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EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program

Identifieur interne : 000356 ( Pmc/Checkpoint ); précédent : 000355; suivant : 000357

EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program

Auteurs : Charline Lasnon [France] ; Elske Quak [France] ; Pierre-Yves Le Roux [France] ; Philippe Robin [France] ; Michael S. Hofman [Australie] ; David Bourhis [France] ; Jason Callahan [Australie] ; David S. Binns [Australie] ; Cédric Desmonts [France] ; Pierre-Yves Salaun [France] ; Rodney J. Hicks [Australie] ; Nicolas Aide [France]

Source :

RBID : PMC:5449363

Abstract

Background

This study evaluates the consistency of PET evaluation response criteria in solid tumours (PERCIST) and European Organisation for Research and Treatment of Cancer (EORTC) classification across different reconstruction algorithms and whether aligning standardized uptake values (SUVs) to the European Association of Nuclear Medicine acquisition (EANM)/EARL standards provides more consistent response classification.

Materials and methods

Baseline (PET1) and response assessment (PET2) scans in 61 patients with non-small cell lung cancer were acquired in protocols compliant with the EANM guidelines and were reconstructed with point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction for optimal tumour detection and with a standardized ordered subset expectation maximization (OSEM) reconstruction known to fulfil EANM harmonizing standards. Patients were recruited in three centres. Following reconstruction, EQ.PET, a proprietary software solution was applied to the PSF ± TOF data (PSF ± TOF.EQ) to harmonize SUVs to the EANM standards. The impact of differing reconstructions on PERCIST and EORTC classification was evaluated using standardized uptake values corrected for lean body mass (SUL).

Results

Using OSEMPET1/OSEMPET2 (standard scenario), responders displayed a reduction of −57.5% ± 23.4 and −63.9% ± 22.4 for SULmax and SULpeak, respectively, while progressing tumours had an increase of +63.4% ± 26.5 and +60.7% ± 19.6 for SULmax and SULpeak respectively. The use of PSF ± TOF reconstruction impacted the classification of tumour response. For example, taking the OSEMPET1/PSF ± TOFPET2 scenario reduced the apparent reduction in SUL in responding tumours (−39.7% ± 31.3 and −55.5% ± 26.3 for SULmax and SULpeak, respectively) but increased the apparent increase in SUL in progressing tumours (+130.0% ± 50.7 and +91.1% ± 39.6 for SULmax and SULpeak, respectively).

Consequently, variation in reconstruction methodology (PSF ± TOFPET1/OSEMPET2 or OSEM PET1/PSF ± TOFPET2) led, respectively, to 11/61 (18.0%) and 10/61 (16.4%) PERCIST classification discordances and to 17/61 (28.9%) and 19/61 (31.1%) EORTC classification discordances. An agreement was better for these scenarios with application of the propriety filter, with kappa values of 1.00 and 0.95 compared to 0.75 and 0.77 for PERCIST and kappa values of 0.93 and 0.95 compared to 0.61 and 0.55 for EORTC, respectively.

Conclusion

PERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either.

Electronic supplementary material

The online version of this article (doi:10.1186/s40658-017-0185-4) contains supplementary material, which is available to authorized users.


Url:
DOI: 10.1186/s40658-017-0185-4
PubMed: 28560574
PubMed Central: 5449363


Affiliations:


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PMC:5449363

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Caen, France</nlm:aff>
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<wicri:regionArea>Caen</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1">
<nlm:aff id="Aff7">
<institution-wrap>
<institution-id institution-id-type="ISNI"> 0000 0004 1785 9671</institution-id>
<institution-id institution-id-type="GRID">grid.460771.3</institution-id>
<institution></institution>
<institution>Normandy University,</institution>
</institution-wrap>
Caen, France</nlm:aff>
<country xml:lang="fr">France</country>
<wicri:regionArea>Caen</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1">
<nlm:aff id="Aff8">
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0004 0472 0160</institution-id>
<institution-id institution-id-type="GRID">grid.411149.8</institution-id>
<institution>Nuclear Medicine Department,</institution>
<institution>Caen University Hospital,</institution>
</institution-wrap>
Avenue Côte de Nacre, 14000 Caen, France</nlm:aff>
<country xml:lang="fr">France</country>
<wicri:regionArea>Avenue Côte de Nacre, 14000 Caen</wicri:regionArea>
<wicri:noRegion>14000 Caen</wicri:noRegion>
<wicri:noRegion>14000 Caen</wicri:noRegion>
</affiliation>
</author>
</analytic>
<series>
<title level="j">EJNMMI Physics</title>
<idno type="eISSN">2197-7364</idno>
<imprint>
<date when="2017">2017</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc>
<textClass></textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">
<sec>
<title>Background</title>
<p>This study evaluates the consistency of PET evaluation response criteria in solid tumours (PERCIST) and European Organisation for Research and Treatment of Cancer (EORTC) classification across different reconstruction algorithms and whether aligning standardized uptake values (SUVs) to the European Association of Nuclear Medicine acquisition (EANM)/EARL standards provides more consistent response classification.</p>
</sec>
<sec>
<title>Materials and methods</title>
<p>Baseline (
<sub>PET1</sub>
) and response assessment (
<sub>PET2</sub>
) scans in 61 patients with non-small cell lung cancer were acquired in protocols compliant with the EANM guidelines and were reconstructed with point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction for optimal tumour detection and with a standardized ordered subset expectation maximization (OSEM) reconstruction known to fulfil EANM harmonizing standards. Patients were recruited in three centres. Following reconstruction, EQ.PET, a proprietary software solution was applied to the PSF ± TOF data (PSF ± TOF.EQ) to harmonize SUVs to the EANM standards. The impact of differing reconstructions on PERCIST and EORTC classification was evaluated using standardized uptake values corrected for lean body mass (SUL).</p>
</sec>
<sec>
<title>Results</title>
<p>Using OSEM
<sub>PET1</sub>
/OSEM
<sub>PET2</sub>
(standard scenario), responders displayed a reduction of −57.5% ± 23.4 and −63.9% ± 22.4 for SUL
<sub>max</sub>
and SUL
<sub>peak</sub>
, respectively, while progressing tumours had an increase of +63.4% ± 26.5 and +60.7% ± 19.6 for SUL
<sub>max</sub>
and SUL
<sub>peak</sub>
respectively. The use of PSF ± TOF reconstruction impacted the classification of tumour response. For example, taking the OSEM
<sub>PET1</sub>
/PSF ± TOF
<sub>PET2</sub>
scenario reduced the apparent reduction in SUL in responding tumours (−39.7% ± 31.3 and −55.5% ± 26.3 for SUL
<sub>max</sub>
and SUL
<sub>peak</sub>
, respectively) but increased the apparent increase in SUL in progressing tumours (+130.0% ± 50.7 and +91.1% ± 39.6 for SUL
<sub>max</sub>
and SUL
<sub>peak</sub>
, respectively).</p>
<p>Consequently, variation in reconstruction methodology (PSF ± TOF
<sub>PET1</sub>
/OSEM
<sub>PET2</sub>
or OSEM
<sub>PET1</sub>
/PSF ± TOF
<sub>PET2</sub>
) led, respectively, to 11/61 (18.0%) and 10/61 (16.4%) PERCIST classification discordances and to 17/61 (28.9%) and 19/61 (31.1%) EORTC classification discordances. An agreement was better for these scenarios with application of the propriety filter, with kappa values of 1.00 and 0.95 compared to 0.75 and 0.77 for PERCIST and kappa values of 0.93 and 0.95 compared to 0.61 and 0.55 for EORTC, respectively.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>PERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either.</p>
