Imaging Epilepsy: Past, Passing, and to Come.

Area of Science:

• Neurology
• Radiology
• Medical Imaging

Background:

• Traditional epilepsy imaging methods were often uncomfortable and less effective.
• Computed tomography (CT) is still used for acute seizure imaging.
• Structural magnetic resonance imaging (MRI) is now the primary tool for epilepsy evaluation.

Purpose of the Study:

• To review the evolution and current role of neuroimaging in epilepsy evaluation.
• To highlight the importance of advanced imaging techniques in presurgical planning and understanding epilepsy pathophysiology.
• To introduce the potential of artificial intelligence (AI) in detecting subtle epilepsy-related lesions.

Main Methods:

• Review of advancements in neuroimaging modalities for epilepsy.
• Discussion of functional imaging techniques like PET, SPECT, and fMRI for presurgical evaluation.
• Exploration of AI and machine learning applications on large MRI datasets for lesion detection.

Main Results:

• Structural MRI is the leading modality for epilepsy assessment.
• Functional imaging (PET, SPECT, fMRI) aids in presurgical planning and cognitive mapping.
• AI/machine learning shows promise in identifying visually undetectable lesions, such as focal cortical dysplasia.

Conclusions:

• Modern neuroimaging has significantly improved epilepsy diagnosis and management.
• AI-driven lesion detection in epilepsy shows potential but requires further validation and clinical integration.
• Neuroimaging is integral to diagnosing, monitoring, and assessing treatment response in inherited metabolic epilepsies.