Language mapping with navigated repetitive TMS: proof of technique and validation

Abstract

Objective: Lesion-based mapping of speech pathways has been possible only during invasive neurosurgical procedures using direct cortical stimulation (DCS). However, navigated transcranial magnetic stimulation (nTMS) may allow for lesion-based interrogation of language pathways noninvasively. Although not lesion-based, magnetoencephalographic imaging (MEGI) is another noninvasive modality for language mapping. In this study, we compare the accuracy of nTMS and MEGI with DCS.

Methods: Subjects with lesions around cortical language areas underwent preoperative nTMS and MEGI for language mapping. nTMS maps were generated using a repetitive TMS protocol to deliver trains of stimulations during a picture naming task. MEGI activation maps were derived from adaptive spatial filtering of beta-band power decreases prior to overt speech during picture naming and verb generation tasks. The subjects subsequently underwent awake language mapping via intraoperative DCS. The language maps obtained from each of the 3 modalities were recorded and compared.

Results: nTMS and MEGI were performed on 12 subjects. nTMS yielded 21 positive language disruption sites (11 speech arrest, 5 anomia, and 5 other) while DCS yielded 10 positive sites (2 speech arrest, 5 anomia, and 3 other). MEGI isolated 32 sites of peak activation with language tasks. Positive language sites were most commonly found in the pars opercularis for all three modalities. In 9 instances the positive DCS site corresponded to a positive nTMS site, while in 1 instance it did not. In 4 instances, a positive nTMS site corresponded to a negative DCS site, while 169 instances of negative nTMS and DCS were recorded. The sensitivity of nTMS was therefore 90%, specificity was 98%, the positive predictive value was 69% and the negative predictive value was 99% as compared with intraoperative DCS. MEGI language sites for verb generation and object naming correlated with nTMS sites in 5 subjects, and with DCS sites in 2 subjects.

Conclusion: Maps of language function generated with nTMS correlate well with those generated by DCS. Negative nTMS mapping also correlates with negative DCS mapping. In our study, MEGI lacks the same level of correlation with intraoperative mapping; nevertheless it provides useful adjunct information in some cases. nTMS may offer a lesion-based method for noninvasively interrogating language pathways and be valuable in managing patients with peri-eloquent lesions.

Keywords: Direct cortical stimulation; Language mapping; Magnetoencephalography; Speech arrest; Transcranial magnetic stimulation.

Copyright © 2013 Elsevier Inc. All rights reserved.

Figures

Figure 1

(a) Auditory verb generation task. Subjects heard a noun and overtly generated a verb. The time window chosen for baseline was 600 ms prior to noun onset, and the active window was 600 ms prior to response. (b) Visual object naming task. Subjects were shown an image and asked to name it. The time window chosen for baseline was 600 ms 1 s after response, and the active window was 600 ms prior to response.

Figure 2

Composite representation of all MEGI-based verb-generation and object naming points across subjects.

Figure 3

Composite representation of all nTMS-based positive speech disruption points across subjects.

Figure 4

Composite representation of all DCS-based positive speech disruption points across subjects.

Figure 5

Composite representation of all MEGI-, nTMS-, and DCS-based positive speech disruption points across subjects.

Figure 6

All positive mapping points overlaid on anatomic regions

Figure 7

Aggregated coverage of nTMS mapping across all subjects. Labels within grid squares represent the number of patients who underwent nTMS mapping at that location.

Figure 8

Aggregated coverage of DCS mapping across all subjects. Labels within grid squares represent the number of patients who underwent DCS mapping at that location.

Figure 9

Probabilites of a positive nTMS site by location. Labels within grid squares represent the probability of a positive nTMS site at that location (No. positive / No. mapped).

Figure 10

Probabilites of a positive DCS site by location. Labels within grid squares represent the probability of a positive DCS site at that location (No. positive / No. mapped).

Figure 11

Aggregated MEGI language sites across all subjects. Labels within grid squares represent the number of patients with positive MEGI mapping sites at that location.

Figure 12

Case examples. (A) 63-year-old man with a left parietal GBM and good concordance between nTMS, DCS, and MEGI; (B) 29-year-old man with a left temporal ganglioglioma and good concordance between nTMS, DCS, and MEGI; (C) 65-year-old woman with GBM and good concordance between nTMS, DCS, and MEGI; (D) 37-year-old woman with left temporal anaplastic ganglioglioma and false positive nTMS site in the posterior temporal region; (E) 31-year-old woman with left frontal oligoastrocytoma and false positive nTMS site in inferior precentral gyrus; (F) 61-year-old man with left temporal GBM and false negative nTMS site in posterior superior temporal gyrus.