Creating three dimensional models of the right ventricular outflow tract: influence of contrast, sequence, operator, and threshold
The use of 3D printed models of the right ventricular outflow tract (RVOT) for surgical and interventional planning is growing and often requires image segmentation of cardiac magnetic resonance (CMR) images. Segmentation results may vary based on contrast, image sequence, signal threshold chosen by...
Gespeichert in:
| Veröffentlicht in: | The International Journal of Cardiovascular Imaging 2019-11, Vol.35 (11), p.2067-2076 |
|---|---|
| Hauptverfasser: | , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 2076 |
|---|---|
| container_issue | 11 |
| container_start_page | 2067 |
| container_title | The International Journal of Cardiovascular Imaging |
| container_volume | 35 |
| creator | Burkhardt, Barbara E. U. Brown, Nicholas K. Carberry, Jaclyn E. Velasco Forte, Marí Nieves Byrne, Nicholas Greil, Gerald Hussain, Tarique Tandon, Animesh |
| description | The use of 3D printed models of the right ventricular outflow tract (RVOT) for surgical and interventional planning is growing and often requires image segmentation of cardiac magnetic resonance (CMR) images. Segmentation results may vary based on contrast, image sequence, signal threshold chosen by the operator, and manual post-processing. The purpose of this study was to determine potential biases and post-processing errors in image segmentation to enable informed decisions. Models of the RVOT and pulmonary arteries from twelve patients who had contrast enhanced CMR angiography with gadopentetate dimeglumine (GPD), gadofosveset trisodium (GFT), and a post-GFT inversion-recovery (IR) whole heart sequence were segmented, trimmed, and aligned by three operators. Geometric agreement and minimal RVOT diameters were compared between sequences and operators. To determine the contribution of threshold, interoperator variability was compared between models created by the same two operators using the same versus different thresholds. Geometric agreement by Dice between objects was high (intraoperator: 0.89–0.95; interoperator: 0.95–0.97), without differences between sequences. Minimal RVOT diameters differed on average by − 1.9 to − 1.3 mm (intraoperator) and by 0.4 to 1.4 mm (interoperator). The contribution of threshold to interoperator geometric agreement was not significant (same threshold: 0.96 ± 0.06, different threshold: 0.93 ± 0.05; p = 0.181), but minimal RVOT diameters were more variable with different versus constant thresholds (− 9.12% vs. 2.42%; p |
| doi_str_mv | 10.1007/s10554-019-01646-1 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2242159584</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2242159584</sourcerecordid><originalsourceid>FETCH-LOGICAL-c375t-cf2d19f3c7d269fe95f807cd2a0ac8bffc8c127a989f68297bc555232ee27b5c3</originalsourceid><addsrcrecordid>eNp9kTtvHCEUhZGVKH4kf8CFhZQmxY7NYxgGd9EqL8lSGqdGLHPZHYuBNTCx0uaXh921Y8mFCwS69zvnXnEQOqfkkhIirzIlQrQNoaqeru0aeoROqJC8IbLlb3bvTjVCqvYYneZ8RwhhhPF36JhTRrjg4gT9XSYwZQxrXDYJAA_jBCGPMRiPpziAzzi62gOcxvWm4N8QShrt7E3CcS7OxwdckrHlGo_B-RmChZ3CxsqZXBY4w_2-usBxC8mUmBbYhGE_L2-iH96jt874DB8e7zP06-uX2-X35ubntx_LzzeN5VKUxjo2UOW4lQPrlAMlXE-kHZghxvYr52xvKZNG9cp1PVNyZYUQjDMAJlfC8jP06eC7TbGulIuexmzBexMgzlkz1jIqlOjbin58gd7FOdU_2VOE9x0RXaXYgbIp5pzA6W0aJ5P-aEr0LiF9SEjXhPQ-IU2r6OLRel5NMPyXPEVSAX4Acm2FNaTn2a_Y_gORrZ3c</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2240386056</pqid></control><display><type>article</type><title>Creating three dimensional models of the right ventricular outflow tract: influence of contrast, sequence, operator, and threshold</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><creator>Burkhardt, Barbara E. U. ; Brown, Nicholas K. ; Carberry, Jaclyn E. ; Velasco Forte, Marí Nieves ; Byrne, Nicholas ; Greil, Gerald ; Hussain, Tarique ; Tandon, Animesh</creator><creatorcontrib>Burkhardt, Barbara E. U. ; Brown, Nicholas K. ; Carberry, Jaclyn E. ; Velasco Forte, Marí Nieves ; Byrne, Nicholas ; Greil, Gerald ; Hussain, Tarique ; Tandon, Animesh</creatorcontrib><description>The use of 3D printed models of the right ventricular outflow tract (RVOT) for surgical and interventional planning is growing and often requires image segmentation of cardiac magnetic resonance (CMR) images. Segmentation results may vary based on contrast, image sequence, signal threshold chosen by the operator, and manual post-processing. The purpose of this study was to determine potential biases and post-processing errors in image segmentation to enable informed decisions. Models of the RVOT and pulmonary arteries from twelve patients who had contrast enhanced CMR angiography with gadopentetate dimeglumine (GPD), gadofosveset trisodium (GFT), and a post-GFT inversion-recovery (IR) whole heart sequence were segmented, trimmed, and aligned by three operators. Geometric agreement and minimal RVOT diameters were compared between sequences and operators. To determine the contribution of threshold, interoperator variability was compared between models created by the same two operators using the same versus different thresholds. Geometric agreement by Dice between objects was high (intraoperator: 0.89–0.95; interoperator: 0.95–0.97), without differences between sequences. Minimal RVOT diameters differed on average by − 1.9 to − 1.3 mm (intraoperator) and by 0.4 to 1.4 mm (interoperator). The contribution of threshold to interoperator geometric agreement was not significant (same threshold: 0.96 ± 0.06, different threshold: 0.93 ± 0.05; p = 0.181), but minimal RVOT diameters were more variable with different versus constant thresholds (− 9.12% vs. 2.42%; p < 0.05). Thresholding does not significantly change interoperator variability for geometric agreement, but does for minimal RVOT diameter. Minimal RVOT diameters showed clinically relevant variation within and between operators.</description><identifier>ISSN: 1569-5794</identifier><identifier>EISSN: 1573-0743</identifier><identifier>EISSN: 1875-8312</identifier><identifier>DOI: 10.1007/s10554-019-01646-1</identifier><identifier>PMID: 31203535</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Agreements ; Angiography ; Arteries ; Cardiac Imaging ; Cardiology ; Contrast Media - administration & dosage ; Gadolinium - administration & dosage ; Gadolinium DTPA - administration & dosage ; Gadopentetate dimeglumine ; Heart ; Heart Defects, Congenital - diagnostic imaging ; Heart Defects, Congenital - physiopathology ; Heart Ventricles - diagnostic imaging ; Heart Ventricles - physiopathology ; Humans ; Image contrast ; Image processing ; Image segmentation ; Imaging ; Imaging, Three-Dimensional ; Magnetic resonance ; Magnetic Resonance Angiography ; Magnetic resonance imaging ; Medicine ; Medicine & Public Health ; Models, Cardiovascular ; Observer Variation ; Operators ; Organometallic Compounds - administration & dosage ; Original Paper ; Patient-Specific Modeling ; Post-production processing ; Predictive Value of Tests ; Pulmonary arteries ; Pulmonary artery ; Pulmonary Artery - diagnostic imaging ; Pulmonary Artery - physiopathology ; Radiology ; Reproducibility of Results ; Signal processing ; Three dimensional models ; Three dimensional printing ; Thresholds ; Variability ; Ventricle</subject><ispartof>The International Journal of Cardiovascular Imaging, 2019-11, Vol.35 (11), p.2067-2076</ispartof><rights>Springer Nature B.V. 2019</rights><rights>The International Journal of Cardiovascular Imaging is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-cf2d19f3c7d269fe95f807cd2a0ac8bffc8c127a989f68297bc555232ee27b5c3</citedby><cites>FETCH-LOGICAL-c375t-cf2d19f3c7d269fe95f807cd2a0ac8bffc8c127a989f68297bc555232ee27b5c3</cites><orcidid>0000-0001-9769-8801 ; 0000-0002-0412-9958</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10554-019-01646-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10554-019-01646-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31203535$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Burkhardt, Barbara E. U.</creatorcontrib><creatorcontrib>Brown, Nicholas K.</creatorcontrib><creatorcontrib>Carberry, Jaclyn E.