Spatial resolution and velocity field improvement of 4D‐flow MRI
Purpose 4D‐flow MRI obtains a time‐dependent 3D velocity field; however, its use for the calculation of higher‐order parameters is limited by noise. We present an algorithm for denoising 4D‐flow data. Theory and Methods By integrating a velocity field and eliminating streamlines in noisy flow, depic...
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| Veröffentlicht in: | Magnetic resonance in medicine 2017-11, Vol.78 (5), p.1959-1968 |
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| container_end_page | 1968 |
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| container_issue | 5 |
| container_start_page | 1959 |
| container_title | Magnetic resonance in medicine |
| container_volume | 78 |
| creator | Callaghan, Fraser M. Grieve, Stuart M. |
| description | Purpose
4D‐flow MRI obtains a time‐dependent 3D velocity field; however, its use for the calculation of higher‐order parameters is limited by noise. We present an algorithm for denoising 4D‐flow data.
Theory and Methods
By integrating a velocity field and eliminating streamlines in noisy flow, depicted by high curvature, a denoised dataset may be extracted. This method, defined as the velocity field improvement (VFIT) algorithm, was validated in an analytical dataset and using in vivo data in comparison with a computation fluid dynamics (CFD) simulation. As a proof of principal, wall shear stress (WSS) measurements in the descending aorta were compared with those defined by CFD.
Results
The VFIT algorithm achieved a >100% noise reduction of a corrupted analytical dataset. In addition, 4D‐flow data were cleaned to show improved spatial resolution and near wall velocity representation. WSS measures compared well with CFD data and bulk flow dynamics were retained ( |
| doi_str_mv | 10.1002/mrm.26557 |
| format | Article |
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4D‐flow MRI obtains a time‐dependent 3D velocity field; however, its use for the calculation of higher‐order parameters is limited by noise. We present an algorithm for denoising 4D‐flow data.
Theory and Methods
By integrating a velocity field and eliminating streamlines in noisy flow, depicted by high curvature, a denoised dataset may be extracted. This method, defined as the velocity field improvement (VFIT) algorithm, was validated in an analytical dataset and using in vivo data in comparison with a computation fluid dynamics (CFD) simulation. As a proof of principal, wall shear stress (WSS) measurements in the descending aorta were compared with those defined by CFD.
Results
The VFIT algorithm achieved a >100% noise reduction of a corrupted analytical dataset. In addition, 4D‐flow data were cleaned to show improved spatial resolution and near wall velocity representation. WSS measures compared well with CFD data and bulk flow dynamics were retained (<2% difference in flow measurements).
Conclusion
This study presents a method for denoising 4D‐flow datasets with improved spatial resolution. Bulk flow dynamics are accurately conserved while velocity and velocity gradient fields are improved; this is important in the calculation of higher‐order parameters such as WSS, which are shown to be more comparable to CFD measures. Magn Reson Med 78:1959–1968, 2017. © 2016 International Society for Magnetic Resonance in Medicine.</description><identifier>ISSN: 0740-3194</identifier><identifier>EISSN: 1522-2594</identifier><identifier>DOI: 10.1002/mrm.26557</identifier><identifier>PMID: 27885707</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>4D‐flow ; Adult ; Algorithms ; Aorta ; Aorta, Thoracic - diagnostic imaging ; Blood Flow Velocity ; Computational fluid dynamics ; Computer Simulation ; Curvature ; Datasets ; denoising ; Fluid dynamics ; Humans ; Hydrodynamics ; Imaging, Three-Dimensional - methods ; Magnetic resonance imaging ; Magnetic Resonance Imaging - methods ; Male ; Mathematical analysis ; Mechanical stimuli ; Noise reduction ; Order parameters ; Shear stress ; Simulation ; Spatial discrimination ; Spatial resolution ; Velocity ; Velocity gradient ; wall shear stress</subject><ispartof>Magnetic resonance in medicine, 2017-11, Vol.78 (5), p.1959-1968</ispartof><rights>2016 International Society for Magnetic Resonance in Medicine</rights><rights>2016 International Society for Magnetic Resonance in Medicine.</rights><rights>2017 International Society for Magnetic Resonance in Medicine</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3887-701ee1764b56b982a11c354f8102c7d306608300c9a254a1235d0b608acc3f883</citedby><cites>FETCH-LOGICAL-c3887-701ee1764b56b982a11c354f8102c7d306608300c9a254a1235d0b608acc3f883</cites></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.26557$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmrm.26557$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,1427,27901,27902,45550,45551,46384,46808</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27885707$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Callaghan, Fraser M.</creatorcontrib><creatorcontrib>Grieve, Stuart M.</creatorcontrib><title>Spatial resolution and velocity field improvement of 4D‐flow MRI</title><title>Magnetic resonance in medicine</title><addtitle>Magn Reson Med</addtitle><description>Purpose
4D‐flow MRI obtains a time‐dependent 3D velocity field; however, its use for the calculation of higher‐order parameters is limited by noise. We present an algorithm for denoising 4D‐flow data.
