Symmetry of the arcuate fasciculus and its impact on language performance of patients with brain tumors in the language-dominant hemisphere

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OBJECTIVE

Cerebral damage in frontal, parietal, and temporal brain areas and, probably more importantly, their interconnections can lead to deficits in language. However, neural plasticity and repair allow the brain to partly compensate for neural injury, mediated by both functional and structural changes. In this study, the authors sought to systematically investigate the relationship between language performance in brain tumor patients and structural perisylvian pathways (i.e., the arcuate fasciculus [AF]) using probabilistic fiber tracking on diffusion tensor imaging. The authors used a previously proposed model in which the AF is divided into anterior, long, and posterior segments. The authors hypothesized that right-handed patients with gliomas in the language-dominant (left) hemisphere would benefit from a more symmetrical or right-lateralized language pathway in terms of better preservation of language abilities. Furthermore, they investigated to what extent specific tumor characteristics, including proximity to the AF, affect language outcome in such patients.

METHODS

Twenty-seven right-handed patients (12 males and 15 females; mean age 52 ± 16 years) with 11 low-grade and 16 high-grade gliomas of the left hemisphere underwent 3-T diffusion-weighted MRI (30 directions) and language assessment as part of presurgical planning. For a systematic quantitative evaluation of the AF, probabilistic fiber tracking with a 2 regions of interest approach was carried out. Volumes of the 3 segments of both hemispheric AFs were evaluated by quantifying normalized and thresholded pathways. Resulting values served to generate the laterality index of the AFs.

RESULTS

Patients without language deficits tended to have an AF that was symmetric or lateralized to the right, whereas patients with deficits in language significantly more often demonstrated a left-lateralized posterior segment of the AF. Patients with high-grade gliomas had more severe language deficits than those with low-grade gliomas. Backward logistic regression revealed the laterality index of the posterior AF segment and tumor grade as the only independent statistically significant predictors for language deficits in this cohort.

CONCLUSIONS

In addition to the well-known fact that tumor entity influences behavioral outcome, the authors' findings suggest that the right homologs of structural language-associated pathways could be supportive for language function and facilitate compensation mechanisms after brain damage in functionally eloquent areas. This further indicates that knowledge about preoperative functional redistribution (identified by neurofunctional imaging) increases the chance for total or near-total resections of tumors in eloquent areas. In the future, longitudinal studies with larger groups are mandatory to overcome the methodological limitations of this cross-sectional study and to map neuroplastic changes associated with language performance and rehabilitation in brain tumor patients.

ABBREVIATIONS AF = arcuate fasciculus; BNT = Boston Naming Test; DWI = diffusion-weighted imaging; HGG = high-grade glioma; LGG = low-grade glioma; LI = lateralization index; p-VFT = phonemic Verbal Fluency Test; ROI = region of interest; SPSP = spontaneous speech; s-VFT = semantic Verbal Fluency Test; TT = Token Test.

Abstract

OBJECTIVE

Cerebral damage in frontal, parietal, and temporal brain areas and, probably more importantly, their interconnections can lead to deficits in language. However, neural plasticity and repair allow the brain to partly compensate for neural injury, mediated by both functional and structural changes. In this study, the authors sought to systematically investigate the relationship between language performance in brain tumor patients and structural perisylvian pathways (i.e., the arcuate fasciculus [AF]) using probabilistic fiber tracking on diffusion tensor imaging. The authors used a previously proposed model in which the AF is divided into anterior, long, and posterior segments. The authors hypothesized that right-handed patients with gliomas in the language-dominant (left) hemisphere would benefit from a more symmetrical or right-lateralized language pathway in terms of better preservation of language abilities. Furthermore, they investigated to what extent specific tumor characteristics, including proximity to the AF, affect language outcome in such patients.

METHODS

Twenty-seven right-handed patients (12 males and 15 females; mean age 52 ± 16 years) with 11 low-grade and 16 high-grade gliomas of the left hemisphere underwent 3-T diffusion-weighted MRI (30 directions) and language assessment as part of presurgical planning. For a systematic quantitative evaluation of the AF, probabilistic fiber tracking with a 2 regions of interest approach was carried out. Volumes of the 3 segments of both hemispheric AFs were evaluated by quantifying normalized and thresholded pathways. Resulting values served to generate the laterality index of the AFs.

RESULTS

Patients without language deficits tended to have an AF that was symmetric or lateralized to the right, whereas patients with deficits in language significantly more often demonstrated a left-lateralized posterior segment of the AF. Patients with high-grade gliomas had more severe language deficits than those with low-grade gliomas. Backward logistic regression revealed the laterality index of the posterior AF segment and tumor grade as the only independent statistically significant predictors for language deficits in this cohort.

CONCLUSIONS

In addition to the well-known fact that tumor entity influences behavioral outcome, the authors' findings suggest that the right homologs of structural language-associated pathways could be supportive for language function and facilitate compensation mechanisms after brain damage in functionally eloquent areas. This further indicates that knowledge about preoperative functional redistribution (identified by neurofunctional imaging) increases the chance for total or near-total resections of tumors in eloquent areas. In the future, longitudinal studies with larger groups are mandatory to overcome the methodological limitations of this cross-sectional study and to map neuroplastic changes associated with language performance and rehabilitation in brain tumor patients.

The neuroanatomical correlates of language have been extensively investigated using MRI over the last 25 years. It has commonly been shown that primary language-associated areas are interconnected by perisylvian fiber bundles termed the arcuate fasciculus (AF).9,38 It is known from lesion studies that damage to the inferior frontal gyrus (Broca) and to the superior temporal gyrus (Wernicke) might lead to disturbances in language function.15 Structural brain connections are important to transfer information from one region to another. Damage of connective pathways can induce functional disturbances that are often much more severe than those resulting from focal cortical brain lesions.17 The AF was previously identified in several neuroanatomical postmortem studies,11 but it can also be visualized using MRI14 and diffusion-weighted imaging (DWI) in vivo.

