2021
DOI: 10.3390/medicina57030294
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The Most Common Lesions Detected by Neuroimaging as Causes of Epilepsy

Abstract: Epilepsy is a common neurological disorder characterized by chronic, unprovoked and recurrent seizures, which are the result of rapid and excessive bioelectric discharges in nerve cells. Neuroimaging is used to detect underlying structural abnormalities which may be associated with epilepsy. This paper reviews the most common abnormalities, such as hippocampal sclerosis, malformations of cortical development and vascular malformation, detected by neuroimaging in patients with epilepsy to help understand the co… Show more

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Cited by 10 publications
(5 citation statements)
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References 77 publications
(32 reference statements)
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“…Epilepsy, one of the most common neurological disorders, affects over 50 million people worldwide ( 1 ). It is characterized by chronic, unprovoked, and recurrent seizures ( 2 ). Epilepsy is usually complicated by numerous neurobiological disorders, cognitive impairment, and psychosocial ramifications, which lead to a severe economic burden and deterioration in the quality of life ( 1 5 ).…”
Section: Introductionmentioning
confidence: 99%
“…Epilepsy, one of the most common neurological disorders, affects over 50 million people worldwide ( 1 ). It is characterized by chronic, unprovoked, and recurrent seizures ( 2 ). Epilepsy is usually complicated by numerous neurobiological disorders, cognitive impairment, and psychosocial ramifications, which lead to a severe economic burden and deterioration in the quality of life ( 1 5 ).…”
Section: Introductionmentioning
confidence: 99%
“…As this name implies, focal seizures tend to be associated with damage to a part of the brain in contrast to generalized seizures (not including generalized seizure resulting secondarily to partial seizures). The most common site of epileptogenic foci are structures within the medial temporal lobes and especially the hippocampus [112].…”
Section: Epilepsymentioning
confidence: 99%
“… 16 - 19 Incorporating network analyses in such models could be helpful ( Figure 1B ). 20 - 22 For example, structural networks have shown promise in predicting seizure outcomes after surgery. 23 - 27 Specifically, more abnormalities remaining in structural networks spared by surgery correlated with post-operative seizure recurrence.…”
Section: Progressmentioning
confidence: 99%