Abnormal trigeminal nerve microstructure and brain white matter in idiopathic trigeminal neuralgia

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www.elsevier.com/locate/pain

Abnormal trigeminal nerve microstructure and brain white matter in idiopathic trigeminal neuralgia Danielle D. DeSouza a,b, Mojgan Hodaie a,b,c,1, Karen D. Davis a,b,c,⇑,1 a

Division of Brain, Imaging and Behaviour Systems Neuroscience, Toronto Western Research Institute, University Health Network, Toronto, ON, Canada Institute of Medical Science, University of Toronto, Toronto, ON, Canada c Division of Neurosurgery, Toronto Western Hospital & University of Toronto, Toronto, ON, Canada b

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

a r t i c l e

i n f o

Article history: Received 18 July 2013 Received in revised form 23 August 2013 Accepted 26 August 2013

Keywords: Trigeminal neuralgia Pain MRI White matter DTI

a b s t r a c t Idiopathic trigeminal neuralgia (TN) is classically associated with neurovascular compression (NVC) of the trigeminal nerve at the root entry zone (REZ), but NVC-induced structural alterations are not always apparent on conventional imaging. Previous studies report lower fractional anisotropy (FA) in the affected trigeminal nerves of TN patients using diffusion tensor imaging (DTI). However, it is not known if TN patients have trigeminal nerve abnormalities of mean, radial, or axial diffusivity (MD, RD, AD – metrics linked to neuroinflammation and edema) or brain white matter (WM) abnormalities. DTI scans in 18 right-sided TN patients and 18 healthy controls were retrospectively analyzed to extract FA, RD, AD, and MD from the trigeminal nerve REZ, and Tract-Based Spatial Statistics (TBSS) was used to assess brain WM. In patients, the affected trigeminal nerve had lower FA, and higher RD, AD, and MD was found bilaterally compared to controls. Group TBSS (P < 0.05, corrected) showed patients had lower FA and increased RD, MD, and AD in brain WM connecting areas involved in the sensory and cognitive-affective dimensions of pain, attention, and motor functions, including the corpus callosum, cingulum, posterior corona radiata, and superior longitudinal fasciculus. These data indicate that TN patients have abnormal tissue microstructure in their affected trigeminal nerves, and as a possible consequence, WM microstructural alterations in the brain. These findings suggest that trigeminal nerve structural abnormalities occur in TN, even if not apparent on gross imaging. Furthermore, MD and RD findings suggest that neuroinflammation and edema may contribute to TN pathophysiology. Ó 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

1. Introduction Idiopathic trigeminal neuralgia (TN) is a severe neuropathic pain disorder affecting the trigeminal nerve. It is characterized by intense, lancinating attacks of facial pain, typically triggered by normally nonpainful stimuli or movements. Unlike many other neuropathic pains, TN patients usually do not exhibit major sensory loss, and are pain-free between pain attacks [40,41]. As the disorder progresses, pain attacks may become more frequent and the pain more sustained [34]. Previous research on TN has mainly focused on gross trigeminal nerve abnormalities, but little is known about the nature of such presumed nerve damage. The most prevalent theory is that TN is ⇑ Corresponding author. Address: Toronto Western Hospital, Room MP13-306, 399 Bathurst Street, Toronto, ON M5T 2S8, Canada. Tel.: +1 416 603 5662; fax: +1 416 603 5745. E-mail address: [email protected] (K.D. Davis). 1 These authors contributed equally to the manuscript.

associated with neurovascular compression (NVC) of the trigeminal nerve at the root entry zone (REZ) [28,40]. The REZ is a transition zone between central and peripheral nervous system myelin and where the trigeminal nerve is believed to be the most vulnerable to vascular compression [55]. Over time, the nerve–vessel contact results in damage or focal myelin loss [18,24,35,37], which can disrupt normal nociceptive transmission. Although gross NVC is not always apparent with standard imaging, magnetic resonance imaging (MRI)-based diffusion tensor imaging (DTI) has been shown to be a useful tool for examining the trigeminal system in great detail [25,53]. Clinical studies using DTI have identified microstructural abnormalities, including decreased fractional anisotropy (FA), in the affected REZ of TN patients with NVC [23,33,36]. Although FA is often used as a quantitative biomarker of white matter (WM) ‘‘integrity,’’ other DTI metrics provide insight into factors underlying WM microstructure and pathology. Previous studies have shown WM abnormalities in the brain following peripheral nerve injury and in chronic pain [16,41]. Importantly, many of these patients also had other significant sen-

