Evidence map›Paper›PMID 29971517›Full record

ArticleEJNMMI research2018

Non-invasive kinetic modelling of PET tracers with radiometabolites using a constrained simultaneous estimation method: evaluation with

Hasan Sari, Kjell Erlandsson, Lisbeth Marner, Ian Law, Henrik B W Larsson, Kris Thielemans, Sébastien Ourselin, Simon Arridge, David Atkinson, Brian F Hutton

Open access · goldAbstract read
In one paragraph

Article in EJNMMI research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Non-invasive kinetic modelling approaches for quantitative analysis of brain PET studies.European journal of nuclear medicine and molecular imaging · 2023
    Pooled it
  2. "Pseudo-reference-based Input Function Shape" (pRef-IFS): Towards a True image-derived input function for PET kinetic modeling.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
    Article
  3. Review
  4. Evaluating image-derived input functions for cerebral [Frontiers in nuclear medicine · 2025
    Article
  5. Article
  6. Non-invasive quantification ofEJNMMI research · 2024
    Article
  7. Article
  8. A shortEJNMMI research · 2024
    Article
  9. Non-invasive quantification ofResearch square · 2023
    Article
  10. Quantitation of dynamic total-body PET imaging: recent developments and future perspectives.European journal of nuclear medicine and molecular imaging · 2023
    Review
  11. Article
  12. Review
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 3 countries.

Hasan SariInstitute of Nuclear Medicine, L.5 University College Hospital, 235 Euston Road, London, NW1 2BU, UK. hasan.sari10@gmail.com.
Kjell ErlandssonInstitute of Nuclear Medicine, L.5 University College Hospital, 235 Euston Road, London, NW1 2BU, UK.
Lisbeth MarnerNeurobiology Research Unit, Center for Integrated Molecular Brain Imaging (CIMBI), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
Ian LawDepartment of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
Henrik B W LarssonDepartment of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
Kris ThielemansInstitute of Nuclear Medicine, L.5 University College Hospital, 235 Euston Road, London, NW1 2BU, UK.
Sébastien OurselinCentre for Medical Imaging Computing, Faculty of Engineering, University College London, London, UK.
Simon ArridgeCentre for Medical Imaging Computing, Faculty of Engineering, University College London, London, UK.
David AtkinsonCentre for Medical Imaging, Division of Medicine, University College London, London, UK.
Brian F HuttonInstitute of Nuclear Medicine, L.5 University College Hospital, 235 Euston Road, London, NW1 2BU, UK.
University College London · GBUniversity of Copenhagen · DKUniversity College Hospital · GBUniversity of Wollongong · AU

Funding

Engineering and Physical Sciences Research Council EP/K005278/1
6 · The paper itself

Abstract

backgroundKinetic analysis of dynamic PET data requires an accurate knowledge of available PET tracer concentration within blood plasma over time, known as the arterial input function (AIF). The gold standard method used to measure the AIF requires serial arterial blood sampling over the course of the PET scan, which is an invasive procedure and makes this method less practical in clinical settings. Traditional image-derived methods are limited to specific tracers and are not accurate if metabolites are present in the plasma.

resultsIn this work, we utilise an image-derived whole blood curve measurement to reduce the computational complexity of the simultaneous estimation method (SIME), which is capable of estimating the AIF directly from tissue time activity curves (TACs). This method was applied to data obtained from a serotonin receptor study (

conclusionsThe results of this work indicate that the proposed method with prior AIF information obtained from a partial volume corrected image-derived whole blood curve, and modelled parent fraction, has the potential to be used as an alternative non-invasive method to perform kinetic analysis of tracers with metabolite products.

Indexed as

Arterial input functionKinetic modellingPET/MRPositron emission tomography

Identifiers

PMID29971517
PMCPMC6029994
OpenAlexW2810300053

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.