A Simplified Model for Intravoxel Incoherent Motion Perfusion Imaging of the Brain
Despite a recent resurgence, intravoxel incoherent motion MRI faces practical challenges, including limited SNR and demanding acquisition and postprocessing requirements. A simplified approach using linear fitting of a subset of higher b-values has seen success in other organ systems. We sought to v...
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Veröffentlicht in: | American journal of neuroradiology : AJNR 2016-12, Vol.37 (12), p.2251-2257 |
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creator | Conklin, J Heyn, C Roux, M Cerny, M Wintermark, M Federau, C |
description | Despite a recent resurgence, intravoxel incoherent motion MRI faces practical challenges, including limited SNR and demanding acquisition and postprocessing requirements. A simplified approach using linear fitting of a subset of higher b-values has seen success in other organ systems. We sought to validate this method for evaluation of brain pathology by comparing perfusion measurements using simplified linear fitting to conventional biexponential fitting.
Forty-nine patients with gliomas and 17 with acute strokes underwent 3T MRI, including DWI with 16 b-values (range, 0-900 s/mm
). Conventional intravoxel incoherent motion was performed using nonlinear fitting of the standard biexponential equation. Simplified intravoxel incoherent motion was performed using linear fitting of the log-normalized signal curves for subsets of b-values >200 s/mm
. Comparisons between ROIs (tumors, strokes, contralateral brain) and between models (biexponential and simplified linear) were performed by using 2-way ANOVA. The root mean square error and coefficient of determination (R
) were computed for the simplified model, with biexponential fitting as the reference standard.
Perfusion maps using simplified linear fitting were qualitatively similar to conventional biexponential fitting. The perfusion fraction was elevated in high-grade (n = 33) compared to low-grade (n = 16) gliomas and was reduced in strokes compared to the contralateral brain (P < .001 for both main effects). Decreasing the number of b-values used for linear fitting resulted in reduced accuracy (higher root mean square error and lower R
) compared with full biexponential fitting.
Intravoxel incoherent motion perfusion imaging of common brain pathology can be performed by using simplified linear fitting, with preservation of clinically relevant perfusion information. |
doi_str_mv | 10.3174/ajnr.A4929 |
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Forty-nine patients with gliomas and 17 with acute strokes underwent 3T MRI, including DWI with 16 b-values (range, 0-900 s/mm
). Conventional intravoxel incoherent motion was performed using nonlinear fitting of the standard biexponential equation. Simplified intravoxel incoherent motion was performed using linear fitting of the log-normalized signal curves for subsets of b-values >200 s/mm
. Comparisons between ROIs (tumors, strokes, contralateral brain) and between models (biexponential and simplified linear) were performed by using 2-way ANOVA. The root mean square error and coefficient of determination (R
) were computed for the simplified model, with biexponential fitting as the reference standard.
Perfusion maps using simplified linear fitting were qualitatively similar to conventional biexponential fitting. The perfusion fraction was elevated in high-grade (n = 33) compared to low-grade (n = 16) gliomas and was reduced in strokes compared to the contralateral brain (P < .001 for both main effects). Decreasing the number of b-values used for linear fitting resulted in reduced accuracy (higher root mean square error and lower R
) compared with full biexponential fitting.
Intravoxel incoherent motion perfusion imaging of common brain pathology can be performed by using simplified linear fitting, with preservation of clinically relevant perfusion information.</description><identifier>ISSN: 0195-6108</identifier><identifier>EISSN: 1936-959X</identifier><identifier>DOI: 10.3174/ajnr.A4929</identifier><identifier>PMID: 27561834</identifier><language>eng</language><publisher>United States: American Society of Neuroradiology</publisher><subject>Adult Brain ; Brain - diagnostic imaging ; Brain - pathology ; Brain Neoplasms - blood supply ; Brain Neoplasms - diagnostic imaging ; Brain Neoplasms - pathology ; Diffusion Magnetic Resonance Imaging - methods ; Female ; Glioma - blood supply ; Glioma - diagnostic imaging ; Glioma - pathology ; Humans ; Image Interpretation, Computer-Assisted - methods ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Models, Theoretical ; Motion ; Perfusion Imaging - methods ; Reproducibility of Results ; Stroke - diagnostic imaging ; Stroke - pathology</subject><ispartof>American journal of neuroradiology : AJNR, 2016-12, Vol.37 (12), p.2251-2257</ispartof><rights>2016 by American Journal of Neuroradiology.</rights><rights>2016 by American Journal of Neuroradiology 2016 American Journal of Neuroradiology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c411t-1397685fb7112021e693d9a03a406323db7af4621fb9b64ab7b12ef1ee9199543</citedby><cites>FETCH-LOGICAL-c411t-1397685fb7112021e693d9a03a406323db7af4621fb9b64ab7b12ef1ee9199543</cites><orcidid>0000-0002-4126-9722 ; 0000-0002-3803-6602 ; 0000-0002-3226-5199 ; 0000-0001-5033-7507 ; 0000-0002-6726-3951 ; 0000-0001-9921-2086</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7963855/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7963855/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27561834$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Conklin, J</creatorcontrib><creatorcontrib>Heyn, C</creatorcontrib><creatorcontrib>Roux, M</creatorcontrib><creatorcontrib>Cerny, M</creatorcontrib><creatorcontrib>Wintermark, M</creatorcontrib><creatorcontrib>Federau, C</creatorcontrib><title>A Simplified Model for Intravoxel Incoherent Motion Perfusion Imaging of the Brain</title><title>American journal of neuroradiology : AJNR</title><addtitle>AJNR Am J Neuroradiol</addtitle><description>Despite a recent resurgence, intravoxel incoherent motion MRI faces practical challenges, including limited SNR and demanding acquisition and postprocessing requirements. A simplified approach using linear fitting of a subset of higher b-values has seen success in other organ systems. We sought to validate this method for evaluation of brain pathology by comparing perfusion measurements using simplified linear fitting to conventional biexponential fitting.
