Influence of contrast agent dispersion on bolus‐based MRI myocardial perfusion measurements: A computational fluid dynamics study
Purpose Bolus‐based dynamic contrast agent (CA) perfusion measurements of the heart are subject to systematic errors due to CA bolus dispersion in the coronary arteries. To better understand these effects on quantification of myocardial blood flow and myocardial perfusion reserve (MPR), an in‐silico...
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| Veröffentlicht in: | Magnetic resonance in medicine 2020-07, Vol.84 (1), p.467-483 |
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| creator | Martens, Johannes Panzer, Sabine den Wijngaard, Jeroen Siebes, Maria Schreiber, Laura M. |
| description | Purpose
Bolus‐based dynamic contrast agent (CA) perfusion measurements of the heart are subject to systematic errors due to CA bolus dispersion in the coronary arteries. To better understand these effects on quantification of myocardial blood flow and myocardial perfusion reserve (MPR), an in‐silico model of the coronary arteries down to the pre‐arteriolar vessels has been developed.
Methods
In this work, a computational fluid dynamics analysis is performed to investigate these errors on the basis of realistic 3D models of the left and right porcine coronary artery trees, including vessels at the pre‐arteriolar level. Using advanced boundary conditions, simulations of blood flow and CA transport are conducted at rest and under stress. These are evaluated with regard to dispersion (assessed by the width of CA concentration time curves and associated vascular transport functions) and errors of myocardial blood flow and myocardial perfusion reserve quantification.
Results
Contrast agent dispersion increases with traveled distance as well as vessel diameter, and decreases with higher flow velocities. Overall, the average myocardial blood flow errors are −28% ± 16% and −8.5% ± 3.3% at rest and stress, respectively, and the average myocardial perfusion reserve error is 26% ± 22%. The calculated values are different in the left and right coronary tree.
Conclusion
Contrast agent dispersion is dependent on a complex interplay of several different factors characterizing the cardiovascular bed, including vessel size and integrated vascular length. Quantification errors evoked by the observed CA dispersion show nonnegligible distortion in dynamic CA bolus‐based perfusion measurements. We expect future improvements of quantitative perfusion measurements to make the systematic errors described here more apparent. |
| doi_str_mv | 10.1002/mrm.28125 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2325299554</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2378589650</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3885-2f57d00be0333604966bda09cd34d20c2642d33cd4915c4ff9185a30082c66e3</originalsourceid><addsrcrecordid>eNp10c9qFTEYh-Egij1WF96ABNzoYtovX5I5ibtS_HOgB6F0P2SSjEyZTI7JBJmd4A14jV6JaU91IQgDWczDm8CPkJcMzhgAnocUzlAxlI_IhknEBqUWj8kGtgIazrQ4Ic9yvgUArbfiKTnhTKFSiBvyYzcPU_Gz9TQO1MZ5SSYv1Hzx80LdmA8-5THOtH59nEr-9f1nb7J3dH-9o2GN1iQ3molWN5R7GbzJJflQA_kdvajNcCiLWeq_6uplo6NunU0YbaZ5KW59Tp4MZsr-xcN5Sm4-vL-5_NRcff64u7y4aixXSjY4yK0D6D1wzlsQum17Z0Bbx4VDsNgKdJxbJzSTVgyDZkoaDqDQtq3np-TNMXtI8WvxeenCmK2fJjP7WHKHHCVqLaWo9PU_9DaWVN9_p7ZKKt1KqOrtUdkUc05-6A5pDCatHYPubpiuDtPdD1Ptq4di6YN3f-WfJSo4P4Jv4-TX_5e6_fX-mPwNsHCZpg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2378589650</pqid></control><display><type>article</type><title>Influence of contrast agent dispersion on bolus‐based MRI myocardial perfusion measurements: A computational fluid dynamics study</title><source>MEDLINE</source><source>Access via Wiley Online Library</source><creator>Martens, Johannes ; Panzer, Sabine ; den Wijngaard, Jeroen ; Siebes, Maria ; Schreiber, Laura M.</creator><creatorcontrib>Martens, Johannes ; Panzer, Sabine ; den Wijngaard, Jeroen ; Siebes, Maria ; Schreiber, Laura M.</creatorcontrib><description>Purpose
Bolus‐based dynamic contrast agent (CA) perfusion measurements of the heart are subject to systematic errors due to CA bolus dispersion in the coronary arteries. To better understand these effects on quantification of myocardial blood flow and myocardial perfusion reserve (MPR), an in‐silico model of the coronary arteries down to the pre‐arteriolar vessels has been developed.