</sec>
<sec>
<title>Electronic supplementary material</title>
<p>The online version of this article (doi:10.1186/s40658-017-0185-4) contains supplementary material, which is available to authorized users.</p>
</sec>
</div>
</front>
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</div1>
</back>
</TEI>
<pmc article-type="research-article">
<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">EJNMMI Phys</journal-id>
<journal-id journal-id-type="iso-abbrev">EJNMMI Phys</journal-id>
<journal-title-group>
<journal-title>EJNMMI Physics</journal-title>
</journal-title-group>
<issn pub-type="epub">2197-7364</issn>
<publisher>
<publisher-name>Springer International Publishing</publisher-name>
<publisher-loc>Cham</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">28560574</article-id>
<article-id pub-id-type="pmc">5449363</article-id>
<article-id pub-id-type="publisher-id">185</article-id>
<article-id pub-id-type="doi">10.1186/s40658-017-0185-4</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>EORTC PET response criteria are more influenced by reconstruction inconsistencies than PERCIST but both benefit from the EARL harmonization program</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Lasnon</surname>
<given-names>Charline</given-names>
</name>
<xref ref-type="aff" rid="Aff1">1</xref>
<xref ref-type="aff" rid="Aff2">2</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Quak</surname>
<given-names>Elske</given-names>
</name>
<xref ref-type="aff" rid="Aff1">1</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Le Roux</surname>
<given-names>Pierre-Yves</given-names>
</name>
<xref ref-type="aff" rid="Aff3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Robin</surname>
<given-names>Philippe</given-names>
</name>
<xref ref-type="aff" rid="Aff3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hofman</surname>
<given-names>Michael S.</given-names>
</name>
<xref ref-type="aff" rid="Aff4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bourhis</surname>
<given-names>David</given-names>
</name>
<xref ref-type="aff" rid="Aff3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Callahan</surname>
<given-names>Jason</given-names>
</name>
<xref ref-type="aff" rid="Aff4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Binns</surname>
<given-names>David S.</given-names>
</name>
<xref ref-type="aff" rid="Aff4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Desmonts</surname>
<given-names>Cédric</given-names>
</name>
<xref ref-type="aff" rid="Aff5">5</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Salaun</surname>
<given-names>Pierre-Yves</given-names>
</name>
<xref ref-type="aff" rid="Aff3">3</xref>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Hicks</surname>
<given-names>Rodney J.</given-names>
</name>
<xref ref-type="aff" rid="Aff4">4</xref>
<xref ref-type="aff" rid="Aff6">6</xref>
</contrib>
<contrib contrib-type="author" corresp="yes" equal-contrib="yes">
<contrib-id contrib-id-type="orcid">http://orcid.org/0000-0001-9207-0847</contrib-id>
<name>
<surname>Aide</surname>
<given-names>Nicolas</given-names>
</name>
<address>
<phone>+33 231065229</phone>
<email>aide-n@chu-caen.fr</email>
</address>
<xref ref-type="aff" rid="Aff2">2</xref>
<xref ref-type="aff" rid="Aff5">5</xref>
<xref ref-type="aff" rid="Aff7">7</xref>
<xref ref-type="aff" rid="Aff8">8</xref>
</contrib>
<aff id="Aff1">
<label>1</label>
Nuclear Medicine Department, François Baclesse Cancer Centre, Caen, France</aff>
<aff id="Aff2">
<label>2</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0001 2186 4076</institution-id>
<institution-id institution-id-type="GRID">grid.412043.0</institution-id>
<institution>INSERM U1086 ANTICIPE, BioTICLA,</institution>
<institution>Caen University,</institution>
</institution-wrap>
Caen, France</aff>
<aff id="Aff3">
<label>3</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0004 0472 3249</institution-id>
<institution-id institution-id-type="GRID">grid.411766.3</institution-id>
<institution>Nuclear Medicine Department and EA 3878 IFR 148,</institution>
<institution>University Hospital,</institution>
</institution-wrap>