Forty-nine patients with gliomas and 17 with acute strokes underwent 3T MRI, including DWI with 16 b-values (range, 0-900 s/mm
). Conventional intravoxel incoherent motion was performed using nonlinear fitting of the standard biexponential equation. Simplified intravoxel incoherent motion was performed using linear fitting of the log-normalized signal curves for subsets of b-values >200 s/mm
. Comparisons between ROIs (tumors, strokes, contralateral brain) and between models (biexponential and simplified linear) were performed by using 2-way ANOVA. The root mean square error and coefficient of determination (R
) were computed for the simplified model, with biexponential fitting as the reference standard.
Perfusion maps using simplified linear fitting were qualitatively similar to conventional biexponential fitting. The perfusion fraction was elevated in high-grade (n = 33) compared to low-grade (n = 16) gliomas and was reduced in strokes compared to the contralateral brain (P < .001 for both main effects). Decreasing the number of b-values used for linear fitting resulted in reduced accuracy (higher root mean square error and lower R
) compared with full biexponential fitting.
Intravoxel incoherent motion perfusion imaging of common brain pathology can be performed by using simplified linear fitting, with preservation of clinically relevant perfusion information.</description><subject>Adult Brain</subject><subject>Brain - diagnostic imaging</subject><subject>Brain - pathology</subject><subject>Brain Neoplasms - blood supply</subject><subject>Brain Neoplasms - diagnostic imaging</subject><subject>Brain Neoplasms - pathology</subject><subject>Diffusion Magnetic Resonance Imaging - methods</subject><subject>Female</subject><subject>Glioma - blood supply</subject><subject>Glioma - diagnostic imaging</subject><subject>Glioma - pathology</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Magnetic Resonance Imaging</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Theoretical</subject><subject>Motion</subject><subject>Perfusion Imaging - methods</subject><subject>Reproducibility of Results</subject><subject>Stroke - diagnostic imaging</subject><subject>Stroke - pathology</subject><issn>0195-6108</issn><issn>1936-959X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkc1LHEEQxRtRdN148Q8Ic5TAmK7-mqlLYCOaLBiUfEBuTc9M927LTPfaPSvxv3c2GkluOVUV7_F4xY-QU6DnHCrx3tyFdL4QyHCPzAC5KlHiz30yo4CyVEDrI3Kc8x2lVGLFDskRq6SCmosZ-boovvlh03vnbVd8iZ3tCxdTsQxjMg_x13QuQxvXNtkwTvroYyhubXLbvNuWg1n5sCqiK8a1LT4m48MbcuBMn-3Jy5yTH1eX3y8-l9c3n5YXi-uyFQBjCRwrVUvXVACMMrAKeYeGciOo4ox3TWWcUAxcg40SpqkaYNaBtQiIUvA5-fCcu9k2g-1au6vc603yg0mPOhqv_1WCX-tVfNAVKl5LOQWcvQSkeL-1edSDz63texNs3GYNtURR85rV_2NlSgqcms_Ju2drm2LOybrXRkD1jpfe8dK_eU3mt3__8Gr9A4g_AbGekS4</recordid><startdate>201612</startdate><enddate>201612</enddate><creator>Conklin, J</creator><creator>Heyn, C</creator><creator>Roux, M</creator><creator>Cerny, M</creator><creator>Wintermark, M</creator><creator>Federau, C</creator><general>American Society of Neuroradiology</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>7X8</scope><scope>7TK</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-4126-9722</orcidid><orcidid>https://orcid.org/0000-0002-3803-6602</orcidid><orcidid>https://orcid.org/0000-0002-3226-5199</orcidid><orcidid>https://orcid.org/0000-0001-5033-7507</orcidid><orcidid>https://orcid.org/0000-0002-6726-3951</orcidid><orcidid>https://orcid.org/0000-0001-9921-2086</orcidid></search><sort><creationdate>201612</creationdate><title>A Simplified Model for Intravoxel Incoherent Motion Perfusion Imaging of the Brain</title><author>Conklin, J ; Heyn, C ; Roux, M ; Cerny, M ; Wintermark, M ; Federau, C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c411t-1397685fb7112021e693d9a03a406323db7af4621fb9b64ab7b12ef1ee9199543</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adult Brain</topic><topic>Brain - diagnostic imaging</topic><topic>Brain - pathology</topic><topic>Brain Neoplasms - blood supply</topic><topic>Brain Neoplasms - diagnostic imaging</topic><topic>Brain Neoplasms - pathology</topic><topic>Diffusion Magnetic Resonance Imaging - methods</topic><topic>Female</topic><topic>Glioma - blood supply</topic><topic>Glioma - diagnostic imaging</topic><topic>Glioma - pathology</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Magnetic