0304-3959/$36.00 Ó 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.pain.2013.08.029

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sory abnormalities, including numbness. It is not understood how TN, without major sensory loss, impacts brain WM. Therefore, we examined WM abnormalities in TN to provide insight into the mechanisms involved in neuropathic pain, without the confounding of other sensory abnormalities. Our study aim was to examine both trigeminal nerve and brain WM using multiple DTI-derived metrics to test the hypothesis that TN is associated with both nerve and brain WM abnormalities.

2.2. Image acquisition

2. Materials and methods

Using a 3T GE MRI system with an 8-channel phased-array head coil (GE Healthcare, WI, USA), 60-direction diffusion-weighted images were acquired with a spin echo echo planar sequence (0.94  0.94  3 mm voxels; TE = 86.6 ms; TR = 12,000 ms; 1 B0; b = 1000 s/mm2; matrix = 128  128; 1 excitation; ASSET. T1-weighted 3D FSPGR axial images were also obtained (0.9  0.9  1 mm3 voxels, 256  256 matrix, FOV = 24 cm (controls), 22 cm (patients), TE = 5 ms, TR = 12 ms, TI = 300 ms).

2.1. Participants

2.3. DTI-derived metrics

Under the University Health Network Research Ethics Board approval, retrospective MR analyses were carried out in 18 patients with right-sided TN, seen at the Toronto Western Hospital, and 18 healthy control participants. All healthy control participants provided written informed consent (note that our Research Ethics Board does not require this for retrospective analyses of patient data as were analyzed here). For each patient, demographic and clinical details were obtained via retrospective chart reviews. Inclusion criteria were: unilateral (right-sided) pain in the distribution of one or more peripheral branches of the trigeminal nerve; intense, sharp, superficial, or stabbing paroxysmal pain precipitated from trigger areas or by trigger factors; stereotyped attacks for each patient; no clinically evident neurological or sensory deficit or not attributed to another disorder [22]; and no previous surgical procedures for TN.

DTI techniques use diffusion-weighted imaging scans, which are sensitized to the diffusion of water molecules [29], to characterize WM microstructure. This property is useful because in healthy WM, diffusion is more restricted across an axon than along it due to structural barriers such as myelin, axonal membranes, microtubules, and neurofilaments [7]. A mathematical model, typically a tensor/ellipsoid, characterized by its 3 orthogonal eigenvectors and their associated eigenvalues (k1, k2, k3), can be applied to each brain voxel to provide information about the 3-dimensional character of the water molecules’ diffusion [29]. The most commonly used DTI-derived metric is FA [4], which ranges from 0 (completely isotropic), meaning water molecules can diffuse equally in all directions (eg, cerebrospinal fluid), to 1 (completely anisotropic), meaning the diffusion of water is hindered (eg, along axons in WM). Other metrics, highlighted in

Fig. 1. Schematic representation of diffusion tensor imaging (DTI)-derived metrics and tensor changes that can occur with lower FA. Four DTI-derived metrics derived from the eigenvalues of the tensor model were examined. Schematic representations of how these metrics were calculated and their formulas are shown in panel (A), with AD being diffusion along the length of the axon (k1) (left), RD being diffusion perpendicular to the length of the axon (average of k2 and k3) (center), and MD being the magnitude of diffusion regardless of direction (average of k1, k2, and k3) (right). Panel (B) shows the tensor model and the formula for FA (top). Also illustrated are 2 scenarios where FA has decreased, but the shape of the tensors are different due to differences in the other 3 DTI-derived metrics (shown in chart). The first scenario is when FA, AD, and MD decrease, but RD remains stable (bottom left); and the second is when FA decreases, but AD, RD, and MD increase (bottom right). For additional potential scenarios of changes to the tensor, see reference [1]. Abbreviations: FA, fractional anisotropy; RD, radial diffusivity; MD, mean diffusivity; AD, axial diffusivity.