Theory and Methods
By integrating a velocity field and eliminating streamlines in noisy flow, depicted by high curvature, a denoised dataset may be extracted. This method, defined as the velocity field improvement (VFIT) algorithm, was validated in an analytical dataset and using in vivo data in comparison with a computation fluid dynamics (CFD) simulation. As a proof of principal, wall shear stress (WSS) measurements in the descending aorta were compared with those defined by CFD.
Results
The VFIT algorithm achieved a >100% noise reduction of a corrupted analytical dataset. In addition, 4D‐flow data were cleaned to show improved spatial resolution and near wall velocity representation. WSS measures compared well with CFD data and bulk flow dynamics were retained (<2% difference in flow measurements).
Conclusion
This study presents a method for denoising 4D‐flow datasets with improved spatial resolution. Bulk flow dynamics are accurately conserved while velocity and velocity gradient fields are improved; this is important in the calculation of higher‐order parameters such as WSS, which are shown to be more comparable to CFD measures. Magn Reson Med 78:1959–1968, 2017. © 2016 International Society for Magnetic Resonance in Medicine.</description><subject>4D‐flow</subject><subject>Adult</subject><subject>Algorithms</subject><subject>Aorta</subject><subject>Aorta, Thoracic - diagnostic imaging</subject><subject>Blood Flow Velocity</subject><subject>Computational fluid dynamics</subject><subject>Computer Simulation</subject><subject>Curvature</subject><subject>Datasets</subject><subject>denoising</subject><subject>Fluid dynamics</subject><subject>Humans</subject><subject>Hydrodynamics</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Magnetic resonance imaging</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Male</subject><subject>Mathematical analysis</subject><subject>Mechanical stimuli</subject><subject>Noise reduction</subject><subject>Order parameters</subject><subject>Shear stress</subject><subject>Simulation</subject><subject>Spatial discrimination</subject><subject>Spatial resolution</subject><subject>Velocity</subject><subject>Velocity gradient</subject><subject>wall shear stress</subject><issn>0740-3194</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kMtKxDAUhoMoznhZ-AJScKOLjie3Jll6V3AQRl2HTJpCh7QZm1aZnY_gM_okVqsuBFcHDh8fPx9CexgmGIAcV001IRnnYg2NMSckJVyxdTQGwSClWLER2opxAQBKCbaJRkRIyQWIMTq9X5q2ND5pXAy-a8tQJ6bOk2fngy3bVVKUzudJWS2b8OwqV7dJKBJ2_v76VvjwkkxnNztoozA-ut3vu40eLy8ezq7T27urm7OT29RSKUUqADuHRcbmPJsrSQzGlnJWSAzEipxCloGkAFYZwpnBhPIc5v3PWEsLKek2Ohy8_ZSnzsVWV2W0zntTu9BFjSVjQCgj0KMHf9BF6Jq6X6ex4pARnineU0cDZZsQY-MKvWzKyjQrjUF_htV9WP0Vtmf3v43dvHL5L_lTsgeOB-Cl9G71v0lPZ9NB-QHDh4AM</recordid><startdate>201711</startdate><enddate>201711</enddate><creator>Callaghan, Fraser M.</creator><creator>Grieve, Stuart M.</creator><general>Wiley Subscription Services, Inc</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>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>201711</creationdate><title>Spatial resolution and velocity field improvement of 4D‐flow MRI</title><author>Callaghan, Fraser M. ; Grieve, Stuart M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3887-701ee1764b56b982a11c354f8102c7d306608300c9a254a1235d0b608acc3f883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>4D‐flow</topic><topic>Adult</topic><topic>Algorithms</topic><topic>Aorta</topic><topic>Aorta, Thoracic - diagnostic imaging</topic><topic>Blood Flow Velocity</topic><topic>Computational fluid