FMRI to Predict Naming Decline: Can We Improve the Grade From a C to an A?. Issue 6 (November 2022)

• Record Type: Journal Article
• Authors: Sarkis, Rani A.
• Is Part Of: Epilepsy currents. Volume 22:Issue 6(2022)
• Page Start: 345
• Page End: 347
• Publication Date: 2022-11
• Subjects: Epilepsy -- Periodicals; 616.853005
• DOI: 10.1177/15357597221126277
• Languages: English
• ISSNs: 1535-7597

Abstract

Prediction of Naming Outcome With fMRI Language Lateralization in Left Temporal Epilepsy Surgery Gross WL, Helfand AI, Swanson SJ, Conant LL, Humphries CJ, Raghavan M, Mueller WM, Busch RM, Allen L, Anderson CT, Carlson CE, Lowe MJ, Langfitt JT, Tivarus ME, Drane DL, Loring DW, Jacobs M, Morgan VL, Allendorfer JB, Szaflarski JP, Bonilha L, Bookheimer S, Grabowski T, Vannest J, Binder JR; FMRI in Anterior Temporal Epilepsy Surgery (FATES) Study. Neurology . 2022;98(23):e2337-e2346. doi:10.1212/WNL.0000000000200552 . PMID: 35410903; PMCID: PMC9202528. 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 ≈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.