Resonance Imaging</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Models, Theoretical</topic><topic>Motion</topic><topic>Perfusion Imaging - methods</topic><topic>Reproducibility of Results</topic><topic>Stroke - diagnostic imaging</topic><topic>Stroke - pathology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Conklin, J</creatorcontrib><creatorcontrib>Heyn, C</creatorcontrib><creatorcontrib>Roux, M</creatorcontrib><creatorcontrib>Cerny, M</creatorcontrib><creatorcontrib>Wintermark, M</creatorcontrib><creatorcontrib>Federau, C</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Neurosciences Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>American journal of neuroradiology : AJNR</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Conklin, J</au><au>Heyn, C</au><au>Roux, M</au><au>Cerny, M</au><au>Wintermark, M</au><au>Federau, C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Simplified Model for Intravoxel Incoherent Motion Perfusion Imaging of the Brain</atitle><jtitle>American journal of neuroradiology : AJNR</jtitle><addtitle>AJNR Am J Neuroradiol</addtitle><date>2016-12</date><risdate>2016</risdate><volume>37</volume><issue>12</issue><spage>2251</spage><epage>2257</epage><pages>2251-2257</pages><issn>0195-6108</issn><eissn>1936-959X</eissn><abstract>Despite a recent resurgence, intravoxel incoherent motion MRI faces practical challenges, including limited SNR and demanding acquisition and postprocessing requirements. A simplified approach using linear fitting of a subset of higher b-values has seen success in other organ systems. We sought to validate this method for evaluation of brain pathology by comparing perfusion measurements using simplified linear fitting to conventional biexponential fitting.
Forty-nine patients with gliomas and 17 with acute strokes underwent 3T MRI, including DWI with 16 b-values (range, 0-900 s/mm
). Conventional intravoxel incoherent motion was performed using nonlinear fitting of the standard biexponential equation. Simplified intravoxel incoherent motion was performed using linear fitting of the log-normalized signal curves for subsets of b-values >200 s/mm
. Comparisons between ROIs (tumors, strokes, contralateral brain) and between models (biexponential and simplified linear) were performed by using 2-way ANOVA. The root mean square error and coefficient of determination (R
) were computed for the simplified model, with biexponential fitting as the reference standard.
Perfusion maps using simplified linear fitting were qualitatively similar to conventional biexponential fitting. The perfusion fraction was elevated in high-grade (n = 33) compared to low-grade (n = 16) gliomas and was reduced in strokes compared to the contralateral brain (P < .001 for both main effects). Decreasing the number of b-values used for linear fitting resulted in reduced accuracy (higher root mean square error and lower R
) compared with full biexponential fitting.
Intravoxel incoherent motion perfusion imaging of common brain pathology can be performed by using simplified linear fitting, with preservation of clinically relevant perfusion information.</abstract><cop>United States</cop><pub>American Society of Neuroradiology</pub><pmid>27561834</pmid><doi>10.3174/ajnr.A4929</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-4126-9722</orcidid><orcidid>https://orcid.org/0000-0002-3803-6602</orcidid><orcidid>https://orcid.org/0000-0002-3226-5199</orcidid><orcidid>https://orcid.org/0000-0001-5033-7507</orcidid><orcidid>https://orcid.org/0000-0002-6726-3951</orcidid><orcidid>https://orcid.org/0000-0001-9921-2086</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Brain Brain - diagnostic imaging Brain - pathology Brain Neoplasms - blood supply Brain Neoplasms - diagnostic imaging Brain Neoplasms - pathology Diffusion Magnetic Resonance Imaging - methods Female Glioma - blood supply Glioma - diagnostic imaging Glioma - pathology Humans Image Interpretation, Computer-Assisted - methods Magnetic Resonance Imaging Male Middle Aged Models, Theoretical Motion Perfusion Imaging - methods Reproducibility of Results Stroke - diagnostic imaging Stroke - pathology |
title | A Simplified Model for Intravoxel Incoherent Motion Perfusion Imaging of the Brain |
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