Searching for alternatives to full kinetic analysis in 18F-FDG PET: an extension of the simplified kinetic analysis method

The most accurate way to estimate the glucose metabolic rate (or its influx constant) from (18)F-FDG PET is to perform a full kinetic analysis (or its simplified Patlak version), requiring dynamic imaging and the knowledge of arterial activity as a function of time. To avoid invasive arterial blood...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Journal of nuclear medicine (1978) 2011-04, Vol.52 (4), p.634-641
Hauptverfasser: Hapdey, Sebastien, Buvat, Irene, Carson, Joann M, Carson, Joan M, Carrasquillo, Jorge A, Whatley, Millie, Bacharach, Stephen L
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 641
container_issue 4
container_start_page 634
container_title The Journal of nuclear medicine (1978)
container_volume 52
creator Hapdey, Sebastien
Buvat, Irene
Carson, Joann M
Carson, Joan M
Carrasquillo, Jorge A
Whatley, Millie
Bacharach, Stephen L
description The most accurate way to estimate the glucose metabolic rate (or its influx constant) from (18)F-FDG PET is to perform a full kinetic analysis (or its simplified Patlak version), requiring dynamic imaging and the knowledge of arterial activity as a function of time. To avoid invasive arterial blood sampling, a simplified kinetic analysis (SKA) has been proposed, based on blood curves measured from a control group. Here, we extend the SKA by allowing for a greater variety of arterial input function (A(t)) curves among patients than in the original SKA and by accounting for unmetabolized (18)F-FDG in the tumor. Ten A(t)s measured in patients were analyzed using a principal-component analysis to derive 2 principal components describing most of the variability of the A(t). The mean distribution volume of (18)F-FDG in tumors for these patients was used to estimate the corresponding quantity in other patients. In subsequent patient studies, the A(t) was described as a linear combination of the 2 principal components, for which the 2 scaling factors were obtained from an early and a late venous sample drawn for the patient. The original and extended SKA (ESKA) were assessed using fifty-seven (18)F-FDG PET scans with various tumor types and locations and using different injection and acquisition protocols, with the K(i) derived from Patlak analysis as a reference. ESKA improved the accuracy or precision of the input function (area under the blood curve) for all protocols examined. The mean errors (±SD) in K(i) estimates were -12% ± 33% for SKA and -7% ± 22% for ESKA for a 20-s injection protocol with a 55-min postinjection PET scan, 20% ± 42% for SKA and 1% ± 29% for ESKA (P < 0.05) for a 120-s injection protocol with a 55-min postinjection PET scan, and -37% ± 19% for SKA and -4% ± 6% for ESKA (P < 0.05) for a 20-s injection protocol with a 120-min postinjection PET scan. Changes in K(i) between the 2 PET scans in the same patients also tended to be estimated more accurately and more precisely with ESKA than with SKA. ESKA, compared with SKA, significantly improved the accuracy and precision of K(i) estimates in (18)F-FDG PET. ESKA is more robust than SKA with respect to various injection and acquisition protocols.
