ArticleEJNMMI physics2023
Image-derived input functions from dynamic
Article in EJNMMI physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Cerebral oxygen extraction fraction as an emerging imaging biomarker in mild cognitive impairment and dementia.Dementia & neuropsychologia · 2026Review
- Innovations in clinical PET image reconstruction: advances in Bayesian penalized likelihood algorithm and deep learning.Annals of nuclear medicine · 2025Review
- Impact of image reconstruction on cerebral blood flow measured withEJNMMI physics · 2025Article
- Optimizing positron emission tomography for accurate plant imaging using Monte Carlo simulations to correct positron range effects.Scientific reports · 2025Article
- Automated extraction of the arterial input function from brain images for parametric PET studies.EJNMMI research · 2024Article
- Kinetic Modeling of Brain [Metabolites · 2024Article
- ParaPET: non-invasive deep learning method for direct parametric brain PET reconstruction using histoimages.EJNMMI research · 2024Article
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Authors and funding
8 authors.
Funding
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Abstract
backgroundQuantitative positron emission tomography (PET) scans of the brain typically require arterial blood sampling but this is complicated and logistically challenging. One solution to remove the need for arterial blood sampling is the use of image-derived input functions (IDIFs). Obtaining accurate IDIFs, however, has proved to be challenging, mainly due to the limited resolution of PET. Here, we employ penalised reconstruction alongside iterative thresholding methods and simple partial volume correction methods to produce IDIFs from a single PET scan, and subsequently, compare these to blood-sampled input curves (BSIFs) as ground truth. Retrospectively we used data from sixteen subjects with two dynamic
resultsIDIFs and BSIFs agreed well in terms of the area under the curve of input curves when comparing peaks, tails and peak-to-tail ratios with R
conclusionOur results show promising results that a robust IDIF can be produced for dynamic
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