Divergent network properties that predict early surgical failure versus late recurrence in temporal lobe epilepsy

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The objectives of this study were to identify functional and structural network properties that are associated with early versus long-term seizure outcomes after mesial temporal lobe epilepsy (mTLE) surgery and to determine how these compare to current clinically used methods for seizure outcome prediction.


In this case-control study, 26 presurgical mTLE patients and 44 healthy controls were enrolled to undergo 3-T MRI for functional and structural connectivity mapping across an 8-region network of mTLE seizure propagation, including the hippocampus (left and right), insula (left and right), thalamus (left and right), one midline precuneus, and one midline mid-cingulate. Seizure outcome was assessed annually for up to 3 years. Network properties and current outcome prediction methods related to early and long-term seizure outcome were investigated.


A network model was previously identified across 8 patients with seizure-free mTLE. Results confirmed that whole-network propagation connectivity patterns inconsistent with the mTLE model predict early surgical failure. In those patients with networks consistent with the mTLE network, specific bilateral within-network hippocampal to precuneus impairment (rather than unilateral impairment ipsilateral to the seizure focus) was associated with mild seizure recurrence. No currently used clinical variables offered the same ability to predict long-term outcome.


It is known that there are important clinical differences between early surgical failure that lead to frequent disabling seizures and late recurrence of less frequent mild seizures. This study demonstrated that divergent network connectivity variability, whole-network versus within-network properties, were uniquely associated with these disparate outcomes.

ABBREVIATIONS FC = functional connectivity; fMRI = functional MRI; mTLE = mesial temporal lobe epilepsy; ROC = receiver operating characteristic; SC = structural connectivity.

Article Information

Correspondence Victoria L. Morgan: Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN. victoria.morgan@vanderbilt.edu.

INCLUDE WHEN CITING Published online April 5, 2019; DOI: 10.3171/2019.1.JNS182875.

Disclosures The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

© AANS, except where prohibited by US copyright law.



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    Whole-network dissimilarity to the mTLE model identifies patients with early surgical failure (n = 26). Left: FC and SC network model identified using 8 mTLE patients with 1-year Engel class Ia outcome. Each region value is the weighted sum of connectivity to all other regions in the network. Units are standard deviations from a healthy control of the same age. Right: Similarity of each patient in the cohort to the model using two similarity metrics. Excluding those patients used to compute the model (blue dots), similarity to the model was successful in discriminating cases of early failure (red dots) from those with a favorable outcome (green dots) (Fisher’s exact test, p < 0.001). Dashed lines represent similarity limits defined by 5000 Monte-Carlo simulations using the mean ± 1.5 SDs of the 8 patients used to compute the model. C = contralateral to seizure focus; Cing = mid-cingulate; F = FC; Hip = hippocampus; I = ipsilateral to seizure focus; Ins = insula; Prec = precuneus; S = SC; Thal = thalamus.

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    Within-network FC between contralateral hippocampus and precuneus is positively correlated with long-term seizure outcome (n = 18). Left: FC of contralateral hippocampus to precuneus (FC HIPC-PREC) is positively linearly correlated with years until postsurgical focal impaired awareness or focal to bilateral tonic-clonic seizure recurrence (Pearson correlation, r = 0.73, p < 0.001). Right: No significant linear relationship between FC of ipsilateral hippocampus to precuneus (FC HIPI-PREC) and years until seizure recurrence (Pearson correlation, r = 0.34, p > 0.05). This connectivity is less than that of an age-matched healthy control regardless of outcome (FC HIPI-PREC < 0; two-sample t-test, p < 0.001). FC units are standard deviations from an age-matched healthy control. Zero line represents the FC of the estimated age-matched healthy controls. recur = recurrence; std = standard deviation.

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    Predictions of 3-year seizure freedom after mTLE surgery. A: ROC curves to predict 3-year freedom from postsurgical recurrence of focal impaired awareness or focal to bilateral tonic-clonic seizures of 5 prediction methods: FC of the contralateral hippocampus to precuneus (FC HIPC-PREC), modified Seizure Freedom Score (mSFS), the Epilepsy Surgery Grading Scale (SGS), the Epilepsy Surgery Nomogram (NOM), and the age-corrected contralateral hippocampal volume (HIPC vol). Shaded region indicates area of highest specificity (> 0.7, 1-specificity < 0.3). FC HIPC-PREC is the only predictor with high sensitivity (> 0.7) in this range (n = 18). B: Area under the whole ROC curve (AUC) from A. Error bars are 95% CI. *Difference between AUC p < 0.05. †Difference between AUC p < 0.01. C: Kaplan-Meier plot illustrating the percentage of patients with seizure freedom each year after surgery using FC HIPC-PREC > 0 (age-matched healthy control) as cutoff for good prediction (n = 21; method includes censored data).

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    Seizure-propagation network theory of postsurgical recurrence. These results suggest that mTLE propagation network patterns inconsistent with the whole-network mTLE model predict early surgical failure (upper). In those patients with networks consistent with the mTLE network, specific within-network contralateral hippocampal to precuneus impairment is associated with earlier mild seizure recurrence (lower).

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    Identification of optimal mesial temporal surgical candidates based on network connectivity. Possible algorithm to incorporate network models into presurgical decision making in mTLE. Figure is available in color online only.





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