Evidence map›Paper›PMID 42245019›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Gray Matter Morphological Networks are Associated with Neurobiological Features, Cognitive Status and Clinical Recovery in Traumatic Brain Injury.

Amir Sadikov, Lanya T Cai, Jaclyn Xiao, Esther L Yuh, Hannah L Choi, Xiaoying Sun, Christine L Mac Donald, Mary J Vassar, Ramon Diaz-Arrastia, Joseph T Giacino and 8 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Amir SadikovDepartment of Radiology & Biomedical Imaging, UCSF, San Francisco, CA, USA.ORCID 0000-0002-0253-3543
Lanya T CaiDepartment of Radiology & Biomedical Imaging, UCSF, San Francisco, CA, USA.ORCID 0000-0001-6750-6506
Jaclyn XiaoDepartment of Radiology & Biomedical Imaging, UCSF, San Francisco, CA, USA.ORCID 0009-0001-5958-8465
Esther L YuhDepartment of Radiology & Biomedical Imaging, UCSF, San Francisco, CA, USA.
Hannah L ChoiDepartment of Radiology & Biomedical Imaging, UCSF, San Francisco, CA, USA.ORCID 0000-0003-0556-8351
Xiaoying SunBiostatistics Research Center, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA.
Christine L Mac DonaldDepartment of Neurological Surgery, University of Washington, Seattle, WA, USA.
Mary J VassarBrain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA.
Ramon Diaz-ArrastiaDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Joseph T GiacinoDepartment of Physical Medicine & Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, MA, USA.
David O OkonkwoDepartment of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Claudia S RobertsonDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.
Murray B SteinDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, USA.
Nancy TemkinDepartment of Neurological Surgery, University of Washington, Seattle, WA, USA.
Michael A McCreaDepartments of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI, USA.
Sonia JainBiostatistics Research Center, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA.
Geoffrey T ManleyBrain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA.
Pratik MukherjeeDepartment of Radiology & Biomedical Imaging, UCSF, San Francisco, CA, USA.ORCID 0000-0001-7473-7409

Funding

Transforming Research and Clinical Knowledge in Traumatic Brain InjuryU01NS086090 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DIAZ-ARRASTIA, RAMON, GIACINO, JOSEPH THOMAS · 2013 to 2017
$19.1M
NINDS NIH HHS U01 NS086090
6 · The paper itself

Abstract

Generalizable neuroimaging biomarkers that detect cerebral cortical changes after traumatic brain injury (TBI) and predict patient outcomes are needed to improve care and to develop targeted therapies. We used morphometric inverse divergence (MIND) analysis of structural MRI to investigate cortical gray matter morphological networks cross-sectionally and longitudinally after TBI and correlate these with symptoms, disability and cognition six months after injury. Our findings support the Triple Network Model from functional MRI of post-traumatic alterations in the relationship between task-positive, default mode and salience networks. However, the strongest associations between early cortical similarity metrics and long-term patient outcomes involved the dorsal attention network and the limbic network as well as similarity metrics across Mesulam's hierarchy of laminar differentiation. Since MIND mapping of cortical gray matter networks only requires data that is a routine part of standard clinical MRI protocols and does not need image harmonization across different scanners, this work reports a promising new tool that is immediately available for advancing research and clinical care in TBI.

Identifiers

PMID42245019
PMCPMC13232381

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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 OpenQuestion graph.