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Fig. 1A, include axial diffusivity (AD), which corresponds to the main diffusion direction, or diffusion along the length of the axon (k1); radial diffusivity (RD), which is diffusion perpendicular to the main diffusion direction (average of k2 and k3); and mean diffusivity (MD), which measures the local magnitude of diffusion regardless of direction (average of k1, k2, and k3). Although FA measurements represent a robust method for assessing the degree of directionality of diffusion, this ratio measure is a function of changes in diffusion in AD and RD. Therefore, if diffusion changes along the length of the tensor (k1) were proportional to those perpendicular to the tensor (RD), then FA would remain relatively unchanged even though abnormalities in diffusion may exist [1]. Additionally, these other measures of tissue microstructure, namely RD and MD, have been linked to pathophysiological mechanisms such as demyelination, neuroinflammation, and edema [2,11]. 2.4. Preprocessing Prior to analyses, all scans underwent standard preprocessing steps using the FMRIB Diffusion Toolbox (FDT), part of FSL v.4.1.8 (FMRIB Software Library; http://www.fmrib.ox.ac.uk/fsl). Briefly, diffusion data were corrected for eddy-current and movement artifacts. Brains were extracted from nonbrain tissues using the Brain Extraction Tool [47], and FA and non-FA (RD, AD, and MD) images were created for each subject by fitting a tensor model to the raw diffusion data using DTIFIT in the FDT toolbox. 2.5. Trigeminal REZ analysis For each participant, values for all DTI-derived metrics (FA, RD, AD, and MD) were extracted from both the left and right trigeminal nerves at the REZ. The trigeminal nerves were identified in the axial plane using color orientation maps created by overlaying the principle eigenvector image (V1) over the FA map. The

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trigeminal nerves were clearly visualized in the pontine cisternal space for each patient. To obtain the DTI-derived values, masks 4 voxels in size were manually placed at each REZ (Fig. 2A) in the axial plane. The REZ is defined as the cisternal part of the trigeminal nerve just as it enters the pons [30]. Between-group comparisons were carried out to compare patient and healthy control REZ values using independent samples t-tests. Also, to assess for abnormalities within the patient group, mean REZ values for the left and right trigeminal nerves of each patient were compared using paired t-tests. All trigeminal REZ analyses were done in SPSS v.21 (IBM, Armonk, NY, USA) and determined to be significant at the P < 0.05 level. 2.6. Tract-based spatial statistics Tract-Based Spatial Statistics (TBSS) [48] was used to compare brain FA between the TN and healthy control groups. Following preprocessing, FA data underwent nonlinear registration to a 1  1  1-mm FA map in standard space (FMRIB58_FA) using a b-spline representation of the registration warp field [44]. The mean FA image created (thresholded at 0.2) was thinned to create a mean FA skeleton that represented the centers of all tracts common to the group. Each subject’s aligned FA data were projected onto this skeleton and the resulting data underwent voxel-wise cross-subject statistics. Permutation-based nonparametric testing was carried out using Randomise with Threshold-Free Cluster Enhancement (part of FSL), which inherently tests for multiple comparisons. Thus, all data were tested for significance at P < 0.05, corrected. In the areas where FA was determined to be significantly different in patients compared to controls, a region of interest analysis was used to test for focal WM alterations in RD, AD, and MD. The non-FA images used for TBSS were created by applying the FA nonlinear registration to the additional parametric maps, and projecting them onto the original mean FA skeleton. Because all significant TBSS results were displayed on the

