Ultra-early response assessment in lymphoma treatment: [18F]FDG PET/MR captures changes in glucose metabolism and cell density within the first 72 hours of treatment
Purpose To determine whether, in patients with Hodgkin lymphoma (HL) or non-Hodgkin lymphoma (NHL), [ 18 F]FDG PET/MR can capture treatment effects within the first week after treatment initiation, and whether changes in glucose metabolism and cell density occur simultaneously. Methods Patients with...
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| Veröffentlicht in: | European journal of nuclear medicine and molecular imaging 2018-06, Vol.45 (6), p.931-940 |
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| creator | Mayerhoefer, Marius E. Raderer, Markus Jaeger, Ulrich Staber, Philipp Kiesewetter, Barbara Senn, Daniela Gallagher, Ferdia A. Brindle, Kevin Porpaczy, Edit Weber, Michael Berzaczy, Dominik Simonitsch-Klupp, Ingrid Sillaber, Christian Skrabs, Cathrin Haug, Alexander |
| description | Purpose
To determine whether, in patients with Hodgkin lymphoma (HL) or non-Hodgkin lymphoma (NHL), [
18
F]FDG PET/MR can capture treatment effects within the first week after treatment initiation, and whether changes in glucose metabolism and cell density occur simultaneously.
Methods
Patients with histologically proven HL or NHL were included in this prospective IRB-approved study. Patients underwent [
18
F]FDG PET/MR before, and then 48–72 h after (follow-up 1, FU-1) and 1 week after (FU-2) initiation of the first cycle of their respective standard chemotherapy (for HL) or immunochemotherapy (for NHL). Standardized [
18
F]FDG uptake values (SUVmax, SUVmean) and apparent diffusion coefficients (ADCmin, ADCmean) based on diffusion-weighted MRI, and metabolic and morphological tumour volumes (MTV, VOL) were assessed at each time-point. Multilevel analyses with an unstructured covariance matrix, and pair-wise post-hoc tests were used to test for significant changes in SUVs, ADCs, MTVs and VOLs between the three time-points.
Results
A total of 58 patients (11 with HL and 47 with NHL) with 166 lesions were analysed. Lesion-based mean rates of change in SUVmax, SUVmean, ADCmin, ADCmean, MTV and VOL between baseline and FU-1 were −46.8%, −33.3%, +20.3%, +14%, −46% and −12.8%, respectively, and between baseline and FU-2 were −65.1%, −49%, +50.7%, +32.4%, −61.1% and −24.2%, respectively. These changes were statistically significant (
P
|
| doi_str_mv | 10.1007/s00259-018-3937-z |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_proquest_miscellaneous_2008376286</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2008197197</sourcerecordid><originalsourceid>FETCH-LOGICAL-p212t-eaed7054d021e8ee3ddff3b1c9e1d4e385a7dba7fc60724b9655f13dc4c57f633</originalsourceid><addsrcrecordid>eNpdkdtqFTEUhkNRetIH8EYCvfFmbA4zk8S7UrurUFGkvRIJmcmazpQ5NStD2X2aXvVBfDKz3dWCEFgh-da__uQn5A1n7zlj6hgZE4XJGNeZNFJl9ztkn5fcZIpp8-LfXrE9coB4wxIotNkle8Lkmkmh98njVR-Dy8CFfk0D4DyNCNQhAuIAY6TdSPv1MLfT4GgM4OLm9AP9wfXq5-rjOf12dnn85Tut3RyX1E_r1o3Xqaa-636pp6Q2QHTV1Hc4UDd6WkPfUw8jdnFN77rYJjS2QJsuYKRK_HpopyUgnZrnga_Iy8b1CK-f6iG5Wp1dnn7KLr6efz49uchmwUVMzwCvWJF7JjhoAOl908iK1wa4z0HqwilfOdXUJVMir0xZFA2Xvs7rQjWllIfk3VZ3DtPtAhjt0OHGsBthWtAKxrRUpdBlQo_-Q2-S7TG5-0Nxo9JK1NsnaqkG8HYO3eDC2v5NIAFiC2C6Sj8XnmU4s5uY7TZmm9Kzm5jtvfwNgKOb5Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2008197197</pqid></control><display><type>article</type><title>Ultra-early response assessment in lymphoma treatment: [18F]FDG PET/MR captures changes in glucose metabolism and cell density within the first 72 hours of treatment</title><source>MEDLINE</source><source>SpringerLink Journals</source><creator>Mayerhoefer, Marius E. ; Raderer, Markus ; Jaeger, Ulrich ; Staber, Philipp ; Kiesewetter, Barbara ; Senn, Daniela ; Gallagher, Ferdia A. ; Brindle, Kevin ; Porpaczy, Edit ; Weber, Michael ; Berzaczy, Dominik ; Simonitsch-Klupp, Ingrid ; Sillaber, Christian ; Skrabs, Cathrin ; Haug, Alexander</creator><creatorcontrib>Mayerhoefer, Marius E. ; Raderer, Markus ; Jaeger, Ulrich ; Staber, Philipp ; Kiesewetter, Barbara ; Senn, Daniela ; Gallagher, Ferdia A. ; Brindle, Kevin ; Porpaczy, Edit ; Weber, Michael ; Berzaczy, Dominik ; Simonitsch-Klupp, Ingrid ; Sillaber, Christian ; Skrabs, Cathrin ; Haug, Alexander</creatorcontrib><description>Purpose
To determine whether, in patients with Hodgkin lymphoma (HL) or non-Hodgkin lymphoma (NHL), [
18
F]FDG PET/MR can capture treatment effects within the first week after treatment initiation, and whether changes in glucose metabolism and cell density occur simultaneously.
