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Purpose: Language functional magnetic resonance imaging (fMRI) is used to noninvasively assess hemispheric language specialization as part of the presurgical work-up in temporal lobe epilepsy (TLE). White matter asymmetries on diffusion tensor imaging (DTI) may be related to language specialization as shown in controls and TLE. To refine our understanding of the effect of epilepsy on the structure–function relationships, we focused on the arcuate fasciculus (ArcF) and the inferior occipitofrontal fasciculus (IOF) and tested the relationship between DTI- and fMRI-based lateralization indices in TLE.
Methods: fMRI with three language tasks and DTI were obtained in 20 patients (12 right and 8 left TLE). The ArcF, a major language-related tract, and the IOF were segmented bilaterally using probabilistic tractography to obtain fractional anisotropy (FA) lateralization indices. These were correlated with fMRI-based lateralization indices computed in the inferior frontal gyrus (Pearson's correlation coefficient).
Results: fMRI indices were left-lateralized in 16 patients and bilateral or right-lateralized in four. In the ArcF, FA was higher on the left than on the right side, reaching significance in right but not in left TLE. We found a positive correlation between ArcF anisotropy and fMRI-based lateralization indices in right TLE (p < 0.009), but not in left TLE patients. No correlation was observed for the IOF.
Conclusions: Right TLE patients with more left-lateralized functional activations also showed a leftward-lateralized arcuate fasciculus. The decoupling between the functional and structural indices of the ArcF underlines the complexity of the language network in left TLE patients.
In the presurgical work-up of patients with intractable temporal lobe epilepsy (TLE), functional magnetic resonance imaging (fMRI) is increasingly used to lateralize language function and to identify eloquent cortex to be spared during epilepsy surgery (Springer et al., 1999; Lehericy et al., 2000; Adcock et al., 2003; Sabbah et al., 2003). Several studies have shown a higher proportion of atypical language representation in TLE patients, especially in those with left-sided intractable seizures (Springer et al., 1999; Sabbah et al., 2003; Thivard et al., 2005; Sveller et al., 2006). This supports a reorganization of language circuits with greater involvement of the right hemisphere, which may represent an adaptive process following a brain insult early in life (Thivard et al., 2005). Hemispheric language dominance is associated with structural brain asymmetries in the size of regions of the cerebral cortex (Geschwind & Levitsky, 1968; Josse et al., 2006). Larger white matter volumes in the left hemisphere could provide a structural basis for greater intrahemispheric connectivity (Golestani et al., 2002; Josse et al., 2006). The role of white matter in hemispheric language specialization is further supported by the use of diffusion tensor imaging (DTI), (Pierpaoli et al., 1996; Le Bihan et al., 2001). Anisotropy measures such as fractional anisotropy (FA) provided by DTI, could reflect the organization of white matter fiber tracts (Beaulieu, 2002). Axonal white matter fibers connecting cortical regions involved in speech, language, and reading may demonstrate asymmetry in their microstructural organization, the degree of axon myelination, or in the integrity of axonal cell membranes (Golestani et al., 2002; Pujol et al., 2002). In line with this, a DTI study revealed a leftwards FA asymmetry of the arcuate fasciculus (ArcF) (Buchel et al., 2004), a white matter tract connecting dorsally the anterior and posterior language poles. Besides the ArcF, the subinsular white matter, a region that contains connections between anterior and posterior cortical language regions, has also been the focus of interest. Leftward structural asymmetries have been reported in the subinsular region in right-handed volunteers (Cao et al., 2003). By segmenting the subinsular area using tractography, it has been shown that two tracts, namely the uncinate fasciculus and the inferior occipitofrontal fasciculus (IOF), also display a leftward structural asymmetry in right-handers (Rodrigo et al., 2007). The IOF connects Wernicke's area and Broca's area ventrally and is likely implicated in the language network (Duffau et al., 2005). Diffusion MR tractography has shown that the IOF also has stronger connections in the left hemisphere in right-handed volunteers (Rodrigo et al., 2007a). Overall, interhemispheric white matter asymmetries of tracts connecting Wernicke's area to Broca's area, namely the ArcF and IOF, may be important anatomical substrates for hemispheric language specialization.
