Evidence map›Paper›PMID 39099405›Full record

ArticleBrain and behavior2024

Characterizing white matter connectome abnormalities in patients with temporal lobe epilepsy using threshold-free network-based statistics.

Daniel Y Chu, Theodore P Imhoff-Smith, Veena A Nair, Timothy Choi, Anusha Adluru, Camille Garcia-Ramos, Kevin Dabbs, Jedidiah Mathis, Andrew S Nencka, Lisa Conant and 7 more

Abstract read
In one paragraph

Article in Brain and behavior, 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. Article
  2. Article
  3. Article
  4. Article
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

17 authors.

Daniel Y ChuDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0001-6455-9514
Theodore P Imhoff-SmithDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0001-9204-063X
Veena A NairDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
Timothy ChoiDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
Anusha AdluruDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
Camille Garcia-RamosDepartment of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0003-4365-9895
Kevin DabbsDepartment of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
Jedidiah MathisDepartment of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Andrew S NenckaDepartment of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Lisa ConantDepartment of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Jeffrey R BinderDepartment of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Mary E MeyerandDepartment of Medical Physics, University of Wisconsin Madison, Madison, Wisconsin, USA.
Andrew L AlexanderWaisman Center, University of Wisconsin Madison, Madison, Wisconsin, USA.
Aaron F StruckDepartment of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
Bruce HermannDepartment of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
Vivek PrabhakaranDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
Nagesh AdluruDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.

Funding

Waisman Center Intellectual and Developmental Disabilities Research CenterP50HD105353 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI Brittany Gail Travers · 2021 to 2026
$8.5M
Integrated Training For Physician-ScientistsT32GM140935 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Anna Huttenlocher, Jeniel E Nett · 2021 to 2026
$6.5M
The Epilepsy Connectome ProjectU01NS093650 · NINDS · MEDICAL COLLEGE OF WISCONSIN · PI BINDER, JEFFREY R, MEYERAND, MARY E. · 2015 to 2018
$5.1M
Stroke Connectome MRI Biomarkers for VCID Risk AssessmentR01NS123378 · NINDS · UNIVERSITY OF WISCONSIN-MADISON · PI Nagesh Adluru, Veena A Nair · 2022 to 2026
$3.6M
The Juvenile Myoclonic Epilepsy Connectome ProjectR01NS111022 · NINDS · UNIVERSITY OF WISCONSIN-MADISON · PI STRUCK, AARON F · 2020 to 2024
$3.1M
Stroke Rehabilitation utilizing BCI technologyR01NS105646 · NINDS · UNIVERSITY OF WISCONSIN-MADISON · PI PRABHAKARAN, VIVEK · 2018 to 2022
$2.3M
American Epilepsy Society 961854NICHD NIH HHS P50 HD105353NIGMS NIH HHS T32 GM140935NIH HHS P50HD105353NIH HHS R01NS105646NIH HHS R01NS111022NIH HHS R01NS123378NIH HHS T32 GM140935NIH HHS U01NS093650NINDS NIH HHS R01 NS105646NINDS NIH HHS R01 NS111022NINDS NIH HHS R01 NS123378NINDS NIH HHS U01 NS093650University of Wisconsin Department of Radiology MSTP Fellowship
6 · The paper itself

Abstract

introductionEmerging evidence illustrates that temporal lobe epilepsy (TLE) involves network disruptions represented by hyperexcitability and other seizure-related neural plasticity. However, these associations are not well-characterized. Our study characterizes the whole brain white matter connectome abnormalities in TLE patients compared to healthy controls (HCs) from the prospective Epilepsy Connectome Project study. Furthermore, we assessed whether aberrant white matter connections are differentially related to cognitive impairment and a history of focal-to-bilateral tonic-clonic (FBTC) seizures.

methodsMulti-shell connectome MRI data were preprocessed using the DESIGNER guidelines. The IIT Destrieux gray matter atlas was used to derive the 162 × 162 structural connectivity matrices (SCMs) using MRTrix3. ComBat data harmonization was applied to harmonize the SCMs from pre- and post-scanner upgrade acquisitions. Threshold-free network-based statistics were used for statistical analysis of the harmonized SCMs. Cognitive impairment status and FBTC seizure status were then correlated with these findings.

resultsWe employed connectome measurements from 142 subjects, including 92 patients with TLE (36 males, mean age = 40.1 ± 11.7 years) and 50 HCs (25 males, mean age = 32.6 ± 10.2 years). Our analysis revealed overall significant decreases in cross-sectional area (CSA) of the white matter tract in TLE group compared to controls, indicating decreased white matter tract integrity and connectivity abnormalities in addition to apparent differences in graph theoretic measures of connectivity and network-based statistics. Focal and generalized cognitive impaired TLE patients showcased higher trend-level abnormalities in the white matter connectome via decreased CSA than those with no cognitive impairment. Patients with a positive FBTC seizure history also showed trend-level findings of association via decreased CSA.

conclusionsWidespread global aberrant white matter connectome changes were observed in TLE patients and characterized by seizure history and cognitive impairment, laying a foundation for future studies to expand on and validate the novel biomarkers and further elucidate TLE's impact on brain plasticity.

Indexed as

ConnectomeEpilepsy, Temporal LobeMagnetic Resonance ImagingWhite MatterAdultBrainCognitive DysfunctionFemaleHumansMaleMiddle AgedNerve NetProspective Studiescognitive impairmentconnectomediffusion‐weighted imaginggeneralized tonic–clonic seizurestemporal lobe epilepsy

Identifiers

PMID39099405
PMCPMC11298711

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.