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

Hippocampal sclerosis and temporal lobe epilepsy following febrile status epilepticus: The FEBSTAT study

OBJECTIVE

This study was undertaken to determine whether hippocampal T2 hyperintensity predicts sequelae of febrile status epilepticus, including hippocampal atrophy, sclerosis, and mesial temporal lobe epilepsy.

METHODS

Acute magnetic resonance imaging (MRI) was obtained within a mean of 4.4 (SD = 5.5, median = 2.0) days after febrile status on >200 infants with follow-up MRI at approximately 1, 5, and 10 years. Hippocampal size, morphology, and T2 signal intensity were scored visually by neuroradiologists blinded to clinical details. Hippocampal volumetry provided quantitative measurement. Upon the occurrence of two or more unprovoked seizures, subjects were reassessed for epilepsy. Hippocampal volumes were normalized using total brain volumes.

RESULTS

Fourteen of 22 subjects with acute hippocampal T2 hyperintensity returned for follow-up MRI, and 10 developed definite hippocampal sclerosis, which persisted through the 10-year follow-up. Hippocampi appearing normal initially remained normal on visual inspection. However, in subjects with normal-appearing hippocampi, volumetrics indicated that male, but not female, hippocampi were smaller than controls, but increasing hippocampal asymmetry was not seen following febrile status. Forty-four subjects developed epilepsy; six developed mesial temporal lobe epilepsy and, of the six, two had definite, two had equivocal, and two had no hippocampal sclerosis. Only one subject developed mesial temporal epilepsy without initial hyperintensity, and that subject had hippocampal malrotation. Ten-year cumulative incidence of all types of epilepsy, including mesial temporal epilepsy, was highest in subjects with initial T2 hyperintensity and lowest in those with normal signal and no other brain abnormalities.

SIGNIFICANCE

Hippocampal T2 hyperintensity following febrile status epilepticus predicted hippocampal sclerosis and significant likelihood of mesial temporal lobe epilepsy. Normal hippocampal appearance in the acute postictal MRI was followed by maintained normal appearance, symmetric growth, and lower risk of epilepsy. Volumetric measurement detected mildly decreased hippocampal volume in males with febrile status.

The asymmetry of glymphatic system dysfunction in patients with temporal lobe epilepsy: A DTI-ALPS study

BACKGROUND AND PURPOSE

While the occurrence of glymphatic system dysfunction has been observed in temporal lobe epilepsy (TLE), the potential asymmetry of this system has yet to be investigated in the TLE context. We aimed to investigate the glymphatic system function in both hemispheres and to analyze asymmetric features of the glymphatic system in TLE patients using diffusion tensor image analysis along the perivascular space (DTI-ALPS) method.

MATERIALS AND METHODS

43 patients (left TLE (LTLE), n = 20; right TLE (RTLE), n = 23) and 39 healthy controls (HC) were enrolled in this study. The DTI-ALPS index was calculated for the left (left ALPS index) and right (right ALPS index) hemispheres respectively. An asymmetry index (AI) was calculated by AI = (Right - Left)/ [(Right + Left)/2] to represent the asymmetric pattern. Independent two sample t-test, two-sample paired t-test or one-way ANOVA with Bonferroni correction were conducted to compare the differences in ALPS indices and AI among the groups.

RESULTS

Both left ALPS index (p = 0.040) and right ALPS index (p = 0.001) of RTLE patients were significantly decreased, while only left ALPS index of LTLE patients (p = 0.005) was reduced. Compared to contralateral ALPS index, the ipsilateral ALPS index was significantly decreased in TLE (p = 0.008) and RTLE (p = 0.009) patients. Leftward asymmetry of the glymphatic system was found in HC (p = 0.045) and RTLE (p = 0.009) patients. The LTLE patients presented reduced asymmetric traits when compared to RTLE patients (p = 0.029).

CONCLUSION

The TLE patients exhibited altered ALPS indices, which could be triggered by glymphatic system dysfunction. Altered ALPS indices were more severe in ipsilateral than in the contralateral hemisphere. Moreover, LTLE and RTLE patients exhibited different change patterns of the glymphatic system. In addition, glymphatic system function presented asymmetric patterns in both normal adult brain and RTLE patients.