dynamics</topic><topic>Computer Simulation</topic><topic>Curvature</topic><topic>Datasets</topic><topic>denoising</topic><topic>Fluid dynamics</topic><topic>Humans</topic><topic>Hydrodynamics</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Magnetic resonance imaging</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Mathematical analysis</topic><topic>Mechanical stimuli</topic><topic>Noise reduction</topic><topic>Order parameters</topic><topic>Shear stress</topic><topic>Simulation</topic><topic>Spatial discrimination</topic><topic>Spatial resolution</topic><topic>Velocity</topic><topic>Velocity gradient</topic><topic>wall shear stress</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Callaghan, Fraser M.</creatorcontrib><creatorcontrib>Grieve, Stuart M.</creatorcontrib><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>Callaghan, Fraser M.</au><au>Grieve, Stuart M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatial resolution and velocity field improvement of 4D‐flow MRI</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn Reson Med</addtitle><date>2017-11</date><risdate>2017</risdate><volume>78</volume><issue>5</issue><spage>1959</spage><epage>1968</epage><pages>1959-1968</pages><issn>0740-3194</issn><eissn>1522-2594</eissn><abstract>Purpose
4D‐flow MRI obtains a time‐dependent 3D velocity field; however, its use for the calculation of higher‐order parameters is limited by noise. We present an algorithm for denoising 4D‐flow data.
Theory and Methods
By integrating a velocity field and eliminating streamlines in noisy flow, depicted by high curvature, a denoised dataset may be extracted. This method, defined as the velocity field improvement (VFIT) algorithm, was validated in an analytical dataset and using in vivo data in comparison with a computation fluid dynamics (CFD) simulation. As a proof of principal, wall shear stress (WSS) measurements in the descending aorta were compared with those defined by CFD.
Results
The VFIT algorithm achieved a >100% noise reduction of a corrupted analytical dataset. In addition, 4D‐flow data were cleaned to show improved spatial resolution and near wall velocity representation. WSS measures compared well with CFD data and bulk flow dynamics were retained (<2% difference in flow measurements).
Conclusion
This study presents a method for denoising 4D‐flow datasets with improved spatial resolution. Bulk flow dynamics are accurately conserved while velocity and velocity gradient fields are improved; this is important in the calculation of higher‐order parameters such as WSS, which are shown to be more comparable to CFD measures. Magn Reson Med 78:1959–1968, 2017. © 2016 International Society for Magnetic Resonance in Medicine.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>27885707</pmid><doi>10.1002/mrm.26557</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; Wiley Online Library; Wiley Online Library Journals Frontfile Complete |
| subjects | 4D‐flow Adult Algorithms Aorta Aorta, Thoracic - diagnostic imaging Blood Flow Velocity Computational fluid dynamics Computer Simulation Curvature Datasets denoising Fluid dynamics Humans Hydrodynamics Imaging, Three-Dimensional - methods Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Mathematical analysis Mechanical stimuli Noise reduction Order parameters Shear stress Simulation Spatial discrimination Spatial resolution Velocity Velocity gradient wall shear stress |
| title | Spatial resolution and velocity field improvement of 4D‐flow MRI |
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