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Advances in MRI-based diagnosis of temporal lobe epilepsy: Correlating hippocampal subfield volumes with histopathology.
Ellsay, Andrea C; Winston, Gavin P.
Afiliación
  • Ellsay AC; Centre for Neuroscience Studies, Faculty of Health Sciences, Queen's University, Kingston, Ontario, Canada.
  • Winston GP; Centre for Neuroscience Studies, Faculty of Health Sciences, Queen's University, Kingston, Ontario, Canada.
J Neuroimaging ; 2024 Aug 02.
Article en En | MEDLINE | ID: mdl-39092876
ABSTRACT
Epilepsy, affecting 0.5%-1% of the global population, presents a significant challenge with 30% of patients resistant to medical treatment. Temporal lobe epilepsy, a common cause of medically refractory epilepsy, is often caused by hippocampal sclerosis (HS). HS can be divided further by subtype, as defined by the International League Against Epilepsy (ILAE). Type 1 HS, the most prevalent form (60%-80% of all cases), is characterized by cell loss and gliosis predominantly in the subfields cornu ammonis (CA1) and CA4. Type 2 HS features cell loss and gliosis primarily in the CA1 sector, and type 3 HS features cell loss and gliosis predominantly in the CA4 subfield. This literature review evaluates studies on hippocampal subfields, exploring whether observable atrophy patterns from in vivo and ex vivo magnetic resonance imaging (MRI) scans correlate with histopathological examinations with manual or automated segmentation techniques. Our findings suggest only ex vivo 1.5 Tesla (T) or 3T MRI with manual segmentation or in vivo 7T MRI with manual or automated segmentations can consistently correlate subfield patterns with histopathologically derived ILAE-HS subtypes. In conclusion, manual and automated segmentation methods offer advantages and limitations in diagnosing ILAE-HS subtypes, with ongoing research crucial for refining hippocampal subfield segmentation techniques and enhancing clinical applicability.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Neuroimaging Asunto de la revista: DIAGNOSTICO POR IMAGEM / NEUROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Canadá

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Neuroimaging Asunto de la revista: DIAGNOSTICO POR IMAGEM / NEUROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Canadá