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Personalized radiation dosimetry for PRRT—how many scans are really required?
Purpose Over recent years, peptide receptor radiotherapy (PRRT) has been recognized as an effective treatment for patients with metastatic neuroendocrine tumors (NETs). Personalized dosimetry can contribute to improve the outcome of peptide receptor radiotherapy (PRRT) in patients with metastatic NE...
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Published in: | EJNMMI physics 2020-05, Vol.7 (1), p.26-26, Article 26 |
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description | Purpose
Over recent years, peptide receptor radiotherapy (PRRT) has been recognized as an effective treatment for patients with metastatic neuroendocrine tumors (NETs). Personalized dosimetry can contribute to improve the outcome of peptide receptor radiotherapy (PRRT) in patients with metastatic NETs. Dosimetry can aid treatment planning, ensuring that absorbed dose to vulnerable normal organs (kidneys and bone marrow) does not exceed safe limits over serial treatments, and that absorbed dose to tumor is sufficient. Absorbed dose is estimated from a series of post-treatment SPECT/CT images. Total self-dose is proportional to the integral under the time activity concentration curve (TACC). Method dependence of image-based absorbed dose calculations has been previously investigated, and we set out here to extend previous work by examining implications of number of data points in the TACC and the numerical integration methods used in estimating absorbed dose.
Methods
In this retrospective study, absorbed dose estimates and effective half-lives were calculated by fitting curves to TACCs for normal organs and tumors in 30 consecutive patients who underwent a series of 4 post-treatment SPECT/CT scans at 4 h, 24 h, 4–5 days, and 1 week following
177
Lu-DOTATATE PRRT. We examined the effects of including only 2 or 3 rather than all 4 data points in the TACC, and the effect of numerical integration method (mono-exponential alone or in combination with trapezoidal rule) on the absorbed dose and half-life estimates. Our current method is the combination of trapezoidal rule over the first 24 h, with mono-exponential fit thereafter extrapolated to infinity. The other methods were compared to this current method.
Results
Differences in absorbed dose and effective half-life between the current method and estimates based only on the second, third, and fourth scans were very small (mean differences < 2.5%), whereas differences between the current method and 4-point mono-exponential fit were higher (mean differences < 5%) with a larger range. It appears that in a 4-point mono-exponential fit the early (4 h) time point may skew results, causing some large errors. Differences between the current method and values based on only 2 time points were relatively small (mean differences < 3.5%) when the 24 h and 1 week scans were used, but when the 24 h and 4–5 days scans, or the 4–5 days and 1 week scans were used, differences were greater.
Conclusion
This study indicates that for |
doi_str_mv | 10.1186/s40658-020-00293-z |
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Over recent years, peptide receptor radiotherapy (PRRT) has been recognized as an effective treatment for patients with metastatic neuroendocrine tumors (NETs). Personalized dosimetry can contribute to improve the outcome of peptide receptor radiotherapy (PRRT) in patients with metastatic NETs. Dosimetry can aid treatment planning, ensuring that absorbed dose to vulnerable normal organs (kidneys and bone marrow) does not exceed safe limits over serial treatments, and that absorbed dose to tumor is sufficient. Absorbed dose is estimated from a series of post-treatment SPECT/CT images. Total self-dose is proportional to the integral under the time activity concentration curve (TACC). Method dependence of image-based absorbed dose calculations has been previously investigated, and we set out here to extend previous work by examining implications of number of data points in the TACC and the numerical integration methods used in estimating absorbed dose.
Methods
In this retrospective study, absorbed dose estimates and effective half-lives were calculated by fitting curves to TACCs for normal organs and tumors in 30 consecutive patients who underwent a series of 4 post-treatment SPECT/CT scans at 4 h, 24 h, 4–5 days, and 1 week following
177
Lu-DOTATATE PRRT. We examined the effects of including only 2 or 3 rather than all 4 data points in the TACC, and the effect of numerical integration method (mono-exponential alone or in combination with trapezoidal rule) on the absorbed dose and half-life estimates. Our current method is the combination of trapezoidal rule over the first 24 h, with mono-exponential fit thereafter extrapolated to infinity. The other methods were compared to this current method.
Results
Differences in absorbed dose and effective half-life between the current method and estimates based only on the second, third, and fourth scans were very small (mean differences < 2.5%), whereas differences between the current method and 4-point mono-exponential fit were higher (mean differences < 5%) with a larger range. It appears that in a 4-point mono-exponential fit the early (4 h) time point may skew results, causing some large errors. Differences between the current method and values based on only 2 time points were relatively small (mean differences < 3.5%) when the 24 h and 1 week scans were used, but when the 24 h and 4–5 days scans, or the 4–5 days and 1 week scans were used, differences were greater.
