Publications by authors named "Neda Mohammadi Mobarakeh"

6 Publications

  • Page 1 of 1

Temporal and extratemporal atrophic manifestation of temporal lobe epilepsy using voxel-based morphometry and corticometry: clinical application in lateralization of epileptogenic zone.

Neurol Sci 2021 Jan 3. Epub 2021 Jan 3.

Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran.

Background: Advances in MRI acquisition and data processing have become important for revealing brain structural changes. Previous studies have reported widespread structural brain abnormalities and cortical thinning in patients with temporal lobe epilepsy (TLE), as the most common form of focal epilepsy.

Methods: In this research, healthy control cases (n = 20) and patients with left TLE (n = 19) and right TLE (n = 14) were recruited, all underwent 3.0 T MRI with magnetization-prepared rapid gradient echo sequence to acquire T1-weighted images. Morphometric alterations in gray matter were identified using voxel-based morphometry (VBM). Volumetric alterations in subcortical structures and cortical thinning were also determined.

Results: Patients with left TLE demonstrated more prevailing and widespread changes in subcortical volumes and cortical thickness than right TLE, mainly in the left hemisphere, compared to the healthy group. Both VBM analysis and subcortical volumetry detected significant hippocampal atrophy in ipsilateral compared to contralateral side in TLE group. In addition to hippocampus, subcortical volumetry found the thalamus and pallidum bilaterally vulnerable to the TLE. Furthermore, the TLE patients underwent cortical thinning beyond the temporal lobe, affecting gray matter cortices in frontal, parietal, and occipital lobes in the majority of patients, more prevalently for left TLE cases. Exploiting volume changes in individual patients in the hippocampus alone led to 63.6% sensitivity and 100% specificity for lateralization of TLE.

Conclusion: Alteration of gray matter volumes in subcortical regions and neocortical temporal structures and also cortical gray matter thickness were evidenced as common effects of epileptogenicity, as manifested by the majority of cases in this study.
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January 2021

Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach.

Neurol Sci 2020 Oct 14. Epub 2020 Oct 14.

Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences, Tehran, Iran.

Purpose: Functional magnetic resonance imaging (fMRI) in resting state can be used to evaluate the functional organization of the human brain in the absence of any task or stimulus. The functional connectivity (FC) has non-stationary nature and consented to be varying over time. By considering the dynamic characteristics of the FC and using graph theoretical analysis and a machine learning approach, we aim to identify the laterality in cases of temporal lobe epilepsy (TLE).

Methods: Six global graph measures are extracted from static and dynamic functional connectivity matrices using fMRI data of 35 unilateral TLE subjects. Alterations in the time trend of the graph measures are quantified. The random forest (RF) method is used for the determination of feature importance and selection of dynamic graph features including mean, variance, skewness, kurtosis, and Shannon entropy. The selected features are used in the support vector machine (SVM) classifier to identify the left and right epileptogenic sides in patients with TLE.

Results: Our results for the performance of SVM demonstrate that the utility of dynamic features improves the classification outcome in terms of accuracy (88.5% for dynamic features compared with 82% for static features). Selecting the best dynamic features also elevates the accuracy to 91.5%.

Conclusion: Accounting for the non-stationary characteristics of functional connectivity, dynamic connectivity analysis of graph measures along with machine learning approach can identify the temporal trend of some specific network features. These network features may be used as potential imaging markers in determining the epileptogenic hemisphere in patients with TLE.
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October 2020

Graph theory application with functional connectivity to distinguish left from right temporal lobe epilepsy.

Epilepsy Res 2020 11 6;167:106449. Epub 2020 Sep 6.

Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences(TUMS), Tehran, Iran; Research Center for Molecular and Cellular Imaging, Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran. Electronic address:

Objective: To investigate the application of graph theory with functional connectivity to distinguish left from right temporal lobe epilepsy (TLE).

Methods: Alterations in functional connectivity within several brain networks - default mode (DMN), attention (AN), limbic (LN), sensorimotor (SMN) and visual (VN) - were examined using resting-state functional MRI (rs-fMRI). The study accrued 21 left and 14 right TLE as well as 17 nonepileptic control subjects. The local nodal degree, a feature of graph theory, was calculated foreach of the brain networks. Multivariate logistic regression analysis was performed to determine the accuracy of identifying seizure laterality based on significant differences in local nodal degree in the selected networks.

