computer assisted tomography</jtitle><addtitle>J Comput Assist Tomogr</addtitle><date>2005-03-01</date><risdate>2005</risdate><volume>29</volume><issue>2</issue><spage>215</spage><epage>222</epage><pages>215-222</pages><issn>0363-8715</issn><abstract>As an application of the computer-aided diagnosis of solitary pulmonary nodules (SPNs), 3-dimensional contrast-enhanced (CE) dynamic helical computed tomography (HCT) was performed to evaluate temporal changes in the internal structure of nodules to differentiate between benign nodules (BNs) and malignant nodules (MNs).
There were 62 SPNs (35 MNs and 27 BNs) included in this study. Scanning (2-mm collimation) was performed before and 2 and 4 minutes after CE dynamic HCT. The CT data were sent to a computer, and the pixels inside the nodule were characterized in terms of 3 parameters (attenuation, shape index, and curvedness value).
Based on the CT data at 4 (MN: 1.81-27.1, BN: -42.8 to -3.29) minutes after CE-dynamic HCT, a score of 0 or higher can be assumed to indicate an MN.
Three-dimensional computer-aided diagnosis of the internal structure of SPNs using CE dynamic HCT was found to be effective for differentiating between BNs and MNs.</abstract><cop>United States</cop><pmid>15772540</pmid><doi>10.1097/01.rct.0000155668.28514.01</doi><tpages>8</tpages></addata></record> |
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| subjects | Adult Aged Aged, 80 and over Child, Preschool Computer Graphics Contrast Media - administration & dosage Diagnosis, Computer-Assisted - methods Diagnosis, Differential Female Fourier Analysis Humans Image Enhancement - methods Image Processing, Computer-Assisted - methods Imaging, Three-Dimensional - methods Injections, Intravenous Iopamidol Linear Models Lung - diagnostic imaging Lung Diseases - diagnostic imaging Lung Neoplasms - diagnostic imaging Male Mathematical Computing Middle Aged ROC Curve Software Solitary Pulmonary Nodule - diagnostic imaging Solitary Pulmonary Nodule - etiology Tomography, Spiral Computed - methods |
| title | Development of a novel computer-aided diagnosis system for automatic discrimination of malignant from benign solitary pulmonary nodules on thin-section dynamic computed tomography |
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