Abstract

Abstract BACKGROUND Few studies have examined concordance between intraoperative electrocorticography (ECoG) and direct electrical stimulation (DES) language mapping, especially across varied naming tasks. METHODS Twelve patients (Mdn age=59; 75% HGG) underwent awake craniotomy with ECoG and DES language mapping. Mapping utilized iPad stimulus presentation coupled to a 4x8 electrode array for both ECoG and DES. Time-frequency ECoG gamma band activity (Early and Late) was visualized for 3 naming paradigms (Object, Action, Auditory). Bipolar DES was also conducted for each task at each electrode pair. ECoG activations and DES hits were overlayed on preoperative MRI. DES hits represented ground truth for eloquence. ECoG accuracy was examined for each task with 3 different criteria: exact (identical electrodes for ECoG activation and DES hits), adjacent (ECoG <1cm of DES hits), and adjacent within a predefined peritumoral region of interest (<2 cm from boundaries). RESULTS 32 DES hits (40% Auditory, 32% Action, 28% Obj) were observed across patients. Exact ECoG-DES accuracy ranged from 78%-90% [Object: Sens=11%, Spec=91%, PPV=6%, NPV=95%; Action: Sens=40%, Spec=93%, PPV=24%, NPV=97%; Auditory: Sens=69%, Spec=78%, PPV=19%, NPV=78%]. Adjacent ECoG-DES accuracy ranged from 82%-91% [Object: Sens=33%, Spec=92%, PPV=18%, NPV=97%; Action: Sens=44%, Spec=93%, PPV=25%, NPV=97%; Auditory: Sens=91%, Spec=81%, PPV=37%, NPV=99%]. When restricted to the peritumoral region, adjacent ECoG-DES accuracy ranged from 94%-97% [Object: Sens=14%, Spec=99%, PPV=25%, NPV=97%; Action: Sens=25%, Spec=99%, PPV=25%, NPV=99%; Auditory: Sens=100%, Spec=94%, PPV=54%, NPV=100%]. For patients with DES hits (N=10), all had at least 1 task activation <1 cm of DES hits, with 7/10 having convergence of activations across at least 2 tasks. CONCLUSIONS Negative ECoG mapping is strongly predictive of non-eloquence confirmed by DES for all naming tasks. Additionally, gamma band activation elicited by auditory naming within the peritumoral region is strongly predictive of eloquence. Findings support task-based ECoG language mapping for prediction of eloquence and identification of targets for DES confirmation.

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