Previous DWI studies by Catani and colleagues demonstrated that the AF can be segmented into 3 major fiber pathways—the anterior, long, and posterior segments8,10—validated by studies using intracortical stimulation32 and functional MRI.39 There is also evidence that the AF is generally left lateralized in the normal population, according to the general left dominance of language function.18,35,36 However, Catani et al.8 demonstrated in 50 healthy subjects that a symmetric pattern of the long segment of the AF instead of left lateralization was associated with better performances in a verbal learning test. Moreover, Forkel et al. investigated the association between AF lateralization and language rehabilitation in a cohort of stroke patients.19 Their longitudinal study indicated that the volume of the long, direct segment of the AF was correlated with the severity of aphasia. In contrast, to date, the association between the laterality of the AF and language has rarely been investigated in patients with brain tumors. Previous findings from DWI studies have suggested that aphasic symptoms occur if the AF is affected by tumor-induced interruptions.6 Furthermore, a longitudinal study observed an association between preoperative AF characteristics and postoperative language recovery.29

On the basis of these previous findings, we subsequently intended to systematically investigate if the laterality of the 3 segments of the AF is a “confounder” or possibly compensatory structure in terms of language function in specific subgroups of brain tumor patients. The scope of our cross-sectional study was to analyze the association between the laterality of language pathways in patients with brain tumors in the left hemisphere and language performance. In this study, we assumed that right-handed patients with gliomas in the language-dominant (i.e., left) hemisphere would benefit from a more symmetric or right-lateralized language pathway in terms of better language abilities. Therefore, we compared patients by language performance and the laterality of the AF segments. To evaluate the impact of tumor-induced AF interruption, we additionally included tumor characteristics and various MRI parameters into multivariate statistics to identify predictors for language performance in this patient group.

Methods

Patients

MRI data including DWI were prospectively obtained for analysis from patients with brain tumors, within a clinical preoperative standard protocol at the Department of Neuroradiology (Medical University of Graz) on a 3.0-T Tim Trio system (Siemens Medical Systems) using a 32-element head coil. Twenty-seven patients with intraaxial brain tumors fulfilled the following inclusion criteria for this study: 1) right-handedness;33 2) intraaxial low-grade glioma (LGG) or high-grade glioma (HGG)30 in the left hemisphere including speech-associated areas (inferior frontal gyrus, superior or middle temporal gyrus, parietotemporal or occipitotemporal areas); 3) German as native language; 4) no contraindications for MRI; 5) no other neurological or additional psychiatric diagnosis; and 6) no signs of intracranial pressure, intracerebral hemorrhage, or disturbed circulation of the cerebrospinal fluid. Language screening tests were used to evaluate language performance. The local ethics committee approved the study and informed consent was obtained.

MRI Data

Structural imaging included a T1-weighted 3D MPRAGE (magnetization-prepared rapid gradient echo) sequence with 1-mm isotropic resolution (TR 1900 msec, TE 2.2 msec, TI 900 msec, flip angle 9°, number of slices 176, and matrix size 256 × 256). Diffusion tensor images were obtained using a diffusion-weighted single-shot spin-echo-echo-planar-imaging sequence (TR 7900 msec, TE 95 msec, flip angle 90°, in-plane resolution 1.88 × 1.88 mm2, slice thickness 1.90 mm, number of slices 60, no gap), where the diffusion-sensitizing gradients were applied in 30 directions with 1 reference scan without diffusion weighting (b0 = 1000 mm2/sec). Tumor identification was done by visual inspection of T1-weighted MR images with and without contrast-enhanced sequences. Following the procedure outlined by Catani et al.,10 tumor-associated MRI signal alterations were manually segmented on T1-weighted images. Binary masks were generated for calculating the tumor volume visible on MRI, and a study-specific lesion overlay map (in normalized 2-mm MNI [Montreal Neurological Institute] space) was generated. An experienced neuroradiologist (H.D.), blinded to the language results, performed lesion mapping and identified the proximity between the AF and the tumor. All further image-processing steps were performed by another author (M.J.) using semiautomatic scripts in FSL (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/fsl).

Data Processing

DWI scans were visually controlled for excessive head motion. Eddy current correction was done to minimize distortion and head movements. Whole-brain tractography was done with BedpostX (FSL) using a bayesian approach for the estimation of diffusion parameters within crossing fibers.3 Probabilistic streamlines were generated with ProbtrackX using a 2 region of interest (ROI) approach. General statistics were carried out using SPSS (version 22.0.0.0, IBM). Group comparisons were done using t-tests with metric variables and Mann-Whitney U-tests for nonparametric (nominal) data. Backward logistic regression was applied to identify those parameters and MRI correlates that were most predictable for language outcome in this specific patient cohort. Individual predictors were assessed using the Wald coefficient. If data did not fulfill the criteria for parametric testing (i.e., normal-distribution tested with Kolmogorov-Smirnov test), nonparametric tests (Mann-Whitney U-test, Kendall Tau-b) were used for further analyses.

Regions of Interest

Regions of interest were manually identified in an MNI standard space brain according to the work of Catani and colleagues.8,10 To construct the anterior segment, the inferior frontal mask (Broca) served as the seed region, and the parietal mask (Geschwind) served as the waypoint mask. For the long segment, the Broca mask served as seed and the temporal mask (Wernicke) as waypoint. For the posterior segment, passing streamlines were computed for the Geschwind seed to the Wernicke mask. A midline mask was specified as the exclusion mask to discharge streamlines that cross over the 2 hemispheres. Waypoint masks also served as termination masks, to stop a tract whenever it reached the specified mask.

Probabilistic Tractography

For fiber tracking, standardized 2-mm seed regions were transformed to the individual native space, and probabilistic tractography was conducted for each subject. After that, probabilistic tracts were retransformed to the standard space to provide comparability between patients. Examples of 2 patients with temporal gliomas are shown in Fig. 1. Tracts were computed in native space, and the resulting masks were then linearly registered to MNI standard space using an affine registration with 12 degrees of freedom and correlation ratio according to the work of Jenkinson and colleagues.24 Both registration results were visually checked for registration failures, as well as for possible misplacement of the ROI. After that, tractography results for each subject were normalized by dividing the pathways by the number of samples that started from each seed to allow for comparability between hemispheres. Probabilistic fiber pathways were thresholded with 0.1% of samples per voxel to exclude those voxels with very low probability values of connectivity.26

FIG. 1.
FIG. 1.

Tractography results for 2 patients with gliomas (pink) involving the temporal cortex on the left hemisphere. Upper: Patient 123. The long (red) and the posterior (yellow) segments show strong connections on the left (L) hemisphere, whereas in the right hemisphere (R) there are rarely connections (red) between the frontal and the temporal ROIs. This patient had language deficits (anomia). Lower: Patient 140. A more symmetrical pattern of the language-associated structural networks is shown. This patient did not exhibit any disturbances in language performance.

Colocalization Between Tumor and AF

A visual quality check, which was done in between to validate MRI analysis steps, showed that quantitative methods (masking thresholded and normed pathways by binary tumor masks) failed to mirror the true regional relationship. Because of the failure of this solely quantitative method, the tumor-AF colocalization (MRI-visible tumor-associated alterations within adjacent edema) was visually identified in each patient by a neuroradiologist (H.D.). Accordingly, patients were allocated into 2 groups (colocalization and no colocalization).

