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The use of single-timepoint images to link administered radioiodine activity (MBq) to a prescribed lesion radiation-absorbed dose (cGy): a regression-based prediction interval tool for the management of well-differentiated thyroid cancer patients
PURPOSE: To introduce a biomarker-based dosimetry method for the rational selection of a treatment activity for patients undergoing radioactive iodine (131)I therapy (RAI) for metastatic differentiated thyroid cancer (mDTC) based on single-timepoint imaging of individual lesion uptake by (124)I PET....
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382352/ https://www.ncbi.nlm.nih.gov/pubmed/37171634 http://dx.doi.org/10.1007/s00259-023-06240-1 |
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author | Mauguen, Audrey Grewal, Ravinder K. Augensen, Finn Abusamra, Murad Mahajan, Sonia Jayaprakasam, Vetri Sudar Osborne, Joseph Haque, Sofia Wong, Bernadette Z. Y. Ghossein, Ronald A. Fagin, James Schӧder, Heiko Tuttle, R. Michael Ho, Alan Humm, John L. Larson, Steven M. |
author_facet | Mauguen, Audrey Grewal, Ravinder K. Augensen, Finn Abusamra, Murad Mahajan, Sonia Jayaprakasam, Vetri Sudar Osborne, Joseph Haque, Sofia Wong, Bernadette Z. Y. Ghossein, Ronald A. Fagin, James Schӧder, Heiko Tuttle, R. Michael Ho, Alan Humm, John L. Larson, Steven M. |
author_sort | Mauguen, Audrey |
collection | PubMed |
description | PURPOSE: To introduce a biomarker-based dosimetry method for the rational selection of a treatment activity for patients undergoing radioactive iodine (131)I therapy (RAI) for metastatic differentiated thyroid cancer (mDTC) based on single-timepoint imaging of individual lesion uptake by (124)I PET. METHODS: Patients referred for RAI therapy of mDTC were enrolled in institutionally approved protocols. A total of 208 mDTC lesions (in 21 patients) with SUV(max) > 1 underwent quantitative PET scans at 24, 48, 72, and 120 h post-administration of 222 MBq of theranostic NaI-(124)I to determine the individual lesion radiation-absorbed dose. Using a general estimating equation, a prediction curve for biomarker development was generated in the form of a best-fit regression line and 95% prediction interval, correlating individual predicted lesion radiation dose metrics, with candidate biomarkers (“predictors”) such as SUV(max) and activity in microcurie per gram, from a single imaging timepoint. RESULTS: In the 169 lesions (in 15 patients) that received (131)I therapy, individual lesion cGy varied over 3 logs with a median of 22,000 cGy, confirming wide heterogeneity of lesion radiation dose. Initial findings from the prediction curve on all 208 lesions confirmed that a 48-h SUV(max) was the best predictor of lesion radiation dose and permitted calculation of the (131)I activity required to achieve a lesional threshold radiation dose (2000 cGy) within defined confidence intervals. CONCLUSIONS: Based on MIRD lesion-absorbed dose estimates and regression statistics, we report on the feasibility of a new single-timepoint (124)I-PET-based dosimetry biomarker for RAI in patients with mDTC. The approach provides clinicians with a tool to select personalized (precision) therapeutic administration of radioactivity (MBq) to achieve a desired target lesion-absorbed dose (cGy) for selected index lesions based on a single 48-h measurement (124)I-PET image, provided the selected activity does not exceed the maximum tolerated activity (MTA) of < 2 Gy to blood, as is standard of care at Memorial Sloan Kettering Cancer Center. TRIAL REGISTRATION: NCT04462471, Registered July 8, 2020. NCT03647358, Registered Aug 27, 2018. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-023-06240-1. |
format | Online Article Text |
id | pubmed-10382352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-103823522023-07-30 The use of single-timepoint images to link administered radioiodine activity (MBq) to a prescribed lesion radiation-absorbed dose (cGy): a regression-based prediction interval tool for the management of well-differentiated thyroid cancer patients Mauguen, Audrey Grewal, Ravinder K. Augensen, Finn Abusamra, Murad Mahajan, Sonia Jayaprakasam, Vetri Sudar Osborne, Joseph Haque, Sofia Wong, Bernadette Z. Y. Ghossein, Ronald A. Fagin, James Schӧder, Heiko Tuttle, R. Michael Ho, Alan Humm, John L. Larson, Steven M. Eur J Nucl Med Mol Imaging Original Article PURPOSE: To introduce a biomarker-based dosimetry method for the rational selection of a treatment activity for patients undergoing radioactive iodine (131)I therapy (RAI) for