doi_str_mv 10.2967/jnumed.110.079079
format Article
fullrecord <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_00653924v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>859059170</sourcerecordid><originalsourceid>FETCH-LOGICAL-h1649-e432b8d5e4167d9056b8541541e691f2f489c5934b2427362893c545e11265b13</originalsourceid><addsrcrecordid>eNqFkU1P3DAQhi1UxG63_IBeKt8qDgGPv2L3tgIWKq0EUuEcOcmk8dZxtnGCoL--QdBeOCC90mhmnhm9miHkM7BTbnV-totTh_UpzDnL7awDsgQlVKa0zj-QJQMNmVJMLcjHlHaMMW2MOSILDpJDDmZJ_vxAN1Stjz9p0w_UhRGH6Eb_gImOPW2mEOgvH3H0FXXRhafkE_WRgtlkm4srent5921uUHwcMSbfR9o3dGyRJt_tg2881m_nOxzbvv5EDhsXEh6_xhW531zenV9n25ur7-frbdaCljZDKXhpaoUSdF5bpnRplIRZqC00vJHGVsoKWXLJc6G5saJSUiEA16oEsSInL3tbF4r94Ds3PBW988X1els81-azKGG5fHhmv76w-6H_PWEai86nCkNwEfspFZZJmYOQ4l3SqNmqhZzN5JdXcirnd_238O8J4i8qjId1</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>859059170</pqid></control><display><type>article</type><title>Searching for alternatives to full kinetic analysis in 18F-FDG PET: an extension of the simplified kinetic analysis method</title><source>MEDLINE</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Hapdey, Sebastien ; Buvat, Irene ; Carson, Joann M ; Carson, Joan M ; Carrasquillo, Jorge A ; Whatley, Millie ; Bacharach, Stephen L</creator><creatorcontrib>Hapdey, Sebastien ; Buvat, Irene ; Carson, Joann M ; Carson, Joan M ; Carrasquillo, Jorge A ; Whatley, Millie ; Bacharach, Stephen L</creatorcontrib><description>The most accurate way to estimate the glucose metabolic rate (or its influx constant) from (18)F-FDG PET is to perform a full kinetic analysis (or its simplified Patlak version), requiring dynamic imaging and the knowledge of arterial activity as a function of time. To avoid invasive arterial blood sampling, a simplified kinetic analysis (SKA) has been proposed, based on blood curves measured from a control group. Here, we extend the SKA by allowing for a greater variety of arterial input function (A(t)) curves among patients than in the original SKA and by accounting for unmetabolized (18)F-FDG in the tumor. Ten A(t)s measured in patients were analyzed using a principal-component analysis to derive 2 principal components describing most of the variability of the A(t). The mean distribution volume of (18)F-FDG in tumors for these patients was used to estimate the corresponding quantity in other patients. In subsequent patient studies, the A(t) was described as a linear combination of the 2 principal components, for which the 2 scaling factors were obtained from an early and a late venous sample drawn for the patient. The original and extended SKA (ESKA) were assessed using fifty-seven (18)F-FDG PET scans with various tumor types and locations and using different injection and acquisition protocols, with the K(i) derived from Patlak analysis as a reference. ESKA improved the accuracy or precision of the input function (area under the blood curve) for all protocols examined. The mean errors (±SD) in K(i) estimates were -12% ± 33% for SKA and -7% ± 22% for ESKA for a 20-s injection protocol with a 55-min postinjection PET scan, 20% ± 42% for SKA and 1% ± 29% for ESKA (P &lt; 0.05) for a 120-s injection protocol with a 55-min postinjection PET scan, and -37% ± 19% for SKA and -4% ± 6% for ESKA (P &lt; 0.05) for a 20-s injection protocol with a 120-min postinjection PET scan. Changes in K(i) between the 2 PET scans in the same patients also tended to be estimated more accurately and more precisely with ESKA than with SKA. ESKA, compared with SKA, significantly improved the accuracy and precision of K(i) estimates in (18)F-FDG PET. ESKA is more robust than SKA with respect to various injection and acquisition protocols.