Language Assessment

Language testing was done by a one author (M.J.). The patients underwent a short language performance screening including spontaneous speech (SPSP) assessed by a semistructured interview,22 semantic and phonemic Verbal Fluency Tests (s-VFT and p-VFT [Regensburger Wortflüssigkeits-Test]),1 the Token Test (TT),12 and a short form of the Boston Naming Test (BNT).27

Results

Demographics

The 27 patients of the selected study group had a mean age of 52 ± 16 years. The cohort included 12 males and 15 females with left-sided tumors (7 of which were recurrences). All patients were right-handed. Eleven patients had LGGs (all WHO Grade II), and 16 patients had HGGs (5 WHO Grade III and 11 WHO Grade IV tumors). The tumors, which included astrocytomas, oligoastrocytomas, gangliogliomas, and glioblastomas, were located in frontal (n = 13), parietal (n = 3), temporal (n = 10), and tempo-rooccipital (n = 1) brain areas. Patient details are provided in Table 1.

TABLE 1.

Demographic data and performances on measures of language tests

Pt No.Age (yrs), SexTumor TypeTumor LocTumor Vol (mm3)WHO GradeTumor LobeSPSPp-VFTs-VFTBNTTT
11765, FAstrocytomaSFG44.69IIIFrontalNo deficitsNANANANA
12162, MGlioblastomaIFG50.86IVFrontalDeficits13NA5
12260, FOligoastrocytomaIFG & STG40.54IIFrontalNo deficits697230
12336, FGangliogliomaSTG9.91IIITemporalNo deficits112230
12559, FOligoastrocytomaIFG19.41IIIFrontalNo deficits6080230
12668, MGlioblastomaIFG12.98IVFrontalDeficits2323NA0
12731, FAstrocytomaIFG23.89IIFrontalNo deficits265231
12824, FAstrocytomaIFG6.47IIFrontalNo deficits170230
12951, FGlioblastomaSTG65.28IVTemporalDeficitsNANA238
13157, MAstrocytomaSMG12.01IITemporooccipitalDeficits1534230
13239, MAstrocytomaIFG17.55IIFrontalNo deficits441230
13756, MGlioblastomaIFG & STG50.00IVTemporalDeficits142018
13940, FGlioblastomapSTG55.95IVTemporalNo deficits6517231
14069, MGlioblastomaaSTG27.42IVTemporalNo deficits9890230
14257, MGlioblastomaSTG62.40IVTemporalDeficits772NA9
14343, FAstrocytomaIFG & insula66.09IIFrontalNo deficits15230
14459, FGlioblastomaSTG36.76IVTemporalNo deficits318170
14566, FOligoastrocytomaPC5.76IIIParietalDeficits3612234
14674, MGlioblastomaIFG41.96IVFrontalNo deficits3650231
14779, MGlioblastomaSMG45.32IVParietalNo deficitsNANANANA
14871, MGlioblastomaSTG67.60IVTemporalDeficits538NA13
15026, FOligoastrocytomaIFG66.97IIFrontalNo deficits131230
15140, MAstrocytomaSTG3.96IITemporalNo deficits2272230
15332, FAstrocytomaIFG5.50IIFrontalNo deficits1891230
15569, MOligoastrocytomaSTG22.69IIITemporalDeficitsNANA232
15644, FAstrocytomaSFG63.11IIFrontalNo deficits990230
15733, FAstrocytomapSTG56.49IIParietalDeficits117231

aSTG = anterior superior temporal gyrus; IFG =inferior frontal gyrus; loc = localization; NA = not available; PC = parietal cortex; pSTG = posterior superior temporal gyrus; Pt = patient; SFG = superior frontal gyrus; SMG = supramarginal gyrus; STG = superior temporal gyrus.

MRI Metrics

The tumors in this study cohort were mainly distributed around the perisylvian fissure, with the highest incidence in the superior temporal gyrus and inferior frontal cortices (Supplemental Fig. 1). In this cohort, LGGs were significantly more often located in frontal areas, whereas HGGs more often occupied temporoparietal areas. The mean tumor size was 36.35 ± 22.49 cm3 (± SD). There was no significant difference in tumor size between LGG and HGG patients (LGG, 32.96 ± 26.13 cm3; HGG, 38.69 ± 20.17 cm3; t25 = −0.643, p = 0.526). A visually identified close tumor-AF colocalization was found in 19 patients, 13 of whom (68.4%) harbored HGGs.

Lateralization of the 3 AF Segments

The volumes of the 3 segments of the AF were evaluated separately for each hemisphere. After that, a lateralization index (LI) was computed using the following formula: (left AF segment − right AF segment)/(left AF segment + right AF segment).41 Indices were computed for all 3 segments (anterior, long, and posterior AFs) within the normalized and thresholded (at 0.1%) voxel values from the probabilistic tracts. The range of possible results for LI was −1 to 1. Lateralization indices (positive values indicate left dominance) are presented in Table 2. All 3 segments of the AF showed, on average, a symmetric distribution over the hemispheres, whereas the anterior segment had a mean LI of 0.05, the long segment had a mean LI of 0.01, and the posterior segment had a mean LI of 0.11 (Fig. 2). Patients whose tumor and AF were close to one another were significantly more likely to have a left-lateralized anterior AF segment (Mann-Whitney U-test = −2.602; p = 0.009). The laterality patterns of the 3 AF segments were similar in LGG and HGG patients.

TABLE 2.

Language performance and quantitative measures for the laterality of the 3 segments of the AFs

VariableAll PtsNo Co-LocCo-Locp Value (no co-loc vs co-loc)LGG PtsHGG Ptsp Value (LGG vs HGG)
SPSP0.011*0.099*
  No deficits17 (63)8 (100)9 (47.4)9 (81.8)8 (50)
  Deficits10 (37)0 (0)10 (52.6)2 (18.2)8 (50)
TT0.134*0.156*
  No errors16 (66.6)7 (87.5)9 (56.3)9 (81.8)7 (53.8)
  Errors8 (33.3)1 (12.5)7 (43.8)2 (18.2)6 (46.2)
BNT0.152*0.056*
  No deficits18 (85.7)8 (100)10 (76.9)11 (100)7 (70)
  Deficits3 (14.3)0 (0)3 (23.1)0 (0)3 (30)
Mean p-VFT score8.70 ± 5.0510.50 ± 6.577.73 ± 3.960.2197.64 ± 2.909.67 ± 4.430.337
Mean s-VFT score18.41 ± 6.6022.63 ± 4.6016.17 ± 6.500.02121.50 ± 5.6415.63 ± 6.360.031
Tumor loc0.342*0.038*
  Frontal13 (48.1)5 (62.5)8 (42.1)8 (72.7)5 (31.3)
  Temporoparietal14 (51.9)3 (37.5)11 (57.9)3 (27.3)11 (68.8)
Mean LI of the AF
  Anterior segment0.05 ± 0.20−0.09 ± 0.100.12 ± 0.200.009*0.03 ± 0.190.07 ± 0.210.657*
  Long segment0.01 ± 0.23−0.11 ± 0.100.06 ± 0.250.167*0.00 ± 0.200.01 ± 0.250.882*
  Posterior segment0.11 ± 0.200.02 ± 0.160.15 ± 0.200.100*0.08 ± 0.200.14 ± 0.200.554*