Imaging the white matter tracts using diffusion tractography can be combined with fMRI using blood-oxygenated level dependent signal changes, to noninvasively explore the in vivo structure–function relationship (Werring et al., 1998; Powell et al., 2006). Recently, a study combining DTI and fMRI reported that right-handed subjects had more extensive frontotemporal connections between Broca's area and Wernicke's area on the left than on the right side (Powell et al., 2006). Interestingly, this study found a correlation between measures of structure and function, with subjects with more lateralized fMRI activation having a more lateralized anisotropy of their frontotemporal connections. These correlations were obtained in a group of strongly right-handed patients, raising the question of the effect of atypical language dominance upon the structure–function relationship. Atypical language representation, defined as right hemisphere dominance or bilateral representation, is more frequent in left-handers, and in patients with left hemispheric lesions (Staudt et al., 2001; Hertz-Pannier et al., 2002). Powell et al. were the first to combine fMRI and diffusion tractography, in a study involving a group of 14 patients with TLE (Powell et al., 2007). They showed that controls and right TLE patients had a left-lateralized pattern of both language-related activations and the associated structural connections. Left TLE patients showed more symmetrical language activations, along with reduced left hemisphere and increased right hemisphere structural connections. If replicated, these findings would have important clinical implications. Indeed, the study of white matter structure using DTI could become a useful adjunct to fMRI in noninvasively predicting postoperative language deficits in TLE patients (Sabsevitz et al., 2003). Recently, another group found unexpected results in a group of 7 right-handed and 13 left-handed volunteers (Vernooij et al., 2007). Replicating the correlation between structural measurements in the ArcF and fMRI language lateralization indices in right-handers, this group found no correlation in left-handed volunteers. They showed an overall leftward asymmetry of the ArcF, regardless of functional hemispheric language lateralization. In light of these conflicting data, we combined fMRI and diffusion probabilistic tractography to search for additional evidence supporting the structure–function relationship in 20 TLE patients. We specifically focused our study on the ArcF and IOF, since these are both structurally asymmetric (Buchel et al., 2004; Rodrigo et al., 2007), connecting Broca's area to Wernicke's area, and therefore potential candidates to reflect functional hemispheric language lateralization.
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- Materials and Methods
The combination of fMRI, to identify cortical regions involved in a given function, and diffusion tractography, to visualize pathways connecting these regions, provides an opportunity to study the relationship between brain structure and function. As previously done for healthy controls (Powell et al., 2006; Vernooij et al., 2007), we combined these two imaging tools to search for relationships between functional hemispheric language lateralization and structural white matter asymmetries in TLE patients. We found a correlation between the ArcF structural lateralization and the leftward asymmetry in functional activation in right TLE patients, with patients with a more lateralized language function having a more lateralized FA measurements. This correlation was no longer observed in left TLE patients, suggesting a decoupling between structural- and functional-based lateralization indices in patients with epilepsy of left temporal origin.
The lateralization of language is a striking feature of human brain function. Left-sided hemispheric language lateralization has been shown, using fMRI, in up to 95% of right-handed controls (Springer et al., 1999). Recent DTI studies showed white matter structural asymmetries in tracts involved in the language network (Cao et al., 2003; Catani et al., 2005; Parker et al., 2005; Rodrigo et al., 2007). Several studies have reported higher anisotropy in the left than in the right ArcF in right-handed volunteers (Buchel et al., 2004; Rodrigo et al., 2007). These findings were reported in subjects whose language lateralization was not known, although it was presumably left-sided in most right-handed participants. Recently, in a series of 10 right-handed controls with confirmed left language representation on fMRI, Powell et al. found greater frontotemporal connectivity in the left hemisphere than in the right (Powell et al., 2006). The putative role of such structural asymmetries in the language network was further strengthened by the correlation between measures of structure and function, with right-handed controls with more lateralized fMRI language activation having a more highly lateralized anisotropy of their connections (Powell et al., 2006). The same group repeated the analysis in TLE patients (Powell et al., 2007). As for right-handed controls, they found that right TLE patients showed greater frontotemporal connectivity in the left hemisphere than in the right. Despite numerous methodological differences, we also found greater leftward anisotropy of the ArcF in right TLE patients, along with a correlation between functional and structural indices in this group of patients. We did, however, use a different approach. We were interested in measuring diffusion anisotropy in two particular bundles, the IOF and the ArcF, which are likely implicated in the language network. Powell et al., on the other hand, analyzed a larger volume of white matter using fMRI-active regions as starting points for fiber tracking (Powell et al., 2007). Our analysis thus complements that of Powell et al. by directly demonstrating that the ArcF likely participates in the structure–function correlation that they found in a large temporal area in right TLE patients (Powell et al., 2007).