Fig. 2. Microstructural abnormalities in the V nerves of TN patients. TN patients had abnormal white matter microstructure in their V nerves (⁄significant at P < 0.05). Axial images were used to locate the trigeminal nerves as they entered the pons. A: Example of an axial T1-weighted image with the V nerves visible in the cisternal space surrounding the pons. On diffusion tensor imaging (DTI) scans, masks 4 voxels in size were manually placed at the REZ of each patient and control (red box shows magnified region of pons and trigeminal nerves with masks circled at REZ). B–E: DTI-derived values ± SEM of controls (black bars) and patients (red bars). Compared to controls, patients had significantly lower FA in their affected V nerve (B), higher RD (C), MD (D), and AD (E) in both their affected and unaffected nerves. There was also a trend (P = 0.055) toward higher RD in the patients’ affected compared to unaffected sides (red bars, panel C). The affected side refers to the right trigeminal REZ (side of pain for patients) and the unaffected side refers to the left trigeminal REZ (pain-free side for patients). Abbreviations: TN, trigeminal neuralgia; REZ, root entry zone; CN V, trigeminal nerve; FA, fractional anisotropy; RD, radial diffusivity; MD, mean diffusivity; AD, axial diffusivity. Diffusion in mm2/s.

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1-voxel-thick skeleton, significant clusters were thickened for visualization purposes using ‘‘tbss_fill,’’ part of FSL. WM tracts with significant microstructural abnormalities were identified using the JHU ICBM-DTI-81 white-matter labels atlas [39] and the JHU White Matter Tractography Atlas [27], both included in FSL. 3. Results 3.1. Patient demographics Patient demographic details are provided in Table 1. The TN group consisted of 18 patients (11 women, 7 men; mean age ± SD: 54.1 ± 17.0 years) with right-sided pain. Patients were on medications for TN pain at the time of their scan acquisition, with the most common one being the antiepileptic medication, carbamazepine. The healthy control group also consisted of 11 women, 7 men; mean age ± SD of 49.6 ± 12.7 years, which was not significantly different from the patient group (P = 0.38). 3.2. Abnormal microstructure at trigeminal root entry zone The FA at the REZ of patients’ affected (right) trigeminal nerves was 22% lower than their unaffected side and 27% lower than that measured in the healthy controls (P < 0.05) (Fig. 2B). FA in the unaffected (left) REZ of patients was not significantly different from controls (P = 0.23). Furthermore, the 3 other DTI-derived measures of WM microstructure (RD, AD, MD) were all significantly greater in patients, compared to controls (P < 0.05) (Fig. 2C–E). This effect was observed for both the nerves on the affected (by 29%–52%) and the unaffected (by 31%–37%) sides. There were no statistically significant differences between the patients’ affected and unaffected sides for AD or MD (P < 0.05), although there was a trend toward significance for RD (P = 0.055). 3.3. Brain white matter abnormalities in corpus callosum, cingulum, corona radiata, and superior longitudinal fasciculus In general, there were widespread regions of brain WM abnormalities in the TN patients with lower FA, and higher RD and MD (P < 0.05, corrected) compared to the healthy controls (Fig. 3). AD was also significantly higher in the brains of patients; however,

Table 1 TN patient demographic details. Patient

Sex

Age, years

Pain distribution

Medication

R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18

F F F F F F M M F M F M F M M F M F

55 44 73 42 76 53 37 24 52 74 54 24 63 38 68 67 51 79

V1/V2 V2 V2 V2/V3 V1/V2 V3 V3 V3 V1 V1/V2/V3 V2/V3 V3 V2/V3 V2 V2 V1/V2 V1/V2/V3 V1/V2/V3

GBP CBZ CBZ GBP; CBZ CBZ GBP PGB; CBZ CBZ CBZ CBZ CBZ CBZ PGB CBZ GBP CBZ – CBZ

Pain distribution refers to the peripheral branches of the trigeminal nerve (V1, ophthalmic branch; V2, maxillary branch; V3, mandibular branch); TN, trigeminal neuralgia; GBP, gabapentin; CBZ, carbamazepine; PGB, pregabalin; –, information not available.