</creatorcontrib><creatorcontrib>Velasco Forte, Marí Nieves</creatorcontrib><creatorcontrib>Byrne, Nicholas</creatorcontrib><creatorcontrib>Greil, Gerald</creatorcontrib><creatorcontrib>Hussain, Tarique</creatorcontrib><creatorcontrib>Tandon, Animesh</creatorcontrib><title>Creating three dimensional models of the right ventricular outflow tract: influence of contrast, sequence, operator, and threshold</title><title>The International Journal of Cardiovascular Imaging</title><addtitle>Int J Cardiovasc Imaging</addtitle><addtitle>Int J Cardiovasc Imaging</addtitle><description>The use of 3D printed models of the right ventricular outflow tract (RVOT) for surgical and interventional planning is growing and often requires image segmentation of cardiac magnetic resonance (CMR) images. Segmentation results may vary based on contrast, image sequence, signal threshold chosen by the operator, and manual post-processing. The purpose of this study was to determine potential biases and post-processing errors in image segmentation to enable informed decisions. Models of the RVOT and pulmonary arteries from twelve patients who had contrast enhanced CMR angiography with gadopentetate dimeglumine (GPD), gadofosveset trisodium (GFT), and a post-GFT inversion-recovery (IR) whole heart sequence were segmented, trimmed, and aligned by three operators. Geometric agreement and minimal RVOT diameters were compared between sequences and operators. To determine the contribution of threshold, interoperator variability was compared between models created by the same two operators using the same versus different thresholds. Geometric agreement by Dice between objects was high (intraoperator: 0.89–0.95; interoperator: 0.95–0.97), without differences between sequences. Minimal RVOT diameters differed on average by − 1.9 to − 1.3 mm (intraoperator) and by 0.4 to 1.4 mm (interoperator). The contribution of threshold to interoperator geometric agreement was not significant (same threshold: 0.96 ± 0.06, different threshold: 0.93 ± 0.05; p = 0.181), but minimal RVOT diameters were more variable with different versus constant thresholds (− 9.12% vs. 2.42%; p < 0.05). Thresholding does not significantly change interoperator variability for geometric agreement, but does for minimal RVOT diameter. Minimal RVOT diameters showed clinically relevant variation within and between operators.</description><subject>Agreements</subject><subject>Angiography</subject><subject>Arteries</subject><subject>Cardiac Imaging</subject><subject>Cardiology</subject><subject>Contrast Media - administration & dosage</subject><subject>Gadolinium - administration & dosage</subject><subject>Gadolinium DTPA - administration & dosage</subject><subject>Gadopentetate dimeglumine</subject><subject>Heart</subject><subject>Heart Defects, Congenital - diagnostic imaging</subject><subject>Heart Defects, Congenital - physiopathology</subject><subject>Heart Ventricles - diagnostic imaging</subject><subject>Heart Ventricles - physiopathology</subject><subject>Humans</subject><subject>Image contrast</subject><subject>Image processing</subject><subject>Image segmentation</subject><subject>Imaging</subject><subject>Imaging, Three-Dimensional</subject><subject>Magnetic resonance</subject><subject>Magnetic Resonance Angiography</subject><subject>Magnetic resonance imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Models, Cardiovascular</subject><subject>Observer Variation</subject><subject>Operators</subject><subject>Organometallic Compounds - administration & dosage</subject><subject>Original Paper</subject><subject>Patient-Specific Modeling</subject><subject>Post-production processing</subject><subject>Predictive Value of Tests</subject><subject>Pulmonary arteries</subject><subject>Pulmonary artery</subject><subject>Pulmonary Artery - diagnostic imaging</subject><subject>Pulmonary Artery - physiopathology</subject><subject>Radiology</subject><subject>Reproducibility of Results</subject><subject>Signal processing</subject><subject>Three dimensional models</subject><subject>Three dimensional printing</subject><subject>Thresholds</subject><subject>Variability</subject><subject>Ventricle</subject><issn>1569-5794</issn><issn>1573-0743</issn><issn>1875-8312</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kTtvHCEUhZGVKH4kf8CFhZQmxY7NYxgGd9EqL8lSGqdGLHPZHYuBNTCx0uaXh921Y8mFCwS69zvnXnEQOqfkkhIirzIlQrQNoaqeru0aeoROqJC8IbLlb3bvTjVCqvYYneZ8RwhhhPF36JhTRrjg4gT9XSYwZQxrXDYJAA_jBCGPMRiPpziAzzi62gOcxvWm4N8QShrt7E3CcS7OxwdckrHlGo_B-RmChZ3CxsqZXBY4w_2-usBxC8mUmBbYhGE_L2-iH96jt874DB8e7zP06-uX2-X35ubntx_LzzeN5VKUxjo2UOW4lQPrlAMlXE-kHZghxvYr52xvKZNG9cp1PVNyZYUQjDMAJlfC8jP06eC7TbGulIuexmzBexMgzlkz1jIqlOjbin58gd7FOdU_2VOE9x0RXaXYgbIp5pzA6W0aJ5P-aEr0LiF9SEjXhPQ-IU2r6OLRel5NMPyXPEVSAX4Acm2FNaTn2a_Y_gORrZ3c</recordid><startdate>20191101</startdate><enddate>20191101</enddate><creator>Burkhardt, Barbara E. U.