ArticleMedical physics2025
Understanding time-activity curve and time-integrated activity variations in radiopharmaceutical therapy challenge: Experience and results.
Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
Corrections and comments
- Erratum issued
Authors and funding
10 authors.
Funding
Abstract
backgroundThe 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. PURPOSE: To address this critical unmet need, the time-activity curve and time-integrated activity variations (TACTIC) AAPM Grand Challenge was designed to explore the variations in TAC modeling for RPT applications.
methodsLaunched in January 2023, the TACTIC challenge consisted of three phases: i) warm-up phase (phase 0, to gain familiarity with the logistics and the modalities of the challenge), ii) TAC fitting based on data from individual patients (phase 1, rated to determine winner 1), and iii) TAC fitting using population-based data (phase 2, rated to determine winner 2). Based on the distributed synthetic biokinetic data of [
resultsA total of 132 teams from over 30 countries registered for this data-driven challenge, of which 95 individual groups submitted their results throughout the challenge. By presenting participants with an identical set of measurement points previously generated from measured biokinetic data and providing additional a priori information about the procedure at different stages of the challenge, we could assess the degree of variation within the TIAC estimation. We investigated which of the commonly used TIAC estimation methods performs best and could therefore be used to harmonize TAC modeling in RPT dosimetry.
conclusionThe results of the TACTIC challenge demonstrate the large variability in TAC fitting despite the participants receiving identical input data. This highlights the fundamental role of TAC fitting methodology selection in the calculation of absorbed doses in RPT and successfully raises awareness of the need for greater harmonization in dosimetric approaches.
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