Language function distribution in left-handers: A navigated transcranial magnetic stimulation study

2016 ◽  
Vol 82 ◽  
pp. 65-73 ◽  
Author(s):  
Lorena Tussis ◽  
Nico Sollmann ◽  
Tobias Boeckh-Behrens ◽  
Bernhard Meyer ◽  
Sandro M. Krieg
Author(s):  
Hanne-Rinck Jeltema ◽  
Ann-Katrin Ohlerth ◽  
Aranka de Wit ◽  
Michiel Wagemakers ◽  
Adrià Rofes ◽  
...  

Abstract The objective of this systematic review is to create an overview of the literature on the comparison of navigated transcranial magnetic stimulation (nTMS) as a mapping tool to the current gold standard, which is (intraoperative) direct cortical stimulation (DCS) mapping. A search in the databases of PubMed, EMBASE, and Web of Science was performed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and recommendations were used. Thirty-five publications were included in the review, describing a total of 552 patients. All studies concerned either mapping of motor or language function. No comparative data for nTMS and DCS for other neurological functions were found. For motor mapping, the distances between the cortical representation of the different muscle groups identified by nTMS and DCS varied between 2 and 16 mm. Regarding mapping of language function, solely an object naming task was performed in the comparative studies on nTMS and DCS. Sensitivity and specificity ranged from 10 to 100% and 13.3–98%, respectively, when nTMS language mapping was compared with DCS mapping. The positive predictive value (PPV) and negative predictive value (NPV) ranged from 17 to 75% and 57–100% respectively. The available evidence for nTMS as a mapping modality for motor and language function is discussed.


2020 ◽  
Vol 132 (4) ◽  
pp. 1033-1042 ◽  
Author(s):  
Nico Sollmann ◽  
Alessia Fratini ◽  
Haosu Zhang ◽  
Claus Zimmer ◽  
Bernhard Meyer ◽  
...  

OBJECTIVENavigated transcranial magnetic stimulation (nTMS) in combination with diffusion tensor imaging fiber tracking (DTI FT) is increasingly used to locate subcortical language-related pathways. The aim of this study was to establish nTMS-based DTI FT for preoperative risk stratification by evaluating associations between lesion-to-tract distances (LTDs) and aphasia and by determining a cut-off LTD value to prevent surgery-related permanent aphasia.METHODSFifty patients with left-hemispheric, language-eloquent brain tumors underwent preoperative nTMS language mapping and nTMS-based DTI FT, followed by tumor resection. nTMS-based DTI FT was performed with a predefined fractional anisotropy (FA) of 0.10, 0.15, 50% of the individual FA threshold (FAT), and 75% FAT (minimum fiber length [FL]: 100 mm). The arcuate fascicle (AF), superior longitudinal fascicle (SLF), inferior longitudinal fascicle (ILF), uncinate fascicle (UC), and frontooccipital fascicle (FoF) were identified in nTMS-based tractography, and minimum LTDs were measured between the lesion and the AF and between the lesion and the closest other subcortical language-related pathway (SLF, ILF, UC, or FoF). LTDs were then associated with the level of aphasia (no/transient or permanent surgery-related aphasia, according to follow-up examinations).RESULTSA significant difference in LTDs was observed between patients with no or only surgery-related transient impairment and those who developed surgery-related permanent aphasia with regard to the AF (FA = 0.10, p = 0.0321; FA = 0.15, p = 0.0143; FA = 50% FAT, p = 0.0106) as well as the closest other subcortical language-related pathway (FA = 0.10, p = 0.0182; FA = 0.15, p = 0.0200; FA = 50% FAT, p = 0.0077). Patients with surgery-related permanent aphasia showed the lowest LTDs in relation to these tracts. Thus, LTDs of ≥ 8 mm (AF) and ≥ 11 mm (SLF, ILF, UC, or FoF) were determined as cut-off values for surgery-related permanent aphasia.CONCLUSIONSnTMS-based DTI FT of subcortical language-related pathways seems suitable for risk stratification and prediction in patients suffering from language-eloquent brain tumors. Thus, the current role of nTMS-based DTI FT might be expanded, going beyond the level of being a mere tool for surgical planning and resection guidance.


2015 ◽  
Vol 123 (2) ◽  
pp. 314-324 ◽  
Author(s):  
Sebastian Ille ◽  
Nico Sollmann ◽  
Theresa Hauck ◽  
Stefanie Maurer ◽  
Noriko Tanigawa ◽  
...  

OBJECT Language mapping by repetitive navigated transcranial magnetic stimulation (rTMS) is increasingly used and has already replaced functional MRI (fMRI) in some institutions for preoperative mapping of neurosurgical patients. Yet some factors affect the concordance of both methods with direct cortical stimulation (DCS), most likely by lesions affecting cortical oxygenation levels. Therefore, the impairment of the accuracy of rTMS and fMRI was analyzed and compared with DCS during awake surgery in patients with intraparenchymal lesions. METHODS Language mapping was performed by DCS, rTMS, and fMRI using an object-naming task in 27 patients with left-sided perisylvian lesions, and the induced language errors of each method were assigned to the cortical parcellation system. Subsequently, the receiver operating characteristics were calculated for rTMS and fMRI and compared with DCS as ground truth for regions with (w/) and without (w/o) the lesion in the mapped regions. RESULTS The w/ subgroup revealed a sensitivity of 100% (w/o 100%), a specificity of 8% (w/o 5%), a positive predictive value of 34% (w/o: 53%), and a negative predictive value (NPV) of 100% (w/o: 100%) for the comparison of rTMS versus DCS. Findings for the comparison of fMRI versus DCS within the w/ subgroup revealed a sensitivity of 32% (w/o: 62%), a specificity of 88% (w/o: 60%), a positive predictive value of 56% (w/o: 62%), and a NPV of 73% (w/o: 60%). CONCLUSIONS Although strengths and weaknesses exist for both rTMS and fMRI, the results show that rTMS is less affected by a brain lesion than fMRI, especially when performing mapping of language-negative cortical regions based on sensitivity and NPV.


2015 ◽  
Vol 8 (2) ◽  
pp. 317-318 ◽  
Author(s):  
Maja Rogić Vidaković ◽  
Marina Zmajević Schönwald ◽  
Tomislav Jurić ◽  
Nikola Erceg ◽  
Andreja Bubić ◽  
...  

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