Language mapping with navigated transcranial magnetic stimulation in pediatric and adult patients undergoing epilepsy surgery: Comparison with extraoperative direct cortical stimulation
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Navigated transcranial magnetic stimulation (nTMS) is becoming increasingly popular in noninvasive preoperative language mapping, as its results correlate well enough with those obtained by direct cortical stimulation (DCS) during awake surgery in adult patients with tumor. Reports in the context of epilepsy surgery or extraoperative DCS in adults are, however, sparse, and validation of nTMS with DCS in children is lacking. Furthermore, little is known about the risk of inducing epileptic seizures with nTMS in pediatric epilepsy patients. We provide the largest validation study to date in an epilepsy surgery population. METHODS: We compared language mapping with nTMS and extraoperative DCS in 20 epilepsy surgery patients (age range 9-32 years; 14 children and adolescents). RESULTS: In comparison with DCS, sensitivity of nTMS was 68%, specificity 76%, positive predictive value 27%, and negative predictive value 95%. Age, location of ictal-onset zone near or within DCS-mapped language areas or severity of cognitive deficits had no significant effect on these values. None of our patients had seizures during nTMS. SIGNIFICANCE: Our study suggests that nTMS language mapping is clinically useful and safe in epilepsy surgery patients, including school-aged children and patients with extensive cognitive dysfunction. Similar to in tumor surgery, mapping results in the frontal region are most reliable. False negative findings may be slightly more likely in epilepsy than in tumor surgery patients. Mapping results should always be verified by other methods in individual patients.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it