4.7 Article

Prediction of Naming Outcome With FMRI Language Lateralization in Left Temporal Epilepsy Surgery

Journal

NEUROLOGY
Volume 98, Issue 23, Pages E2337-E2346

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1212/WNL.0000000000200552

Keywords

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Funding

  1. NIH National Institute of Neurological Disorders and Stroke [R01 NS35929]
  2. NIH National Center for Advancing Translational Sciences [KL2 TR001438]

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This study aimed to evaluate the predictive role of preoperative language functional magnetic resonance imaging (fMRI) in naming decline after left temporal lobe epilepsy (TLE) surgery. A large multicenter cohort study was conducted on 81 patients, and the results showed that fMRI was the strongest predictor of naming decline, with a negative correlation. These findings provide evidence supporting the use of preoperative language fMRI in predicting language outcome in TLE surgery patients.
Background and Objectives Naming decline after left temporal lobe epilepsy (TLE) surgery is common and difficult to predict. Preoperative language fMRI may predict naming decline, but this application is still lacking evidence. We performed a large multicenter cohort study of the effectiveness of fMRI in predicting naming deficits after left TLE surgery. Methods At 10 US epilepsy centers, 81 patients with left TLE were prospectively recruited and given the Boston Naming Test (BNT) before and approximate to 7 months after anterior temporal lobectomy. An fMRI language laterality index (LI) was measured with an auditory semantic decision-tone decision task contrast. Correlations and a multiple regression model were built with a priori chosen predictors. Results Naming decline occurred in 56% of patients and correlated with fMRI LI (r = -0.41, p < 0.001), age at epilepsy onset (r = -0.30, p = 0.006), age at surgery (r = -0.23, p = 0.039), and years of education (r = 0.24, p = 0.032). Preoperative BNT score and duration of epilepsy were not correlated with naming decline. The regression model explained 31% of the variance, with fMRI contributing 14%, with a 96% sensitivity and 44% specificity for predicting meaningful naming decline. Cross-validation resulted in an average prediction error of 6 points. Discussion An fMRI-based regression model predicted naming outcome after left TLE surgery in a large, prospective multicenter sample, with fMRI as the strongest predictor. These results provide evidence supporting the use of preoperative language fMRI to predict language outcome in patients undergoing left TLE surgery. Classification of Evidence This study provides Class I evidence that fMRI language lateralization can help in predicting naming decline after left TLE surgery.

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