metastatic differentiated thyroid cancer (mDTC) based on single-timepoint imaging of individual lesion uptake by (124)I PET. METHODS: Patients referred for RAI therapy of mDTC were enrolled in institutionally approved protocols. A total of 208 mDTC lesions (in 21 patients) with SUV(max) > 1 underwent quantitative PET scans at 24, 48, 72, and 120 h post-administration of 222 MBq of theranostic NaI-(124)I to determine the individual lesion radiation-absorbed dose. Using a general estimating equation, a prediction curve for biomarker development was generated in the form of a best-fit regression line and 95% prediction interval, correlating individual predicted lesion radiation dose metrics, with candidate biomarkers (“predictors”) such as SUV(max) and activity in microcurie per gram, from a single imaging timepoint. RESULTS: In the 169 lesions (in 15 patients) that received (131)I therapy, individual lesion cGy varied over 3 logs with a median of 22,000 cGy, confirming wide heterogeneity of lesion radiation dose. Initial findings from the prediction curve on all 208 lesions confirmed that a 48-h SUV(max) was the best predictor of lesion radiation dose and permitted calculation of the (131)I activity required to achieve a lesional threshold radiation dose (2000 cGy) within defined confidence intervals. CONCLUSIONS: Based on MIRD lesion-absorbed dose estimates and regression statistics, we report on the feasibility of a new single-timepoint (124)I-PET-based dosimetry biomarker for RAI in patients with mDTC. The approach provides clinicians with a tool to select personalized (precision) therapeutic administration of radioactivity (MBq) to achieve a desired target lesion-absorbed dose (cGy) for selected index lesions based on a single 48-h measurement (124)I-PET image, provided the selected activity does not exceed the maximum tolerated activity (MTA) of < 2 Gy to blood, as is standard of care at Memorial Sloan Kettering Cancer Center. TRIAL REGISTRATION: NCT04462471, Registered July 8, 2020. NCT03647358, Registered Aug 27, 2018. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-023-06240-1. Springer Berlin Heidelberg 2023-05-12 2023 /pmc/articles/PMC10382352/ /pubmed/37171634 http://dx.doi.org/10.1007/s00259-023-06240-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Mauguen, Audrey Grewal, Ravinder K. Augensen, Finn Abusamra, Murad Mahajan, Sonia Jayaprakasam, Vetri Sudar Osborne, Joseph Haque, Sofia Wong, Bernadette Z. Y. Ghossein, Ronald A. Fagin, James Schӧder, Heiko Tuttle, R. Michael Ho, Alan Humm, John L. Larson, Steven M. The use of single-timepoint images to link administered radioiodine activity (MBq) to a prescribed lesion radiation-absorbed dose (cGy): a regression-based prediction interval tool for the management of well-differentiated thyroid cancer patients |
title | The use of single-timepoint images to link administered radioiodine activity (MBq) to a prescribed lesion radiation-absorbed dose (cGy): a regression-based prediction interval tool for the management of well-differentiated thyroid cancer patients |
title_full | The use of single-timepoint images to link administered radioiodine activity (MBq) to a prescribed lesion radiation-absorbed dose (cGy): a regression-based prediction interval tool for the management of well-differentiated thyroid cancer patients |
title_fullStr | The use of single-timepoint images to link administered radioiodine activity (MBq) to a prescribed lesion radiation-absorbed dose (cGy): a regression-based prediction interval tool for the management of well-differentiated thyroid cancer patients |
title_full_unstemmed | The use of single-timepoint images to link administered radioiodine activity (MBq) to a prescribed lesion radiation-absorbed dose (cGy): a regression-based prediction interval tool for the management of well-differentiated thyroid cancer patients |
title_short | The use of single-timepoint images to link administered radioiodine activity (MBq) to a prescribed lesion radiation-absorbed dose (cGy): a regression-based prediction interval tool for the management of well-differentiated thyroid cancer patients |
title_sort | use of single-timepoint images to link administered radioiodine activity (mbq) to a prescribed lesion radiation-absorbed dose (cgy): a regression-based prediction interval tool for the management of well-differentiated thyroid cancer patients |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382352/ https://www.ncbi.nlm.nih.gov/pubmed/37171634 http://dx.doi.org/10.1007/s00259-023-06240-1 |
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