Values are presented as the number of patients (%) unless indicated otherwise. Statistical comparisons were done to test differences between the 2 subgroups. Mean values are presented as the mean ± SD. Boldface type indicates statistical significance (p < 0.05).

Mann-Whitney U-test.

t-test.

FIG. 2.
FIG. 2.

LI for the 3 segments of the arcuate fasciculus (AF). A: LI (mean 0.05) of the anterior segment of the AF (green). B: LI (mean 0.01) of the long segment (red). C: LI (mean 0.11) of the posterior segment (yellow). D: Example for the reconstruction of the 3 segments of the AF in 1 healthy subject. It can be seen that the group results of this study tended to show a symmetrical AF pattern consistent with previously published results of healthy subjects by Catani and colleagues, 2007.

Language Performance

Seventeen of 27 patients (63%) had no deficits in SPSP, 18 patients (66.7%) could name all 23 objects from a shortened version of the BNT with 23 items, and 16 patients (59.3%) solved the TT without failure (age corrected22). Patients produced a mean of 8.70 ± 5.05 words for the p-VFT and a mean of 18.41 ± 6.60 words per minute for the s-VFT.

Predictors for Language Deficits in Brain Tumor Patients

Based on previous studies,6,13,19,42 we considered tumor localization (frontal/temporal), tumor grade (LGG/HGG), tumor volume (mm3), laterality of the 3 AF segments (LI), and tumor-AF proximity (proximal/distant) as predictive variables for language deficits in our patients. Backward logistic regression showed that only the laterality of the posterior AF segment and tumor grade were significant predictors for speech disturbance (posterior AF segment LI: β = 6.436 [Wald = 4.028], p = 0.045; tumor grade: β = 2.430 [Wald = 4.963], p = 0.026). No other variables included in the analysis revealed statistical significance.

Relationship Between Language Performance and Lateralization of the 3 AF Segments

An exploratory analysis of the data showed that 7 of 10 patients (70%) with deficits in SPSP, 5 of 8 patients (62.5%) with (age corrected22) deficits in the TT, and all 3 patients (100%) with deficits in the BNT tended to have a left-lateralized (LI > 0.17) anterior segment of the AF. Similar results were found for the other 2 segments of the AF. Patients with deficits in the language tests more often had left-lateralized long and posterior segments of the AF than patients with normal language performance (visually displayed by the distribution curve in Fig. 3). Nonparametric group comparisons (Mann-Whitney U-test) revealed that patients with deficits in SPSP (n = 10) had a left-lateralized posterior segment of the AF (Mann-Whitney U-test = −2.510, p = 0.012), and patients with deficits on the BNT (n = 3) had a left-lateralized anterior AF segment (Mann-Whitney U-test = −2.412, p = 0.016). Nonparametric correlation analyses (Kendall Tau-b) did not reveal significant correlations between the p-VFT or s-VFT and the LIs of the 3 AF segments. We used a k-means 2-step cluster analysis to classify the patients into groups according to their AF lateralization. Two groups could be separated by the lateralization indices of the 3 segments. Group 1 comprised 15 patients with symmetric or right-lateralized AF segments (mean anterior, long, and posterior LIs: −0.09, −0.17, and 0.02, respectively). Group 2 included 12 patients with left-lateralized AF segments (mean anterior, long, and posterior LIs: 0.23, 0.22, and 0.23, respectively). Regarding language performance, 12 of 15 patients (80%) in Group 1 did not have deficits in SPSP, 11 of 14 (79%) had no deficits on the TT, and 11 of 12 (92%) had no errors on the BNT. On the contrary, the language outcome of Group 2 patients (with left-lateralized segments) was more ambiguous: 7 of 12 patients (58%) had deficits in SPSP, 5 of 10 patients (50%) had errors on the TT, and 2 of 9 patients (22%) had errors on the BNT. Differences between the groups separated by the AF LI was significant for SPSP, indicating that left-lateralized AF segments were associated with SPSP deficits (Mann-Whitney U-test −2.011, p = 0.044).

FIG. 3.
FIG. 3.

Distribution of laterality indices for the 3 language tests (SPSP, TT, and BNT) and the 3 segments of the AF. Patients are classified by their tumor grade and are marked by color brightness. The x axis indicates the laterality index (from 0.60 [left] until −0.60 [right]), where positive values are on the right side and negative values are on the left side of this diagram. A straight line in the center of the diagram represents the point of 0 (symmetric), and the intermittent lines represent an index of 0.20 (−0.20) as a threshold for laterality. Curves are displaying a tendency of left laterality for patients with deficits in language, whereas the mean curves of patients without deficits incline to be right lateralized or symmetric.

Language Performance and Tumor Entity

Group comparisons showed a significant difference between LGG and HGG patients in the semantic verbal fluency; LGG patients performed better. Apart from this, no differences were found for SPSP, p-VFT, the TT, or the BNT (detailed results are displayed in Table 2).

Laterality Differences Between LGG and HGG Patients

In LGG patients, right-lateralized anterior and long AF segments were significantly correlated with better performance on the 2 VFTs (anterior AF LI: Kendall Tau-b = −0.491, p = 0.036; posterior AF LI: Kendall Tau-b = −0.491, p = 0.036). On the other language tests (SPSP, TT, and BNT) only 2 of 11 LGG patients (18.2%) had deficits, and thus we decided to discard the representations of these results. HGG patients revealed better results in the SPSP, in the TT, and the BNT if the anterior and long segments of the AF were right lateralized. The laterality of the posterior segment tended to be leftward in HGG patients with as well as in patients without deficits in language (Fig. 3).