</creator><creator>Brown, Nicholas K.</creator><creator>Carberry, Jaclyn E.</creator><creator>Velasco Forte, Marí Nieves</creator><creator>Byrne, Nicholas</creator><creator>Greil, Gerald</creator><creator>Hussain, Tarique</creator><creator>Tandon, Animesh</creator><general>Springer Netherlands</general><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>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M7Z</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9769-8801</orcidid><orcidid>https://orcid.org/0000-0002-0412-9958</orcidid></search><sort><creationdate>20191101</creationdate><title>Creating three dimensional models of the right ventricular outflow tract: influence of contrast, sequence, operator, and threshold</title><author>Burkhardt, Barbara E. U. ; Brown, Nicholas K. ; Carberry, Jaclyn E. ; Velasco Forte, Marí Nieves ; Byrne, Nicholas ; Greil, Gerald ; Hussain, Tarique ; Tandon, Animesh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-cf2d19f3c7d269fe95f807cd2a0ac8bffc8c127a989f68297bc555232ee27b5c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Agreements</topic><topic>Angiography</topic><topic>Arteries</topic><topic>Cardiac Imaging</topic><topic>Cardiology</topic><topic>Contrast Media - administration & dosage</topic><topic>Gadolinium - administration & dosage</topic><topic>Gadolinium DTPA - administration & dosage</topic><topic>Gadopentetate dimeglumine</topic><topic>Heart</topic><topic>Heart Defects, Congenital - diagnostic imaging</topic><topic>Heart Defects, Congenital - physiopathology</topic><topic>Heart Ventricles - diagnostic imaging</topic><topic>Heart Ventricles - physiopathology</topic><topic>Humans</topic><topic>Image contrast</topic><topic>Image processing</topic><topic>Image segmentation</topic><topic>Imaging</topic><topic>Imaging, Three-Dimensional</topic><topic>Magnetic resonance</topic><topic>Magnetic Resonance Angiography</topic><topic>Magnetic resonance imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Models, Cardiovascular</topic><topic>Observer Variation</topic><topic>Operators</topic><topic>Organometallic Compounds - administration & dosage</topic><topic>Original Paper</topic><topic>Patient-Specific Modeling</topic><topic>Post-production processing</topic><topic>Predictive Value of Tests</topic><topic>Pulmonary arteries</topic><topic>Pulmonary artery</topic><topic>Pulmonary Artery - diagnostic imaging</topic><topic>Pulmonary Artery - physiopathology</topic><topic>Radiology</topic><topic>Reproducibility of Results</topic><topic>Signal processing</topic><topic>Three dimensional models</topic><topic>Three dimensional printing</topic><topic>Thresholds</topic><topic>Variability</topic><topic>Ventricle</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Burkhardt, Barbara E. U.</creatorcontrib><creatorcontrib>Brown, Nicholas K.</creatorcontrib><creatorcontrib>Carberry, Jaclyn E.</creatorcontrib><creatorcontrib>Velasco Forte, Marí Nieves</creatorcontrib><creatorcontrib>Byrne, Nicholas</creatorcontrib><creatorcontrib>Greil, Gerald</creatorcontrib><creatorcontrib>Hussain, Tarique</creatorcontrib><creatorcontrib>Tandon, Animesh</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>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>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>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>The International Journal of Cardiovascular Imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Burkhardt, Barbara E. U.</au><au>Brown, Nicholas K.</au><au>Carberry, Jaclyn E.