Results 121 to 130 of about 402,861 (290)

Multimodal modeling of the ictal onset zone in refractory insular epilepsy and seizure outcome of magnetic resonance‐guided laser interstitial therapy: A pediatric single‐center retrospective study

Epilepsia, EarlyView.
Abstract Objective This study was undertaken to evaluate seizure outcomes after magnetic resonance‐guided laser interstitial thermal therapy (MRgLITT) in children with insular epilepsy and to assess how the extent of ablation overlaps with multimodal definitions of the ictal onset zone (IOZ).
Lelio Guida, Emma Losito, Sebastian Rodrigo, Catherine Chiron, Ludovic Fillon, Marie Bourgeois, Anna Kaminska, Johan Pallud, Nicole Chemaly, Volodia Dangouloff‐Ross, Stephane Auvin, Blandine Dozieres, Rima Nabbout, Olivier David, Nathalie Boddaert, Thomas Blauwblomme   +15 more
wiley   +1 more source

Transcriptomic analysis reveals distinct expression patterns in focal cortical dysplasia

Epilepsia, EarlyView.
Abstract Objective Focal cortical dysplasia (FCD) is a common cause of drug‐resistant epilepsy in children and adults and exhibits substantial clinical and histopathological heterogeneity. However, morphological classification alone does not fully explain variability in epileptogenicity, disease severity, or treatment response.
Shivani Sonawane, Michal Hendrych, Michaela Ručková, Robin Jugas, Jan Vrbský, Martin Pail, Barbora Straka, Martina Strnadová, Lenka Krsková, Adam Vácha, Miroslav Koblížek, Barbora Splítková, Kateřina Koželková, Eliška Hloušková, Tereza Vaňková, Josef Zámečník, Štefánia Aulická, Markéta Hermanová, Pavel Kršek, Ondřej Slabý, Milan Brázdil   +20 more
wiley   +1 more source

FOCAL CORTICAL DYSPLASIA: ALGORITHM OF PREOPERATIVE EXAMINATION

, 2016
In this paper we are discussing the issues of diagnosis, classification, features of preoperative evaluation and surgical treatment of focal cortical dysplasia in children. Particular attention is paid to the complexities of visualization of FCD, as well
S. O. Ayvazyan
core  

Repetitive clustered low‐voltage fast activity on intracranial electroencephalogram in mild malformation of cortical development with oligodendroglial hyperplasia and epilepsy: A candidate electroencephalographic biomarker study

Epilepsia, EarlyView.
Abstract Objective Mild malformation of cortical development with oligodendroglial hyperplasia and epilepsy (MOGHE) is a recently recognized cause of drug‐resistant focal epilepsy. It is often magnetic resonance imaging‐negative or radiologically resembles focal cortical dysplasias, which makes recognition difficult and limits presurgical counseling ...
Vadym Gnatkovsky, Ekaterina Poguzhelskaya, Valeri Borger, Tobias Baumgartner, Rainer Surges, Kerstin Alexandra Klotz, Valentina Zschernack, Till Hartlieb, Manfred Kudernatsch, Ahmed Gaballa, Thomas Cloppenborg, Friedrich G. Woermann, Thilo Kalbhenn, Hajo Hamer, Stephanie Gollwitzer, Stefan Rampp, Daniel Delev, Florian Mayer, Karl Rössler, Valerie Anne Quinot, Angelika Mühlebner, Rafael Toledano, Antonio Gil‐Nagel, Roland Coras, Ingmar Blümcke, Katja Kobow   +25 more
wiley   +1 more source

Reasons for not reoperating and outcomes of reoperation after seizure recurrence in pediatric epilepsy surgery: A population‐based study

Epilepsia, EarlyView.
Abstract Objective Epilepsy surgery is an established and effective treatment for children with drug‐resistant epilepsy. Although the majority of patients become seizure‐free postoperatively, 20%–40% experience seizure recurrence. Although repeat surgery can achieve seizure freedom in selected cases, the reasons children with seizure recurrence do not ...
Vincent Zheng, Atte Karppinen, Eija Gaily, Päivi Koroknay‐Pál, Henri Lehtinen, Eeva‐Liisa Metsähonkala   +5 more
wiley   +1 more source

Cortical neuronal densities and lamination in focal cortical dysplasia.

, 2005
Focal cortical dysplasia (FCD) is considered to represent a malformation due to abnormal cortical development (MCD) and is an important cause of focal epilepsy.
Martinian, L, Sisodiya, SM, Sen, A, Thom, M, Sen, Arjune, Cross, JH, Harding, BN   +6 more
core   +1 more source

Epilepsy syndromes classification

Epilepsia Open, EarlyView.
Abstract Epilepsy syndromes are distinct electroclinical entities which have been recently defined by the International League Against Epilepsy Nosology and Definitions Task Force. Each syndrome is associated with “a characteristic cluster of clinical and EEG features, often supported by specific etiologic findings”.
Elaine C. Wirrell, Nicola Specchio, Rima Nabbout, Phillip L. Pearl, Kate Riney   +4 more
wiley   +1 more source

Precision therapies for genetic epilepsies in 2025: Promises and pitfalls

Epilepsia Open, EarlyView.
Abstract By targeting the underlying etiology, precision therapies offer an exciting paradigm shift to improve the stagnant outcomes of drug‐resistant epilepsies, including developmental and epileptic encephalopathies. Unlike conventional antiseizure medications (ASMs) which only treat the symptoms (seizures) but have no effect on the underlying ...
Shuyu Wang, Emilio Perucca, Samuel F. Berkovic, Piero Perucca   +3 more
wiley   +1 more source

Febrile status epilepticus and epileptogenesis: The FEBSTAT study

Epilepsia Open, EarlyView.
Abstract The multicenter FEBSTAT study (Consequences of Prolonged Febrile Seizures in Childhood: https://grantome.com/grant/NIH/R37‐NS043209‐12; PI S. Shinnar) examined the outcome of febrile status epilepticus (FSE) in over 200 prospectively enrolled infants, with many followed for 10 years after FSE.
Darrell V. Lewis, Douglas R. Nordli Jr., Douglas R. Nordli III, Shlomo Shinnar, Stephen Chan, Jacqueline A. Bello, L. Matthew Frank, James Voyvodic, William Gallentine, Syndi Seinfeld, Yoshimi Sogawa, Erica Weiss, David Masur, Yuan Xu, Solomon L. Moshé   +14 more
wiley   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source