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Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans
To evaluate a semi-automatic landmark-based lesion tracking software enabling navigation between RECIST lesions in baseline and follow-up CT-scans. The software automatically detects 44 stable anatomical landmarks in each thoraco/abdominal/pelvic CT-scan, sets up a patient specific coordinate-system...
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Published in: | Cancer imaging 2014-04, Vol.14 (1), p.6-6, Article 6 |
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description | To evaluate a semi-automatic landmark-based lesion tracking software enabling navigation between RECIST lesions in baseline and follow-up CT-scans.
The software automatically detects 44 stable anatomical landmarks in each thoraco/abdominal/pelvic CT-scan, sets up a patient specific coordinate-system and cross-links the coordinate-systems of consecutive CT-scans. Accuracy of the software was evaluated on 96 RECIST lesions (target- and non-target lesions) in baseline and follow-up CT-scans of 32 oncologic patients (64 CT-scans). Patients had to present at least one thoracic, one abdominal and one pelvic RECIST lesion. Three radiologists determined the deviation between lesions' centre and the software's navigation result in consensus.
The initial mean runtime of the system to synchronize baseline and follow-up examinations was 19.4 ± 1.2 seconds, with subsequent navigation to corresponding RECIST lesions facilitating in real-time. Mean vector length of the deviations between lesions' centre and the semi-automatic navigation result was 10.2 ± 5.1 mm without a substantial systematic error in any direction. Mean deviation in the cranio-caudal dimension was 5.4 ± 4.0 mm, in the lateral dimension 5.2 ± 3.9 mm and in the ventro-dorsal dimension 5.3 ± 4.0 mm.
The investigated software accurately and reliably navigates between lesions in consecutive CT-scans in real-time, potentially accelerating and facilitating cancer staging. |
doi_str_mv | 10.1186/1470-7330-14-6 |
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The software automatically detects 44 stable anatomical landmarks in each thoraco/abdominal/pelvic CT-scan, sets up a patient specific coordinate-system and cross-links the coordinate-systems of consecutive CT-scans. Accuracy of the software was evaluated on 96 RECIST lesions (target- and non-target lesions) in baseline and follow-up CT-scans of 32 oncologic patients (64 CT-scans). Patients had to present at least one thoracic, one abdominal and one pelvic RECIST lesion. Three radiologists determined the deviation between lesions' centre and the software's navigation result in consensus.
The initial mean runtime of the system to synchronize baseline and follow-up examinations was 19.4 ± 1.2 seconds, with subsequent navigation to corresponding RECIST lesions facilitating in real-time. Mean vector length of the deviations between lesions' centre and the semi-automatic navigation result was 10.2 ± 5.1 mm without a substantial systematic error in any direction. Mean deviation in the cranio-caudal dimension was 5.4 ± 4.0 mm, in the lateral dimension 5.2 ± 3.9 mm and in the ventro-dorsal dimension 5.3 ± 4.0 mm.