Discussion

Laterality of the AF and Language in Patients With Left-Sided Brain Tumors

Using probabilistic tractography, we explored the association between language performance and laterality of the AF in patients with left-sided brain tumors. The results suggest a relationship between a symmetric or right lateralization of the posterior part of the AF and better performances in language tasks in brain tumor patients. Conversely, left laterality of the AF segments was associated with deficits on various language tests. On the basis of these observations, it may be speculated that the AF in the right hemisphere (in the context of a left-hemisphere tumor in right-handed patients) supports the compensation of possible tumor-induced deficits in language. Forkel and colleagues found similar results in their study with stroke patients. The patients in their cohort experienced infarctions of the left middle cerebral artery and showed aphasic symptoms. Tractography results indicated that the long segment of the right hemisphere aided in language recovery.19 Extrapolating these results to our study, it can be speculated that the functions of pathways that are responsible for language were adopted by parts of the contralateral AF.

When comparing the results of our study with previous investigations in healthy controls, it can be seen that our patients had, on average, symmetric patterns of the anterior, long, and posterior segments of the AF. Catani and colleagues found in 50 healthy subjects that averaged values of fractional anisotropy of the 3 AF segments were likewise symmetric between hemispheres.8 Separating the group by a k-means cluster analysis, the authors showed that the majority of individuals had a strong left-sided lateralization, and only 17.5% showed a more bilateral symmetry of the long segment of AF. Moreover, subjects with more symmetric long segments performed better in the semantic verbal recall.8 This indicates that a more symmetric predisposition of the AF supports superior language abilities, even in healthy subjects.

Classifying our clinical cohort into 2 groups by laterality of the AF, we observed that the majority of patients in the group with symmetric, or rather, right-lateralized segments had fewer deficits in their spontaneous speech than the patients in the left-lateralized group. In the patient group with left-lateralized AF segments, the language outcome was more divergent, indicating that laterality plays a role in language performance, but there may be other important influential factors that impact language competencies (e.g., level of education, age, sex, brain compression, and edematous parenchyma).26 A future study with a larger cohort allowing homogeneous subgroups is desirable for investigation of the contribution of AF laterality and influential factors on language performance.

Comparison Between Slowly and Rapidly Growing Tumors

The second variable that we investigated regarding the predictive role for language performance was the tumor entity. We compared patients with slow- and fast-growing tumors by dichotomizing our cohort (LGG and HGG groups). The behavioral data showed that the subgroups, which did not differ in terms of tumor size, differed in the semantic verbal fluency test. In contrast to patients with LGGs, those with HGGs had impairments in semantic components of verbal expression. In our cohort, HGGs were more often located in temporoparietal regions. These regions are known to contribute to semantic verbal fluency tasks over frontal regions, which might explain the group difference in s-VFT results in our study.2 In addition, slow-growing tumors more likely allow for possible adaptation processes,13,28 and aphasic symptoms were probably better compensated in our LGG group.

Our results are limited by the inclusion of patients with recurrent tumors after surgery (to increase the group size). Neuroplastic adaptations due to tumor recurrences regarding language functions are not yet well known. There are indicators that the surgery itself, rehabilitation, radio-and/or chemotherapy, and tumor regrowth can stimulate further neuroplastic reorganization,16 potentially making our patient cohort more heterogeneous because of these additional confounders. In future studies, such subjects should be excluded or handled separately as a subgroup in larger cohorts. The small overall and subgroup sizes were another limitation of the study. Multicenter trials with large homogeneous patient samples are required to enable parametric statistical investigations regarding the laterality of language and structural connectivity.

Besides differences in neuroplasticity, there are also other factors that differ between LGGs and HGGs. Bello and colleagues performed subcortical stimulation of the language tract and reported that patients with LGGs had more functional tracts inside the tumor mass than those with HGGs.5 They argued that HGGs destroy the tissue within the tumor by aggressive growth. With preoperative MRI, as carried out in our study, we were not able to differentiate between functionally intact or disrupted tracts in LGGs. To extend the results of our study, inclusion of data from postoperative scans might be beneficial to validate the finding that pre- and postoperative visualization of the AF is correlated with improvement in language performance.21,29 Our results support cautious decision making concerning surgical strategies to preserve functionally eloquent brain structures, such as the perisylvian white matter paths. Nonetheless, we have to admit that surrounding edema, which is often found in HGG, could not be considered (because T2-weighted images were not available for this cohort), although it is known that perilesional edema can induce transient language deficits.6 To overcome artificial MRI signal due to edema affecting tractography, it was previously recommended to decrease the FA threshold within or around lesions to minimize the occurrence of false-negative results that could significantly impact the surgical outcome.29 We therefore chose a constant threshold to minimize subjectivity3,4 and normalized each tract with the number of total streamlines that were sent out from the seed masks and thresholded it by 0.1%. This threshold was chosen to avoid uncertain connections by excluding voxels that have only a 1-in-1000 chance to be part of the tract of interest.19,37 Future studies should additionally include edema maps into analyses to check for the influence of an edema.

Tumor Growing and Neuroplasticity

Regarding the type of disease, it may also be speculated that the slowness of tumor growth facilitates adaptation processes, which again may lead to neuroplastic changes in homolog white matter tracts of the contralesional hemisphere. Training-induced neuroplasticity phenomena accompanied by compensatory functions have been reported in several previous studies.31,40 White matter changes can occur in terms of new organization of fibers, leading to stronger connections, but also microstructural alterations, such as myelin formation and remodeling, astrocytic proliferation, or angiogenesis, can encourage growth of structural connectivity.43 With the data in our study, we cannot differentiate if the laterality patterns existed before the tumor grew or if they were a consequence of tumor growth. Notwithstanding this fact, we suggest that homolog brain structures of the healthy hemisphere support, or rather enhance, functional performance, as can occur in stroke patients19,37 and even in healthy subjects.23 Future studies investigating changes in white matter connectivity in the contralateral AF in patients with LGGs are necessary to provide better insight into neuroplasticity.

Studies in tumor patients with subcortical stimulation demonstrated a good concordance between preoperatively contracted probabilistic tractography and intraoperative-stimulated positive responses for white matter bundles.7,25 Furthermore, the results of our study showed that patients with more strongly lateralized right-sided language pathways had better performance in language, possibly indicating compensation mechanisms.20,34 Additional intraoperative subcortical stimulation would be useful to validate our MRI findings but would definitely exceed the setting of the current study. We would expect a better intraoperative performance (fewer positive sites) because of this greater extent of resection in patients with right-lateralized AFs due to the compensation mechanisms discussed above.