Methods
Patients with histologically proven HL or NHL were included in this prospective IRB-approved study. Patients underwent [
18
F]FDG PET/MR before, and then 48–72 h after (follow-up 1, FU-1) and 1 week after (FU-2) initiation of the first cycle of their respective standard chemotherapy (for HL) or immunochemotherapy (for NHL). Standardized [
18
F]FDG uptake values (SUVmax, SUVmean) and apparent diffusion coefficients (ADCmin, ADCmean) based on diffusion-weighted MRI, and metabolic and morphological tumour volumes (MTV, VOL) were assessed at each time-point. Multilevel analyses with an unstructured covariance matrix, and pair-wise post-hoc tests were used to test for significant changes in SUVs, ADCs, MTVs and VOLs between the three time-points.
Results
A total of 58 patients (11 with HL and 47 with NHL) with 166 lesions were analysed. Lesion-based mean rates of change in SUVmax, SUVmean, ADCmin, ADCmean, MTV and VOL between baseline and FU-1 were −46.8%, −33.3%, +20.3%, +14%, −46% and −12.8%, respectively, and between baseline and FU-2 were −65.1%, −49%, +50.7%, +32.4%, −61.1% and −24.2%, respectively. These changes were statistically significant (
P
< 0.01) except for the change in VOL between baseline and FU-1 (
P
= 0.079).
Conclusion
In lymphoma patients, [
18
F]FDG PET/MR can capture treatment-induced changes in glucose metabolism and cell density as early as 48–72 h after treatment initiation.</description><identifier>ISSN: 1619-7070</identifier><identifier>EISSN: 1619-7089</identifier><identifier>DOI: 10.1007/s00259-018-3937-z</identifier><identifier>PMID: 29480328</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Cardiology ; Cell Count ; Cell density ; Chemotherapy ; Covariance matrix ; Density ; Female ; Fluorine isotopes ; Fluorodeoxyglucose F18 ; Germany ; Glucose ; Glucose metabolism ; Hodgkin Disease - diagnostic imaging ; Humans ; Imaging ; Immunotherapy ; Lesions ; Lymphoma ; Lymphoma, Non-Hodgkin - diagnostic imaging ; Magnetic Resonance Imaging ; Medicine ; Medicine & Public Health ; Metabolism ; Nuclear Medicine ; Oncology ; Original Article ; Orthopedics ; Patients ; Positron-Emission Tomography ; Pregnancy ; Prospective Studies ; Radiology ; Radiopharmaceuticals ; Statistical analysis ; Tomography, X-Ray Computed ; Tumors</subject><ispartof>European journal of nuclear medicine and molecular imaging, 2018-06, Vol.45 (6), p.931-940</ispartof><rights>The Author(s) 2018</rights><rights>European Journal of Nuclear Medicine and Molecular Imaging is a copyright of Springer, (2018). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-p212t-eaed7054d021e8ee3ddff3b1c9e1d4e385a7dba7fc60724b9655f13dc4c57f633</cites><orcidid>0000-0001-8786-8686</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00259-018-3937-z$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00259-018-3937-z$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29480328$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mayerhoefer, Marius E.</creatorcontrib><creatorcontrib>Raderer, Markus</creatorcontrib><creatorcontrib>Jaeger, Ulrich</creatorcontrib><creatorcontrib>Staber, Philipp</creatorcontrib><creatorcontrib>Kiesewetter, Barbara</creatorcontrib><creatorcontrib>Senn, Daniela</creatorcontrib><creatorcontrib>Gallagher, Ferdia A.</creatorcontrib><creatorcontrib>Brindle, Kevin</creatorcontrib><creatorcontrib>Porpaczy, Edit</creatorcontrib><creatorcontrib>Weber, Michael</creatorcontrib><creatorcontrib>Berzaczy, Dominik</creatorcontrib><creatorcontrib>Simonitsch-Klupp, Ingrid</creatorcontrib><creatorcontrib>Sillaber, Christian</creatorcontrib><creatorcontrib>Skrabs, Cathrin</creatorcontrib><creatorcontrib>Haug, Alexander</creatorcontrib><title>Ultra-early response assessment in lymphoma treatment: [18F]FDG PET/MR captures changes in glucose metabolism and cell density within the first 72 hours of treatment</title><title>European journal of nuclear medicine and molecular imaging</title><addtitle>Eur J Nucl Med Mol Imaging</addtitle><addtitle>Eur J Nucl Med Mol Imaging</addtitle><description>Purpose
