Automatic determination of minimal cardiac motion phases for computed tomography imaging: initial experience
Low motion phases for cardiac computed tomography reconstructions are currently detected manually in a user-dependent selection process which is often time consuming and suboptimal. The concept of motion maps was recently introduced to achieve automatic phase selection. This pilot study compared the...
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Veröffentlicht in: | European radiology 2006-02, Vol.16 (2), p.365-373 |
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description | Low motion phases for cardiac computed tomography reconstructions are currently detected manually in a user-dependent selection process which is often time consuming and suboptimal. The concept of motion maps was recently introduced to achieve automatic phase selection. This pilot study compared the accuracy of motion-map phase selection to that with manual iterative selection. The study included 20 patients, consisting of one group with low and one with high heart rate. The technique automatically derives a motion strength function between multiple low-resolution reconstructions through the cardiac cycle, with periods of lowest difference between neighboring phases indicating minimal cardiac motion. A high level of agreement was found for phase selection achieved with the motion map approach compared with the manual iterative selection process. The motion maps allowed automated quiescent phase detection of the cardiac cycle in 85% of cases, with best results at low heart rates and for the left coronary artery. They can also provide additional information such as the presence of breathing artifacts. Motion maps show promise as a rapid off-line tool to automatically detect quiescent cardiac phases in a variety of patients. |
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The concept of motion maps was recently introduced to achieve automatic phase selection. This pilot study compared the accuracy of motion-map phase selection to that with manual iterative selection. The study included 20 patients, consisting of one group with low and one with high heart rate. The technique automatically derives a motion strength function between multiple low-resolution reconstructions through the cardiac cycle, with periods of lowest difference between neighboring phases indicating minimal cardiac motion. A high level of agreement was found for phase selection achieved with the motion map approach compared with the manual iterative selection process. The motion maps allowed automated quiescent phase detection of the cardiac cycle in 85% of cases, with best results at low heart rates and for the left coronary artery. They can also provide additional information such as the presence of breathing artifacts. Motion maps show promise as a rapid off-line tool to automatically detect quiescent cardiac phases in a variety of patients.</description><identifier>ISSN: 0938-7994</identifier><identifier>EISSN: 1432-1084</identifier><identifier>DOI: 10.1007/s00330-005-2849-z</identifier><identifier>PMID: 16021450</identifier><language>eng</language><publisher>Germany: Springer Nature B.V</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Automatic pilots ; Computed tomography ; Coronary Angiography - methods ; Coronary artery ; Female ; Heart rate ; Heart Rate - physiology ; Humans ; Image Enhancement - methods ; Image Processing, Computer-Assisted - methods ; Male ; Middle Aged ; Motion perception ; Myocardial Contraction - physiology ; Observer Variation ; Phases ; Tomography ; Tomography, X-Ray Computed - methods</subject><ispartof>European radiology, 2006-02, Vol.16 (2), p.365-373</ispartof><rights>Springer-Verlag 2005.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c424t-ecfea27ef494b560362b98c47768832fbac9e884108e2f6f7f447a6731c984163</citedby><cites>FETCH-LOGICAL-c424t-ecfea27ef494b560362b98c47768832fbac9e884108e2f6f7f447a6731c984163</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16021450$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hoffmann, Martin H K</creatorcontrib><creatorcontrib>Lessick, Jonathan</creatorcontrib><creatorcontrib>Manzke, Robert</creatorcontrib><creatorcontrib>Schmid, Florian T</creatorcontrib><creatorcontrib>Gershin, Edward</creatorcontrib><creatorcontrib>Boll, Daniel T</creatorcontrib><creatorcontrib>Rispler, Shmuel</creatorcontrib><creatorcontrib>Aschoff, Andrik J</creatorcontrib><creatorcontrib>Grass, Michael</creatorcontrib><title>Automatic determination of minimal cardiac motion phases for computed tomography imaging: initial experience</title><title>European radiology</title><addtitle>Eur Radiol</addtitle><description>Low motion phases for cardiac computed tomography reconstructions are currently detected manually in a user-dependent selection process which is often time consuming and suboptimal. The concept of motion maps was recently introduced to achieve automatic phase selection. This pilot study compared the accuracy of motion-map phase selection to that with manual iterative selection. The study included 20 patients, consisting of one group with low and one with high heart rate. The technique automatically derives a motion strength function between multiple low-resolution reconstructions through the cardiac cycle, with periods of lowest difference between neighboring phases indicating minimal cardiac motion. A high level of agreement was found for phase selection achieved with the motion map approach compared with the manual iterative selection process. The motion maps allowed automated quiescent phase detection of the cardiac cycle in 85% of cases, with best results at low heart rates and for the left coronary artery. They can also provide additional information such as the presence of breathing artifacts. Motion maps show promise as a rapid off-line tool to automatically detect quiescent cardiac phases in a variety of patients.