Methods
In this work, a computational fluid dynamics analysis is performed to investigate these errors on the basis of realistic 3D models of the left and right porcine coronary artery trees, including vessels at the pre‐arteriolar level. Using advanced boundary conditions, simulations of blood flow and CA transport are conducted at rest and under stress. These are evaluated with regard to dispersion (assessed by the width of CA concentration time curves and associated vascular transport functions) and errors of myocardial blood flow and myocardial perfusion reserve quantification.
Results
Contrast agent dispersion increases with traveled distance as well as vessel diameter, and decreases with higher flow velocities. Overall, the average myocardial blood flow errors are −28% ± 16% and −8.5% ± 3.3% at rest and stress, respectively, and the average myocardial perfusion reserve error is 26% ± 22%. The calculated values are different in the left and right coronary tree.
Conclusion
Contrast agent dispersion is dependent on a complex interplay of several different factors characterizing the cardiovascular bed, including vessel size and integrated vascular length. Quantification errors evoked by the observed CA dispersion show nonnegligible distortion in dynamic CA bolus‐based perfusion measurements. We expect future improvements of quantitative perfusion measurements to make the systematic errors described here more apparent.</description><identifier>ISSN: 0740-3194</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.28125</identifier><identifier>PMID: 31828822</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Animals ; Arteries ; Blood flow ; Blood vessels ; bolus‐based perfusion measurement ; Boundary conditions ; Computational fluid dynamics ; Computer applications ; Computer simulation ; Concentration time ; Contrast agents ; Contrast Media ; Coronary artery ; Coronary Artery Disease ; Coronary Circulation ; Coronary vessels ; Diameters ; Dispersion ; Flow velocity ; Fluid dynamics ; Hydrodynamics ; Magnetic Resonance Imaging ; Mathematical analysis ; myocardial blood flow ; Myocardial Perfusion Imaging ; myocardial perfusion reserve ; Perfusion ; Swine ; Systematic errors ; Three dimensional models ; Transport</subject><ispartof>Magnetic resonance in medicine, 2020-07, Vol.84 (1), p.467-483</ispartof><rights>2019 The Authors. in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine</rights><rights>2019 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.</rights><rights>2019. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3885-2f57d00be0333604966bda09cd34d20c2642d33cd4915c4ff9185a30082c66e3</citedby><cites>FETCH-LOGICAL-c3885-2f57d00be0333604966bda09cd34d20c2642d33cd4915c4ff9185a30082c66e3</cites><orcidid>0000-0003-0170-3122 ; 0000-0002-7034-5843</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fmrm.28125$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmrm.28125$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31828822$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Martens, Johannes</creatorcontrib><creatorcontrib>Panzer, Sabine</creatorcontrib><creatorcontrib>den Wijngaard, Jeroen</creatorcontrib><creatorcontrib>Siebes, Maria</creatorcontrib><creatorcontrib>Schreiber, Laura M.</creatorcontrib><title>Influence of contrast agent dispersion on bolus‐based MRI myocardial perfusion measurements: A computational fluid dynamics study</title><title>Magnetic resonance in medicine</title><addtitle>Magn Reson Med</addtitle><description>Purpose
Bolus‐based dynamic contrast agent (CA) perfusion measurements of the heart are subject to systematic errors due to CA bolus dispersion in the coronary arteries. To better understand these effects on quantification of myocardial blood flow and myocardial perfusion reserve (MPR), an in‐silico model of the coronary arteries down to the pre‐arteriolar vessels has been developed.
Methods
In this work, a computational fluid dynamics analysis is performed to investigate these errors on the basis of realistic 3D models of the left and right porcine coronary artery trees, including vessels at the pre‐arteriolar level. Using advanced boundary conditions, simulations of blood flow and CA transport are conducted at rest and under stress. These are evaluated with regard to dispersion (assessed by the width of CA concentration time curves and associated vascular transport functions) and errors of myocardial blood flow and myocardial perfusion reserve quantification.
