European Radiology

, Volume 29, Issue 12, pp 6750–6761 | Cite as

Alterations of white matter network in patients with left and right non-lesional temporal lobe epilepsy

  • Yunli Yu
  • Lan ChuEmail author
  • Chunfeng Liu
  • Mingming Huang
  • Houfen Wang
Molecular Imaging



The goal of this study was to investigate alterations of white matter (WM) network in patients with left non-lesional temporal lobe epilepsy (nl-TLE) and right nl-TLE to assess the relationship between the white matter network properties and clinical parameters.


T1 magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) were acquired for 45 participants, including 30 nl-TLE patients (13 left, 17 right) and 15 healthy controls. Diffusion tensor tractography was computed to model the WM structural network. The topologic properties of the WM network were obtained by graph theoretical analysis, and the between-group differences in global and nodal properties of the WM network were examined by network-based statistical analysis (NBS). The relationship between WM network properties and clinical parameters was assessed by Pearson’s correlation analysis.


NBS results indicated that patients with left and right nl-TLE experienced distinct changes of WM nodal and global network properties compared with HCs. Positive correlation coefficients were found in several regions. The structural disruptions of networks in the two nl-TLE groups were observed to be different in distribution and severity.


This study provides evidence for changes of the WM network topological properties and structural connectivity in nl-TLE patients, which provide useful insights for the understanding of disease mechanisms of TLE and improving treatment outcomes for nl-TLE.

Key Points

• This study aims to investigate alterations of white matter (WM) network in patients with non-lesional temporal lobe epilepsy (nl-TLE).

• Network-based statistical analysis results indicated that patients with left and right nl-TLE experienced distinct changes of WM nodal and global network properties compared with healthy controls.

• This study provides useful insights for the understanding of disease mechanisms of TLE and improving treatment outcomes for nl-TLE.


Non-lesional temporal lobe epilepsy White matter network Diffusion tensor tractography Graph theory 





Boston Naming Test


Diffusion tensor imaging


Digit symbol substitution test




Fractional anisotropy


Fiber assignment by continuous tracking


Field of view


Hamilton Depression Scale


Healthy controls


Hippocampal sclerosis


Mini-mental state examination


Montreal Neurological Institute


Montreal Cognitive Assessment


Magnetic resonance imaging


Mesial TLE


Non-lesional temporal lobe epilepsy


Posterior cingulate gyrus


Superior frontal gyrus (dorsolateral)


Superior parietal gyrus


Tract-based spatial statistics method


Echo time


Temporal lobe epilepsy


Repetition time


White matter



The authors state that this work has not received any funding.

Compliance with ethical standards


The scientific guarantor of this publication is Lan Chu.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors has significant statistical expertise.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.


• prospective

• diagnostic or prognostic study

• performed at one institution


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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  1. 1.Department of NeurologyThe Second Affiliated Hospital of Soochow UniversitySuzhouChina
  2. 2.Department of NeurologyThe Affiliated Hospital of Guizhou Medical UniversityGuiyangChina
  3. 3.Department of Neurology, Institute of NeuroscienceSoochow UniversitySuzhouChina
  4. 4.Department of ImageThe Affiliated Hospital of Guizhou Medical UniversityGuiyangChina

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