Conclusion
This study indicates that for
177
Lu-DOTATATE PRRT, accurate estimates of absorbed dose for organs and tumors may be estimated from scans at 24 h, 72 h, and 1 week post-treatment without an earlier scan. It may even be possible to cut out the 72 h scan, though the uncertainty increases. However, further work on more patients is required to validate this.</description><identifier>ISSN: 2197-7364</identifier><identifier>EISSN: 2197-7364</identifier><identifier>DOI: 10.1186/s40658-020-00293-z</identifier><identifier>PMID: 32394075</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>177Lu-DOTATATE ; Applied and Technical Physics ; Bone marrow ; Computational Mathematics and Numerical Analysis ; Computed tomography ; Curve fitting ; Data points ; Dosimeters ; Dosimetry ; Engineering ; Estimates ; Half-life ; Imaging ; Lutetium isotopes ; Mathematical analysis ; Medical imaging ; Medicine ; Medicine & Public Health ; Metastasis ; Method dependence ; Methods ; Neuroendocrine tumors ; Nuclear Medicine ; Numerical integration ; Numerical methods ; Organs ; Peptides ; Radiation therapy ; Radiology ; Receptors ; Short Communication ; Tumors</subject><ispartof>EJNMMI physics, 2020-05, Vol.7 (1), p.26-26, Article 26</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c644t-3d5e9c13eb4f1ff80378e72e5af75fdc96acf94379c9e40ea4965f89843bb91a3</citedby><cites>FETCH-LOGICAL-c644t-3d5e9c13eb4f1ff80378e72e5af75fdc96acf94379c9e40ea4965f89843bb91a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2400891079/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2400891079?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32394075$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-437013$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Freedman, Nanette</creatorcontrib><creatorcontrib>Sandström, Mattias</creatorcontrib><creatorcontrib>Kuten, Jonathan</creatorcontrib><creatorcontrib>Shtraus, Natan</creatorcontrib><creatorcontrib>Ospovat, Inna</creatorcontrib><creatorcontrib>Schlocker, Albert</creatorcontrib><creatorcontrib>Even-Sapir, Einat</creatorcontrib><title>Personalized radiation dosimetry for PRRT—how many scans are really required?</title><title>EJNMMI physics</title><addtitle>EJNMMI Phys</addtitle><addtitle>EJNMMI Phys</addtitle><description>Purpose
Over recent years, peptide receptor radiotherapy (PRRT) has been recognized as an effective treatment for patients with metastatic neuroendocrine tumors (NETs). Personalized dosimetry can contribute to improve the outcome of peptide receptor radiotherapy (PRRT) in patients with metastatic NETs. Dosimetry can aid treatment planning, ensuring that absorbed dose to vulnerable normal organs (kidneys and bone marrow) does not exceed safe limits over serial treatments, and that absorbed dose to tumor is sufficient. Absorbed dose is estimated from a series of post-treatment SPECT/CT images. Total self-dose is proportional to the integral under the time activity concentration curve (TACC). Method dependence of image-based absorbed dose calculations has been previously investigated, and we set out here to extend previous work by examining implications of number of data points in the TACC and the numerical integration methods used in estimating absorbed dose.
Methods
In this retrospective study, absorbed dose estimates and effective half-lives were calculated by fitting curves to TACCs for normal organs and tumors in 30 consecutive patients who underwent a series of 4 post-treatment SPECT/CT scans at 4 h, 24 h, 4–5 days, and 1 week following
177
Lu-DOTATATE PRRT. We examined the effects of including only 2 or 3 rather than all 4 data points in the TACC, and the effect of numerical integration method (mono-exponential alone or in combination with trapezoidal rule) on the absorbed dose and half-life estimates. Our current method is the combination of trapezoidal rule over the first 24 h, with mono-exponential fit thereafter extrapolated to infinity. The other methods were compared to this current method.
Results
Differences in absorbed dose and effective half-life between the current method and estimates based only on the second, third, and fourth scans were very small (mean differences < 2.5%), whereas differences between the current method and 4-point mono-exponential fit were higher (mean differences < 5%) with a larger range. It appears that in a 4-point mono-exponential fit the early (4 h) time point may skew results, causing some large errors. Differences between the current method and values based on only 2 time points were relatively small (mean differences < 3.5%) when the 24 h and 1 week scans were used, but when the 24 h and 4–5 days scans, or the 4–5 days and 1 week scans were used, differences were greater.
