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Comparison of temporal filtering methods for dynamic contrast MRI myocardial perfusion studies
Dynamic contrast myocardial perfusion studies may benefit from methods that speed up the acquisition. Unaliasing by Fourier encoding the overlaps using the temporal dimension (UNFOLD), and a similar linear interpolation method have been shown to be effective at reducing the number of phase encodes n...
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Published in: | Magnetic resonance in medicine 2003-05, Vol.49 (5), p.895-902 |
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description | Dynamic contrast myocardial perfusion studies may benefit from methods that speed up the acquisition. Unaliasing by Fourier encoding the overlaps using the temporal dimension (UNFOLD), and a similar linear interpolation method have been shown to be effective at reducing the number of phase encodes needed for cardiac wall motion studies by using interleaved sampling and temporal filtering. Here such methods are evaluated in cardiac dynamic contrast studies, with particular regard to the effects of the choice of filter and the interframe motion. Four different filters were evaluated using a motion‐free canine study. Full k‐space was acquired and then downsampled to allow for a measure of truth. The different filters gave nearly equivalent images and quantitative flow estimates compared to full k‐space. The effect of respiratory motion on these schemes was graphically depicted, and the performance of the four temporal filters was evaluated in seven human subjects with respiratory motion present. The four filters provided images of similar quality. However, none of the filters were effective at eliminating motion artifacts. Motion registration methods or motion‐free acquisitions may be necessary to make these reduced FOV approaches clinically useful. Magn Reson Med 49:895–902, 2003. © 2003 Wiley‐Liss, Inc. |
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Unaliasing by Fourier encoding the overlaps using the temporal dimension (UNFOLD), and a similar linear interpolation method have been shown to be effective at reducing the number of phase encodes needed for cardiac wall motion studies by using interleaved sampling and temporal filtering. Here such methods are evaluated in cardiac dynamic contrast studies, with particular regard to the effects of the choice of filter and the interframe motion. Four different filters were evaluated using a motion‐free canine study. Full k‐space was acquired and then downsampled to allow for a measure of truth. The different filters gave nearly equivalent images and quantitative flow estimates compared to full k‐space. The effect of respiratory motion on these schemes was graphically depicted, and the performance of the four temporal filters was evaluated in seven human subjects with respiratory motion present. The four filters provided images of similar quality. 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Reson. Med</addtitle><description>Dynamic contrast myocardial perfusion studies may benefit from methods that speed up the acquisition. Unaliasing by Fourier encoding the overlaps using the temporal dimension (UNFOLD), and a similar linear interpolation method have been shown to be effective at reducing the number of phase encodes needed for cardiac wall motion studies by using interleaved sampling and temporal filtering. Here such methods are evaluated in cardiac dynamic contrast studies, with particular regard to the effects of the choice of filter and the interframe motion. Four different filters were evaluated using a motion‐free canine study. Full k‐space was acquired and then downsampled to allow for a measure of truth. The different filters gave nearly equivalent images and quantitative flow estimates compared to full k‐space. The effect of respiratory motion on these schemes was graphically depicted, and the performance of the four temporal filters was evaluated in seven human subjects with respiratory motion present. The four filters provided images of similar quality. However, none of the filters were effective at eliminating motion artifacts. Motion registration methods or motion‐free acquisitions may be necessary to make these reduced FOV approaches clinically useful. Magn Reson Med 49:895–902, 2003. © 2003 Wiley‐Liss, Inc.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Biological and medical sciences</subject><subject>Dogs</subject><subject>Filtration - instrumentation</subject><subject>gadolinium</subject><subject>gadolinium, rapid imaging</subject><subject>Heart - physiology</subject><subject>Heart - physiopathology</subject><subject>Humans</subject><subject>Image Enhancement</subject><subject>Image Interpretation, Computer-Assisted - instrumentation</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Magnetic Resonance Imaging - instrumentation</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Medical sciences</subject><subject>Movement - physiology</subject><subject>myocardial perfusion imaging</subject><subject>Myocardium</subject><subject>rapid imaging</subject><subject>Respiration</subject><subject>temporal filtering</subject><subject>UNFOLD</subject><issn>0740-3194</issn><issn>1522-2594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><recordid>eNqFkU9PFDEchhujgRU5-AVIL5pwGOjf6fRoVkGQFUIw3Gw6nRar0-nYzkT321PYVU7GU3t43vdNnh8ArzE6wgiR45BC-TAqn4EF5oRUhEv2HCyQYKiiWLJd8DLn7wghKQXbAbuYCMSEIAvwdRnDqJPPcYDRwcmGMSbdQ-f7ySY_3MFgp2-xy9DFBLv1oIM30MRhSjpPcHV9BsM6Gp06X1KjTW7OvnTlae68za_AC6f7bPe37x74cvLhZvmxurg8PVu-u6gMI0hWrTANFjW1pCaNk6JFRret1kRQiiTrmlZwK5nlvBWsoQ5TSihv2hoJY5jBdA-83fSOKf6cbZ5U8NnYvteDjXNWgpYZVv8fxI0gjDJawMMNaFLMOVmnxuSDTmuFkXqwrop19Wi9sAfb0rkNtnsit5oL8GYL6Gx075IejM9PHBMclWMV7njD_fK9Xf97Ua2uV3-mq03C58n-_pvQ6YeqBRVc3X4-Vbf8_afl-RUqGu4BWxGoEg</recordid><startdate>200305</startdate><enddate>200305</enddate><creator>Di Bella, E.V.R.