Results: Left and right TLE patients showed dissimilar patterns of alteration in functional connectivity when compared to control subjects. Compared with right TLE, patients with left TLE exhibited greater nodal degree' (i.e. hyperconnectivity) with right superomedial frontal gyrus (in DMN), inferior frontal gyrus pars triangularis (in AN), right caudate and left superior temporal gyrus (in LN) and left paracentral lobule (in SMN), while showing lesser nodal degree (i.e. hypoconnectivity) with left temporal pole (in DMN), right insula (in LN), left supplementary motor area (in SMN), and left fusiform gyrus (in VN). The LN showed the highest accuracy of 82.9% among all considered networks in determining laterality of the TLE. By combinations of local degree attributes in the DMN, AN, LN, and VN, logistic regression analysis demonstrated an accuracy of 94.3% by comparison.

Conclusion: Our study demonstrates the utility of graph theory application to brain network analysis as a potential biomarker to assist in the determination of TLE laterality and improve the confidence in presurgical decision-making in cases of TLE.
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November 2020

Distinct patterns of hippocampal subfield volume loss in left and right mesial temporal lobe epilepsy.

Neurol Sci 2021 Apr 12;42(4):1411-1421. Epub 2020 Aug 12.

Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences (TUMS), Tehran, Iran.

Objective: To investigate the pattern and severity of hippocampal subfield volume loss in patients with left and right mesial temporal lobe epilepsy (mTLE) using quantitative MRI volumetric analysis.

Methods: A total of 21 left and 14 right mTLE subjects, as well as 15 healthy controls, were enrolled in this cross-sectional study. A publically available magnetic resonance imaging (MRI) brain volumetry system (volBrain) was used for volumetric analysis of hippocampal subfields. The T1-weighted images were processed with a HIPS pipeline.

Results: A distinct pattern of hippocampal subfield atrophy was found between left and right mTLE patients when compared with controls. Patients with left mTLE exhibited ipsilateral hippocampal atrophy and segmental volume depletion of the Cornu Ammonis (CA) 2/CA3, CA4/dentate gyrus (DG), and strata radiatum-lacunosum-moleculare (SR-SL-SM). Those with right mTLE exhibited similar ipsilateral hippocampal atrophy but with additional segmental CA1 volume depletion. More extensive bilateral subfield volume loss was apparent with right mTLE patients.

Conclusion: We demonstrate that left and right mTLE patients show a dissimilar pattern of hippocampal subfield atrophy, suggesting the pathophysiology of epileptogenesis in left and right mTLE to be different.
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April 2021

Evolution of Graph Theory in Dynamic Functional Connectivity for Lateralization of Temporal Lobe Epilepsy.

Annu Int Conf IEEE Eng Med Biol Soc 2019 Jul;2019:628-631

Resting-state functional magnetic resonance imaging (rsfMRI) has described the functional architecture of the human brain in the absence of any task or stimulus. Since the functional connectivity (FC), has non-stationary nature, it is evidenced to be varying over time. Using dynamic functional connectivity, six graph theoretical characteristics were measured and compared between left and right temporal lobe epilepsy (TLE). We also obtain a trend for each characteristic in the time course of experiments. The results demonstrated that the static connectivity analysis failed to fully separate the left and right TLE patients for some characteristics, whereby the dynamic analysis has been shown capable of identifying the laterality. Furthermore, the results suggest that the temporal trend of some graph theoretical characteristics can be exploited as a novel marker for TLE laterality.
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July 2019

1H-MRS metabolite's ratios show temporal alternation in temporal lobe seizure: Comparison between interictal and postictal phases.

Epilepsy Res 2016 12 9;128:158-162. Epub 2016 Sep 9.

Isfahan Neurosciences Research Center, Neurology Department, Isfahan University of Medical Sciences, Isfahan, Iran. Electronic address:

Purposes: To determine H-MRSI metabolites changes in interictal and postictal phases of patients suffering from mesial temporal lobe epilepsy with hippocampal sclerosis and lateralization of seizure foci.

Materials And Methods: MR spectroscopic imaging was performed in 5 adult patients with refractory temporal lobe epilepsy interictally and immediately after the seizure and in 4 adult control subjects. All patients underwent MR imaging and VideoEEG Monitoring.

Results: The results showed statistically significant decreases in N-acetylaspartate/Creatine, N-acetylaspartate/Choline and N-acetylaspartate/(creatine+choline) immediately after ictus in ipsilateral hippocampus as compared with control data and contralateral hippocampus of patients while no statistically significant difference was presented in interictal phase.

Conclusion: The present study clearly indicates H-MRS abnormalities following an ictus of temporal lobe epilepsy with metabolite recovery in interictal phase. This finding suggests postictal H-MRS as a possible useful tool to assist in lateralizing and localizing of seizure foci in epileptic patients with structural lesions.
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December 2016