Brest, France</aff>
<aff id="Aff4">
<label>4</label>
Cancer Imaging, Peter Mac Callum Cancer Institute, Parkville, Australia</aff>
<aff id="Aff5">
<label>5</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0004 0472 0160</institution-id>
<institution-id institution-id-type="GRID">grid.411149.8</institution-id>
<institution>Nuclear Medicine Department,</institution>
<institution>University Hospital,</institution>
</institution-wrap>
Caen, France</aff>
<aff id="Aff6">
<label>6</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0001 2179 088X</institution-id>
<institution-id institution-id-type="GRID">grid.1008.9</institution-id>
<institution>The Sir Peter MacCallum Department of Oncology,</institution>
<institution>the University of Melbourne,</institution>
</institution-wrap>
Melbourne, Australia</aff>
<aff id="Aff7">
<label>7</label>
<institution-wrap>
<institution-id institution-id-type="ISNI"> 0000 0004 1785 9671</institution-id>
<institution-id institution-id-type="GRID">grid.460771.3</institution-id>
<institution></institution>
<institution>Normandy University,</institution>
</institution-wrap>
Caen, France</aff>
<aff id="Aff8">
<label>8</label>
<institution-wrap>
<institution-id institution-id-type="ISNI">0000 0004 0472 0160</institution-id>
<institution-id institution-id-type="GRID">grid.411149.8</institution-id>
<institution>Nuclear Medicine Department,</institution>
<institution>Caen University Hospital,</institution>
</institution-wrap>
Avenue Côte de Nacre, 14000 Caen, France</aff>
</contrib-group>
<pub-date pub-type="epub">
<day>30</day>
<month>5</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="pmc-release">
<day>30</day>
<month>5</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="collection">
<month>12</month>
<year>2017</year>
</pub-date>
<volume>4</volume>
<elocation-id>17</elocation-id>
<history>
<date date-type="received">
<day>7</day>
<month>4</month>
<year>2017</year>
</date>
<date date-type="accepted">
<day>19</day>
<month>5</month>
<year>2017</year>
</date>
</history>
<permissions>
<copyright-statement>© The Author(s). 2017</copyright-statement>
<license license-type="OpenAccess">
<license-p>
<bold>Open Access</bold>
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>
), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.</license-p>
</license>
</permissions>
<abstract id="Abs1">
<sec>
<title>Background</title>
<p>This study evaluates the consistency of PET evaluation response criteria in solid tumours (PERCIST) and European Organisation for Research and Treatment of Cancer (EORTC) classification across different reconstruction algorithms and whether aligning standardized uptake values (SUVs) to the European Association of Nuclear Medicine acquisition (EANM)/EARL standards provides more consistent response classification.</p>
</sec>
<sec>
<title>Materials and methods</title>
<p>Baseline (
<sub>PET1</sub>
) and response assessment (
<sub>PET2</sub>
) scans in 61 patients with non-small cell lung cancer were acquired in protocols compliant with the EANM guidelines and were reconstructed with point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction for optimal tumour detection and with a standardized ordered subset expectation maximization (OSEM) reconstruction known to fulfil EANM harmonizing standards. Patients were recruited in three centres. Following reconstruction, EQ.PET, a proprietary software solution was applied to the PSF ± TOF data (PSF ± TOF.EQ) to harmonize SUVs to the EANM standards. The impact of differing reconstructions on PERCIST and EORTC classification was evaluated using standardized uptake values corrected for lean body mass (SUL).</p>
</sec>
<sec>
<title>Results</title>
<p>Using OSEM
<sub>PET1</sub>
/OSEM
<sub>PET2</sub>
(standard scenario), responders displayed a reduction of −57.5% ± 23.4 and −63.9% ± 22.4 for SUL
<sub>max</sub>
and SUL
<sub>peak</sub>
, respectively, while progressing tumours had an increase of +63.4% ± 26.5 and +60.7% ± 19.6 for SUL
<sub>max</sub>
and SUL
<sub>peak</sub>
respectively. The use of PSF ± TOF reconstruction impacted the classification of tumour response. For example, taking the OSEM
<sub>PET1</sub>
/PSF ± TOF
<sub>PET2</sub>
scenario reduced the apparent reduction in SUL in responding tumours (−39.7% ± 31.3 and −55.5% ± 26.3 for SUL
