Evidence map›Paper›PMID 42099305›Full record

ArticleBrain communications2026

Convergent structural brain alterations in chronic pain: a multi-metric individual participant data meta-analysis.

Ryan W J Loke, Oscar Ortiz, Sylvia M Gustin, Michèle Hubli, Clas Linnman, Abigail Livny, Yann Quidé, Paulina S Scheuren, John L K Kramer

Abstract read
In one paragraph

Article in Brain communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Ryan W J LokeDepartment of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine, University of British Columbia, Vancouver, Bc v6t 1z3, Canada.
Oscar OrtizInternational Collaborations on Repair Discoveries (ICORD), University of British Columbia, Vancouver, Bc v5z 1n1, Canada.
Sylvia M GustinNeuroRecovery Research Hub, School of Psychology, The University of New South Wales (UNSW) Sydney, Sydney, NSW 2052, Australia.
Michèle HubliSpinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich 8008, Switzerland.
Clas LinnmanDepartment of Psychiatry, Massachusetts General Brigham & Harvard Medical School, Boston, MA 02115, USA.
Abigail LivnyClinical Brain Imaging R&D Center, Sheba Medical Center, Tel Aviv 5262000, Israel.ORCID https://orcid.org/0000-0003-2216-7357
Yann QuidéNeuroRecovery Research Hub, School of Psychology, The University of New South Wales (UNSW) Sydney, Sydney, NSW 2052, Australia.ORCID https://orcid.org/0000-0002-8569-7139
Paulina S ScheurenDepartment of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine, University of British Columbia, Vancouver, Bc v6t 1z3, Canada.ORCID https://orcid.org/0000-0001-7568-0133
John L K KramerDepartment of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine, University of British Columbia, Vancouver, Bc v6t 1z3, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic pain is a leading contributor to all-cause morbidity and disability, encompassing numerous biopsychosocial dimensions that persistently engage complex networks of brain regions. Meta-analyses have advanced our understanding of structural brain differences in chronic pain but rely exclusively on summary statistics which may introduce heterogeneity related to completeness of reporting and differences in methodological approaches. To address these limitations, we conducted the first individual participant data (IPD) meta-analysis of brain structure alterations in chronic pain. Using traditional morphometric measures (i.e. volume, cortical thickness, and surface area) and differential-geometric shape metrics (i.e. intrinsic and extrinsic curvature), we aimed to reveal alterations in brain structure convergent across chronic pain conditions. We hypothesized that chronic pain would be associated with region-specific grey matter reductions in regions previously implicated in chronic pain (e.g. parahippocampal gyrus and insula) and explored whether curvature metrics would reveal additional structural changes. Anatomical MRI images from eight publicly available datasets spanning five conditions and 401 individuals with chronic pain (and 245 age- and sex- matched healthy controls) were analysed: (i) knee osteoarthritis, (ii) chronic low back pain, (iii) fibromyalgia, (iv) migraine, and (v) primary trigeminal neuralgia. FreeSurfer was used to parcellate T1-weighted anatomical images, and metrics for cortical and subcortical regions were extracted. Meta-analysis revealed a range of structural changes in the brain associated with chronic pain. Cortical thinning and volume loss were small and localized to the temporo-occipital regions, including bilateral volumetric reductions in the entorhinal cortex in individuals with chronic pain. Increases in intrinsic curvature were widespread, involving 49 out of 68 cortical regions. No significant alterations were detected in subcortical volumes. Intrinsic curvature and subcortical volumetric estimates had higher levels of inter-study heterogeneity compared to other metrics, reflecting potential condition and sample-specific variability. Leveraging harmonized processing across a large sample size, our novel IPD meta-analysis highlights both widespread and region-specific structural remodelling of chronic pain-related neuroanatomy.

Indexed as

brain morphologychronic paincurvatureindividual participant data meta-analysis

Identifiers

PMID42099305
PMCPMC13148768

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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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 Socratic graph.