On the basis of our results, it can be seen that deficits in object naming and spontaneous speech are slightly dependent on left lateralization of the anterior, long, and posterior segments of the AF and are mainly found in HGG patients. It can be concluded that anomia, which leads to deficits on both tests (SPSP and BNT), is associated with left laterality of all 3 AF segments in patients with fast-growing brain tumors. When interpreting our results, one must consider that HGG patients more often had tumors closer to the left AF than LGG patients and in temporal brain areas, which may have favored on the one hand the relationship between language outcome and tumor grade and on the other hand the correlation between the laterality of the posterior AF segment and language function. To consider these potentially confounding aspects in more detail, studies with larger cohorts are desirable. Validating the observed relationship between laterality of the AF and language performance in a larger cohort of brain tumor patients might provide deeper understanding of pathological cerebral processes and their functional outcome and could probably have indications for future surgical interventions. For example, resection borders of left-sided tumor could probably be extended in patients with a bilateral distribution of the AF segments while preserving language functions. In presurgical planning and intraoperative decision making, the sum of several factors (language function, clinical parameters, tumor characteristics, and, importantly, potentials of neural plasticity) needs to be considered to optimize lesion removal. New, sophisticated methods in neuroimaging can contribute to this process.

Conclusions

The hemispheric distribution of the AF seems to play an important role in processing language in healthy subjects, in patients with stroke, and, as shown here, in patients with brain tumors. Given the importance of language function in daily life, the results of our study should stimulate further research in this field to collect more information about structural and functional correlates of language compensation in patients with brain tumors. Furthermore, subsequent studies with larger cohorts could provide significant results for surgical decision making. In addition, longitudinal study designs with diffusion tensor imaging–based evaluation methods might provide insights into compensatory mechanisms for language deficits on the level of white matter plasticity in patients with brain tumors.

Acknowledgments

We thank Fritz Studencnik and Stephan Wolff for their technical support. This study was partly supported by the BA-Visiting-Program (recipient: Margit Jehna).

Disclosures

The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Author Contributions

Conception and design: Jehna, Becker, Zaar, von Campe, Fazekas, Enzinger, Deutschmann. Acquisition of data: Jehna, Zaar, von Campe, Mahdy Ali, Reishofer, Payer, Enzinger, Deutschmann. Analysis and interpretation of data: Jehna, Becker, Zaar, Mahdy Ali, Reishofer. Drafting the article: Jehna, Becker, Enzinger, Deutschmann. Critically revising the article: Jehna, Becker, von Campe, Mahdy Ali, Reishofer, Payer, Synowitz, Fazekas, Enzinger. Approved the final version of the manuscript on behalf of all authors: Jehna. Statistical analysis: Jehna, Becker, Enzinger. Administrative/technical/material support: Fazekas, Deutschmann. Study supervision: Fazekas, Enzinger, Deutschmann.

Supplemental Information

Online-Only Content

Supplemental material is available with the online version of the article.

References

  • 1

    Aschenbrenner STucha OLange KW: Regensburger Wortflüssigkeits-Test GöttingenHogrefe Verlag für Psychologie2000

  • 2

    Baldo JVSchwartz SWilkins DDronkers NF: Role of frontal versus temporal cortex in verbal fluency as revealed by voxel-based lesion symptom mapping. J Int Neuropsychol Soc 12:8969002006

  • 3

    Behrens TEJBerg HJJbabdi SRushworth MFSWoolrich MW: Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?. Neuroimage 34:1441552007

  • 4

    Behrens TEJWoolrich MWJenkinson MJohansen-Berg HNunes RGClare S: Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med 50:107710882003

  • 5

    Bello LGallucci MFava MCarrabba GGiussani CAcerbi F: Intraoperative subcortical language tract mapping guides surgical removal of gliomas involving speech areas. Neurosurgery 60:67822007

  • 6

    Bizzi ANava SFerrè FCastelli GAquino DCiaraffa F: Aphasia induced by gliomas growing in the ventrolateral frontal region: assessment with diffusion MR tractography, functional MR imaging and neuropsychology. Cortex 48:2552722012

  • 7

    Bucci MMandelli MLBerman JIAmirbekian BNguyen CBerger MS: Quantifying diffusion MRI tractography of the corticospinal tract in brain tumors with deterministic and probabilistic methods. Neuroimage Clin 3:3613682013

  • 8

    Catani MAllin MPHusain MPugliese LMesulam MMMurray RM: Symmetries in human brain language pathways correlate with verbal recall. Proc Natl Acad Sci U S A 104:17163171682007

  • 9

    Catani Mffytche DH: The rises and falls of disconnection syndromes. Brain 128:222422392005

  • 10

    Catani MJones DKffytche DH: Perisylvian language networks of the human brain. Ann Neurol 57:8162005

  • 11

    Catani MMesulam M: The arcuate fasciculus and the disconnection theme in language and aphasia: history and current state. Cortex 44:9539612008

  • 12

    De Renzi EVignolo LA: The token test: A sensitive test to detect receptive disturbances in aphasics. Brain 85:6656781962

  • 13

    Desmurget MBonnetblanc FDuffau H: Contrasting acute and slow-growing lesions: a new door to brain plasticity. Brain 130:8989142007

  • 14

    Dick ASTremblay P: Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language. Brain 135:352935502012

  • 15

    Dronkers NFWilkins DPVan Valin RD JrRedfern BBJaeger JJ: Lesion analysis of the brain areas involved in language comprehension. Cognition 92:1451772004

  • 16

    Duffau H: Brain Mapping: From Neural Basis of Cognition to Surgical Applications ViennaSpringer2011

  • 17

    Duffau H: The huge plastic potential of adult brain and the role of connectomics: new insights provided by serial mappings in glioma surgery. Cortex 58:3253372014

  • 18

    Fernández-Miranda JCWang YPathak SStefaneau LVerstynen TYeh FC: Asymmetry, connectivity, and segmentation of the arcuate fascicle in the human brain. Brain Struct Funct 220:166516802015

  • 19

    Forkel SJThiebaut de Schotten MDell'Acqua FKalra LMurphy DGWilliams SC: Anatomical predictors of aphasia recovery: a tractography study of bilateral perisylvian language networks. Brain 137:202720392014

  • 20

    Giussani CRoux FEOjemann JSganzerla EPPirillo DPapagno C: Is preoperative functional magnetic resonance imaging reliable for language areas mapping in brain tumor surgery?. Review of language functional magnetic resonance imaging and direct cortical stimulation correlation studies Neurosurgery 66:1131202010

  • 21

    Hayashi YKinoshita MNakada MHamada J: Correlation between language function and the left arcuate fasciculus detected by diffusion tensor imaging tractography after brain tumor surgery. J Neurosurg 117:8398432012