Alteration of intracranial blood perfusion in temporal lobe epilepsy, an arterial spin labeling study

Background

A critical necessity before surgical resection in mesial temporal lobe epilepsy (mTLE) is lateralizing the seizure focus in the temporal lobe. This study aimed to investigate the differences in perfusion pattern changes in right and left mTLE.

Methods

42 mTLE patients (22 left and 20 right mTLE) and 14 controls were surveyed with pulsed arterial spin labeling at 3.0 T. The mean cerebral blood flow (CBF) and asymmetry index (AI) were calculated in the bilateral temporal lobe, amygdala, hippocampus, parahippocampus, and nine bilateral vascular territories ROIs. The alterations in whole-brain CBF were identified using statistical parametric mapping (SPM).

Results

CBF decreased in ipsilateral sides in both epilepsy subcohorts, with right mTLE showing a significant difference in most ROIs while left mTLE exhibiting no significant change. CBF comparison of left mTLE and controls showed a significant drop in ROI analysis in left middle temporal and left intermediate posterior cerebral artery and in AI analysis in parahippocampus, distal anterior cerebral artery, distal middle cerebral artery, and intermediate anterior cerebral artery. CBF hypoperfusion was seen in ROI analysis in the left intermediate anterior cerebral artery, left middle temporal, right middle temporal, left superior temporal in the right mTLE compared to controls. Left mTLE CBF differed significantly from right mTLE CBF in right distal middle cerebral artery ROI and AI of proximal middle cerebral artery.

Conclusion

Our result revealed that mTLE affects extratemporal regions and both mTLE subcohorts with different perfusion patterns, which may enhance the performance of preoperative MRI assessment in lateralization procedures.

Morphometric and microstructural characteristics of hippocampal subfields in mesial temporal lobe epilepsy and their correlates with mnemonic discrimination

Introduction

Pattern separation (PS) is a fundamental aspect of memory creation that defines the ability to transform similar memory representations into distinct ones, so they do not overlap when storing and retrieving them. Experimental evidence in animal models and the study of other human pathologies have demonstrated the role of the hippocampus in PS, in particular of the dentate gyrus (DG) and CA3. Patients with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HE) commonly report mnemonic deficits that have been associated with failures in PS. However, the link between these impairments and the integrity of the hippocampal subfields in these patients has not yet been determined. The aim of this work is to explore the association between the ability to perform mnemonic functions and the integrity of hippocampal CA1, CA3, and DG in patients with unilateral MTLE-HE.

Method

To reach this goal we evaluated the memory of patients with an improved object mnemonic similarity test. We then analyzed the hippocampal complex structural and microstructural integrity using diffusion weighted imaging.

Results

Our results indicate that patients with unilateral MTLE-HE present alterations in both volume and microstructural properties at the level of the hippocampal subfields DG, CA1, CA3, and the subiculum, that sometimes depend on the lateralization of their epileptic focus. However, none of the specific changes was found to be directly related to the performance of the patients in a pattern separation task, which might indicate a contribution of various alterations to the mnemonic deficits or the key contribution of other structures to the function.

Discussion

we established for the first time the alterations in both the volume and the microstructure at the level of the hippocampal subfields in a group of unilateral MTLE patients. We observed that these changes are greater in the DG and CA1 at the macrostructural level, and in CA3 and CA1 in the microstructural level. None of these changes had a direct relation to the performance of the patients in a pattern separation task, which suggests a contribution of various alterations to the loss of function.

Application of Artificial Intelligence in Image Processing of Neurodegenerative Disorders: A Review Study

: Neurodegenerative diseases can make life difficult and lead to death in many cases. They also can be difficult, time-consuming, and costly to diagnose with enough accuracy/certainty. Artificial intelligence (AI) has shown promise in tackling some of the challenges present in medical imaging and is anticipated to become a crucial tool in health care applications in the near future. In particular, deep learning methods have displayed great performance in various subfields of image processing, including but not limited to image segmentation, image synthesis, and image reconstruction. In this paper, many state-of-the-art applications of deep learning models in image processing were reviewed.