</description><identifier>ISSN: 0161-5505</identifier><identifier>EISSN: 1535-5667</identifier><identifier>DOI: 10.2967/jnumed.110.079079</identifier><identifier>PMID: 21421718</identifier><language>eng</language><publisher>United States: Society of Nuclear Medicine</publisher><subject>Algorithms ; Area Under Curve ; Artificial Intelligence ; Carcinoma, Renal Cell - diagnostic imaging ; Fluorodeoxyglucose F18 - pharmacokinetics ; Humans ; Image Processing, Computer-Assisted ; Infusions, Intravenous ; Kidney Neoplasms - diagnostic imaging ; Kinetics ; Lymphatic Metastasis - diagnostic imaging ; Magnetic Resonance Imaging ; Models, Statistical ; Neoplasms - diagnostic imaging ; Neoplasms - metabolism ; Positron-Emission Tomography - methods ; Positron-Emission Tomography - statistics &amp; numerical data ; Radiopharmaceuticals - pharmacokinetics ; Reproducibility of Results ; Tomography, X-Ray Computed</subject><ispartof>The Journal of nuclear medicine (1978), 2011-04, Vol.52 (4), p.634-641</ispartof><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-7053-6471 ; 0000-0002-3967-434X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21421718$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-00653924$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Hapdey, Sebastien</creatorcontrib><creatorcontrib>Buvat, Irene</creatorcontrib><creatorcontrib>Carson, Joann M</creatorcontrib><creatorcontrib>Carson, Joan M</creatorcontrib><creatorcontrib>Carrasquillo, Jorge A</creatorcontrib><creatorcontrib>Whatley, Millie</creatorcontrib><creatorcontrib>Bacharach, Stephen L</creatorcontrib><title>Searching for alternatives to full kinetic analysis in 18F-FDG PET: an extension of the simplified kinetic analysis method</title><title>The Journal of nuclear medicine (1978)</title><addtitle>J Nucl Med</addtitle><description>The most accurate way to estimate the glucose metabolic rate (or its influx constant) from (18)F-FDG PET is to perform a full kinetic analysis (or its simplified Patlak version), requiring dynamic imaging and the knowledge of arterial activity as a function of time. To avoid invasive arterial blood sampling, a simplified kinetic analysis (SKA) has been proposed, based on blood curves measured from a control group. Here, we extend the SKA by allowing for a greater variety of arterial input function (A(t)) curves among patients than in the original SKA and by accounting for unmetabolized (18)F-FDG in the tumor. Ten A(t)s measured in patients were analyzed using a principal-component analysis to derive 2 principal components describing most of the variability of the A(t). The mean distribution volume of (18)F-FDG in tumors for these patients was used to estimate the corresponding quantity in other patients. In subsequent patient studies, the A(t) was described as a linear combination of the 2 principal components, for which the 2 scaling factors were obtained from an early and a late venous sample drawn for the patient. The original and extended SKA (ESKA) were assessed using fifty-seven (18)F-FDG PET scans with various tumor types and locations and using different injection and acquisition protocols, with the K(i) derived from Patlak analysis as a reference. ESKA improved the accuracy or precision of the input function (area under the blood curve) for all protocols examined. The mean errors (±SD) in K(i) estimates were -12% ± 33% for SKA and -7% ± 22% for ESKA for a 20-s injection protocol with a 55-min postinjection PET scan, 20% ± 42% for SKA and 1% ± 29% for ESKA (P &lt; 0.05) for a 120-s injection protocol with a 55-min postinjection PET scan, and -37% ± 19% for SKA and -4% ± 6% for ESKA (P &lt; 0.05) for a 20-s injection protocol with a 120-min postinjection PET scan. Changes in K(i) between the 2 PET scans in the same patients also tended to be estimated more accurately and more precisely with ESKA than with SKA. ESKA, compared with SKA, significantly improved the accuracy and precision of K(i) estimates in (18)F-FDG PET. ESKA is more robust than SKA with respect to various injection and acquisition protocols.