Evidence map›Paper›PMID 27405726›Full record

ArticleBrain connectivity2016

Network Analysis on Predicting Mean Diffusivity Change at Group Level in Temporal Lobe Epilepsy.

Farras Abdelnour, Ashish Raj, Orrin Devinsky, Thomas Thesen

Abstract read
In one paragraph

Article in Brain connectivity, 2016. 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
  3. 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

4 authors.

Farras Abdelnour1 Department of Radiology, Weill Cornell Medical College , New York, New York.
Ashish Raj1 Department of Radiology, Weill Cornell Medical College , New York, New York.
Orrin Devinsky2 Department of Neurology, New York University , New York, New York.
Thomas Thesen2 Department of Neurology, New York University , New York, New York.

Funding

Multimodal modeling framework for fusing structural and functional connectome dataR01EB022717 · NIBIB · WEILL MEDICAL COLL OF CORNELL UNIV · PI NAGARAJAN, SRIKANTAN S., RAJ, ASHISH · 2016 to 2018
$1.6M
NIBIB NIH HHS R01 EB022717
6 · The paper itself

Abstract

The two most common types of temporal lobe epilepsy are medial temporal sclerosis (TLE-MTS) epilepsy and MRI-normal temporal lobe epilepsy (TLE-no). TLE-MTS is specified by its stereotyped focus and spread pattern of neuronal damage, with pronounced neuronal loss in the hippocampus. TLE-no exhibits normal-appearing hippocampus and more widespread neuronal loss. In both cases, neuronal loss spread appears to be constrained by the white matter connections. Both varieties of epilepsy reveal pathological abnormalities in increased mean diffusivity (MD). We model MD distribution as a simple consequence of the propagation of neuronal damage. By applying this model on the structural brain connectivity network of healthy subjects, we can predict at group level the MD gray matter change in the epilepsy cohorts relative to a control group. Diffusion tensor imaging images were acquired from 10 patients with TLE-MTS, 11 patients with TLE-no, and 35 healthy subjects. Statistical validation at the group level suggests high correlation with measured neuronal loss (R = 0.56 for the TLE-MTS group and R = 0.364 for the TLE-no group). The results of this exploratory work pave the way for potential future clinical application of the proposed model on individual patients, including predicting neuronal loss spread, identification of seizure onset zones, and helping in surgical planning.

Indexed as

epilepsygraph theorynetworks

Identifiers

PMID27405726
PMCPMC5069737

What OpenQuestion holds

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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.