In left TLE patients, we observed a loss of the significantly greater leftward anisotropy within the ArcF, along with the lack of correlation between the ArcF structural lateralization and the leftward asymmetry in functional activation. Atypical language representation is observed more frequently in TLE patients with a left-sided epileptic focus, suggesting that the side of the epileptogenic process plays a role in language lateralization (Adcock et al., 2003; Sabbah et al., 2003; Thivard et al., 2005). Accordingly, we found atypical fMRI language representation more frequently in left TLE than in right TLE patients. In left TLE patients, Powell et al. recently found a correlation between functional lateralization and lateralization of the mean FA of frontal connections (Powell et al., 2007). In that study, left TLE patients showed more symmetrical language activations than controls and right TLE patients, along with reduced left frontal and increased right frontal structural connections. However, in that study, anisotropy was measured in a relatively large “connectivity volume,” which provides a global measurement over the frontal white matter but does not allow the pathways that most contribute to this structure–function relationship to be identified. In our study, the relationship between brain structure and function that was observed in right TLE patients for the ArcF was not maintained in left TLE patients. This could simply be due to the large variability in fMRI and diffusion-based indices between patients and the relatively small sample of left TLE patients in our study. It could also indicate that the functional reorganization that presumably occurs as a result of chronic ictal discharge arising from the left temporal lobe is not associated with a shift from the left towards the right ArcF. The fact that the asymmetry of the ArcF connectivity in left TLE patients was not driven by hemispheric language specialization can be compared with recent DTI findings that showed a leftward asymmetry of the ArcF in volunteers, irrespective of handedness or hemispheric specialization (Vernooij et al., 2007). The question arises about the functional interpretation of the leftward ArcF asymmetry. It seems likely that the ArcF is not exclusively involved in language processing but also plays a role in other functions that could be lateralized to the left hemisphere irrespective of the side of language lateralization, such as acoustic processing (Zatorre & Belin, 2001). Thus, the leftward asymmetry of the ArcF connectivity found in controls, irrespective of their manual preference (Vernooij et al., 2007), in most right TLE, and in some left TLE patients could be driven by the summation of these functional roles and not solely reflect hemispheric language specialization. This suggests that careful consideration should be given to the ArcF during surgery of the left hemisphere, irrespective of the side of functional language dominance (Vernooij et al., 2007).
Besides the dorsal ArcF, Parker et al. identified a ventral pathway in humans, the existence of which has been suggested by nonhuman primate studies (Parker et al., 2005). This ventral route, which connects the posterior superior temporal region with the orbitofrontal and dorsolateral prefontal regions, might anatomically correspond, at least in part, to the IOF (Catani et al., 2002). Its putative role for the semantic processing system is supported by corticosubcortical electrostimulation data, especially in the left dominant hemisphere (Duffau et al., 2005). Using DTI, Parker et al. were able to identify this ventral pathway only in the left hemisphere, implying more extensive anatomical connectivity on the left than on the right, in right-handed volunteers (Parker et al., 2005). In TLE patients, our results did not confirm the leftward FA asymmetry of the IOF that was found in right-handed controls (Rodrigo et al., 2007). We are unaware of any imaging study that has attempted to compare the diffusion-based measurement in the IOF with lateralization indices derived from fMRI language tasks in controls or in epilepsy patients. Given that we did not find any correlation between functional and structural indices measured in the IOF, this bundle might not constitute a major component of the language reorganization network in epilepsy.
Finally, the neuronal reorganization of language in epilepsy may involve other paths than the ArcF and IOF, and rely on a widespread neuronal network. In left TLE patients, this distributed network could be hosted by the right frontal white matter, within the large “connectivity volume” where the mean anisotropy was computed by Powell et al. Although speculative, this would reconcile our negative finding in the ArcF with the positive findings of Powell et al. in a large “connectivity volume” in the frontal lobe in left TLE patients (Powell et al., 2007).
Our study has several limitations. First, we did not include a control group. However, leftward structural asymmetry of white matter pathways in relation to functional language lateralization has previously been reported in right-handed volunteers, using nonprobabilistic and probabilistic tractography (Catani et al., 2005; Parker et al., 2005; Vernooij et al., 2007). Second, we chose to use a two ROI-based approach for fiber tracking to specifically study the ArcF and the IOF, the course of which have been documented using DTI (Catani et al., 2002). To avoid observer bias inherent in manual ROI definition in each patient, we decided to draw on the MNI template a set of predefined ROIs, which were then used for all patients after having transformed them into each patient's space. This procedure avoids repeating freehand ROI definition in each patient but might induce false-negative or false-positive tracking because of misregistration. We initially chose relatively large ROIs to minimize the risk of missing the ArcF and the IOF. This proved rather successful since the ArcF tracking was obtained bilaterally in all cases and the IOF could not be segmented in only two patients. Each of the tracts was checked for consistency with known anatomy and no aberrant tracts were observed. It is unlikely that misregistrations had a great impact on our DTI measurements given that our findings in right TLE patients are in line with reports of leftward asymmetry of the ArcF using a different methodology (Powell et al., 2007). Last, to be clinically compatible when combined with fMRI, DTI acquisition time was limited to 7 min and we aimed at covering the whole brain with isotropic voxels. We chose to maximize the spatial resolution (2.5 mm), which allowed for 15 diffusion gradient directions within the time constraints. Increasing the number of directions would most likely have improved the accuracy of connectivity measurements (Behrens et al., 2007).
We have combined probabilistic tractography and fMRI to study the effect of TLE upon the structure—function relationship. We found a correlation between the ArcF structural lateralization and the leftward asymmetry in functional activation in right TLE patients, with patients with a more lateralized language function having a more lateralized FA measurements. This suggests that probabilistic tractography and fMRI can be combined to confirm a left hemispheric language specialization in patients with right TLE. The decoupling between structure and function in left TLE suggests that neuronal reorganization of language may involve other paths than the ArcF and IOF, and rely on a widespread neuronal network. Before fMRI and diffusion combined analysis becomes clinically applicable for predicting postoperative deficits, additional work needs to be done to understand the structural bases of the language network and how it is affected by chronic seizures.