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Improved PET/MRI attenuation correction in the pelvic region using a statistical decomposition method on T2-weighted images
Background Attenuation correction of PET/MRI is a remaining problem for whole-body PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlas-based method that calculates synthetic CTs from T2-weighted MRI scans. In this study, we evaluated the application of SDA for attenuation...
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| Published in: | EJNMMI physics 2020-11, Vol.7 (1), Article 68 |
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| container_title | EJNMMI physics |
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| creator | Wallstén, Elin Axelsson, Jan Jonsson, Joakim Karlsson, Camilla Thellenberg Nyholm, Tufve Larsson, Anne |
| description | Background
Attenuation correction of PET/MRI is a remaining problem for whole-body PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlas-based method that calculates synthetic CTs from T2-weighted MRI scans. In this study, we evaluated the application of SDA for attenuation correction of PET images in the pelvic region.
Materials and method
Twelve patients were retrospectively selected from an ongoing prostate cancer research study. The patients had same-day scans of [11C]acetate PET/MRI and CT. The CT images were non-rigidly registered to the PET/MRI geometry, and PET images were reconstructed with attenuation correction employing CT, SDA-generated CT, and the built-in Dixon sequence-based method of the scanner. The PET images reconstructed using CT-based attenuation correction were used as ground truth.
Results
The mean whole-image PET uptake error was reduced from − 5.4% for Dixon-PET to − 0.9% for SDA-PET. The prostate standardized uptake value (SUV) quantification error was significantly reduced from − 5.6% for Dixon-PET to − 2.3% for SDA-PET.
Conclusion
Attenuation correction with SDA improves quantification of PET/MR images in the pelvic region compared to the Dixon-based method. |
| doi_str_mv | 10.1186/s40658-020-00336-5 |
| format | article |
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Attenuation correction of PET/MRI is a remaining problem for whole-body PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlas-based method that calculates synthetic CTs from T2-weighted MRI scans. In this study, we evaluated the application of SDA for attenuation correction of PET images in the pelvic region.
Materials and method
Twelve patients were retrospectively selected from an ongoing prostate cancer research study. The patients had same-day scans of [11C]acetate PET/MRI and CT. The CT images were non-rigidly registered to the PET/MRI geometry, and PET images were reconstructed with attenuation correction employing CT, SDA-generated CT, and the built-in Dixon sequence-based method of the scanner. The PET images reconstructed using CT-based attenuation correction were used as ground truth.
Results
The mean whole-image PET uptake error was reduced from − 5.4% for Dixon-PET to − 0.9% for SDA-PET. The prostate standardized uptake value (SUV) quantification error was significantly reduced from − 5.6% for Dixon-PET to − 2.3% for SDA-PET.
Conclusion
Attenuation correction with SDA improves quantification of PET/MR images in the pelvic region compared to the Dixon-based method.</description><identifier>ISSN: 2197-7364</identifier><identifier>EISSN: 2197-7364</identifier><identifier>DOI: 10.1186/s40658-020-00336-5</identifier><identifier>PMID: 33226495</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Algorithms ; Applied and Technical Physics ; Attenuation ; Attenuation correction ; Computational Mathematics and Numerical Analysis ; Computed tomography ; Decomposition ; Engineering ; Error reduction ; Ground truth ; Image reconstruction ; Imaging ; Magnetic resonance imaging ; Medical imaging ; Medicine ; Medicine & Public Health ; Nuclear Medicine ; Original Research ; Pelvis ; PET ; PET-MRI ; Positron emission ; Prostate ; Prostate cancer ; Radiology ; Statistical analysis ; Tomography</subject><ispartof>EJNMMI physics, 2020-11, Vol.7 (1), Article 68</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/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-c556t-6a364b6f8719baf8dbdf52d0fa3bd1b45a2302f7e8f61a59b7b9d401d42670753</citedby><cites>FETCH-LOGICAL-c556t-6a364b6f8719baf8dbdf52d0fa3bd1b45a2302f7e8f61a59b7b9d401d42670753</cites><orcidid>0000-0002-3353-6501</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2473378581/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2473378581?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,44590,53791,53793,74998</link.rule.ids><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-178388$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Wallstén, Elin</creatorcontrib><creatorcontrib>Axelsson, Jan</creatorcontrib><creatorcontrib>Jonsson, Joakim</creatorcontrib><creatorcontrib>Karlsson, Camilla Thellenberg</creatorcontrib><creatorcontrib>Nyholm, Tufve</creatorcontrib><creatorcontrib>Larsson, Anne</creatorcontrib><title>Improved PET/MRI attenuation correction in the pelvic region using a statistical decomposition method on T2-weighted images</title><title>EJNMMI physics</title><addtitle>EJNMMI Phys</addtitle><description>Background
Attenuation correction of PET/MRI is a remaining problem for whole-body PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlas-based method that calculates synthetic CTs from T2-weighted MRI scans. In this study, we evaluated the application of SDA for attenuation correction of PET images in the pelvic region.
