Contralateral Preoperative Resting-State Functional MRI Network                    Integration Is Associated with Surgical Outcome in Temporal Lobe                    Epilepsy

OBJECT Predicting cognitive function following resective surgery remains an important clinical goal. Each MRI neuroimaging technique can potentially provide unique and distinct insight into changes that occur in the structural or functional organization of “at-risk” cognitive functions. The authors tested for the singular and combined power of 3 imaging techniques (functional MRI [fMRI], resting state fMRI, diffusion tensor imaging) to predict cognitive outcome following left (dominant) anterior temporal lobectomy for intractable epilepsy. METHODS The authors calculated the degree of deviation from normal, determined the rate of change in this measure across the pre- and postsurgical imaging sessions, and then compared these measures for their ability to predict verbal fluency changes following surgery. RESULTS The data show that the 3 neuroimaging techniques, in a combined model, can reliably predict cognitive outcome following anterior temporal lobectomy for medically intractable temporal lobe epilepsy. CONCLUSIONS These findings suggest that these 3 imaging modalities can be used effectively, in an additive fashion, to predict functional reorganization and cognitive outcome following anterior temporal lobectomy.

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Presurgical thalamic “hubness” predicts surgical outcome in temporal lobe epilepsy

Neurology ◽

10.1212/wnl.0000000000004035 ◽

2017 ◽

Vol 88 (24) ◽

pp. 2285-2293 ◽

Cited By ~ 56

Author(s):

Xiaosong He ◽

Gaelle E. Doucet ◽

Dorian Pustina ◽

Michael R. Sperling ◽

Ashwini D. Sharan ◽

...

Keyword(s):

Temporal Lobe Epilepsy ◽

Temporal Lobe ◽

Resting State ◽

Surgical Outcome ◽

Clinical Characteristics ◽

Temporal Lobectomy ◽

Support Vector ◽

Healthy Controls ◽

Resting State Functional Connectivity ◽

Potential Biomarker

Objective:To characterize the presurgical brain functional architecture presented in patients with temporal lobe epilepsy (TLE) using graph theoretical measures of resting-state fMRI data and to test its association with surgical outcome.Methods:Fifty-six unilateral patients with TLE, who subsequently underwent anterior temporal lobectomy and were classified as obtaining a seizure-free (Engel class I, n = 35) vs not seizure-free (Engel classes II–IV, n = 21) outcome at 1 year after surgery, and 28 matched healthy controls were enrolled. On the basis of their presurgical resting-state functional connectivity, network properties, including nodal hubness (importance of a node to the network; degree, betweenness, and eigenvector centralities) and integration (global efficiency), were estimated and compared across our experimental groups. Cross-validations with support vector machine (SVM) were used to examine whether selective nodal hubness exceeded standard clinical characteristics in outcome prediction.Results:Compared to the seizure-free patients and healthy controls, the not seizure-free patients displayed a specific increase in nodal hubness (degree and eigenvector centralities) involving both the ipsilateral and contralateral thalami, contributed by an increase in the number of connections to regions distributed mostly in the contralateral hemisphere. Simulating removal of thalamus reduced network integration more dramatically in not seizure-free patients. Lastly, SVM models built on these thalamic hubness measures produced 76% prediction accuracy, while models built with standard clinical variables yielded only 58% accuracy (both were cross-validated).Conclusions:A thalamic network associated with seizure recurrence may already be established presurgically. Thalamic hubness can serve as a potential biomarker of surgical outcome, outperforming the clinical characteristics commonly used in epilepsy surgery centers.

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