Conclusion
This study indicates that for
177
Lu-DOTATATE PRRT, accurate estimates of absorbed dose for organs and tumors may be estimated from scans at 24 h, 72 h, and 1 week post-treatment without an earlier scan. It may even be possible to cut out the 72 h scan, though the uncertainty increases. However, further work on more patients is required to validate this.</description><subject>177Lu-DOTATATE</subject><subject>Applied and Technical Physics</subject><subject>Bone marrow</subject><subject>Computational Mathematics and Numerical Analysis</subject><subject>Computed tomography</subject><subject>Curve fitting</subject><subject>Data points</subject><subject>Dosimeters</subject><subject>Dosimetry</subject><subject>Engineering</subject><subject>Estimates</subject><subject>Half-life</subject><subject>Imaging</subject><subject>Lutetium isotopes</subject><subject>Mathematical analysis</subject><subject>Medical imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metastasis</subject><subject>Method dependence</subject><subject>Methods</subject><subject>Neuroendocrine tumors</subject><subject>Nuclear Medicine</subject><subject>Numerical integration</subject><subject>Numerical methods</subject><subject>Organs</subject><subject>Peptides</subject><subject>Radiation therapy</subject><subject>Radiology</subject><subject>Receptors</subject><subject>Short Communication</subject><subject>Tumors</subject><issn>2197-7364</issn><issn>2197-7364</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kstu1DAUhiMEolXpC7BAkdiwIHB8i-MNqCq3SpVaVYWt5bFPph5l4tZOqGZWPARPyJPgTobSYcHKls93Pt_-onhO4A0hTf02cahFUwGFCoAqVq0fFfuUKFlJVvPHD-Z7xWFKCwAgVNSU0KfFHqNMcZBivzg7x5hCbzq_RldG47wZfOhLF5Jf4hBXZRtieX5xcfnrx8-rcFsuTb8qkzV9Kk3EMqLpulUebkYf0b1_VjxpTZfwcDseFF8_fbw8_lKdnn0-OT46rWzN-VAxJ1BZwnDGW9K2DTDZoKQoTCtF66yqjW0VZ1JZhRzQcFWLtlENZ7OZIoYdFCeT1wWz0NfRL01c6WC83iyEONcmDt52qK1jIC1pQVnHRS2NoOBqAg1YqGu02fV6cqVbvB5nO7YP_tvRxjaOOh8HCMv4uwnP7BKdxX6Iptvp2q30_krPw3ctKeGiuRO82gpiuBkxDXrpk8WuMz2GMWnKgTQgBIOMvvwHXYQx5u_aUNAoAlJlik6UjSGliO39YQjou7ToKS06p0Vv0qLXuenFw2vct_zJRgbY9llyqZ9j_Lv3f7S_AVWnzGI</recordid><startdate>20200511</startdate><enddate>20200511</enddate><creator>Freedman, Nanette</creator><creator>Sandström, Mattias</creator><creator>Kuten, Jonathan</creator><creator>Shtraus, Natan</creator><creator>Ospovat, Inna</creator><creator>Schlocker, Albert</creator><creator>Even-Sapir, Einat</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><general>SpringerOpen</general><scope>C6C</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>ACNBI</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>D8T</scope><scope>DF2</scope><scope>ZZAVC</scope><scope>DOA</scope></search><sort><creationdate>20200511</creationdate><title>Personalized radiation dosimetry for PRRT—how many scans are really required?</title><author>Freedman, Nanette ; Sandström, Mattias ; Kuten, Jonathan ; Shtraus, Natan ; Ospovat, Inna ; Schlocker, Albert ; Even-Sapir, Einat</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c644t-3d5e9c13eb4f1ff80378e72e5af75fdc96acf94379c9e40ea4965f89843bb91a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>177Lu-DOTATATE</topic><topic>Applied and Technical Physics</topic><topic>Bone marrow</topic><topic>Computational Mathematics and Numerical Analysis</topic><topic>Computed tomography</topic><topic>Curve fitting</topic><topic>Data points</topic><topic>Dosimeters</topic><topic>Dosimetry</topic><topic>Engineering</topic><topic>Estimates</topic><topic>Half-life</topic><topic>Imaging</topic><topic>Lutetium isotopes</topic><topic>Mathematical analysis</topic><topic>Medical imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metastasis</topic><topic>Method dependence</topic><topic>Methods</topic><topic>Neuroendocrine tumors</topic><topic>Nuclear Medicine</topic><topic>Numerical integration</topic><topic>Numerical methods</topic><topic>Organs</topic><topic>Peptides</topic><topic>Radiation therapy</topic><topic>Radiology</topic><topic>Receptors</topic><topic>Short Communication</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Freedman, Nanette</creatorcontrib><creatorcontrib>Sandström, Mattias</creatorcontrib><creatorcontrib>Kuten, Jonathan</creatorcontrib><creatorcontrib>Shtraus, Natan</creatorcontrib><creatorcontrib>Ospovat, Inna</creatorcontrib><creatorcontrib>Schlocker, Albert</creatorcontrib><creatorcontrib>Even-Sapir, Einat</creatorcontrib><collection>SpringerOpen(OpenAccess)</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</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><collection>PubMed Central (Full Participant titles)</collection><collection>SWEPUB Uppsala universitet full text</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Uppsala universitet</collection><collection>SwePub Articles full text</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>EJNMMI physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Freedman, Nanette</au><au>Sandström, Mattias</au><au>Kuten, Jonathan</au><au>Shtraus, Natan</au><au>Ospovat, Inna</au><au>Schlocker, Albert</au><au>Even-Sapir, Einat</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Personalized radiation dosimetry for PRRT—how many scans are really required?