1. fMRI prediction of naming change after adult temporal lobe epilepsy surgery: Activation matters.
- Author
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You X, Zachery AN, Fanto EJ, Norato G, Germeyan SC, Emery EJ, Sepeta LN, Berl MM, Black CL, Wiggs E, Zaghloul K, Inati SK, Gaillard WD, and Theodore WH
- Subjects
- Adolescent, Adult, Age of Onset, Epilepsy, Temporal Lobe diagnostic imaging, Female, Functional Neuroimaging, Humans, Language Tests, Magnetic Resonance Imaging, Male, Middle Aged, Predictive Value of Tests, Risk Factors, Young Adult, Epilepsy, Temporal Lobe surgery, Language Disorders etiology
- Abstract
Objective: We aimed to predict language deficits after epilepsy surgery. In addition to evaluating surgical factors examined previously, we determined the impact of the extent of functional magnetic resonance imaging (fMRI) activation that was resected on naming ability., Method: Thirty-five adults (mean age 37.5 ± 10.9 years, 13 male) with temporal lobe epilepsy completed a preoperative fMRI auditory description decision task, which reliably activates frontal and temporal language networks. Patients underwent temporal lobe resections (20 left resection). The Boston Naming Test (BNT) was used to determine language functioning before and after surgery. Language dominance was determined for Broca and Wernicke area (WA) by calculating a laterality index following statistical parametric mapping processing. We used an innovative method to generate anatomic resection masks automatically from pre- and postoperative MRI tissue map comparison. This mask provided the following: (a) resection volume; (b) overlap between resection and preoperative activation; and (c) overlap between resection and WA. We examined postoperative language change predictors using stepwise linear regression. Predictors included parameters described above as well as age at seizure onset (ASO), preoperative BNT score, and resection side and its relationship to language dominance., Results: Seven of 35 adults had significant naming decline (6 dominant-side resections). The final regression model predicted 38% of the naming score change variance (adjusted r
2 = 0.28, P = 0.012). The percentage of top 10% fMRI activation resected (P = 0.017) was the most significant contributor. Other factors in the model included WA LI, ASO, volume of WA resected, and WA LI absolute value (extent of laterality)., Significance: Resection of fMRI activation during a word-definition decision task is an important factor for postoperative change in naming ability, along with other previously reported predictors. Currently, many centers establish language dominance using fMRI. Our results suggest that the amount of the top 10% of language fMRI activation in the intended resection area provides additional predictive power and should be considered when planning surgical resection., (Published 2019. This article is a U.S. Government work and is in the public domain in the USA.)- Published
- 2019
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