Structural connectivity as a predictive factor for perampanel response in patients with epilepsy

Area of Science:

• Neuroscience
• Clinical Neurology
• Medical Imaging

Background:

• Epilepsy management often involves trial-and-error with anti-seizure medications.
• Perampanel (PER) is an anti-seizure medication used to treat epilepsy.
• Predicting patient response to PER is crucial for optimizing treatment efficacy.

Purpose of the Study:

• To identify clinical predictors of response to perampanel (PER) in epilepsy patients.
• To investigate whether structural brain connectivity can predict PER response.

Main Methods:

• 106 epilepsy patients receiving PER were analyzed over 12 months.
• Patients were categorized as good responders (>50% seizure reduction) or poor responders (<50% reduction).
• Diffusion tensor imaging and graph theoretical analysis assessed structural connectivity.

Main Results:

• Good PER responders received fewer prior anti-seizure medications (3 vs. 4) and earlier PER treatment (46.2% vs. 21.3%).
• Higher global efficiency and lower characteristic path length in cortical networks were observed in good responders.
• Increased mean clustering coefficient and small-worldness index in subcortical networks distinguished good responders.

Conclusions:

• Early PER administration is a significant predictor of good treatment response in epilepsy.
• Structural brain connectivity metrics show potential clinical utility in predicting PER response.
• These findings may guide personalized epilepsy treatment strategies.