To determine whether, in patients with Hodgkin lymphoma (HL) or non-Hodgkin lymphoma (NHL), [
18
F]FDG PET/MR can capture treatment effects within the first week after treatment initiation, and whether changes in glucose metabolism and cell density occur simultaneously.
Methods
Patients with histologically proven HL or NHL were included in this prospective IRB-approved study. Patients underwent [
18
F]FDG PET/MR before, and then 48–72 h after (follow-up 1, FU-1) and 1 week after (FU-2) initiation of the first cycle of their respective standard chemotherapy (for HL) or immunochemotherapy (for NHL). Standardized [
18
F]FDG uptake values (SUVmax, SUVmean) and apparent diffusion coefficients (ADCmin, ADCmean) based on diffusion-weighted MRI, and metabolic and morphological tumour volumes (MTV, VOL) were assessed at each time-point. Multilevel analyses with an unstructured covariance matrix, and pair-wise post-hoc tests were used to test for significant changes in SUVs, ADCs, MTVs and VOLs between the three time-points.
Results
A total of 58 patients (11 with HL and 47 with NHL) with 166 lesions were analysed. Lesion-based mean rates of change in SUVmax, SUVmean, ADCmin, ADCmean, MTV and VOL between baseline and FU-1 were −46.8%, −33.3%, +20.3%, +14%, −46% and −12.8%, respectively, and between baseline and FU-2 were −65.1%, −49%, +50.7%, +32.4%, −61.1% and −24.2%, respectively. These changes were statistically significant (
P
< 0.01) except for the change in VOL between baseline and FU-1 (
P
= 0.079).
Conclusion
In lymphoma patients, [
18
F]FDG PET/MR can capture treatment-induced changes in glucose metabolism and cell density as early as 48–72 h after treatment initiation.</description><subject>Cardiology</subject><subject>Cell Count</subject><subject>Cell density</subject><subject>Chemotherapy</subject><subject>Covariance matrix</subject><subject>Density</subject><subject>Female</subject><subject>Fluorine isotopes</subject><subject>Fluorodeoxyglucose F18</subject><subject>Germany</subject><subject>Glucose</subject><subject>Glucose metabolism</subject><subject>Hodgkin Disease - diagnostic imaging</subject><subject>Humans</subject><subject>Imaging</subject><subject>Immunotherapy</subject><subject>Lesions</subject><subject>Lymphoma</subject><subject>Lymphoma, Non-Hodgkin - diagnostic imaging</subject><subject>Magnetic Resonance Imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolism</subject><subject>Nuclear Medicine</subject><subject>Oncology</subject><subject>Original Article</subject><subject>Orthopedics</subject><subject>Patients</subject><subject>Positron-Emission Tomography</subject><subject>Pregnancy</subject><subject>Prospective Studies</subject><subject>Radiology</subject><subject>Radiopharmaceuticals</subject><subject>Statistical analysis</subject><subject>Tomography, X-Ray Computed</subject><subject>Tumors</subject><issn>1619-7070</issn><issn>1619-7089</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNpdkdtqFTEUhkNRetIH8EYCvfFmbA4zk8S7UrurUFGkvRIJmcmazpQ5NStD2X2aXvVBfDKz3dWCEFgh-da__uQn5A1n7zlj6hgZE4XJGNeZNFJl9ztkn5fcZIpp8-LfXrE9coB4wxIotNkle8Lkmkmh98njVR-Dy8CFfk0D4DyNCNQhAuIAY6TdSPv1MLfT4GgM4OLm9AP9wfXq5-rjOf12dnn85Tut3RyX1E_r1o3Xqaa-636pp6Q2QHTV1Hc4UDd6WkPfUw8jdnFN77rYJjS2QJsuYKRK_HpopyUgnZrnga_Iy8b1CK-f6iG5Wp1dnn7KLr6efz49uchmwUVMzwCvWJF7JjhoAOl908iK1wa4z0HqwilfOdXUJVMir0xZFA2Xvs7rQjWllIfk3VZ3DtPtAhjt0OHGsBthWtAKxrRUpdBlQo_-Q2-S7TG5-0Nxo9JK1NsnaqkG8HYO3eDC2v5NIAFiC2C6Sj8XnmU4s5uY7TZmm9Kzm5jtvfwNgKOb5Q</recordid><startdate>20180601</startdate><enddate>20180601</enddate><creator>Mayerhoefer, Marius E.