these findings were not as widespread as FA, RD, and MD abnormalities. The main WM regions of interest that showed prominent abnormalities are highlighted in Fig. 4. Specifically, FA was lower (by 9%) in the corpus callosum (genu, body, and splenium) of patients, while RD and MD were 7%–16% higher (P < 0.05, corrected) (Fig. 4A–C). AD was also higher (by 5%) in the corpus callosum; however, this finding was limited to the splenium (Fig. 4D). Additionally, patterns of lower FA and higher RD and MD were found in the cingulum and the posterior corona radiata (bilaterally) of patients (Fig. 4A–C). WM abnormalities were also found in the left superior longitudinal fasciculus (SLF) of patients, contralateral to their side of pain, as characterized by lower FA and higher RD (P < 0.05, corrected) (Fig. 4A, C). The SLF abnormalities were predominantly localized to the parietal and temporal SLF. 4. Discussion This is the first study to demonstrate that patients with idiopathic TN not only have WM abnormalities in their trigeminal nerves, but also in their central nervous system (CNS) WM. The brain WM abnormalities were located in tracts connecting regions implicated in the multidimensional experience of pain, attention, and motor function. These WM abnormalities, characterized by lower FA, and higher RD, MD, and AD, suggest not only disrupted nerve/tract organization, but also other pathological features such as neuroinflammation, and edema of the nerve/axons. 4.1. Trigeminal root entry zone abnormalities Although the precise mechanism of TN pathophysiology is not entirely understood, the most prevalent theory involves alterations to the trigeminal nerve, usually by vascular compression [41]. Structurally, these alterations can include NVC-induced focal demyelination of the WM fibers in the trigeminal REZ [41], resulting in the abnormal firing of trigeminal nerve afferents. Consistent with this theory and with previous studies examining FA at the trigeminal REZ [23,33,36], we report lower FA at the affected trigeminal REZ of TN patients, compared to their unaffected side and to healthy controls. Our findings are consistent with a decrease in WM ‘‘integrity’’ by NVC only at the affected trigeminal REZ. A decrease in FA can occur in multiple scenarios [1] (Fig. 1B). For the affected REZ of TN patients, a disproportionately greater increase in RD and MD over AD could account for the significantly lower FA. This ratio may reflect focal injury and/or demyelination from NVC at the REZ of the affected nerve, but not the unaffected nerve, or general microstructural disintegration of the affected nerve. MD and AD were not significantly different between the TN patients’ affected and unaffected sides, although there was a trend toward greater RD in the affected trigeminal REZ, in line with the theory that NVC results in focal demyelination of the affected side [49]. Interestingly, all 3 measures, on both the affected and unaffected sides, were different compared to controls. Therefore, subtle microstructural abnormalities may occur in the trigeminal system as a whole in this patient group. One possibility is that individuals who develop TN are more susceptible to chronic pain because of preexisting abnormalities in their WM, possibly explaining why some individuals with NVC of the trigeminal nerve never develop TN. With preexisting trigeminal nerve abnormalities (eg, higher MD, AD, and/or RD) [26,34,52], vascular compression may be sufficient to result in TN pain, and additionally, lower FA. The current study cannot test this scenario; however, it remains possible that there are individual differences in susceptibility to develop chronic pain [14,26].

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Fig. 3. Abnormalities in brain white matter microstructure using multiple diffusion tensor imaging (DTI) metrics. Group Tract-Based Spatial Statistics results revealed widespread regions of brain white matter abnormalities in trigeminal neuralgia patients compared to healthy controls for all 4 of the DTI-metrics examined (P < 0.05, corrected). Blue clusters indicate patients < controls (FA) and red clusters indicate patients > controls (MD, RD, and AD). Abbreviations: FA, fractional anisotropy; MD, mean diffusivity; RD, radial diffusivity; AD, axial diffusivity. Note that the brain images at x = 0 appear darker due to the presence of the falx cerebri.