</au><au>Velasco Forte, Marí Nieves</au><au>Byrne, Nicholas</au><au>Greil, Gerald</au><au>Hussain, Tarique</au><au>Tandon, Animesh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Creating three dimensional models of the right ventricular outflow tract: influence of contrast, sequence, operator, and threshold</atitle><jtitle>The International Journal of Cardiovascular Imaging</jtitle><stitle>Int J Cardiovasc Imaging</stitle><addtitle>Int J Cardiovasc Imaging</addtitle><date>2019-11-01</date><risdate>2019</risdate><volume>35</volume><issue>11</issue><spage>2067</spage><epage>2076</epage><pages>2067-2076</pages><issn>1569-5794</issn><eissn>1573-0743</eissn><eissn>1875-8312</eissn><abstract>The use of 3D printed models of the right ventricular outflow tract (RVOT) for surgical and interventional planning is growing and often requires image segmentation of cardiac magnetic resonance (CMR) images. Segmentation results may vary based on contrast, image sequence, signal threshold chosen by the operator, and manual post-processing. The purpose of this study was to determine potential biases and post-processing errors in image segmentation to enable informed decisions. Models of the RVOT and pulmonary arteries from twelve patients who had contrast enhanced CMR angiography with gadopentetate dimeglumine (GPD), gadofosveset trisodium (GFT), and a post-GFT inversion-recovery (IR) whole heart sequence were segmented, trimmed, and aligned by three operators. Geometric agreement and minimal RVOT diameters were compared between sequences and operators. To determine the contribution of threshold, interoperator variability was compared between models created by the same two operators using the same versus different thresholds. Geometric agreement by Dice between objects was high (intraoperator: 0.89–0.95; interoperator: 0.95–0.97), without differences between sequences. Minimal RVOT diameters differed on average by − 1.9 to − 1.3 mm (intraoperator) and by 0.4 to 1.4 mm (interoperator). The contribution of threshold to interoperator geometric agreement was not significant (same threshold: 0.96 ± 0.06, different threshold: 0.93 ± 0.05; p = 0.181), but minimal RVOT diameters were more variable with different versus constant thresholds (− 9.12% vs. 2.42%; p < 0.05). Thresholding does not significantly change interoperator variability for geometric agreement, but does for minimal RVOT diameter. Minimal RVOT diameters showed clinically relevant variation within and between operators.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>31203535</pmid><doi>10.1007/s10554-019-01646-1</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-9769-8801</orcidid><orcidid>https://orcid.org/0000-0002-0412-9958</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1569-5794 |
| ispartof | The International Journal of Cardiovascular Imaging, 2019-11, Vol.35 (11), p.2067-2076 |
| issn | 1569-5794 1573-0743 1875-8312 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2242159584 |
| source | MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | Agreements Angiography Arteries Cardiac Imaging Cardiology Contrast Media - administration & dosage Gadolinium - administration & dosage Gadolinium DTPA - administration & dosage Gadopentetate dimeglumine Heart Heart Defects, Congenital - diagnostic imaging Heart Defects, Congenital - physiopathology Heart Ventricles - diagnostic imaging Heart Ventricles - physiopathology Humans Image contrast Image processing Image segmentation Imaging Imaging, Three-Dimensional Magnetic resonance Magnetic Resonance Angiography Magnetic resonance imaging Medicine Medicine & Public Health Models, Cardiovascular Observer Variation Operators Organometallic Compounds - administration & dosage Original Paper Patient-Specific Modeling Post-production processing Predictive Value of Tests Pulmonary arteries Pulmonary artery Pulmonary Artery - diagnostic imaging Pulmonary Artery - physiopathology Radiology Reproducibility of Results Signal processing Three dimensional models Three dimensional printing Thresholds Variability Ventricle |
| title | Creating three dimensional models of the right ventricular outflow tract: influence of contrast, sequence, operator, and threshold |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-02T11%3A20%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Creating%20three%20dimensional%20models%20of%20the%20right%20ventricular%20outflow%20tract:%20influence%20of%20contrast,%20sequence,%20operator,%20and%20threshold&rft.jtitle=The%20International%20Journal%20of%20Cardiovascular%20Imaging&rft.au=Burkhardt,%20Barbara%20E.%20U.&rft.date=2019-11-01&rft.volume=35&rft.issue=11&rft.spage=2067&rft.epage=2076&rft.pages=2067-2076&rft.issn=1569-5794&rft.eissn=1573-0743&rft_id=info:doi/10.1007/s10554-019-01646-1&rft_dat=%3Cproquest_cross%3E2242159584%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2240386056&rft_id=info:pmid/31203535&rfr_iscdi=true |