The investigated software accurately and reliably navigates between lesions in consecutive CT-scans in real-time, potentially accelerating and facilitating cancer staging.</description><identifier>ISSN: 1470-7330</identifier><identifier>ISSN: 1740-5025</identifier><identifier>EISSN: 1470-7330</identifier><identifier>DOI: 10.1186/1470-7330-14-6</identifier><identifier>PMID: 25609496</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Adult ; Aged ; Analysis ; Cancer staging ; CAT scans ; Diagnosis, Computer-Assisted ; Female ; Humans ; Male ; Middle Aged ; Neoplasms - diagnostic imaging ; Software ; Tomography, X-Ray Computed</subject><ispartof>Cancer imaging, 2014-04, Vol.14 (1), p.6-6, Article 6</ispartof><rights>COPYRIGHT 2014 BioMed Central Ltd.</rights><rights>Copyright © 2014 Dankerl et al.; licensee BioMed Central Ltd. 2014 Dankerl et al.; licensee BioMed Central Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c488t-962a6375e5e14d4d0056ae787f7c901c47a890c027d0fcfdcb3127023ba417f43</citedby><cites>FETCH-LOGICAL-c488t-962a6375e5e14d4d0056ae787f7c901c47a890c027d0fcfdcb3127023ba417f43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212533/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212533/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25609496$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dankerl, Peter</creatorcontrib><creatorcontrib>Cavallaro, Alexander</creatorcontrib><creatorcontrib>Dietzel, Matthias</creatorcontrib><creatorcontrib>Tsymbal, Alexey</creatorcontrib><creatorcontrib>Kramer, Martin</creatorcontrib><creatorcontrib>Seifert, Sascha</creatorcontrib><creatorcontrib>Uder, Michael</creatorcontrib><creatorcontrib>Hammon, Matthias</creatorcontrib><title>Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans</title><title>Cancer imaging</title><addtitle>Cancer Imaging</addtitle><description>To evaluate a semi-automatic landmark-based lesion tracking software enabling navigation between RECIST lesions in baseline and follow-up CT-scans.
The software automatically detects 44 stable anatomical landmarks in each thoraco/abdominal/pelvic CT-scan, sets up a patient specific coordinate-system and cross-links the coordinate-systems of consecutive CT-scans. Accuracy of the software was evaluated on 96 RECIST lesions (target- and non-target lesions) in baseline and follow-up CT-scans of 32 oncologic patients (64 CT-scans). Patients had to present at least one thoracic, one abdominal and one pelvic RECIST lesion. Three radiologists determined the deviation between lesions' centre and the software's navigation result in consensus.
The initial mean runtime of the system to synchronize baseline and follow-up examinations was 19.4 ± 1.2 seconds, with subsequent navigation to corresponding RECIST lesions facilitating in real-time. Mean vector length of the deviations between lesions' centre and the semi-automatic navigation result was 10.2 ± 5.1 mm without a substantial systematic error in any direction. Mean deviation in the cranio-caudal dimension was 5.4 ± 4.0 mm, in the lateral dimension 5.2 ± 3.9 mm and in the ventro-dorsal dimension 5.3 ± 4.0 mm.
The investigated software accurately and reliably navigates between lesions in consecutive CT-scans in real-time, potentially accelerating and facilitating cancer staging.</description><subject>Adult</subject><subject>Aged</subject><subject>Analysis</subject><subject>Cancer staging</subject><subject>CAT scans</subject><subject>Diagnosis, Computer-Assisted</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Neoplasms - diagnostic imaging</subject><subject>Software</subject><subject>Tomography, X-Ray Computed</subject><issn>1470-7330</issn><issn>1740-5025</issn><issn>1470-7330</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNptks9rFTEQx4MotlavHmVBEC-p-bXJ7kUoD39BwUu9eAnzspP3YrNJ3exW_O_N0vp4hZJDhpnPfJlfhLzm7JzzTn_gyjBqpGSUK6qfkNOD4-mRfUJelPKLMdF3vXlOTkSrWa96fUp-bmJIwUFs8BbiAnPIqcm-KTgGCsucx-pyTYQ0jDBd0y0UHJqIZeXmCdx1SLumZD__gQkbn6dmc0WLg1RekmceYsFX9_8Z-fH509XmK738_uXb5uKSOtV1M-21AC1Niy1yNaiBsVYDms5443rGnTLQ9cwxYQbmnR_cVnJhmJBbUNx4Jc_Ixzvdm2U74uAw1bqivZlCrfivzRDsw0gKe7vLt1YJLlopq8D7e4Ep_16wzHYMxWGsTWNeiuW6FYoJIbuKvr1DdxDRhuTzOoMVtxetqnUp2etKnT9C1TfUqbqc0Ifqf5Dw7ihhjxDnfclxWbdRHlV2Uy5lQn9okzO7HoRdd27XnVfLrglvjodzwP9fgPwHSZWvYA</recordid><startdate>20140422</startdate><enddate>20140422</enddate><creator>Dankerl, Peter</creator><creator>Cavallaro, Alexander</creator><creator>Dietzel, Matthias</creator><creator>Tsymbal, Alexey</creator><creator>Kramer, Martin</creator><creator>Seifert, Sascha</creator><creator>Uder, Michael</creator><creator>Hammon, Matthias</creator><general>BioMed