Results
Contrast agent dispersion increases with traveled distance as well as vessel diameter, and decreases with higher flow velocities. Overall, the average myocardial blood flow errors are −28% ± 16% and −8.5% ± 3.3% at rest and stress, respectively, and the average myocardial perfusion reserve error is 26% ± 22%. The calculated values are different in the left and right coronary tree.
Conclusion
Contrast agent dispersion is dependent on a complex interplay of several different factors characterizing the cardiovascular bed, including vessel size and integrated vascular length. Quantification errors evoked by the observed CA dispersion show nonnegligible distortion in dynamic CA bolus‐based perfusion measurements. We expect future improvements of quantitative perfusion measurements to make the systematic errors described here more apparent.</description><subject>Animals</subject><subject>Arteries</subject><subject>Blood flow</subject><subject>Blood vessels</subject><subject>bolus‐based perfusion measurement</subject><subject>Boundary conditions</subject><subject>Computational fluid dynamics</subject><subject>Computer applications</subject><subject>Computer simulation</subject><subject>Concentration time</subject><subject>Contrast agents</subject><subject>Contrast Media</subject><subject>Coronary artery</subject><subject>Coronary Artery Disease</subject><subject>Coronary Circulation</subject><subject>Coronary vessels</subject><subject>Diameters</subject><subject>Dispersion</subject><subject>Flow velocity</subject><subject>Fluid dynamics</subject><subject>Hydrodynamics</subject><subject>Magnetic Resonance Imaging</subject><subject>Mathematical analysis</subject><subject>myocardial blood flow</subject><subject>Myocardial Perfusion Imaging</subject><subject>myocardial perfusion reserve</subject><subject>Perfusion</subject><subject>Swine</subject><subject>Systematic errors</subject><subject>Three dimensional models</subject><subject>Transport</subject><issn>0740-3194</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp10c9qFTEYh-Egij1WF96ABNzoYtovX5I5ibtS_HOgB6F0P2SSjEyZTI7JBJmd4A14jV6JaU91IQgDWczDm8CPkJcMzhgAnocUzlAxlI_IhknEBqUWj8kGtgIazrQ4Ic9yvgUArbfiKTnhTKFSiBvyYzcPU_Gz9TQO1MZ5SSYv1Hzx80LdmA8-5THOtH59nEr-9f1nb7J3dH-9o2GN1iQ3molWN5R7GbzJJflQA_kdvajNcCiLWeq_6uplo6NunU0YbaZ5KW59Tp4MZsr-xcN5Sm4-vL-5_NRcff64u7y4aixXSjY4yK0D6D1wzlsQum17Z0Bbx4VDsNgKdJxbJzSTVgyDZkoaDqDQtq3np-TNMXtI8WvxeenCmK2fJjP7WHKHHCVqLaWo9PU_9DaWVN9_p7ZKKt1KqOrtUdkUc05-6A5pDCatHYPubpiuDtPdD1Ptq4di6YN3f-WfJSo4P4Jv4-TX_5e6_fX-mPwNsHCZpg</recordid><startdate>202007</startdate><enddate>202007</enddate><creator>Martens, Johannes</creator><creator>Panzer, Sabine</creator><creator>den Wijngaard, Jeroen</creator><creator>Siebes, Maria</creator><creator>Schreiber, Laura M.</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</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>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-0170-3122</orcidid><orcidid>https://orcid.org/0000-0002-7034-5843</orcidid></search><sort><creationdate>202007</creationdate><title>Influence of contrast agent dispersion on bolus‐based MRI myocardial perfusion measurements: A computational fluid dynamics study</title><author>Martens, Johannes ; Panzer, Sabine ; den Wijngaard, Jeroen ; Siebes, Maria ; Schreiber, Laura M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3885-2f57d00be0333604966bda09cd34d20c2642d33cd4915c4ff9185a30082c66e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Animals</topic><topic>Arteries</topic><topic>Blood flow</topic><topic>Blood vessels</topic><topic>bolus‐based perfusion measurement</topic><topic>Boundary conditions</topic><topic>Computational fluid dynamics</topic><topic>Computer applications</topic><topic>Computer simulation</topic><topic>Concentration time</topic><topic>Contrast agents</topic><topic>Contrast Media</topic><topic>Coronary artery</topic><topic>Coronary Artery Disease</topic><topic>Coronary Circulation</topic><topic>Coronary vessels</topic><topic>Diameters</topic><topic>Dispersion</topic><topic>Flow velocity</topic><topic>Fluid dynamics</topic><topic>Hydrodynamics</topic><topic>Magnetic Resonance Imaging</topic><topic>Mathematical analysis</topic><topic>myocardial blood flow</topic><topic>Myocardial Perfusion Imaging</topic><topic>myocardial perfusion reserve</topic><topic>Perfusion</topic><topic>Swine</topic><topic>Systematic errors</topic><topic>Three dimensional models</topic><topic>Transport</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Martens, Johannes</creatorcontrib><creatorcontrib>Panzer, Sabine</creatorcontrib><creatorcontrib>den Wijngaard, Jeroen</creatorcontrib><creatorcontrib>Siebes, Maria</creatorcontrib><creatorcontrib>Schreiber, Laura M.