Evidence map›Paper›PMID 36388214›Full record

ReviewFrontiers in neurology2022

Site effects how-to and when: An overview of retrospective techniques to accommodate site effects in multi-site neuroimaging analyses.

Johanna M M Bayer, Paul M Thompson, Christopher R K Ching, Mengting Liu, Andrew Chen, Alana C Panzenhagen, Neda Jahanshad, Andre Marquand, Lianne Schmaal, Philipp G Sämann

Abstract readReview
In one paragraph

Review in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 2 pooled it
–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

63 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Habenula Alterations in Resting-State Functional Connectivity Among Autistic Individuals.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Characterizing Continuous and Discrete Hybrid Latent Spaces for Structural Connectomes.Proceedings of SPIE--the International Society for Optical Engineering · 2026
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

3 more citing papers are in PubMed but not listed here.

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.

Johanna M M BayerCentre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia.
Paul M ThompsonImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States.
Christopher R K ChingImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States.
Mengting LiuSchool of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China.
Andrew ChenDepartment of Biostatistics, Epidemiology, and Informatics, Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA, United States.
Alana C PanzenhagenPrograma de Pós-graduação em Ciências Biológicas: Bioquímica, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
Neda JahanshadLaboratory of Brain eScience, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, United States.
Andre MarquandDepartment of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboudumc, Nijmegen, Netherlands.
Lianne SchmaalCentre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia.
Philipp G SämannMax Planck Institute of Psychiatry, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Site differences, or systematic differences in feature distributions across multiple data-acquisition sites, are a known source of heterogeneity that may adversely affect large-scale meta- and mega-analyses of independently collected neuroimaging data. They influence nearly all multi-site imaging modalities and biomarkers, and methods to compensate for them can improve reliability and generalizability in the analysis of genetics, omics, and clinical data. The origins of statistical site effects are complex and involve both

Indexed as

ComBatdeep learninggenerative adversarial networks (GANs)MRImulti-site studyneuroimagingnormative modelingsite effect

Identifiers

PMID36388214
PMCPMC9661923

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.