An alternate explanation is that these bilateral abnormalities reflect compensatory motor behaviors. The trigeminal nerve contains a motor branch that innervates the muscles of mastication. As normally nonpainful movements, such as chewing, are wellknown triggers of TN pain [8], patients often restrict facial movements. Given the bilateral innervation in this system, nocifensive behaviors, including limiting jaw movements, may result in abnormalities to both trigeminal nerves or to CNS WM along motor pathways. 4.2. Abnormalities in WM connecting brain regions involved in the multidimensional experience of pain and motor function Although TN is known to involve trigeminal nerve dysfunction, other theories of TN propose CNS pathology [46]. CNS plasticity can

occur following peripheral nerve injury [16,51]. In line with other studies of neuropathic pain, we recently reported cortical and subcortical brain gray matter (GM) abnormalities in TN patients in regions involved in the sensory, cognitive-affective, and modulatory aspects of pain and motor function [17]. Many of these brain areas are anatomically and/or functionally connected. We report several areas of abnormal brain WM in TN patients, mainly marked by lower FA and higher RD and MD in the corpus callosum, cingulum, posterior corona radiata, and superior longitudinal fasciculus. These tracts connect brain regions known to participate in the multidimensional experience of pain, attention, and motor function, and may be contributing to the unique symptoms of TN pain and/or compensatory motor behaviors. The corpus callosum interconnects the cerebral hemispheres, allowing for the rapid transfer and integration of sensory and

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Fig. 4. Abnormal brain white matter (WM) in corpus callosum, cingulum, posterior corona radiata, and superior longitudinal fasciculus. The main regions of brain WM abnormalities from the group Tract-Based Spatial Statistics results (P < 0.05, corrected) are highlighted for each diffusion tensor imaging (DTI) metric, with graphs of the extracted DTI-derived values ± SEM to the right: controls (black bars), patients (red bars). Blue clusters indicate patients < controls and red clusters indicate patients > controls. Abbreviations: pCR, posterior corona radiata; CC, corpus callosum; CB, cingulum bundle; SLF, superior longitudinal fasciculus; FA, fractional anisotropy; RD, radial diffusivity; MD, mean diffusivity; AD, axial diffusivity. Diffusion in mm2/s.

motor information [12]. However, the nature of these connections is not well understood [10]. The corpus callosum is topographically organized with anterior callosal fibers connecting frontal regions, including motor, anterior cingulate, and prefrontal cortices, and posterior fibers connecting parietal, temporal, and occipital brain areas, including somatosensory regions [20]. The WM abnormalities in this study spanned the length of the corpus callosum, suggesting that there may be differences in how TN patients integrate cognitive, sensory, and motor information. Corroborating this, we have previously shown abnormal GM thickness in the prefrontal, sensory, and motor cortices of TN patients [17]. While abnormal sensory integration may result from differences in the amount of nociceptive information entering the CNS from the trigeminal system, abnormal differences in the corpus callosal fibers connecting motor cortices may reflect the restriction of facial movement by TN patients to prevent or lessen pain attacks. Abnormal sensory integration is also suggested by our findings of WM abnormalities observed in the posterior corona radiata (adjacent to the posterior parietal cortex). The parietal cortex is known for its role in multisensory integration, which aids in the detection, localization, and reaction to external stimuli [3]. Microstructural abnormalities in the form of lower FA in brain WM have been reported in other chronic pains [13,21,38,43,50], and studies of chronic pain affecting the trigeminal system have reported lower FA in the corpus callosum [38,57,58]. Of the studies that examined multiple DTI metrics [38,57], differences in these metrics were not consistent, despite lower FA in these cases. Patients with temporomandibular disorder (TMD) had higher RD and MD in regions of lower FA [38]; however, migraine patients had lower MD and AD, but unchanged RD [57]. Because various

pathological processes affect these metrics differently [11], this highlights the need to examine other DTI-derived metrics in addition to FA, in order to gain insight into possible differences in pathophysiological mechanisms between chronic pains. As TN and TMD patients share a similar pattern of microstructural abnormality in the corpus callosum, similar mechanisms may be involved in these patients groups that are not shared with migraine patients. Additionally, we found abnormal WM microstructure bilaterally in the cingulum bundle (adjacent to the midcingulate cortex) of patients. Abnormal cingulum WM has previously been reported in TMD [38]. The cingulum is thought to be involved in the affective dimension of pain, and cingulotomy procedures have successfully been used to provide pain relief for patients with intractable pain [56]. Abnormalities in cingulum WM may reflect the high degree of pain unpleasantness associated with having TN. TN patients also had abnormal WM in the SLF underlying the left temporoparietal cortex. The temporoparietal junction is a component of the ventral attention network, a right-lateralized system activated by salient stimuli, including prolonged pain [31]. However, the left temporoparietal junction, in conjunction with the frontal lobes, is also thought to play a role in attention [42] and higher-order cognitive processing [45]. Together, abnormal cingulum and SLF microstructure may reflect abnormal processing of the cognitiveaffective dimension of pain in TN patients. 4.3. Mechanisms underlying WM microstructural abnormalities As in GM, the mechanisms underlying experience-dependent changes to WM microstructure have been shown to have an influence on neuroimaging measures [11,59]. Candidate mechanisms