Central Ltd</general><general>BioMed Central</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><scope>5PM</scope></search><sort><creationdate>20140422</creationdate><title>Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans</title><author>Dankerl, Peter ; Cavallaro, Alexander ; Dietzel, Matthias ; Tsymbal, Alexey ; Kramer, Martin ; Seifert, Sascha ; Uder, Michael ; Hammon, Matthias</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c488t-962a6375e5e14d4d0056ae787f7c901c47a890c027d0fcfdcb3127023ba417f43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Analysis</topic><topic>Cancer staging</topic><topic>CAT scans</topic><topic>Diagnosis, Computer-Assisted</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Neoplasms - diagnostic imaging</topic><topic>Software</topic><topic>Tomography, X-Ray Computed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dankerl, Peter</creatorcontrib><creatorcontrib>Cavallaro, Alexander</creatorcontrib><creatorcontrib>Dietzel, Matthias</creatorcontrib><creatorcontrib>Tsymbal, Alexey</creatorcontrib><creatorcontrib>Kramer, Martin</creatorcontrib><creatorcontrib>Seifert, Sascha</creatorcontrib><creatorcontrib>Uder, Michael</creatorcontrib><creatorcontrib>Hammon, Matthias</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><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancer imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dankerl, Peter</au><au>Cavallaro, Alexander</au><au>Dietzel, Matthias</au><au>Tsymbal, Alexey</au><au>Kramer, Martin</au><au>Seifert, Sascha</au><au>Uder, Michael</au><au>Hammon, Matthias</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans</atitle><jtitle>Cancer imaging</jtitle><addtitle>Cancer Imaging</addtitle><date>2014-04-22</date><risdate>2014</risdate><volume>14</volume><issue>1</issue><spage>6</spage><epage>6</epage><pages>6-6</pages><artnum>6</artnum><issn>1470-7330</issn><issn>1740-5025</issn><eissn>1470-7330</eissn><abstract>To evaluate a semi-automatic landmark-based lesion tracking software enabling navigation between RECIST lesions in baseline and follow-up CT-scans.
The software automatically detects 44 stable anatomical landmarks in each thoraco/abdominal/pelvic CT-scan, sets up a patient specific coordinate-system and cross-links the coordinate-systems of consecutive CT-scans. Accuracy of the software was evaluated on 96 RECIST lesions (target- and non-target lesions) in baseline and follow-up CT-scans of 32 oncologic patients (64 CT-scans). Patients had to present at least one thoracic, one abdominal and one pelvic RECIST lesion. Three radiologists determined the deviation between lesions' centre and the software's navigation result in consensus.
The initial mean runtime of the system to synchronize baseline and follow-up examinations was 19.4 ± 1.2 seconds, with subsequent navigation to corresponding RECIST lesions facilitating in real-time. Mean vector length of the deviations between lesions' centre and the semi-automatic navigation result was 10.2 ± 5.1 mm without a substantial systematic error in any direction. Mean deviation in the cranio-caudal dimension was 5.4 ± 4.0 mm, in the lateral dimension 5.2 ± 3.9 mm and in the ventro-dorsal dimension 5.3 ± 4.0 mm.
The investigated software accurately and reliably navigates between lesions in consecutive CT-scans in real-time, potentially accelerating and facilitating cancer staging.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>25609496</pmid><doi>10.1186/1470-7330-14-6</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Aged Analysis Cancer staging CAT scans Diagnosis, Computer-Assisted Female Humans Male Middle Aged Neoplasms - diagnostic imaging Software Tomography, X-Ray Computed |
title | Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans |
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