</atitle><jtitle>EJNMMI physics</jtitle><stitle>EJNMMI Phys</stitle><addtitle>EJNMMI Phys</addtitle><date>2020-05-11</date><risdate>2020</risdate><volume>7</volume><issue>1</issue><spage>26</spage><epage>26</epage><pages>26-26</pages><artnum>26</artnum><issn>2197-7364</issn><eissn>2197-7364</eissn><abstract>Purpose
Over recent years, peptide receptor radiotherapy (PRRT) has been recognized as an effective treatment for patients with metastatic neuroendocrine tumors (NETs). Personalized dosimetry can contribute to improve the outcome of peptide receptor radiotherapy (PRRT) in patients with metastatic NETs. Dosimetry can aid treatment planning, ensuring that absorbed dose to vulnerable normal organs (kidneys and bone marrow) does not exceed safe limits over serial treatments, and that absorbed dose to tumor is sufficient. Absorbed dose is estimated from a series of post-treatment SPECT/CT images. Total self-dose is proportional to the integral under the time activity concentration curve (TACC). Method dependence of image-based absorbed dose calculations has been previously investigated, and we set out here to extend previous work by examining implications of number of data points in the TACC and the numerical integration methods used in estimating absorbed dose.
Methods
In this retrospective study, absorbed dose estimates and effective half-lives were calculated by fitting curves to TACCs for normal organs and tumors in 30 consecutive patients who underwent a series of 4 post-treatment SPECT/CT scans at 4 h, 24 h, 4–5 days, and 1 week following
177
Lu-DOTATATE PRRT. We examined the effects of including only 2 or 3 rather than all 4 data points in the TACC, and the effect of numerical integration method (mono-exponential alone or in combination with trapezoidal rule) on the absorbed dose and half-life estimates. Our current method is the combination of trapezoidal rule over the first 24 h, with mono-exponential fit thereafter extrapolated to infinity. The other methods were compared to this current method.
Results
Differences in absorbed dose and effective half-life between the current method and estimates based only on the second, third, and fourth scans were very small (mean differences < 2.5%), whereas differences between the current method and 4-point mono-exponential fit were higher (mean differences < 5%) with a larger range. It appears that in a 4-point mono-exponential fit the early (4 h) time point may skew results, causing some large errors. Differences between the current method and values based on only 2 time points were relatively small (mean differences < 3.5%) when the 24 h and 1 week scans were used, but when the 24 h and 4–5 days scans, or the 4–5 days and 1 week scans were used, differences were greater.
Conclusion
This study indicates that for
177
Lu-DOTATATE PRRT, accurate estimates of absorbed dose for organs and tumors may be estimated from scans at 24 h, 72 h, and 1 week post-treatment without an earlier scan. It may even be possible to cut out the 72 h scan, though the uncertainty increases. However, further work on more patients is required to validate this.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>32394075</pmid><doi>10.1186/s40658-020-00293-z</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 177Lu-DOTATATE Applied and Technical Physics Bone marrow Computational Mathematics and Numerical Analysis Computed tomography Curve fitting Data points Dosimeters Dosimetry Engineering Estimates Half-life Imaging Lutetium isotopes Mathematical analysis Medical imaging Medicine Medicine & Public Health Metastasis Method dependence Methods Neuroendocrine tumors Nuclear Medicine Numerical integration Numerical methods Organs Peptides Radiation therapy Radiology Receptors Short Communication Tumors |
title | Personalized radiation dosimetry for PRRT—how many scans are really required? |
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