Functional connectivity of the thalamocortical circuit in patients with seizure relapse after antiseizure medication withdrawal.

OBJECTIVE

To characterize the features of thalamocortical functional connectivity during seizure recurrence at the time of antiseizure medication (ASM) withdrawal.

METHODS

Patients with chronic epilepsy who attempted to discontinue medications were prospectively registered and followed up; 19 patients remained seizure-free (SF-group), 18 patients had seizure relapses (SR-group) after ASM withdrawal, and 28 healthy controls were recruited. Resting-state functional magnetic resonance imaging was performed before ASM withdrawal. Thalamus subdivisions were set as seeds to calculate voxelwise functional connectivity. Partial correlation analysis between functional connectivity and clinical variables was performed. A support vector machine was used to assess the predictive ability of the specific functional connectivity for seizure relapse.

RESULTS

The within-group comparison indicated that the SR-group had more extensive functional connectivity than the SF-group; the left inferior pulvinar, left medial pulvinar, and right anterior pulvinar showed a significantly stronger functional connection with the precuneus in the SR-group than in the SF-group (Gaussian random field correction, voxel-level p < .001 and cluster-level p < .05). In the SR-group, a positive correlation was found between the left inferior pulvinar-precuneus connectivity and the active period (r = .46, p = .05), seizure-free period (r = .67, p = .002), and disease duration (r = .53, p = .02), and between the left medial pulvinar-precuneus connectivity and the seizure-free period (r = .58, p = .01). The combination of these thalamocortical connections showed a high predictive ability, with an area under the curve of .92 and accuracy of .90 (p = .01).

SIGNIFICANCE

This study determined distinct features of thalamocortical functional connectivity at the time of ASM withdrawal in patients with and without seizure relapse, showing a potential for predicting seizure outcomes following ASM withdrawal.