Task-based functional magnetic resonance imaging prediction of postsurgical cognitive outcomes in temporal lobe epilepsy: A systematic review, meta-analysis, and new data.

Task-based functional magnetic resonance imaging (tfMRI) has developed as a common alternative in epilepsy surgery to the intracarotid amobarbital procedure, also known as the Wada procedure. Prior studies have implicated tfMRI as a comparable predictor of postsurgical cognitive outcomes. However, the predictive validity of tfMRI has not been established. This preregistered systematic review and meta-analysis (CRD42020183563) synthesizes the literature predicting postsurgical cognitive outcomes in temporal lobe epilepsy (TLE) using tfMRI. The PubMed and PsycINFO literature databases were queried for English-language articles published between January 1, 2009 and December 31, 2020 associating tfMRI laterality indices or symmetry of task activation with outcomes in TLE. Their references were reviewed for additional relevant literature, and unpublished data from our center were incorporated. Nineteen studies were included in the meta-analysis. tfMRI studies predicted postsurgical cognitive outcomes in left TLE ( ρ ̂ = -.27, 95% confidence interval [CI] = -.32 to -.23) but not right TLE ( ρ ̂ = -.02, 95% CI = -.08 to .03). Among studies of left TLE, language tfMRI studies were more robustly predictive of postsurgical cognitive outcomes ( ρ ̂ = -.27, 95% CI = -.33 to -.20) than memory tfMRI studies ( ρ ̂ = -.27, 95% CI = -.43 to -.11). Further moderation by cognitive outcome domain indicated language tfMRI predicted confrontation naming ( ρ ̂ = -.32, 95% CI = -.41 to -.22) and verbal memory ( ρ ̂ = -.26, 95% CI = -.35 to -.17) outcomes, whereas memory tfMRI forecasted only verbal memory outcomes ( ρ ̂ = -.37, 95% CI = -.57 to -.18). Surgery type, birth sex, level of education, age at onset, disease duration, and hemispheric language dominance moderated study outcomes. Sensitivity analyses suggested the interval of postsurgical follow-up, and reporting and methodological practices influenced study outcomes as well. These findings intimate tfMRI is a modest predictor of outcomes in left TLE that should be considered in the context of a larger surgical workup.

Enhanced co-registration methods to improve intracranial electrode contact localization.

Background: Electrode contact locations are important when planning tailored brain surgeries to identify pathological tissue targeted for resection and conversely avoid eloquent tissue. Current methods employ trained experts to use neuroimaging scans that are manually co-registered and localize contacts within ~2 mm. Yet, the state of the art is limited by either the expertise needed for each type of intracranial electrode or the inter-modality co-registration which increases error, reducing accuracy. Patients often have a variety of strips, grids and depths implanted; therefore, it is cumbersome and time-consuming to apply separate localization methods for each type of electrode, requiring expertise across different approaches. New method: To overcome these limitations, a computational method was developed by separately registering an implant magnetic resonance image (MRI) and implant computed tomography image (CT) to the pre-implant MRI, then calculating an iterative closest point transformation using the contact locations extracted from the signal voids as ground truth. Results: The implant MRI is robustly co-registered to the pre-implant MRI with a boundary-based registration algorithm. By extracting and utilizing 'signal voids' (the metal induced artifacts from the implant MRI) as electrode fiducials, the novel method is an all-in-one approach for all types of intracranial electrodes while eliminating inter-modality co-registration errors. Comparison with existing methods: The distance between each electrode centroid and the brain's surface was measured, for the proposed method as well as the state of the art method using two available software packages, SPM 12 and FSL 4.1. The method presented here achieves the smallest distances to the brain's surface for all strip and grid type electrodes, i.e. contacts designed to rest directly on the brain surface. Conclusion: We use one of the largest reported sample sizes in localization studies to validate this novel method for localizing different kinds of intracranial electrodes including grids, strips and depth electrodes.