Estimation of tissue perfusion by dynamic contrast-enhanced imaging: simulation-based evaluation of the steepest slope method
Objective Tissue perfusion is frequently determined from dynamic contrast-enhanced CT or MRI image series by means of the steepest slope method. It was thus the aim of this study to systematically evaluate the reliability of this analysis method on the basis of simulated tissue curves. Methods 9600...
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Veröffentlicht in: | European radiology 2010-09, Vol.20 (9), p.2166-2175 |
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creator | Brix, Gunnar Zwick, Stefan Griebel, Jürgen Fink, Christian Kiessling, Fabian |
description | Objective
Tissue perfusion is frequently determined from dynamic contrast-enhanced CT or MRI image series by means of the steepest slope method. It was thus the aim of this study to systematically evaluate the reliability of this analysis method on the basis of simulated tissue curves.
Methods
9600 tissue curves were simulated for four noise levels, three sampling intervals and a wide range of physiological parameters using an axially distributed reference model and subsequently analysed by the steepest slope method.
Results
Perfusion is systematically underestimated with errors becoming larger with increasing perfusion and decreasing intravascular volume. For curves sampled after rapid contrast injection with a temporal resolution of 0.72 s, the bias was less than 23% when the mean residence time of tracer molecules in the intravascular distribution space was greater than 6 s. Increasing the sampling interval and the noise level substantially reduces the accuracy and precision of estimates, respectively.
Conclusions
The steepest slope method allows absolute quantification of tissue perfusion in a computationally simple and numerically robust manner. The achievable degree of accuracy and precision is considered to be adequate for most clinical applications. |
doi_str_mv | 10.1007/s00330-010-1787-6 |
format | Article |
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Tissue perfusion is frequently determined from dynamic contrast-enhanced CT or MRI image series by means of the steepest slope method. It was thus the aim of this study to systematically evaluate the reliability of this analysis method on the basis of simulated tissue curves.
Methods
9600 tissue curves were simulated for four noise levels, three sampling intervals and a wide range of physiological parameters using an axially distributed reference model and subsequently analysed by the steepest slope method.
Results
Perfusion is systematically underestimated with errors becoming larger with increasing perfusion and decreasing intravascular volume. For curves sampled after rapid contrast injection with a temporal resolution of 0.72 s, the bias was less than 23% when the mean residence time of tracer molecules in the intravascular distribution space was greater than 6 s. Increasing the sampling interval and the noise level substantially reduces the accuracy and precision of estimates, respectively.
Conclusions
The steepest slope method allows absolute quantification of tissue perfusion in a computationally simple and numerically robust manner. The achievable degree of accuracy and precision is considered to be adequate for most clinical applications.</description><identifier>ISSN: 0938-7994</identifier><identifier>EISSN: 1432-1084</identifier><identifier>DOI: 10.1007/s00330-010-1787-6</identifier><identifier>PMID: 20407900</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Algorithms ; Computer Simulation ; Contrast Media - pharmacokinetics ; Diagnostic Radiology ; Diffusion Magnetic Resonance Imaging - methods ; Experimental ; Humans ; Image Interpretation, Computer-Assisted - methods ; Imaging ; Internal Medicine ; Interventional Radiology ; Inverse problems ; Magnetic Resonance Angiography - methods ; Magnetic resonance imaging ; Medicine ; Medicine & Public Health ; Models, Biological ; Neuroradiology ; Nuclear medicine ; Physiology ; Plasma ; Radiation ; Radiology ; Reproducibility of Results ; Sensitivity and Specificity ; Ultrasound</subject><ispartof>European radiology, 2010-09, Vol.20 (9), p.2166-2175</ispartof><rights>European Society of Radiology 2010</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c370t-fd62c482145764635c3ccb77686fc98525a36284661bddfb4a6e637df3f115aa3</citedby><cites>FETCH-LOGICAL-c370t-fd62c482145764635c3ccb77686fc98525a36284661bddfb4a6e637df3f115aa3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00330-010-1787-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00330-010-1787-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20407900$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Brix, Gunnar</creatorcontrib><creatorcontrib>Zwick, Stefan</creatorcontrib><creatorcontrib>Griebel, Jürgen</creatorcontrib><creatorcontrib>Fink, Christian</creatorcontrib><creatorcontrib>Kiessling, Fabian</creatorcontrib><title>Estimation of tissue perfusion by dynamic contrast-enhanced imaging: simulation-based evaluation of the steepest slope method</title><title>European radiology</title><addtitle>Eur Radiol</addtitle><addtitle>Eur Radiol</addtitle><description>Objective
Tissue perfusion is frequently determined from dynamic contrast-enhanced CT or MRI image series by means of the steepest slope method. It was thus the aim of this study to systematically evaluate the reliability of this analysis method on the basis of simulated tissue curves.
Methods
9600 tissue curves were simulated for four noise levels, three sampling intervals and a wide range of physiological parameters using an axially distributed reference model and subsequently analysed by the steepest slope method.
Results
Perfusion is systematically underestimated with errors becoming larger with increasing perfusion and decreasing intravascular volume. For curves sampled after rapid contrast injection with a temporal resolution of 0.72 s, the bias was less than 23% when the mean residence time of tracer molecules in the intravascular distribution space was greater than 6 s. Increasing the sampling interval and the noise level substantially reduces the accuracy and precision of estimates, respectively.
