Combined noninvasive language mapping by navigated transcranial magnetic stimulation and functional MRI and its comparison with direct cortical stimulation

Abstract

OBJECT Repetitive navigated transcranial magnetic stimulation (rTMS) is now increasingly used for preoperative language mapping in patients with lesions in language-related areas of the brain. Yet its correlation with intraoperative direct cortical stimulation (DCS) has to be improved. To increase rTMS's specificity and positive predictive value, the authors aim to provide thresholds for rTMS's positive language areas. Moreover, they propose a protocol for combining rTMS with functional MRI (fMRI) to combine the strength of both methods. METHODS The authors performed multimodal language mapping in 35 patients with left-sided perisylvian lesions by using rTMS, fMRI, and DCS. The rTMS mappings were conducted with a picture-to-trigger interval (PTI, time between stimulus presentation and stimulation onset) of either 0 or 300 msec. The error rates (ERs; that is, the number of errors per number of stimulations) were calculated for each region of the cortical parcellation system (CPS). Subsequently, the rTMS mappings were analyzed through different error rate thresholds (ERT; that is, the ER at which a CPS region was defined as language positive in terms of rTMS), and the 2-out-of-3 rule (a stimulation site was defined as language positive in terms of rTMS if at least 2 out of 3 stimulations caused an error). As a second step, the authors combined the results of fMRI and rTMS in a predefined protocol of combined noninvasive mapping. To validate this noninvasive protocol, they correlated its results to DCS during awake surgery. RESULTS The analysis by different rTMS ERTs obtained the highest correlation regarding sensitivity and a low rate of false positives for the ERTs of 15%, 20%, 25%, and the 2-out-of-3 rule. However, when comparing the combined fMRI and rTMS results with DCS, the authors observed an overall specificity of 83%, a positive predictive value of 51%, a sensitivity of 98%, and a negative predictive value of 95%. CONCLUSIONS In comparison with fMRI, rTMS is a more sensitive but less specific tool for preoperative language mapping than DCS. Moreover, rTMS is most reliable when using ERTs of 15%, 20%, 25%, or the 2-out-of-3 rule and a PTI of 0 msec. Furthermore, the combination of fMRI and rTMS leads to a higher correlation to DCS than both techniques alone, and the presented protocols for combined noninvasive language mapping might play a supportive role in the language-mapping assessment prior to the gold-standard intraoperative DCS.