Evidence map›Paper›PMID 33993794›Full record

ArticleJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism2021

Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge.

Mattia Veronese, Gaia Rizzo, Martin Belzunce, Julia Schubert, Graham Searle, Alex Whittington, Ayla Mansur, Joel Dunn, Andrew Reader, Roger N Gunn and 1 more

Abstract readHistorical Article
In one paragraph

Article in Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

  1. Building an open infrastructure for molecular neuroimaging: Standards and tools from the OpenNeuroPET initiative.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
    Review
  2. Article
  3. Review
  4. Article
  5. Review
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  7. Review
  8. Neuroimaging Biomarkers in Addiction.medRxiv : the preprint server for health sciences · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. An automatic analysis framework for FDOPA PET neuroimaging.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2023
    Article
  14. Article
  15. 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

11 authors.

Mattia VeroneseCentre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.ORCID 0000-0003-3562-0683
Gaia RizzoInvicro LLC, London, UK.
Martin BelzunceSchool of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, London, UK.ORCID 0000-0001-6085-484X
Julia SchubertCentre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Graham SearleInvicro LLC, London, UK.
Alex WhittingtonInvicro LLC, London, UK.
Ayla MansurInvicro LLC, London, UK.ORCID 0000-0002-2512-5745
Joel DunnSchool of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, London, UK.
Andrew ReaderSchool of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, London, UK.
Roger N GunnInvicro LLC, London, UK.
Grand Challenge Participants#

Funding

Department of HealthWellcome TrustWellcome Trust 148/Z/16/Z
6 · The paper itself

Abstract

The reproducibility of findings is a compelling methodological problem that the neuroimaging community is facing these days. The lack of standardized pipelines for image processing, quantification and statistics plays a major role in the variability and interpretation of results, even when the same data are analysed. This problem is well-known in MRI studies, where the indisputable value of the method has been complicated by a number of studies that produce discrepant results. However, any research domain with complex data and flexible analytical procedures can experience a similar lack of reproducibility. In this paper we investigate this issue for brain PET imaging. During the 2018 NeuroReceptor Mapping conference, the brain PET community was challenged with a computational contest involving a simulated neurotransmitter release experiment. Fourteen international teams analysed the same imaging dataset, for which the ground-truth was known. Despite a plurality of methods, the solutions were consistent across participants, although not identical. These results should create awareness that the increased sharing of PET data alone will only be one component of enhancing confidence in neuroimaging results and that it will be important to complement this with full details of the analysis pipelines and procedures that have been used to quantify data.

Indexed as

Congresses as TopicFemaleHistory, 21st CenturyHumansMaleNeuroimagingPositron-Emission TomographyReproducibility of Resultsdata analysisdata sharing“NRM2018 PET Grand Challenge”PETreproducibility crisis

Identifiers

PMID33993794
PMCPMC8504414

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.