</creator><creator>Raderer, Markus</creator><creator>Jaeger, Ulrich</creator><creator>Staber, Philipp</creator><creator>Kiesewetter, Barbara</creator><creator>Senn, Daniela</creator><creator>Gallagher, Ferdia A.</creator><creator>Brindle, Kevin</creator><creator>Porpaczy, Edit</creator><creator>Weber, Michael</creator><creator>Berzaczy, Dominik</creator><creator>Simonitsch-Klupp, Ingrid</creator><creator>Sillaber, Christian</creator><creator>Skrabs, Cathrin</creator><creator>Haug, Alexander</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>3V.</scope><scope>7RV</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</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>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>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-8786-8686</orcidid></search><sort><creationdate>20180601</creationdate><title>Ultra-early response assessment in lymphoma treatment: [18F]FDG PET/MR captures changes in glucose metabolism and cell density within the first 72 hours of treatment</title><author>Mayerhoefer, Marius E. ; Raderer, Markus ; Jaeger, Ulrich ; Staber, Philipp ; Kiesewetter, Barbara ; Senn, Daniela ; Gallagher, Ferdia A. ; Brindle, Kevin ; Porpaczy, Edit ; Weber, Michael ; Berzaczy, Dominik ; Simonitsch-Klupp, Ingrid ; Sillaber, Christian ; Skrabs, Cathrin ; Haug, Alexander</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p212t-eaed7054d021e8ee3ddff3b1c9e1d4e385a7dba7fc60724b9655f13dc4c57f633</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Cardiology</topic><topic>Cell Count</topic><topic>Cell density</topic><topic>Chemotherapy</topic><topic>Covariance matrix</topic><topic>Density</topic><topic>Female</topic><topic>Fluorine isotopes</topic><topic>Fluorodeoxyglucose F18</topic><topic>Germany</topic><topic>Glucose</topic><topic>Glucose metabolism</topic><topic>Hodgkin Disease - diagnostic imaging</topic><topic>Humans</topic><topic>Imaging</topic><topic>Immunotherapy</topic><topic>Lesions</topic><topic>Lymphoma</topic><topic>Lymphoma, Non-Hodgkin - diagnostic imaging</topic><topic>Magnetic Resonance Imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolism</topic><topic>Nuclear Medicine</topic><topic>Oncology</topic><topic>Original Article</topic><topic>Orthopedics</topic><topic>Patients</topic><topic>Positron-Emission Tomography</topic><topic>Pregnancy</topic><topic>Prospective Studies</topic><topic>Radiology</topic><topic>Radiopharmaceuticals</topic><topic>Statistical analysis</topic><topic>Tomography, X-Ray Computed</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mayerhoefer, Marius E.</creatorcontrib><creatorcontrib>Raderer, Markus</creatorcontrib><creatorcontrib>Jaeger, Ulrich</creatorcontrib><creatorcontrib>Staber, Philipp</creatorcontrib><creatorcontrib>Kiesewetter, Barbara</creatorcontrib><creatorcontrib>Senn, Daniela</creatorcontrib><creatorcontrib>Gallagher, Ferdia A.</creatorcontrib><creatorcontrib>Brindle, Kevin</creatorcontrib><creatorcontrib>Porpaczy, Edit</creatorcontrib><creatorcontrib>Weber, Michael</creatorcontrib><creatorcontrib>Berzaczy, Dominik</creatorcontrib><creatorcontrib>Simonitsch-Klupp, Ingrid</creatorcontrib><creatorcontrib>Sillaber, Christian</creatorcontrib><creatorcontrib>Skrabs, Cathrin</creatorcontrib><creatorcontrib>Haug, Alexander</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</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>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 Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</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>MEDLINE - Academic</collection><jtitle>European journal of nuclear medicine and molecular imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mayerhoefer, Marius E.</au><au>Raderer, Markus</au><au>Jaeger, Ulrich</au><au>Staber, Philipp</au><au>Kiesewetter, Barbara</au><au>Senn, Daniela</au><au>Gallagher, Ferdia A.