Materials and method
Twelve patients were retrospectively selected from an ongoing prostate cancer research study. The patients had same-day scans of [11C]acetate PET/MRI and CT. The CT images were non-rigidly registered to the PET/MRI geometry, and PET images were reconstructed with attenuation correction employing CT, SDA-generated CT, and the built-in Dixon sequence-based method of the scanner. The PET images reconstructed using CT-based attenuation correction were used as ground truth.
Results
The mean whole-image PET uptake error was reduced from − 5.4% for Dixon-PET to − 0.9% for SDA-PET. The prostate standardized uptake value (SUV) quantification error was significantly reduced from − 5.6% for Dixon-PET to − 2.3% for SDA-PET.
Conclusion
Attenuation correction with SDA improves quantification of PET/MR images in the pelvic region compared to the Dixon-based method.</description><subject>Algorithms</subject><subject>Applied and Technical Physics</subject><subject>Attenuation</subject><subject>Attenuation correction</subject><subject>Computational Mathematics and Numerical Analysis</subject><subject>Computed tomography</subject><subject>Decomposition</subject><subject>Engineering</subject><subject>Error reduction</subject><subject>Ground truth</subject><subject>Image reconstruction</subject><subject>Imaging</subject><subject>Magnetic resonance imaging</subject><subject>Medical imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Nuclear Medicine</subject><subject>Original Research</subject><subject>Pelvis</subject><subject>PET</subject><subject>PET-MRI</subject><subject>Positron emission</subject><subject>Prostate</subject><subject>Prostate cancer</subject><subject>Radiology</subject><subject>Statistical analysis</subject><subject>Tomography</subject><issn>2197-7364</issn><issn>2197-7364</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNp9kUtv1DAUhSMEolXpH2BlibWpH_EjG6SqtDBSEQgNbC0nvsm4msTBdqZC_Hk8DwHdsPKV73fP0dGpqteUvKVUy6tUEyk0JoxgQjiXWDyrzhltFFZc1s__mc-qy5QeCCGUCckoe1mdcc6YrBtxXv1ajXMMO3Doy-366tPXFbI5w7TY7MOEuhAjdIfRTyhvAM2w3fkORRj2n0vy04AsSrnwKfvObpGDLoxzSP5wNkLeBIfKtGb4EfywycXLj3aA9Kp60dttgsvTe1F9u7td33zE958_rG6u73EnhMxY2hKilb1WtGltr13resEc6S1vHW1rYRknrFege0mtaFrVNq4m1NVMKqIEv6jwUTc9wry0Zo7FP_40wXrz3n-_NiEOZhkXQ5XmWhf-3ZEv8AiugylHu31y9nQz-Y0Zws4oqbkSpAi8OQnE8GOBlM1DWOJUMhpWK86VFpoWih2pLoaUIvR_HCgx-47NsWNTOjaHjs0-Cz9lKfA0QPwr_Z-r30KtquU</recordid><startdate>20201123</startdate><enddate>20201123</enddate><creator>Wallstén, Elin</creator><creator>Axelsson, Jan</creator><creator>Jonsson, Joakim</creator><creator>Karlsson, Camilla Thellenberg</creator><creator>Nyholm, Tufve</creator><creator>Larsson, Anne</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope><scope>ADHXS</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D8T</scope><scope>D93</scope><scope>ZZAVC</scope><orcidid>https://orcid.org/0000-0002-3353-6501</orcidid></search><sort><creationdate>20201123</creationdate><title>Improved PET/MRI attenuation correction in the pelvic region using a statistical decomposition method on T2-weighted images</title><author>Wallstén, Elin ; Axelsson, Jan ; Jonsson, Joakim ; Karlsson, Camilla Thellenberg ; Nyholm, Tufve ; Larsson, Anne</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c556t-6a364b6f8719baf8dbdf52d0fa3bd1b45a2302f7e8f61a59b7b9d401d42670753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Applied and Technical Physics</topic><topic>Attenuation</topic><topic>Attenuation correction</topic><topic>Computational Mathematics and Numerical Analysis</topic><topic>Computed tomography</topic><topic>Decomposition</topic><topic>Engineering</topic><topic>Error reduction</topic><topic>Ground truth</topic><topic>Image reconstruction</topic><topic>Imaging</topic><topic>Magnetic