  • 22

    Huber WWillmes KPoeck K: Aachener Aphasie-Test GöttingenVerlag für Psychologie Hogrefe1983

  • 23

    Hugdahl KWesterhausen R: The Two Halves of the Brain Cambridge, MAMIT Press2010

  • 24

    Jenkinson MBannister PBrady MSmith S: Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17:8258412002

  • 25

    Jiménez de la Peña MGil Robles SRecio Rodríguez MRuiz Ocaña CMartínez de Vega V: Cortical and subcortical mapping of language areas: correlation of functional MRI and tractography in a 3T scanner with intraoperative cortical and subcortical stimulation in patients with brain tumors located in eloquent areas. Radiologia 55:5055132013

  • 26

    Johansen-Berg HBehrens TEJ: Diffusion MRI LondonElsevier2009

  • 27

    Kaplan EGoodglass HWeintraub S: The Boston Naming Test PhiladelphiaLea & Febiger1983

  • 28

    Keidel JLWelbourne SRLambon Ralph MA: Solving the paradox of the equipotential and modular brain: a neurocomputational model of stroke vs. slow-growing glioma. Neuropsychologia 48:171617242010

  • 29

    Kinoshita MNakada MOkita HHamada JHayashi Y: Predictive value of fractional anisotropy of the arcuate fasciculus for the functional recovery of language after brain tumor resection: a preliminary study. Clin Neurol Neurosurg 117:45502014

  • 30

    Louis DNOhgaki HWiestler ODCavenee WKBurger PCJouvet A: The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol 114:971092007

  • 31

    Maguire EAGadian DGJohnsrude ISGood CDAshburner JFrackowiak RS: Navigation-related structural change in the hippocampi of taxi drivers. Proc Natl Acad Sci U S A 97:439844032000

  • 32

    Matsumoto RNair DRLaPresto ENajm IBingaman WShibasaki H: Functional connectivity in the human language system: a cortico-cortical evoked potential study. Brain 127:231623302004

  • 33

    Oldfield RC: The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9:971131971

  • 34

    Papagno CGallucci MCasarotti ACastellano AFalini AFava E: Connectivity constraints on cortical reorganization of neural circuits involved in object naming. Neuroimage 55:130613132011

  • 35

    Parker GJMLuzzi SAlexander DCWheeler-Kingshott CAMCiccarelli OLambon Ralph MA: Lateralization of ventral and dorsal auditory-language pathways in the human brain. Neuroimage 24:6566662005

  • 36

    Powell HWRParker GJMAlexander DCSymms MRBoulby PAWheeler-Kingshott CAM: Hemispheric asymmetries in language-related pathways: a combined functional MRI and tractography study. Neuroimage 32:3883992006

  • 37

    Saur DLange RBaumgaertner ASchraknepper VWillmes KRijntjes M: Dynamics of language reorganization after stroke. Brain 129:137113842006

  • 38

    Schmahmann JDPandya DNWang RDai GD'Arceuil HEde Crespigny AJ: Association fibre pathways of the brain: parallel observations from diffusion spectrum imaging and autoradiography. Brain 130:6306532007

  • 39

    Schmithorst VJHolland SK: Sex differences in the development of neuroanatomical functional connectivity underlying intelligence found using Bayesian connectivity analysis. Neuroimage 35:4064192007

  • 40

    Scholz JKlein MCBehrens TEJohansen-Berg H: Training induces changes in white-matter architecture. Nat Neurosci 12:137013712009

  • 41

    Seghier ML: Laterality index in functional MRI: methodological issues. Magn Reson Imaging 26:5946012008

  • 42

    Taphoorn MJBKlein M: Cognitive deficits in adult patients with brain tumours. Lancet Neurol 3:1591682004

  • 43

    Zatorre RJFields RDJohansen-Berg H: Plasticity in gray and white: neuroimaging changes in brain structure during learning. Nat Neurosci 15:5285362012

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Article Information

Correspondence Margit Jehna, Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Auenbruggerplatz 9, Graz 8036, Austria. email: margit.jehna@medunigraz.at.

INCLUDE WHEN CITING Published online January 27, 2017; DOI: 10.3171/2016.9.JNS161281.

Disclosures The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

© AANS, except where prohibited by US copyright law.

Headings

Figures

  • View in gallery

    Tractography results for 2 patients with gliomas (pink) involving the temporal cortex on the left hemisphere. Upper: Patient 123. The long (red) and the posterior (yellow) segments show strong connections on the left (L) hemisphere, whereas in the right hemisphere (R) there are rarely connections (red) between the frontal and the temporal ROIs. This patient had language deficits (anomia). Lower: Patient 140. A more symmetrical pattern of the language-associated structural networks is shown. This patient did not exhibit any disturbances in language performance.

  • View in gallery

    LI for the 3 segments of the arcuate fasciculus (AF). A: LI (mean 0.05) of the anterior segment of the AF (green). B: LI (mean 0.01) of the long segment (red). C: LI (mean 0.11) of the posterior segment (yellow). D: Example for the reconstruction of the 3 segments of the AF in 1 healthy subject. It can be seen that the group results of this study tended to show a symmetrical AF pattern consistent with previously published results of healthy subjects by Catani and colleagues, 2007.

  • View in gallery

    Distribution of laterality indices for the 3 language tests (SPSP, TT, and BNT) and the 3 segments of the AF. Patients are classified by their tumor grade and are marked by color brightness. The x axis indicates the laterality index (from 0.60 [left] until −0.60 [right]), where positive values are on the right side and negative values are on the left side of this diagram. A straight line in the center of the diagram represents the point of 0 (symmetric), and the intermittent lines represent an index of 0.20 (−0.20) as a threshold for laterality. Curves are displaying a tendency of left laterality for patients with deficits in language, whereas the mean curves of patients without deficits incline to be right lateralized or symmetric.

