Evidence map›Paper›PMID 41963485›Full record

ArticleScientific reports2026

Cross-vendor reliability of functional and structural brain connectivity in a travelling cohort.

Lionel Butry, Johanna Thomä, Johannes Forsting, Elena K Enax-Krumova, Lara Schlaffke

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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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

5 authors.

Lionel ButryRuhr University Bochum, BG University Hospital Bergmannsheil, Department of Neurology, Bochum, Germany. lionelbutry@gmail.com.
Johanna ThomäRuhr University Bochum, BG University Hospital Bergmannsheil, Department of Neurology, Bochum, Germany.
Johannes ForstingRuhr University Bochum, BG University Hospital Bergmannsheil, Department of Neurology, Bochum, Germany.
Elena K Enax-KrumovaRuhr University Bochum, BG University Hospital Bergmannsheil, Department of Neurology, Bochum, Germany.
Lara SchlaffkeRuhr University Bochum, BG University Hospital Bergmannsheil, Department of Neurology, Bochum, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Scanner-related bias is a major challenge in multi-centre neuroimaging studies. This study assesses cross-vendor reliability of functional and structural brain connectivity (FC, SC) and evaluates the effect of neuroComBat harmonisation. A travelling cohort (n = 10) of healthy participants was scanned on a Siemens Prisma 3T and a Philips Achieva 3.0T system within one week. Reliability metrics of FC (Pearson’s r) and SC (based on iFOD2 & SIFT2) were calculated for each edge before and after neuroComBat harmonisation. At the subject-level, reliability was poor for FC (ICC: 0.22 ± 0.23, wsCV: 62 ± 14%, unharmonised) and fair for SC (ICC: 0.43 ± 0.32, wsCV: 28 ± 15%, unharmonised). At the group-level, Bland-Altman analyses showed minimal systematic bias between scanners in both modalities, but with wide limits of agreement. Pattern similarity was 0.63 (FC) and 0.98 (SC). G Theory analyses showed the scanner accounted for 11.8% (FC) and 7.9% (SC) of the variance. After harmonisation, subject-level reliability only improved marginally, but scanner-dependent variability dropped to 0.8% and 1.1% in FC and SC, respectively. Overall, reliability was higher for SC than FC mirroring their differential temporal stability, for group-averaged than subject-level data, and for full-connectome organisation than for individual edges. NeuroComBat worked as designed, successfully mitigating scanner-dependent variance at the group but not the subject level.

Indexed as

BrainConnectomeMagnetic Resonance ImagingNeuroimagingAdultBrain MappingCohort StudiesFemaleHumansMaleReproducibility of ResultsConnectomeDTIfMRIGeneralizabilityHarmonisationMagnetic resonance imaging

Identifiers

PMID41963485
PMCPMC13070028

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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.