Table · dataset · 2026
Supplementary file 1_Modelling image quality over extended [18F]FDG uptake times for low-dose positron emission mammography.docx
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Description
Introduction<p>This study investigated the effect of [<sup>18</sup>F]fluorodeoxyglucose ([<sup>18</sup>F]FDG) uptake time on image quality in low-dose positron emission mammography (PEM) using kinetic modelling.</p>Methods<p>Fifteen malignant lesions from thirteen women newly diagnosed with breast cancer were imaged using low-dose [<sup>18</sup>F]FDG PEM. Tumour and normal breast tissue time-activity curves (TACs) were generated using a population-based arterial input function (AIF) and a two-tissue compartmental model.
Modelling was performed at [<sup>18</sup>F]FDG doses of 1, 2, 5, and 10 mCi (37, 74, 185, and 370 MBq), and image quality was assessed using contrast-to-noise ratio (CNR) over a 6-hour uptake period.</p>Results<p>Extending uptake times beyond the 1-hour clinical standard significantly improved CNR across all doses, with comparable proportional gains. Relative to 1 hour post-injection, CNR increased by approximately 30% at 1.5 hours, 53% at 2 hours, and 77% at 3 hours, although uncertainty widened at 3 hours and beyond, particularly at the lowest dose (1 mCi).
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Relatively small variations in uptake time were also found to produce substantial changes in the standardized uptake value (SUV).</p>Discussion<p>These findings demonstrate that extending uptake times by even 30 minutes beyond the 1-hour clinical standard may significantly enhance image CNR for low-dose [<sup>18</sup>F]FDG PEM. The sensitivity of SUV to small variations in uptake time supports the need to closely match uptake time between baseline and follow-up scans in treatment response assessment.
Overall, these modelling results encourage further clinical research into optimizing uptake time protocols, which may help support the broader adoption of low-dose PEM in future work.</p>Clinical Trials Registration<p>clinicaltrials.gov/study/NCT03520218, identifier NCT03520218.</p>
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Where it is published
- DOI doi.org/10.3389/fonc.2026.1880803.s001 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
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- Astronomy & Astrophysics · Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Medicine & Health · Ocean & Atmospheric Science · Social Science
- Inferred from text
- Cancer 75% · Image 75% · Oncology and carcinogenesis 71%
Provenance · 1 source records, 19 field assertions
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