References

1

Aschenbrenner STucha OLange KW: Regensburger Wortflüssigkeits-Test GöttingenHogrefe Verlag für Psychologie2000

2

Baldo JVSchwartz SWilkins DDronkers NF: Role of frontal versus temporal cortex in verbal fluency as revealed by voxel-based lesion symptom mapping. J Int Neuropsychol Soc 12:8969002006

3

Behrens TEJBerg HJJbabdi SRushworth MFSWoolrich MW: Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?. Neuroimage 34:1441552007

4

Behrens TEJWoolrich MWJenkinson MJohansen-Berg HNunes RGClare S: Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med 50:107710882003

5

Bello LGallucci MFava MCarrabba GGiussani CAcerbi F: Intraoperative subcortical language tract mapping guides surgical removal of gliomas involving speech areas. Neurosurgery 60:67822007

6

Bizzi ANava SFerrè FCastelli GAquino DCiaraffa F: Aphasia induced by gliomas growing in the ventrolateral frontal region: assessment with diffusion MR tractography, functional MR imaging and neuropsychology. Cortex 48:2552722012

7

Bucci MMandelli MLBerman JIAmirbekian BNguyen CBerger MS: Quantifying diffusion MRI tractography of the corticospinal tract in brain tumors with deterministic and probabilistic methods. Neuroimage Clin 3:3613682013

8

Catani MAllin MPHusain MPugliese LMesulam MMMurray RM: Symmetries in human brain language pathways correlate with verbal recall. Proc Natl Acad Sci U S A 104:17163171682007

9

Catani Mffytche DH: The rises and falls of disconnection syndromes. Brain 128:222422392005

10

Catani MJones DKffytche DH: Perisylvian language networks of the human brain. Ann Neurol 57:8162005

11

Catani MMesulam M: The arcuate fasciculus and the disconnection theme in language and aphasia: history and current state. Cortex 44:9539612008

12

De Renzi EVignolo LA: The token test: A sensitive test to detect receptive disturbances in aphasics. Brain 85:6656781962

13

Desmurget MBonnetblanc FDuffau H: Contrasting acute and slow-growing lesions: a new door to brain plasticity. Brain 130:8989142007

14

Dick ASTremblay P: Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language. Brain 135:352935502012

15

Dronkers NFWilkins DPVan Valin RD JrRedfern BBJaeger JJ: Lesion analysis of the brain areas involved in language comprehension. Cognition 92:1451772004

16

Duffau H: Brain Mapping: From Neural Basis of Cognition to Surgical Applications ViennaSpringer2011

17

Duffau H: The huge plastic potential of adult brain and the role of connectomics: new insights provided by serial mappings in glioma surgery. Cortex 58:3253372014

18

Fernández-Miranda JCWang YPathak SStefaneau LVerstynen TYeh FC: Asymmetry, connectivity, and segmentation of the arcuate fascicle in the human brain. Brain Struct Funct 220:166516802015

19

Forkel SJThiebaut de Schotten MDell'Acqua FKalra LMurphy DGWilliams SC: Anatomical predictors of aphasia recovery: a tractography study of bilateral perisylvian language networks. Brain 137:202720392014

20

Giussani CRoux FEOjemann JSganzerla EPPirillo DPapagno C: Is preoperative functional magnetic resonance imaging reliable for language areas mapping in brain tumor surgery?. Review of language functional magnetic resonance imaging and direct cortical stimulation correlation studies Neurosurgery 66:1131202010

21

Hayashi YKinoshita MNakada MHamada J: Correlation between language function and the left arcuate fasciculus detected by diffusion tensor imaging tractography after brain tumor surgery. J Neurosurg 117:8398432012

22

Huber WWillmes KPoeck K: Aachener Aphasie-Test GöttingenVerlag für Psychologie Hogrefe1983

23

Hugdahl KWesterhausen R: The Two Halves of the Brain Cambridge, MAMIT Press2010

24

Jenkinson MBannister PBrady MSmith S: Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17:8258412002

25

Jiménez de la Peña MGil Robles SRecio Rodríguez MRuiz Ocaña CMartínez de Vega V: Cortical and subcortical mapping of language areas: correlation of functional MRI and tractography in a 3T scanner with intraoperative cortical and subcortical stimulation in patients with brain tumors located in eloquent areas. Radiologia 55:5055132013

26

Johansen-Berg HBehrens TEJ: Diffusion MRI LondonElsevier2009

27

Kaplan EGoodglass HWeintraub S: The Boston Naming Test PhiladelphiaLea & Febiger1983

28

Keidel JLWelbourne SRLambon Ralph MA: Solving the paradox of the equipotential and modular brain: a neurocomputational model of stroke vs. slow-growing glioma. Neuropsychologia 48:171617242010

29

Kinoshita MNakada MOkita HHamada JHayashi Y: Predictive value of fractional anisotropy of the arcuate fasciculus for the functional recovery of language after brain tumor resection: a preliminary study. Clin Neurol Neurosurg 117:45502014

30

Louis DNOhgaki HWiestler ODCavenee WKBurger PCJouvet A: The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol 114:971092007

31

Maguire EAGadian DGJohnsrude ISGood CDAshburner JFrackowiak RS: Navigation-related structural change in the hippocampi of taxi drivers. Proc Natl Acad Sci U S A 97:439844032000

32

Matsumoto RNair DRLaPresto ENajm IBingaman WShibasaki H: Functional connectivity in the human language system: a cortico-cortical evoked potential study. Brain 127:231623302004

33

Oldfield RC: The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9:971131971

34

Papagno CGallucci MCasarotti ACastellano AFalini AFava E: Connectivity constraints on cortical reorganization of neural circuits involved in object naming. Neuroimage 55:130613132011

35

Parker GJMLuzzi SAlexander DCWheeler-Kingshott CAMCiccarelli OLambon Ralph MA: Lateralization of ventral and dorsal auditory-language pathways in the human brain. Neuroimage 24:6566662005

36

Powell HWRParker GJMAlexander DCSymms MRBoulby PAWheeler-Kingshott CAM: Hemispheric asymmetries in language-related pathways: a combined functional MRI and tractography study. Neuroimage 32:3883992006

37

Saur DLange RBaumgaertner ASchraknepper VWillmes KRijntjes M: Dynamics of language reorganization after stroke. Brain 129:137113842006

38

Schmahmann JDPandya DNWang RDai GD'Arceuil HEde Crespigny AJ: Association fibre pathways of the brain: parallel observations from diffusion spectrum imaging and autoradiography. Brain 130:6306532007

39

Schmithorst VJHolland SK: Sex differences in the development of neuroanatomical functional connectivity underlying intelligence found using Bayesian connectivity analysis. Neuroimage 35:4064192007

40

Scholz JKlein MCBehrens TEJohansen-Berg H: Training induces changes in white-matter architecture. Nat Neurosci 12:137013712009

41

Seghier ML: Laterality index in functional MRI: methodological issues. Magn Reson Imaging 26:5946012008

42

Taphoorn MJBKlein M: Cognitive deficits in adult patients with brain tumours. Lancet Neurol 3:1591682004

43

Zatorre RJFields RDJohansen-Berg H: Plasticity in gray and white: neuroimaging changes in brain structure during learning. Nat Neurosci 15:5285362012

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