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Automatic pilots</subject><subject>Computed tomography</subject><subject>Coronary Angiography - methods</subject><subject>Coronary artery</subject><subject>Female</subject><subject>Heart rate</subject><subject>Heart Rate - physiology</subject><subject>Humans</subject><subject>Image Enhancement - methods</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Motion perception</subject><subject>Myocardial Contraction - physiology</subject><subject>Observer Variation</subject><subject>Phases</subject><subject>Tomography</subject><subject>Tomography, X-Ray Computed - methods</subject><issn>0938-7994</issn><issn>1432-1084</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkU1r3DAQhkVpabab_oBcgiCQm9vRh_WRWwhJWwj0kpyFVjvaONiWI9nQ5NdH6S4UculpNKP3fWHmIeSEwTcGoL8XACGgAWgbbqRtXj6QFZOCNwyM_EhWYIVptLXyiHwp5REALJP6MzliCjiTLaxIf7nMafBzF-gWZ8xDN9YmjTRFWt_d4HsafN52PtAh_f2ZHnzBQmPKNKRhWmbc0pqRdtlPD8-0WnbduLug1T131Y5_JswdjgGPyafo-4JfD3VN7m-u765-Nre_f_y6urxtguRybjBE9FxjlFZuWgVC8Y01QWqtjBE8bnywaIysWyKPKuoopfZKCxZsnSqxJuf73CmnpwXL7IauBOx7P2JaitOgLJf1Uv8TMitbxnRbhWfvhI9pyWNdwgnGlVFSVBRrwvaqkFMpGaObcj1HfnYM3BsxtyfmKjH3Rsy9VM_pIXnZDLj95zggEq9lPpI9</recordid><startdate>20060201</startdate><enddate>20060201</enddate><creator>Hoffmann, Martin H K</creator><creator>Lessick, Jonathan</creator><creator>Manzke, Robert</creator><creator>Schmid, Florian T</creator><creator>Gershin, Edward</creator><creator>Boll, Daniel T</creator><creator>Rispler, Shmuel</creator><creator>Aschoff, Andrik J</creator><creator>Grass, Michael</creator><general>Springer Nature B.V</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>3V.</scope><scope>7QO</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PJZUB</scope><scope>PKEHL</scope><scope>PPXIY</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>20060201</creationdate><title>Automatic determination of minimal cardiac motion phases for computed tomography imaging: initial experience</title><author>Hoffmann, Martin H K ; Lessick, Jonathan ; Manzke, Robert ; Schmid, Florian T ; Gershin, Edward ; Boll, Daniel T ; Rispler, Shmuel ; Aschoff, Andrik J ; Grass, Michael</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c424t-ecfea27ef494b560362b98c47768832fbac9e884108e2f6f7f447a6731c984163</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Automatic pilots</topic><topic>Computed tomography</topic><topic>Coronary Angiography - methods</topic><topic>Coronary artery</topic><topic>Female</topic><topic>Heart rate</topic><topic>Heart Rate - physiology</topic><topic>Humans</topic><topic>Image Enhancement - methods</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Motion perception</topic><topic>Myocardial Contraction - physiology</topic><topic>Observer Variation</topic><topic>Phases</topic><topic>Tomography</topic><topic>Tomography, X-Ray Computed - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hoffmann, Martin H K</creatorcontrib><creatorcontrib>Lessick, Jonathan</creatorcontrib><creatorcontrib>Manzke, Robert</creatorcontrib><creatorcontrib>Schmid, Florian T</creatorcontrib><creatorcontrib>Gershin, Edward</creatorcontrib><creatorcontrib>Boll, Daniel T</creatorcontrib><creatorcontrib>Rispler, Shmuel</creatorcontrib><creatorcontrib>Aschoff, Andrik J</creatorcontrib><creatorcontrib>Grass, Michael</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>European radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hoffmann, Martin H K</au><au>Lessick, Jonathan</au><au>Manzke, Robert</au><au>Schmid, Florian T</au><au>Gershin, Edward</au><au>Boll, Daniel T</au><au>Rispler, Shmuel</au><au>Aschoff, Andrik J</au><au>Grass, Michael</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automatic determination of minimal cardiac motion phases for computed tomography imaging: initial experience</atitle><jtitle>European radiology</jtitle><addtitle>Eur Radiol</addtitle><date>2006-02-01</date><risdate>2006</risdate><volume>16</volume><issue>2</issue><spage>365</spage><epage>373</epage><pages>365-373</pages><issn>0938-7994</issn><eissn>1432-1084</eissn><abstract>Low motion phases for cardiac computed tomography reconstructions are currently detected manually in a user-dependent selection process which is often time consuming and suboptimal. The concept of motion maps was recently introduced to achieve automatic phase selection. This pilot study compared the accuracy of motion-map phase selection to that with manual iterative selection. The study included 20 patients, consisting of one group with low and one with high heart rate. The technique automatically derives a motion strength function between multiple low-resolution reconstructions through the cardiac cycle, with periods of lowest difference between neighboring phases indicating minimal cardiac motion. A high level of agreement was found for phase selection achieved with the motion map approach compared with the manual iterative selection process. The motion maps allowed automated quiescent phase detection of the cardiac cycle in 85% of cases, with best results at low heart rates and for the left coronary artery. They can also provide additional information such as the presence of breathing artifacts. Motion maps show promise as a rapid off-line tool to automatically detect quiescent cardiac phases in a variety of patients.</abstract><cop>Germany</cop><pub>Springer Nature B.V</pub><pmid>16021450</pmid><doi>10.1007/s00330-005-2849-z</doi><tpages>9</tpages></addata></record> |
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subjects | Adult Aged Aged, 80 and over Automatic pilots Computed tomography Coronary Angiography - methods Coronary artery Female Heart rate Heart Rate - physiology Humans Image Enhancement - methods Image Processing, Computer-Assisted - methods Male Middle Aged Motion perception Myocardial Contraction - physiology Observer Variation Phases Tomography Tomography, X-Ray Computed - methods |
title | Automatic determination of minimal cardiac motion phases for computed tomography imaging: initial experience |
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