<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Ivashchenko OV</submitter><funding>Universitas Indonesia</funding><funding>DAAD (German Academic Exchange Service), Förderkennzeichen</funding><pagination>e70043</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12464796</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>52(10)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>The process of determining/calculating the time-activity curve (TAC) for radiopharmaceutical therapy (RPT) is generally heavily dependent on user- and site-dependent steps (e.g., the number and schedule of measurement points to be used, selection of the fit function), each having a notable effect on the determination of the time-integrated activity coefficient (TIAC) and thus on the calculated absorbed dose. Despite the high clinical importance of absorbed doses, there is no consensus on the methodology for processing time-activity data or even a clear understanding of the influence of various uncertainties and user-dependent variations in personalized RPT dosimetry on the accuracy of TAC calculations.&lt;h4>Purpose&lt;/h4>To address this critical unmet need, the time-activity</pubmed_abstract><journal>Medical physics</journal><pubmed_title>Understanding time-activity curve and time-integrated activity variations in radiopharmaceutical therapy challenge: Experience and results.</pubmed_title><pmcid>PMC12464796</pmcid><funding_grant_id>NKB-739/UN2.RST/HKP.05.00/2023</funding_grant_id><funding_grant_id>57657089</funding_grant_id><funding_grant_id>NKB‐739/UN2.RST/HKP.05.00/2023</funding_grant_id><pubmed_authors>O'Doherty J</pubmed_authors><pubmed_authors>Hippelainen E</pubmed_authors><pubmed_authors>Grassi E</pubmed_authors><pubmed_authors>Tran-Gia J</pubmed_authors><pubmed_authors>Glatting G</pubmed_authors><pubmed_authors>Heemskerk JWT</pubmed_authors><pubmed_authors>Sandstrom M</pubmed_authors><pubmed_authors>Hardiansyah D</pubmed_authors><pubmed_authors>Ivashchenko OV</pubmed_authors><pubmed_authors>Cremonesi M</pubmed_authors></additional><is_claimable>false</is_claimable><name>Understanding time-activity curve and time-integrated activity variations in radiopharmaceutical therapy challenge: Experience and results.</name><description>&lt;h4>Background&lt;/h4>The process of determining/calculating the time-activity curve (TAC) for radiopharmaceutical therapy (RPT) is generally heavily dependent on user- and site-dependent steps (e.g., the number and schedule of measurement points to be used, selection of the fit function), each having a notable effect on the determination of the time-integrated activity coefficient (TIAC) and thus on the calculated absorbed dose. Despite the high clinical importance of absorbed doses, there is no consensus on the methodology for processing time-activity data or even a clear understanding of the influence of various uncertainties and user-dependent variations in personalized RPT dosimetry on the accuracy of TAC calculations.&lt;h4>Purpose&lt;/h4>To address this critical unmet need, the time-activity</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Oct</publication><modification>2026-07-14T17:14:21.109Z</modification><creation>2026-06-21T03:12:37.889Z</creation></dates><accession>S-EPMC12464796</accession><cross_references><pubmed>41000030</pubmed><doi>10.1002/mp.70043</doi></cross_references></HashMap>