Frontotemporal phase lag index correlates with seizure severity in patients with temporal lobe epilepsy.

OBJECTIVES

To find the brain network indicators correlated with the seizure severity in temporal lobe epilepsy (TLE) by graph theory analysis.

METHODS

We enrolled 151 patients with TLE and 36 age- and sex-matched controls with video-EEG monitoring. The 90-s interictal EEG data were acquired. We adopted a network analyzing pipeline based on graph theory to quantify and localize their functional networks, including weighted classical network, minimum spanning tree, community structure, and LORETA. The seizure severities were evaluated using the seizure frequency, drug-resistant epilepsy (DRE), and VA-2 scores.

RESULTS

Our network analysis pipeline showed ipsilateral frontotemporal activation in patients with TLE. The frontotemporal phase lag index () values increased in the theta band (4-7 Hz), which were elevated in patients with higher seizure severities ( < 0.05). Multivariate linear regression analysis showed that the VA-2 scores were independently correlated with frontotemporal values in the theta band ( = 0.259, = 0.001) and age of onset ( = -0.215, = 0.007).

SIGNIFICANCE

This study illustrated that the frontotemporal in the theta band independently correlated with seizure severity in patients with TLE. Our network analysis provided an accessible approach to guide the treatment strategy in routine clinical practice.