The Efficacy of Intraoperative Passive Language Mapping for Glioma Surgery: A Case Report

Background: Recently, electrocorticographic (ECoG) studies have emphasized the importance of gamma band-based functional mapping in the presurgical localization of the eloquent cortex. Passive functional mapping using ECoG signals provides a reliable method for identifying receptive language areas w...

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Veröffentlicht in:Frontiers in neurology 2021-08, Vol.12
Hauptverfasser: Kanaya, Kohei, Mitsuhashi, Takumi, Kiuchi, Takafumi, Kobayashi, Sumio
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Sprache:eng
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Zusammenfassung:Background: Recently, electrocorticographic (ECoG) studies have emphasized the importance of gamma band-based functional mapping in the presurgical localization of the eloquent cortex. Passive functional mapping using ECoG signals provides a reliable method for identifying receptive language areas without many of the risks and limitations associated with electrical cortical stimulation. We report a surgical case of left temporal malignant glioma with intraoperative passive language mapping. Case Description: A 78-year-old woman was diagnosed with left temporal glioma with inspection of her language difficulty. MRI showed a left temporal tumor measuring 74.6 × 50.0 × 51.5 mm in size. Real-time CortiQ-based mapping using high-gamma activity by word-listening and story-listening tasks was performed. Significant listening task-evoked high gamma activities were detected in 5 channels in the superior temporal gyrus and one channel in the middle temporal gyrus. The tumor was grossly removed except for the region corresponding to listening task-evoked high gamma activities. Postoperatively, the patient's symptoms of language comprehension difficulty improved, and no new neurological deficits were observed. Conclusion: Intraoperative passive language mapping was successfully performed, and the patient's language function was well-preserved. Intraoperative passive language mapping, which is applicable in a short time and under general anesthesia, can be an important tool for detecting language areas.
ISSN:1664-2295
1664-2295
DOI:10.3389/fneur.2021.652401