resonance imaging</topic><topic>Medical imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Nuclear Medicine</topic><topic>Original Research</topic><topic>Pelvis</topic><topic>PET</topic><topic>PET-MRI</topic><topic>Positron emission</topic><topic>Prostate</topic><topic>Prostate cancer</topic><topic>Radiology</topic><topic>Statistical analysis</topic><topic>Tomography</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wallstén, Elin</creatorcontrib><creatorcontrib>Axelsson, Jan</creatorcontrib><creatorcontrib>Jonsson, Joakim</creatorcontrib><creatorcontrib>Karlsson, Camilla Thellenberg</creatorcontrib><creatorcontrib>Nyholm, Tufve</creatorcontrib><creatorcontrib>Larsson, Anne</creatorcontrib><collection>SpringerOpen</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</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>PubMed Central (Full Participant titles)</collection><collection>SWEPUB Umeå universitet full text</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Umeå universitet</collection><collection>SwePub Articles full text</collection><jtitle>EJNMMI physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wallstén, Elin</au><au>Axelsson, Jan</au><au>Jonsson, Joakim</au><au>Karlsson, Camilla Thellenberg</au><au>Nyholm, Tufve</au><au>Larsson, Anne</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Improved PET/MRI attenuation correction in the pelvic region using a statistical decomposition method on T2-weighted images</atitle><jtitle>EJNMMI physics</jtitle><stitle>EJNMMI Phys</stitle><date>2020-11-23</date><risdate>2020</risdate><volume>7</volume><issue>1</issue><artnum>68</artnum><issn>2197-7364</issn><eissn>2197-7364</eissn><abstract>Background
Attenuation correction of PET/MRI is a remaining problem for whole-body PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlas-based method that calculates synthetic CTs from T2-weighted MRI scans. In this study, we evaluated the application of SDA for attenuation correction of PET images in the pelvic region.
Materials and method
Twelve patients were retrospectively selected from an ongoing prostate cancer research study. The patients had same-day scans of [11C]acetate PET/MRI and CT. The CT images were non-rigidly registered to the PET/MRI geometry, and PET images were reconstructed with attenuation correction employing CT, SDA-generated CT, and the built-in Dixon sequence-based method of the scanner. The PET images reconstructed using CT-based attenuation correction were used as ground truth.
Results
The mean whole-image PET uptake error was reduced from − 5.4% for Dixon-PET to − 0.9% for SDA-PET. The prostate standardized uptake value (SUV) quantification error was significantly reduced from − 5.6% for Dixon-PET to − 2.3% for SDA-PET.
Conclusion
Attenuation correction with SDA improves quantification of PET/MR images in the pelvic region compared to the Dixon-based method.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>33226495</pmid><doi>10.1186/s40658-020-00336-5</doi><orcidid>https://orcid.org/0000-0002-3353-6501</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Applied and Technical Physics Attenuation Attenuation correction Computational Mathematics and Numerical Analysis Computed tomography Decomposition Engineering Error reduction Ground truth Image reconstruction Imaging Magnetic resonance imaging Medical imaging Medicine Medicine & Public Health Nuclear Medicine Original Research Pelvis PET PET-MRI Positron emission Prostate Prostate cancer Radiology Statistical analysis Tomography |
| title | Improved PET/MRI attenuation correction in the pelvic region using a statistical decomposition method on T2-weighted images |
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