</creator><creator>Wu, Y.J.</creator><creator>Alexander, A.L.</creator><creator>Parker, D.L.</creator><creator>Green, D.</creator><creator>McGann, C.J.</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><general>Williams & Wilkins</general><scope>BSCLL</scope><scope>IQODW</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>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>200305</creationdate><title>Comparison of temporal filtering methods for dynamic contrast MRI myocardial perfusion studies</title><author>Di Bella, E.V.R. ; Wu, Y.J. ; Alexander, A.L. ; Parker, D.L. ; Green, D. ; McGann, C.J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4209-b7c81763e2628f97b0cabbaa2733094d8b75e94e55b7483f1332358b607cc4c13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Biological and medical sciences</topic><topic>Dogs</topic><topic>Filtration - instrumentation</topic><topic>gadolinium</topic><topic>gadolinium, rapid imaging</topic><topic>Heart - physiology</topic><topic>Heart - physiopathology</topic><topic>Humans</topic><topic>Image Enhancement</topic><topic>Image Interpretation, Computer-Assisted - instrumentation</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Magnetic Resonance Imaging - instrumentation</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Medical sciences</topic><topic>Movement - physiology</topic><topic>myocardial perfusion imaging</topic><topic>Myocardium</topic><topic>rapid imaging</topic><topic>Respiration</topic><topic>temporal filtering</topic><topic>UNFOLD</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Di Bella, E.V.R.</creatorcontrib><creatorcontrib>Wu, Y.J.</creatorcontrib><creatorcontrib>Alexander, A.L.</creatorcontrib><creatorcontrib>Parker, D.L.</creatorcontrib><creatorcontrib>Green, D.</creatorcontrib><creatorcontrib>McGann, C.J.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</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>Di Bella, E.V.R.</au><au>Wu, Y.J.</au><au>Alexander, A.L.</au><au>Parker, D.L.</au><au>Green, D.</au><au>McGann, C.J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of temporal filtering methods for dynamic contrast MRI myocardial perfusion studies</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn. Reson. Med</addtitle><date>2003-05</date><risdate>2003</risdate><volume>49</volume><issue>5</issue><spage>895</spage><epage>902</epage><pages>895-902</pages><issn>0740-3194</issn><eissn>1522-2594</eissn><coden>MRMEEN</coden><notes>istex:716422D8B87F4C96E89B8AA213AAA4F2847F925E</notes><notes>Fujisawa Healthcare Inc.</notes><notes>ark:/67375/WNG-W5DKCJP0-7</notes><notes>ArticleID:MRM10439</notes><notes>ObjectType-Article-2</notes><notes>SourceType-Scholarly Journals-1</notes><notes>ObjectType-Feature-1</notes><notes>content type line 23</notes><notes>ObjectType-Article-1</notes><notes>ObjectType-Feature-2</notes><abstract>Dynamic contrast myocardial perfusion studies may benefit from methods that speed up the acquisition. Unaliasing by Fourier encoding the overlaps using the temporal dimension (UNFOLD), and a similar linear interpolation method have been shown to be effective at reducing the number of phase encodes needed for cardiac wall motion studies by using interleaved sampling and temporal filtering. Here such methods are evaluated in cardiac dynamic contrast studies, with particular regard to the effects of the choice of filter and the interframe motion. Four different filters were evaluated using a motion‐free canine study. Full k‐space was acquired and then downsampled to allow for a measure of truth. The different filters gave nearly equivalent images and quantitative flow estimates compared to full k‐space. The effect of respiratory motion on these schemes was graphically depicted, and the performance of the four temporal filters was evaluated in seven human subjects with respiratory motion present. The four filters provided images of similar quality. However, none of the filters were effective at eliminating motion artifacts. Motion registration methods or motion‐free acquisitions may be necessary to make these reduced FOV approaches clinically useful. Magn Reson Med 49:895–902, 2003. © 2003 Wiley‐Liss, Inc.</abstract><cop>New York</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>12704772</pmid><doi>10.1002/mrm.10439</doi><tpages>8</tpages></addata></record> |
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subjects | Algorithms Animals Biological and medical sciences Dogs Filtration - instrumentation gadolinium gadolinium, rapid imaging Heart - physiology Heart - physiopathology Humans Image Enhancement Image Interpretation, Computer-Assisted - instrumentation Image Interpretation, Computer-Assisted - methods Magnetic Resonance Imaging - instrumentation Magnetic Resonance Imaging - methods Medical sciences Movement - physiology myocardial perfusion imaging Myocardium rapid imaging Respiration temporal filtering UNFOLD |
title | Comparison of temporal filtering methods for dynamic contrast MRI myocardial perfusion studies |
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