</description><subject>Algorithms</subject><subject>Area Under Curve</subject><subject>Artificial Intelligence</subject><subject>Carcinoma, Renal Cell - diagnostic imaging</subject><subject>Fluorodeoxyglucose F18 - pharmacokinetics</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted</subject><subject>Infusions, Intravenous</subject><subject>Kidney Neoplasms - diagnostic imaging</subject><subject>Kinetics</subject><subject>Lymphatic Metastasis - diagnostic imaging</subject><subject>Magnetic Resonance Imaging</subject><subject>Models, Statistical</subject><subject>Neoplasms - diagnostic imaging</subject><subject>Neoplasms - metabolism</subject><subject>Positron-Emission Tomography - methods</subject><subject>Positron-Emission Tomography - statistics &amp; numerical data</subject><subject>Radiopharmaceuticals - pharmacokinetics</subject><subject>Reproducibility of Results</subject><subject>Tomography, X-Ray Computed</subject><issn>0161-5505</issn><issn>1535-5667</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkU1P3DAQhi1UxG63_IBeKt8qDgGPv2L3tgIWKq0EUuEcOcmk8dZxtnGCoL--QdBeOCC90mhmnhm9miHkM7BTbnV-totTh_UpzDnL7awDsgQlVKa0zj-QJQMNmVJMLcjHlHaMMW2MOSILDpJDDmZJ_vxAN1Stjz9p0w_UhRGH6Eb_gImOPW2mEOgvH3H0FXXRhafkE_WRgtlkm4srent5921uUHwcMSbfR9o3dGyRJt_tg2881m_nOxzbvv5EDhsXEh6_xhW531zenV9n25ur7-frbdaCljZDKXhpaoUSdF5bpnRplIRZqC00vJHGVsoKWXLJc6G5saJSUiEA16oEsSInL3tbF4r94Ds3PBW988X1els81-azKGG5fHhmv76w-6H_PWEai86nCkNwEfspFZZJmYOQ4l3SqNmqhZzN5JdXcirnd_238O8J4i8qjId1</recordid><startdate>201104</startdate><enddate>201104</enddate><creator>Hapdey, Sebastien</creator><creator>Buvat, Irene</creator><creator>Carson, Joann M</creator><creator>Carson, Joan M</creator><creator>Carrasquillo, Jorge A</creator><creator>Whatley, Millie</creator><creator>Bacharach, Stephen L</creator><general>Society of Nuclear Medicine</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0002-7053-6471</orcidid><orcidid>https://orcid.org/0000-0002-3967-434X</orcidid></search><sort><creationdate>201104</creationdate><title>Searching for alternatives to full kinetic analysis in 18F-FDG PET: an extension of the simplified kinetic analysis method</title><author>Hapdey, Sebastien ; Buvat, Irene ; Carson, Joann M ; Carson, Joan M ; Carrasquillo, Jorge A ; Whatley, Millie ; Bacharach, Stephen L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-h1649-e432b8d5e4167d9056b8541541e691f2f489c5934b2427362893c545e11265b13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithms</topic><topic>Area Under Curve</topic><topic>Artificial Intelligence</topic><topic>Carcinoma, Renal Cell - diagnostic imaging</topic><topic>Fluorodeoxyglucose F18 - pharmacokinetics</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted</topic><topic>Infusions, Intravenous</topic><topic>Kidney Neoplasms - diagnostic imaging</topic><topic>Kinetics</topic><topic>Lymphatic Metastasis - diagnostic imaging</topic><topic>Magnetic Resonance Imaging</topic><topic>Models, Statistical</topic><topic>Neoplasms - diagnostic imaging</topic><topic>Neoplasms - metabolism</topic><topic>Positron-Emission Tomography - methods</topic><topic>Positron-Emission Tomography - statistics &amp; numerical data</topic><topic>Radiopharmaceuticals - pharmacokinetics</topic><topic>Reproducibility of Results</topic><topic>Tomography, X-Ray Computed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hapdey, Sebastien</creatorcontrib><creatorcontrib>Buvat, Irene</creatorcontrib><creatorcontrib>Carson, Joann M</creatorcontrib><creatorcontrib>Carson, Joan M</creatorcontrib><creatorcontrib>Carrasquillo, Jorge A</creatorcontrib><creatorcontrib>Whatley, Millie</creatorcontrib><creatorcontrib>Bacharach, Stephen L</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>The Journal of nuclear medicine (1978)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hapdey, Sebastien</au><au>Buvat, Irene</au><au>Carson, Joann M</au><au>Carson, Joan M</au><au>Carrasquillo, Jorge A</au><au>Whatley, Millie</au><au>Bacharach, Stephen L</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Searching for alternatives to full kinetic analysis in 18F-FDG PET: an extension of the simplified kinetic analysis method</atitle><jtitle>The Journal of nuclear medicine (1978)</jtitle><addtitle>J Nucl Med</addtitle><date>2011-04</date><risdate>2011</risdate><volume>52</volume><issue>4</issue><spage>634</spage><epage>641</epage><pages>634-641</pages><issn>0161-5505</issn><eissn>1535-5667</eissn><abstract>The most accurate way to estimate the glucose metabolic rate (or its influx constant) from (18)F-FDG PET is to perform a full kinetic analysis (or its simplified Patlak version), requiring dynamic imaging and the knowledge of arterial activity as a function of time. To avoid invasive arterial blood sampling, a simplified kinetic analysis (SKA) has been proposed, based on blood curves measured from a control group. Here, we extend the SKA by allowing for a greater variety of arterial input function (A(t)) curves among patients than in the original SKA and by accounting for unmetabolized (18)F-FDG in the tumor. Ten A(t)s measured in patients were analyzed using a principal-component analysis to derive 2 principal components describing most of the variability of the A(t). The mean distribution volume of (18)F-FDG in tumors for these patients was used to estimate the corresponding quantity in other patients. In subsequent patient studies, the A(t) was described as a linear combination of the 2 principal components, for which the 2 scaling factors were obtained from an early and a late venous sample drawn for the patient. The original and extended SKA (ESKA) were assessed using fifty-seven (18)F-FDG PET scans with various tumor types and locations and using different injection and acquisition protocols, with the K(i) derived from Patlak analysis as a reference. ESKA improved the accuracy or precision of the input function (area under the blood curve) for all protocols examined. The mean errors (±SD) in K(i) estimates were -12% ± 33% for SKA and -7% ± 22% for ESKA for a 20-s injection protocol with a 55-min postinjection PET scan, 20% ± 42% for SKA and 1% ± 29% for ESKA (P &lt; 0.05) for a 120-s injection protocol with a 55-min postinjection PET scan, and -37% ± 19% for SKA and -4% ± 6% for ESKA (P &lt; 0.05) for a 20-s injection protocol with a 120-min postinjection PET scan. Changes in K(i) between the 2 PET scans in the same patients also tended to be estimated more accurately and more precisely with ESKA than with SKA. ESKA, compared with SKA, significantly improved the accuracy and precision of K(i) estimates in (18)F-FDG PET. ESKA is more robust than SKA with respect to various injection and acquisition protocols.</abstract><cop>United States</cop><pub>Society of Nuclear Medicine</pub><pmid>21421718</pmid><doi>10.2967/jnumed.110.079079</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-7053-6471</orcidid><orcidid>https://orcid.org/0000-0002-3967-434X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0161-5505
ispartof The Journal of nuclear medicine (1978), 2011-04, Vol.52 (4), p.634-641
issn 0161-5505
1535-5667
language eng
recordid cdi_hal_primary_oai_HAL_hal_00653924v1
source MEDLINE; EZB-FREE-00999 freely available EZB journals
subjects Algorithms
Area Under Curve
Artificial Intelligence
Carcinoma, Renal Cell - diagnostic imaging
Fluorodeoxyglucose F18 - pharmacokinetics
Humans
Image Processing, Computer-Assisted
Infusions, Intravenous
Kidney Neoplasms - diagnostic imaging
Kinetics
Lymphatic Metastasis - diagnostic imaging
Magnetic Resonance Imaging
Models, Statistical
Neoplasms - diagnostic imaging
Neoplasms - metabolism
Positron-Emission Tomography - methods
Positron-Emission Tomography - statistics & numerical data
Radiopharmaceuticals - pharmacokinetics
Reproducibility of Results
Tomography, X-Ray Computed
title Searching for alternatives to full kinetic analysis in 18F-FDG PET: an extension of the simplified kinetic analysis method
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T07%3A55%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Searching%20for%20alternatives%20to%20full%20kinetic%20analysis%20in%2018F-FDG%20PET:%20an%20extension%20of%20the%20simplified%20kinetic%20analysis%20method&rft.jtitle=The%20Journal%20of%20nuclear%20medicine%20(1978)&rft.au=Hapdey,%20Sebastien&rft.date=2011-04&rft.volume=52&rft.issue=4&rft.spage=634&rft.epage=641&rft.pages=634-641&rft.issn=0161-5505&rft.eissn=1535-5667&rft_id=info:doi/10.2967/jnumed.110.079079&rft_dat=%3Cproquest_hal_p%3E859059170%3C/proquest_hal_p%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=859059170&rft_id=info:pmid/21421718&rfr_iscdi=true