Artikel
Region and linguistic specific nTMS-based DTI fiber tracking of language pathways in brain tumor patients
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Autoren
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Giovanni Raffa
- Neurosurgical Clinic, Department of Neuroscience, University of Messina, Italy; Department of Clinical and Experimental Medicine, University of Messina, Italy
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Ina Bährend
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Germany
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Heike Schneider
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Germany
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Peter Vajkoczy
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Germany
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Thomas Picht
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Germany
| Veröffentlicht: | 8. Juni 2016 |
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Gliederung
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Objective: To assess the feasibility and reliability of using cortical seeding areas defined by error type specific navigated transcranial magnetic stimulation (nTMS) language mapping to perform DTI fiber tracking (DTI-FT) in patients affected by language-eloquent brain tumors.
Method: We collected neuroimaging data of 10 patients (6 m, 4 f, age 57 ± 14) suffering from left perisylvian brain tumors that underwent language mapping using repetitive nTMS. We computed language pathways through 3 different DTI-FT techniques: 1) standard DTI-FT of arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), inferior fronto-occipital fasciculus (IFOF) and uncinate fasciculus (UF); 2) nTMS-based "all-spots" DTI-FT; 3) nTMS-based "single-spot" DTI-FT. We compared the fractional anisotropy (FA) value and ratio needed for the visualization of each fascicle by using the standard vs the two nTMS-based techniques. Also, we analyzed the ability of the 3 techniques in computing fibers connecting cortical nTMS-positive spots to any of the main pathways. Lastly, we analyzed the concordance between the presumed function of each fascicle and the error type of connected nTMS-positive spots. We also analyzed the likelihood of connections for nTMS-positive vs nTMS-negative spots.
Results: AF, ILF, IFOF and UF were computed in all patients by using all 3 techniques. Mean FA values and ratios were higher when using the nTMS-based strategies. We obtained a higher number of spots connected to the main fascicles, especially by using the nTMS-based “single-spot” strategy (p=0.009). We observed a significant concordance between the expected role of AF (p=0.01), IFOF (p=0.007), and ILF (p=0.001), and the error type of connected nTMS-positive spots. Finally, connected nTMS-negative spots were significantly fewer as compared to the non-connected ones (1.1 ± 0.9 vs 10.9 ± 0.9; p<0.0001). The likelihood of connections was 39.9 ± 6.7% for nTMS-positive spots (true-positive connections) vs 9.1 ± 8.2% for nTMS-negative spots (false-positive connections) (p<0.0001).
Conclusions: nTMS-based DTI-FT, especially the "single-spot" strategy, allows for a more reliable detection of connections between cortical language areas and subcortical language pathways as compared to the standard DTI-FT.
