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Updated: May 8, 2026

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
Published on: November 13, 2016
The effect of structural white matter abnormalities on the clinical course of epilepsy
Victor V Evstigneev1, Volha V Kistsen, Igor V Bulaev
1Department of Neurology and Neurosurgery, Belarusian Medical Academy of Postgraduate Education, Minsk, Belarus.
Objectives:
The aim of this study was to assess the impact of the extent of brain white matter lesions on the development of cognitive and psychoemotional disorders, and to investigate correlations between the degree of integration of brain pathway structures and the clinical features of epilepsy.
Material And Methods:
Forty-six epileptic patients (36 with pharmacoresistant epilepsy and 10 who had been in remission for over a year) and 10 normal volunteers (the control group) were examined. To evaluate diffusion tensor MRI findings, the index of fractional anisotropy (FA) and index of apparent diffusion coefficient (ADC) were used. For an intergroup comparison of DTI data, the Mann-Whitney test was used, criterion; correlation analysis was performed using the Spearman rank correlation coefficient. The threshold of statistical significance was set at р < 0.05.
Results:
A significant difference was noted in the ADC data on the side of the epileptic focus in the patients in persistent remission as compared to the pharmacoresistant patients (р < 0.05). No differences were found between the patient groups' fractional anisotropy data. In cases of mesial temporal sclerosis in patients with pharmacoresistant epilepsy, a "weakening" of the tractography pattern in the opposite hemisphere was found (r = 0.66, p = 0.0005). Decreases in the tracts appearing in brain temporal lobes was typical of patients with pharmacoresistant forms of epilepsy (r = 0.46, p = 0.0005). A pathological decrease in FA and an increase in ADC correlated with the results on the Beck scale and the Spielberger-Khanin anxiety scale (r = -0.2, p < 0.001) as well as with P300 peak latency data (r = 0.23, p < 0.001). Analyses of the peculiarities of EEG patterns and FA data demonstrated a correlation between the existence of epileptic activity and a decrease in FA (r = -0.7, t = -2.44, p = 0.01).
Conclusions:
Microstructural brain matter changes make it possible to assess the course of epilepsy to predict the outcomes of medicamental correction of paroxysmal states.
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