</au><au>Brindle, Kevin</au><au>Porpaczy, Edit</au><au>Weber, Michael</au><au>Berzaczy, Dominik</au><au>Simonitsch-Klupp, Ingrid</au><au>Sillaber, Christian</au><au>Skrabs, Cathrin</au><au>Haug, Alexander</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Ultra-early response assessment in lymphoma treatment: [18F]FDG PET/MR captures changes in glucose metabolism and cell density within the first 72 hours of treatment</atitle><jtitle>European journal of nuclear medicine and molecular imaging</jtitle><stitle>Eur J Nucl Med Mol Imaging</stitle><addtitle>Eur J Nucl Med Mol Imaging</addtitle><date>2018-06-01</date><risdate>2018</risdate><volume>45</volume><issue>6</issue><spage>931</spage><epage>940</epage><pages>931-940</pages><issn>1619-7070</issn><eissn>1619-7089</eissn><abstract>Purpose
To determine whether, in patients with Hodgkin lymphoma (HL) or non-Hodgkin lymphoma (NHL), [
18
F]FDG PET/MR can capture treatment effects within the first week after treatment initiation, and whether changes in glucose metabolism and cell density occur simultaneously.
Methods
Patients with histologically proven HL or NHL were included in this prospective IRB-approved study. Patients underwent [
18
F]FDG PET/MR before, and then 48–72 h after (follow-up 1, FU-1) and 1 week after (FU-2) initiation of the first cycle of their respective standard chemotherapy (for HL) or immunochemotherapy (for NHL). Standardized [
18
F]FDG uptake values (SUVmax, SUVmean) and apparent diffusion coefficients (ADCmin, ADCmean) based on diffusion-weighted MRI, and metabolic and morphological tumour volumes (MTV, VOL) were assessed at each time-point. Multilevel analyses with an unstructured covariance matrix, and pair-wise post-hoc tests were used to test for significant changes in SUVs, ADCs, MTVs and VOLs between the three time-points.
Results
A total of 58 patients (11 with HL and 47 with NHL) with 166 lesions were analysed. Lesion-based mean rates of change in SUVmax, SUVmean, ADCmin, ADCmean, MTV and VOL between baseline and FU-1 were −46.8%, −33.3%, +20.3%, +14%, −46% and −12.8%, respectively, and between baseline and FU-2 were −65.1%, −49%, +50.7%, +32.4%, −61.1% and −24.2%, respectively. These changes were statistically significant (
P
< 0.01) except for the change in VOL between baseline and FU-1 (
P
= 0.079).
Conclusion
In lymphoma patients, [
18
F]FDG PET/MR can capture treatment-induced changes in glucose metabolism and cell density as early as 48–72 h after treatment initiation.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>29480328</pmid><doi>10.1007/s00259-018-3937-z</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-8786-8686</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | European journal of nuclear medicine and molecular imaging, 2018-06, Vol.45 (6), p.931-940 |
| issn | 1619-7070 1619-7089 |
| language | eng |
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| source | MEDLINE; SpringerLink Journals |
| subjects | Cardiology Cell Count Cell density Chemotherapy Covariance matrix Density Female Fluorine isotopes Fluorodeoxyglucose F18 Germany Glucose Glucose metabolism Hodgkin Disease - diagnostic imaging Humans Imaging Immunotherapy Lesions Lymphoma Lymphoma, Non-Hodgkin - diagnostic imaging Magnetic Resonance Imaging Medicine Medicine & Public Health Metabolism Nuclear Medicine Oncology Original Article Orthopedics Patients Positron-Emission Tomography Pregnancy Prospective Studies Radiology Radiopharmaceuticals Statistical analysis Tomography, X-Ray Computed Tumors |
| title | Ultra-early response assessment in lymphoma treatment: [18F]FDG PET/MR captures changes in glucose metabolism and cell density within the first 72 hours of treatment |
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