Conclusions
The steepest slope method allows absolute quantification of tissue perfusion in a computationally simple and numerically robust manner. The achievable degree of accuracy and precision is considered to be adequate for most clinical applications.</description><subject>Algorithms</subject><subject>Computer Simulation</subject><subject>Contrast Media - pharmacokinetics</subject><subject>Diagnostic Radiology</subject><subject>Diffusion Magnetic Resonance Imaging - methods</subject><subject>Experimental</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Imaging</subject><subject>Internal Medicine</subject><subject>Interventional Radiology</subject><subject>Inverse problems</subject><subject>Magnetic Resonance Angiography - methods</subject><subject>Magnetic resonance imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Models, Biological</subject><subject>Neuroradiology</subject><subject>Nuclear medicine</subject><subject>Physiology</subject><subject>Plasma</subject><subject>Radiation</subject><subject>Radiology</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Ultrasound</subject><issn>0938-7994</issn><issn>1432-1084</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp1kE1v3CAQhlHVqLtJ-gN6qVDvJIPBgHuronxJkXJJzhbGsOto_VEGV9pD_nvYOu2eckLDvO8zMy8h3zhccAB9iQBCAAMOjGujmfpE1lyKgnEw8jNZQyUM01UlV-QU8QUAKi71F7IqQIKuANbk9RpT19vUjQMdA00d4uzp5GOY8fDX7Gm7H2zfOerGIUWLiflhawfnW5qNm27Y_KTY9fPuL4Q1FnPH_7G7-UjdeorJ-8ljorgbJ097n7Zje05Ogt2h__r-npHnm-unqzv28Hh7f_XrgTmhIbHQqsJJU3BZaiWVKJ1wrtFaGRVcZcqitEIVRirFm7YNjbTKK6HbIALnpbXijPxYuFMcf895i_plnOOQR9ZaCmNACp5FfBG5OCJGH-op5gvjvuZQH_Kul7xrONQ571plz_d38Nz0vv3v-BdwFhSLAHNr2Ph4nPwx9Q0K3Iz_</recordid><startdate>20100901</startdate><enddate>20100901</enddate><creator>Brix, Gunnar</creator><creator>Zwick, Stefan</creator><creator>Griebel, Jürgen</creator><creator>Fink, Christian</creator><creator>Kiessling, Fabian</creator><general>Springer-Verlag</general><general>Springer Nature B.V</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>3V.</scope><scope>7QO</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20100901</creationdate><title>Estimation of tissue perfusion by dynamic contrast-enhanced imaging: simulation-based evaluation of the steepest slope method</title><author>Brix, Gunnar ; Zwick, Stefan ; Griebel, Jürgen ; Fink, Christian ; Kiessling, Fabian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-fd62c482145764635c3ccb77686fc98525a36284661bddfb4a6e637df3f115aa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Algorithms</topic><topic>Computer Simulation</topic><topic>Contrast Media - pharmacokinetics</topic><topic>Diagnostic Radiology</topic><topic>Diffusion Magnetic Resonance Imaging - methods</topic><topic>Experimental</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Imaging</topic><topic>Internal Medicine</topic><topic>Interventional Radiology</topic><topic>Inverse problems</topic><topic>Magnetic Resonance Angiography - methods</topic><topic>Magnetic resonance imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Models, Biological</topic><topic>Neuroradiology</topic><topic>Nuclear medicine</topic><topic>Physiology</topic><topic>Plasma</topic><topic>Radiation</topic><topic>Radiology</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Ultrasound</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Brix, Gunnar</creatorcontrib><creatorcontrib>Zwick, Stefan</creatorcontrib><creatorcontrib>Griebel, Jürgen</creatorcontrib><creatorcontrib>Fink, Christian</creatorcontrib><creatorcontrib>Kiessling, Fabian</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - 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Tissue perfusion is frequently determined from dynamic contrast-enhanced CT or MRI image series by means of the steepest slope method. It was thus the aim of this study to systematically evaluate the reliability of this analysis method on the basis of simulated tissue curves.
Methods
9600 tissue curves were simulated for four noise levels, three sampling intervals and a wide range of physiological parameters using an axially distributed reference model and subsequently analysed by the steepest slope method.
Results
Perfusion is systematically underestimated with errors becoming larger with increasing perfusion and decreasing intravascular volume. For curves sampled after rapid contrast injection with a temporal resolution of 0.72 s, the bias was less than 23% when the mean residence time of tracer molecules in the intravascular distribution space was greater than 6 s. Increasing the sampling interval and the noise level substantially reduces the accuracy and precision of estimates, respectively.
Conclusions
The steepest slope method allows absolute quantification of tissue perfusion in a computationally simple and numerically robust manner. The achievable degree of accuracy and precision is considered to be adequate for most clinical applications.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><pmid>20407900</pmid><doi>10.1007/s00330-010-1787-6</doi><tpages>10</tpages></addata></record> |
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subjects | Algorithms Computer Simulation Contrast Media - pharmacokinetics Diagnostic Radiology Diffusion Magnetic Resonance Imaging - methods Experimental Humans Image Interpretation, Computer-Assisted - methods Imaging Internal Medicine Interventional Radiology Inverse problems Magnetic Resonance Angiography - methods Magnetic resonance imaging Medicine Medicine & Public Health Models, Biological Neuroradiology Nuclear medicine Physiology Plasma Radiation Radiology Reproducibility of Results Sensitivity and Specificity Ultrasound |
title | Estimation of tissue perfusion by dynamic contrast-enhanced imaging: simulation-based evaluation of the steepest slope method |
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