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Magnetic resonance in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Martens, Johannes</au><au>Panzer, Sabine</au><au>den Wijngaard, Jeroen</au><au>Siebes, Maria</au><au>Schreiber, Laura M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Influence of contrast agent dispersion on bolus‐based MRI myocardial perfusion measurements: A computational fluid dynamics study</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn Reson Med</addtitle><date>2020-07</date><risdate>2020</risdate><volume>84</volume><issue>1</issue><spage>467</spage><epage>483</epage><pages>467-483</pages><issn>0740-3194</issn><eissn>1522-2594</eissn><abstract>Purpose
Bolus‐based dynamic contrast agent (CA) perfusion measurements of the heart are subject to systematic errors due to CA bolus dispersion in the coronary arteries. To better understand these effects on quantification of myocardial blood flow and myocardial perfusion reserve (MPR), an in‐silico model of the coronary arteries down to the pre‐arteriolar vessels has been developed.
Methods
In this work, a computational fluid dynamics analysis is performed to investigate these errors on the basis of realistic 3D models of the left and right porcine coronary artery trees, including vessels at the pre‐arteriolar level. Using advanced boundary conditions, simulations of blood flow and CA transport are conducted at rest and under stress. These are evaluated with regard to dispersion (assessed by the width of CA concentration time curves and associated vascular transport functions) and errors of myocardial blood flow and myocardial perfusion reserve quantification.
Results
Contrast agent dispersion increases with traveled distance as well as vessel diameter, and decreases with higher flow velocities. Overall, the average myocardial blood flow errors are −28% ± 16% and −8.5% ± 3.3% at rest and stress, respectively, and the average myocardial perfusion reserve error is 26% ± 22%. The calculated values are different in the left and right coronary tree.
Conclusion
Contrast agent dispersion is dependent on a complex interplay of several different factors characterizing the cardiovascular bed, including vessel size and integrated vascular length. Quantification errors evoked by the observed CA dispersion show nonnegligible distortion in dynamic CA bolus‐based perfusion measurements. We expect future improvements of quantitative perfusion measurements to make the systematic errors described here more apparent.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>31828822</pmid><doi>10.1002/mrm.28125</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0003-0170-3122</orcidid><orcidid>https://orcid.org/0000-0002-7034-5843</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Magnetic resonance in medicine, 2020-07, Vol.84 (1), p.467-483 |
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| source | MEDLINE; Access via Wiley Online Library |
| subjects | Animals Arteries Blood flow Blood vessels bolus‐based perfusion measurement Boundary conditions Computational fluid dynamics Computer applications Computer simulation Concentration time Contrast agents Contrast Media Coronary artery Coronary Artery Disease Coronary Circulation Coronary vessels Diameters Dispersion Flow velocity Fluid dynamics Hydrodynamics Magnetic Resonance Imaging Mathematical analysis myocardial blood flow Myocardial Perfusion Imaging myocardial perfusion reserve Perfusion Swine Systematic errors Three dimensional models Transport |
| title | Influence of contrast agent dispersion on bolus‐based MRI myocardial perfusion measurements: A computational fluid dynamics study |
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