Amygdala enlargement: Temporal lobe epilepsy subtype or nonspecific finding?

Reyes, Anny; Thesen, Thomas; Kuzniecky, Ruben; Devinsky, Orrin; McDonald, Carrie R.; Jackson, Graeme D.; Vaughan, David N.; Blackmon, Karen

doi:10.1016/j.eplepsyres.2017.02.019

Cited by 21 publications

(35 citation statements)

References 20 publications

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“…Hippocampal abnormalities were not observed in this subgroup, suggesting that the patterns of reduced hippocampal grey matter observed in the aggregate group were driven by the inclusion of MTLEs with hippocampal sclerosis. Unlike the IGE, MTLE, and aggregate epilepsy cohorts, this subgroup also showed bilateral enlargement of the amygdala—a phenomenon previously reported in non-lesional localization-related epilepsies ( Reyes et al , 2017 ) and non-lesional MTLEs ( Takaya et al , 2012 ; Coan et al , 2013 ). Non-lesional MTLEs formed a large proportion of this ‘all-other-epilepsies’ cohort (43.3%; 445 individuals), but the subgroup included many other focal and unclassified syndromes, potentially obscuring specific biological interpretations.…”

Section: Discussionsupporting

confidence: 65%

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Whelan

Altmann

Botía³

et al. 2018

Brain

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Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by metaanalysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen's d = À0.24 to À0.73; P 5 1.49 Â 10 À4 ), and lower thickness in the precentral gyri bilaterally (d = À0.34 to À0.52; P 5 4.31 Â 10 À6 ). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = À1.73 to À1.91, P 5 1.4 Â 10 À19 ), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = À0.36 to À0.52; P 5 1.49 Â 10 À4 ). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = À0.29 to À0.54; P 5 1.49 Â 10 À4 ). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = À0.27 to À0.51; P 5 1.49 Â 10 À4 ). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b 5 À0.0018; P 5 1.49 Â 10 À4 ). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.

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Section: Discussionsupporting

confidence: 65%

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Whelan

Altmann

Botía³

et al. 2018

Brain

Self Cite

405

470

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“…Second, the amygdala is a known kindling site in animal studies, where electrical stimulation can lead to recurring after-discharges and seizures (Cleeren et al, 2016; Li et al, 2016; Wicker and Forcelli, 2016). In addition, structural changes occur in patients suffering from temporal lobe epilepsy (Reyes et al, 2017), which further complicates target localization at least in these patients.…”

Section: Connections Of the Amygdala With Motor Areas And Implicationmentioning

confidence: 99%

Beyond Emotions: Oscillations of the Amygdala and Their Implications for Electrical Neuromodulation

Schönfeld

Wojtecki

2019

Front. Neurosci.

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The amygdala is a structure involved in emotions, fear, learning and memory and is highly interconnected with other brain regions, for example the motor cortex and the basal ganglia that are often targets of treatments involving electrical stimulation. Deep brain stimulation of the basal ganglia is successfully used to treat movement disorders, but can carry along non-motor side effects. The origin of these non-motor side effects is not fully understood yet, but might be altered oscillatory communication between specific motor areas and the amygdala. Oscillations in various frequency bands have been detected in the amygdala during cognitive and emotional tasks, which can couple with oscillations in cortical regions or the hippocampus. However, data on oscillatory coupling between the amygdala and motor areas are still lacking. This review provides a summary of oscillation frequencies measured in the amygdala and their possible functional relevance in different species, followed by evidence for connectivity between the amygdala and motor areas, such as the basal ganglia and the motor cortex. We hypothesize that the amygdala could communicate with motor areas through coherence of low frequency bands in the theta-alpha range. Furthermore, we discuss a potential role of the amygdala in therapeutic approaches based on electrical stimulation.

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“…The inclusion of more cases with specific tissue pathology for CNN training will also likely improve performance. The finding of increased amygdala volume along with normal overall hippocampal volumes in cases with temporal lobe seizures was unanticipated, however, increased amygdala volume in temporal lobe epilepsy has been reported previously (Capizzano et al, 2019; Lv et al, 2014; Reyes et al, 2017).…”

Section: Discussionmentioning

confidence: 58%

High resolution automated labeling of the hippocampus and amygdala using a 3D convolutional neural network trained on whole brain 700 μm isotropic 7T MP2RAGE MRI

Pardoe¹,

Antony

Hetherington

et al. 2021

Human Brain Mapping

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Image labeling using convolutional neural networks (CNNs) are a template‐free alternative to traditional morphometric techniques. We trained a 3D deep CNN to label the hippocampus and amygdala on whole brain 700 μm isotropic 3D MP2RAGE MRI acquired at 7T. Manual labels of the hippocampus and amygdala were used to (i) train the predictive model and (ii) evaluate performance of the model when applied to new scans. Healthy controls and individuals with epilepsy were included in our analyses. Twenty‐one healthy controls and sixteen individuals with epilepsy were included in the study. We utilized the recently developed DeepMedic software to train a CNN to label the hippocampus and amygdala based on manual labels. Performance was evaluated by measuring the dice similarity coefficient (DSC) between CNN‐based and manual labels. A leave‐one‐out cross validation scheme was used. CNN‐based and manual volume estimates were compared for the left and right hippocampus and amygdala in healthy controls and epilepsy cases. The CNN‐based technique successfully labeled the hippocampus and amygdala in all cases. Mean DSC = 0.88 ± 0.03 for the hippocampus and 0.8 ± 0.06 for the amygdala. CNN‐based labeling was independent of epilepsy diagnosis in our sample (p = .91). CNN‐based volume estimates were highly correlated with manual volume estimates in epilepsy cases and controls. CNNs can label the hippocampus and amygdala on native sub‐mm resolution MP2RAGE 7T MRI. Our findings suggest deep learning techniques can advance development of morphometric analysis techniques for high field strength, high spatial resolution brain MRI.

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Amygdala enlargement: Temporal lobe epilepsy subtype or nonspecific finding?

Cited by 21 publications

References 20 publications

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Beyond Emotions: Oscillations of the Amygdala and Their Implications for Electrical Neuromodulation

High resolution automated labeling of the hippocampus and amygdala using a 3D convolutional neural network trained on whole brain 700 μm isotropic 7T MP2RAGE MRI

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