ArticleEuropean journal of nuclear medicine and molecular imaging2021
Ultra-low-activity total-body dynamic PET imaging allows equal performance to full-activity PET imaging for investigating kinetic metrics of
Article in European journal of nuclear medicine and molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed, 99 citations in OpenAlex.
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- QUALIPAED-A retrospective quality control study evaluating pediatric long axial field-of-view low-dose FDG-PET/CT.Frontiers in nuclear medicine · 2024Article
- Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning.European journal of nuclear medicine and molecular imaging · 2023Article
- One-tenth-activity total-body positron emission tomography versus full-activity imaging in patients with a complex of hepatic malignant tumors: a retrospective study.Quantitative imaging in medicine and surgery · 2023Article
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9 authors at 3 institutions in 1 country.
Funding
Abstract
purposeTo investigate the feasibility of ultra-low-activity total-body positron emission tomography (PET) dynamic imaging for quantifying kinetic metrics of 2-[
methodsDynamic total-body PET imaging was performed in 20 healthy volunteers, with eight using full activity (3.7 MBq/kg) of
resultsAll constant rates, corresponding CoVs, and image contrast in different organs were comparable with none significant differences between full- and ultra-low-activity groups. PET images in the ultra-low-activity group generated significantly lower effective radiation dose (median, 0.419 vs. 4.886 mSv, P < 0.001), reduced prompt counts (median, 2.79 vs. 55.68 billion, P < 0.001), and smaller data size (median, 71.11 vs. 723.18 GB, P < 0.001).
conclusionTotal-body dynamic PET imaging using 10× reduction of injected activity could achieve relevant kinetic metrics of
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.