<sub>max</sub>
and SUL
<sub>peak</sub>
, respectively) but increased the apparent increase in SUL in progressing tumours (+130.0% ± 50.7 and +91.1% ± 39.6 for SUL
<sub>max</sub>
and SUL
<sub>peak</sub>
, respectively).</p>
<p>Consequently, variation in reconstruction methodology (PSF ± TOF
<sub>PET1</sub>
/OSEM
<sub>PET2</sub>
or OSEM
<sub>PET1</sub>
/PSF ± TOF
<sub>PET2</sub>
) led, respectively, to 11/61 (18.0%) and 10/61 (16.4%) PERCIST classification discordances and to 17/61 (28.9%) and 19/61 (31.1%) EORTC classification discordances. An agreement was better for these scenarios with application of the propriety filter, with kappa values of 1.00 and 0.95 compared to 0.75 and 0.77 for PERCIST and kappa values of 0.93 and 0.95 compared to 0.61 and 0.55 for EORTC, respectively.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>PERCIST classification is less sensitive to reconstruction algorithm-dependent variability than EORTC classification but harmonizing SULs within the EARL program is equally effective with either.</p>
</sec>
<sec>
<title>Electronic supplementary material</title>
<p>The online version of this article (doi:10.1186/s40658-017-0185-4) contains supplementary material, which is available to authorized users.</p>
</sec>
</abstract>
<kwd-group xml:lang="en">
<title>Keywords</title>
<kwd>PET</kwd>
<kwd>
<sup>18</sup>
F-FDG</kwd>
<kwd>Therapy response</kwd>
<kwd>PERCIST</kwd>
<kwd>EORTC</kwd>
<kwd>Harmonization</kwd>
</kwd-group>
<custom-meta-group>
<custom-meta>
<meta-name>issue-copyright-statement</meta-name>
<meta-value>© The Author(s) 2017</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
</pmc>
<affiliations>
<list>
<country>
<li>Australie</li>
<li>France</li>
</country>
<region>
<li>Basse-Normandie</li>
<li>Région Normandie</li>
</region>
<settlement>
<li>Caen</li>
</settlement>
</list>
<tree>
<country name="France">
<region name="Région Normandie">
<name sortKey="Lasnon, Charline" sort="Lasnon, Charline" uniqKey="Lasnon C" first="Charline" last="Lasnon">Charline Lasnon</name>
</region>
<name sortKey="Aide, Nicolas" sort="Aide, Nicolas" uniqKey="Aide N" first="Nicolas" last="Aide">Nicolas Aide</name>
<name sortKey="Aide, Nicolas" sort="Aide, Nicolas" uniqKey="Aide N" first="Nicolas" last="Aide">Nicolas Aide</name>
<name sortKey="Aide, Nicolas" sort="Aide, Nicolas" uniqKey="Aide N" first="Nicolas" last="Aide">Nicolas Aide</name>
<name sortKey="Aide, Nicolas" sort="Aide, Nicolas" uniqKey="Aide N" first="Nicolas" last="Aide">Nicolas Aide</name>
<name sortKey="Bourhis, David" sort="Bourhis, David" uniqKey="Bourhis D" first="David" last="Bourhis">David Bourhis</name>
<name sortKey="Desmonts, Cedric" sort="Desmonts, Cedric" uniqKey="Desmonts C" first="Cédric" last="Desmonts">Cédric Desmonts</name>
<name sortKey="Lasnon, Charline" sort="Lasnon, Charline" uniqKey="Lasnon C" first="Charline" last="Lasnon">Charline Lasnon</name>
<name sortKey="Le Roux, Pierre Yves" sort="Le Roux, Pierre Yves" uniqKey="Le Roux P" first="Pierre-Yves" last="Le Roux">Pierre-Yves Le Roux</name>
<name sortKey="Quak, Elske" sort="Quak, Elske" uniqKey="Quak E" first="Elske" last="Quak">Elske Quak</name>
<name sortKey="Robin, Philippe" sort="Robin, Philippe" uniqKey="Robin P" first="Philippe" last="Robin">Philippe Robin</name>
<name sortKey="Salaun, Pierre Yves" sort="Salaun, Pierre Yves" uniqKey="Salaun P" first="Pierre-Yves" last="Salaun">Pierre-Yves Salaun</name>
</country>
<country name="Australie">
<noRegion>
<name sortKey="Hofman, Michael S" sort="Hofman, Michael S" uniqKey="Hofman M" first="Michael S." last="Hofman">Michael S. Hofman</name>
</noRegion>
<name sortKey="Binns, David S" sort="Binns, David S" uniqKey="Binns D" first="David S." last="Binns">David S. Binns</name>
<name sortKey="Callahan, Jason" sort="Callahan, Jason" uniqKey="Callahan J" first="Jason" last="Callahan">Jason Callahan</name>
<name sortKey="Hicks, Rodney J" sort="Hicks, Rodney J" uniqKey="Hicks R" first="Rodney J." last="Hicks">Rodney J. Hicks</name>
<name sortKey="Hicks, Rodney J" sort="Hicks, Rodney J" uniqKey="Hicks R" first="Rodney J." last="Hicks">Rodney J. Hicks</name>
</country>
</tree>
</affiliations>
</record>

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