Evidence map›Paper›PMID 39355442›Full record

ArticleNetwork neuroscience (Cambridge, Mass.)2024

Modeling the impact of MRI acquisition bias on structural connectomes: Harmonizing structural connectomes.

Jagruti Patel, Mikkel Schöttner, Anjali Tarun, Sebastien Tourbier, Yasser Alemán-Gómez, Patric Hagmann, Thomas A W Bolton

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Network neuroscience (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. The progression of sex differences in brain networks across the lifespan.bioRxiv : the preprint server for biology · 2026
    Article
  2. Review
  3. Article
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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

7 authors.

Jagruti PatelDepartment of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.ORCID https://orcid.org/0009-0005-3249-7626
Mikkel SchöttnerDepartment of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-4521-9837
Anjali TarunDepartment of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-3422-9853
Sebastien TourbierDepartment of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-4441-899X
Yasser Alemán-GómezDepartment of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.ORCID https://orcid.org/0000-0001-6067-8639
Patric HagmannDepartment of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-2854-6561
Thomas A W BoltonDepartment of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-2081-4031

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One way to increase the statistical power and generalizability of neuroimaging studies is to collect data at multiple sites or merge multiple cohorts. However, this usually comes with site-related biases due to the heterogeneity of scanners and acquisition parameters, negatively impacting sensitivity. Brain structural connectomes are not an exception: Being derived from T1-weighted and diffusion-weighted magnetic resonance images, structural connectivity is impacted by differences in imaging protocol. Beyond minimizing acquisition parameter differences, removing bias with postprocessing is essential. In this work we create, from the exhaustive Human Connectome Project Young Adult dataset, a resampled dataset of different

Indexed as

Acquisition biasDiffusion MRIFingerprintingHarmonizationHuman Connectome ProjectNeuroimaging

Identifiers

PMID39355442
PMCPMC11340995

What Socratic 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 Socratic graph.