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underlying MR-detectable axonal plasticity include changes in fiber organization such as packing density, axonal sprouting/ branching, axon size/number, crossing fibers, and myelin remodeling [7,11,59]. Other factors such as astrocyte morphology and angiogenesis have also been shown to influence MR-detectable changes in WM [59]. In our study, we show that TN patients have lower FA in their affected trigeminal nerves at the REZ and brain WM, compared to healthy controls. Lower FA in the affected REZ of TN patients may be related to NVC-induced axonal damage, which may include less fiber organization and/or nerve atrophy [19,35,37]. Also, lower FA in the brain WM of TN patients may correspond to less fiber organization, including more axonal sprouting/branching, more crossing fibers, or larger axons [59]. Our finding of increased MD and RD may be linked to NVC-induced focal demyelination of the trigeminal REZ [37], neuroinflammatory processes, and/or edema [5,7]. Injury to the trigeminal REZ may involve neuroinflammation and edema as part of the injury response. Additionally, neuropathic pain is typically associated with prolonged nociceptive activity to the central nervous system. This could lead to central sensitization [32,54], a process involving central neuroinflammatory processes and edema. Indeed, evidence that chronic pain may induce neuroinflammation in the brain and, in turn, influence brain WM, has been reported [15], suggesting that these mechanisms may also contribute to the RD and MD abnormalities in the brain WM of TN patients. One caveat of note is that all study patients were on medications for TN pain, the most common being the antiepileptic drug, carbamazepine. The effects of antiepileptics on brain structure are not well understood, but there is evidence to suggest they influence immune activity [6,9]. Therefore, it is possible that these medications contributed to changes in the DTI-derived metrics associated with inflammation and/or edema. Conflict of interest statement The authors have no conflicts of interest to disclose. Acknowledgements We thank Mr. Udi Blankstein for his help in the recruitment of the healthy control participants. This work was supported by the PSI Foundation and the CIHR Strategic Training Fellowship, TGF53877. References [1] Acosta-Cabronero J, Williams GB, Pengas G, Nestor PJ. Absolute diffusivities define the landscape of white matter degeneration in Alzheimer’s disease. Brain 2010;133:529–39. [2] Alexander AL, Lee JE, Lazar M, Field AS. Diffusion tensor imaging of the brain. Neurotherapeutics 2007;4:316–29. [3] Avillac M, Ben Hamed S, Duhamel JR. Multisensory integration in the ventral intraparietal area of the macaque monkey. J Neurosci 2007;27:1922–32. [4] Basser PJ, Mattiello J, LeBihan D. MR diffusion tensor spectroscopy and imaging. Biophys J 1994;66:259–67. [5] Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B 1996;111:209–19. [6] Basta-Kaim A, Budziszewska B, Lason W. Effects of antiepileptic drugs on immune system. Przegl Lek 2008;65:799–802. [7] Beaulieu C. The basis of anisotropic water diffusion in the nervous system – a technical review. NMR Biomed 2002;15:435–55. [8] Bennetto L, Patel NK, Fuller G. Trigeminal neuralgia and its management. BMJ 2007;334:201–5. [9] Black JA, Liu S, Carrithers M, Carrithers LM, Waxman SG. Exacerbation of experimental autoimmune encephalomyelitis after withdrawal of phenytoin and carbamazepine. Ann Neurol 2007;62:21–33. [10] Bloom JS, Hynd GW. The role of the corpus callosum in interhemispheric transfer of information: excitation or inhibition? Neuropsychol Rev 2005;15:59–71.

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