Epilepsy in Pediatric Patients—Evaluation of Brain Structures’ Volume Using VolBrain Software

Epilepsy is one of the most frequent serious brain disorders. Approximately 30,000 of the 150,000 children and adolescents who experience unprovoked seizures are diagnosed with epilepsy each year. Magnetic resonance imaging is the method of choice in diagnosing and monitoring patients with this condition. However, one very effective tool using MR images is volBrain software, which automatically generates information about the volume of brain structures. A total of 57 consecutive patients (study group) suffering from epilepsy and 34 healthy patients (control group) who underwent MR examination qualified for the study. Images were then evaluated by volBrain. Results showed atrophy of the brain and particular structures—GM, cerebrum, cerebellum, brainstem, putamen, thalamus, hippocampus and nucleus accumbens volume. Moreover, the statistically significant difference in the volume between the study and the control group was found for brain, lateral ventricle and putamen. A volumetric analysis of the CNS in children with epilepsy confirms a decrease in the volume of brain tissue. A volumetric assessment of brain structures based on MR data has the potential to be a useful diagnostic tool in children with epilepsy and can be implemented in clinical work; however, further studies are necessary to enhance the effectiveness of this software.

Comparison of Hippocampal Subfield Segmentation Agreement between 2 Automated Protocols across the Adult Life Span

BACKGROUND AND PURPOSE

The hippocampus is a frequent focus of quantitative neuroimaging research, and structural hippocampal alterations are related to multiple neurocognitive disorders. An increasing number of neuroimaging studies are focusing on hippocampal subfield regional involvement in these disorders using various automated segmentation approaches. Direct comparisons among these approaches are limited. The purpose of this study was to compare the agreement between two automated hippocampal segmentation algorithms in an adult population.

MATERIALS AND METHODS

We compared the results of 2 automated segmentation algorithms for hippocampal subfields (FreeSurfer v6.0 and volBrain) within a single imaging data set from adults (n = 176, 89 women) across a wide age range (20-79 years). Brain MR imaging was acquired on a single 3T scanner as part of the IXI Brain Development Dataset and included T1- and T2-weighted MR images. We also examined subfield volumetric differences related to age and sex and the impact of different intracranial volume and total hippocampal volume normalization methods.

RESULTS

Estimated intracranial volume and total hippocampal volume of both protocols were strongly correlated (r = 0.93 and 0.9, respectively; both P < .001). Hippocampal subfield volumes were correlated (ranging from r = 0.42 for the subiculum to r = 0.78 for the cornu ammonis [CA]1, all P < .001). However, absolute volumes were significantly different between protocols. volBrain produced larger CA1 and CA4-dentate gyrus and smaller CA2-CA3 and subiculum volumes compared with FreeSurfer v6.0. Regional age- and sex-related differences in subfield volumes were qualitatively and quantitatively different depending on segmentation protocol and intracranial volume/total hippocampal volume normalization method.

CONCLUSIONS

The hippocampal subfield volume relationship to demographic factors and disease states should undergo nuanced interpretation, especially when considering different segmentation protocols.

Factors affecting interictal unilateral and bilateral discharges and ictal diffusion patterns of scalp electroencephalogram in temporal lobe epilepsy

BACKGROUND

The interictal discharges of temporal lobe epilepsy (TLE) can be unilateral or bilateral. In addition, the ictal electroencephalogram (EEG) showed the discharges also tend to spread to the contralateral brain in TLE.

OBJECTIVE

The factors influencing unilateral and bilateral interictal discharges in TLE as well as ictal diffusion patterns in scalp EEG during onset of seizure were evaluated in the present study.

MATERIALS AND METHODS

This was a retrospective analysis of 129 patients with TLE. Cases were classified into unilateral and bilateral discharge groups based on interictal discharge patterns in the EEG. Differences between the two groups in age, gender, disease duration, seizure frequency, magnetic resonance imaging (MRI) findings, origin of TLE, antiepileptic drug (AED) administration, and ictal diffusion patterns during seizures were statistically analyzed. In addition, the differences in ictal diffusion patterns between left and right TLE were statistically analyzed.

RESULTS

Statistically significant differences were not observed in gender, disease duration, seizure frequency, MRI findings, administration of AEDs, and ictal diffusion patterns between interictal unilateral and bilateral discharge groups but with statistically significant differences in age and side of origin of the TLE. In addition, whether the EEG-recorded diffusion pattern was confined to the same hemisphere or spread to both hemispheres was investigated and shown statistically significant differences between the left and right temporal lobes.

CONCLUSIONS

Age and side of origin of TLE affects the TLE interictal discharge patterns. Older patients are more prone to bilateral discharges. Bilateral discharges are more common in right TLE, and the onset of EEG more likely to bilateral diffusion in right TLE.

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

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.

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

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.