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Original Article

White matter microstructure abnormalities in pediatric migraine patients

Cephalalgia 0(0) 1–9 ! International Headache Society 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0333102415578428 cep.sagepub.com

Roberta Messina1,2, Maria A Rocca1,2, Bruno Colombo2, Elisabetta Pagani1, Andrea Falini3, Giancarlo Comi2 and Massimo Filippi1,2 Abstract Background: Diffusion tensor (DT) magnetic resonance imaging (MRI) provides several quantities with the potential to disclose white matter (WM) microstructural abnormalities. We explored alterations of WM architecture in pediatric migraine patients using DT MRI and two different methods of analysis. Methods: Dual-echo and DT MRI scans were acquired from 15 pediatric migraine patients and 15 age-matched controls. Whole-brain voxel-wise comparisons of WM DT MRI abnormalities were performed using tract-based-spatial-statistics (TBSS). A DT probabilistic tractography analysis was also run. Results: Both TBSS and DT tractography analysis showed that, compared to controls, pediatric migraine patients had significant lower mean (MD), axial (AD) and radial (RD) diffusivity of WM tracts located in the brainstem, thalamus and fronto-temporo-occipital lobes, bilaterally. Patients also experienced increased fractional anisotropy (FA) of the optic radiations. No correlation was found between WM tract abnormalities and disease duration and attack frequency. Conclusions: Pediatric migraine patients harbor diffuse brain WM microstructural abnormalities. High FA and low MD, AD and RD in these patients might be explained by repeated neuronal activation, which may lead to cell swelling and stimulate activity-dependent myelin-modulation, or by increased fiber and dendritic densities. Both these mechanisms might reflect a hyperexcitability of the brain in migraineurs. Keywords Migraine, pediatric migraine, white matter damage, diffusion tensor MRI Date received: 10 November 2014; revised: 8 January 2015; accepted: 26 February 2015

Introduction Migraine affects around 15% of the population and is associated with a substantial personal and social burden. It is the most common acute and recurrent headache syndrome in children, with up to 75% of children reporting a notable headache by the age of 15 years (1). During the past few years, the extensive application of advanced structural and functional magnetic resonance imaging (MRI) techniques has contributed to improving our understanding of the pathophysiology of migraine and to elucidating novel mechanisms that might become the target of future therapeutic interventions (2). What is now established is that migraine is not simply a disease related to pain occurring intermittently, but rather a process that over time either affects the brain or acts on a predisposed brain (3).

The vast majority of structural MRI studies have demonstrated that adult migraine patients experience a distributed pattern of gray matter (GM) and white matter (WM) abnormalities to regions involved in 1

Neuroimaging Research Unit, Vita-Salute San Raffaele University, Milan, Italy 2 Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University, Milan, Italy 3 Department of Neuroradiology, San Raffaele Scientific Institute, VitaSalute San Raffaele University, Italy Corresponding author: Massimo Filippi, Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina, 60, 20132 Milan, Italy. Email: [email protected]

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2 nociception, visual and sensorimotor processing (3). Whether these morphological abnormalities represent the consequence of attack repetition over time or rather a phenotypic biomarker of the disease is still a matter of debate (2). Although studying pediatric patients with migraine might help to unravel this issue, so far only one study has mapped the distribution of GM and WM volume abnormalities in pediatric migraine patients and found distributed GM abnormalities of brain regions involved in nociceptive and visual processing, but no WM volume abnormalities (4). Diffusion tensor imaging (DTI) is a quantitative technique that exploits the diffusion of water within biological tissues, allowing the in vivo visualization of microscopic pathological abnormalities occurring in the central nervous system (CNS). From the tensor, it is possible to derive several indexes, which include fractional anisotropy (FA), a dimensionless index that reflects axonal integrity and fiber organization; mean diffusivity (MD), which measures the overall magnitude of diffusion; axial diffusivity (AD), which is associated with fiber density and axon intrinsic characteristics; and radial diffusivity (RD), which mostly reflects the degree of myelination (5). Against this background, we performed an explanatory DT MRI analysis to assess the presence and extent of brain WM tract abnormalities from a cohort of pediatric patients with migraine. To provide some clues about the nature of the detected changes, we also assessed their correlation with disease duration and attack frequency.

Methods This study was approved by the local ethics committees on human studies, and all participants’ parents provided written informed consent prior to study participation.

Participants We included 19 right-handed pediatric patients with episodic migraine and 15 right-handed, genderand age-matched healthy controls without a familial history of migraine, no history of neurological dysfunction (including migraine), a normal perinatal and child development and a normal neurological exam. Healthy controls were relatives of colleagues or friends who were kindly willing to take part in the study. Migraine patients were in a headache-free state for at least one month prior to the MRI scan. Patients with perinatal or pediatric diseases, hypertension, hypercholesteremia, diabetes mellitus, vascular/heart diseases and other major systemic, neurological or psychiatric conditions were excluded. Patients were recruited

Cephalalgia 0(0) consecutively from the migraine population attending the Outpatient Clinic, Department of Neurology, San Raffaele Scientific Institute. All patients met the criteria of the International Classification of Headache Disorders for the diagnosis of migraine (6). None of the patients suffered from episodic syndromes frequently associated with migraine in childhood (e.g. benign paroxysmal vertigo, cyclic vomiting). Images of four patients were discarded during the analysis because of motion artifacts (the demographic and clinical characteristics of these patients did not differ from those of the remaining group). Eight patients had a diagnosis of migraine with aura (MWA) (seven had visual aura and one sensory and speech disturbances), and seven had migraine without aura (MWoA). Apart from three patients who suffered from a right-sided migraine, all the remaining patients had bilateral migraine. Twelve patients had a familial history of migraine. Apart from three patients who complained of attacks lasting more than 24 hours, the duration of migraine attacks was of a few hours in the majority of the patients. At the time of MRI, five patients were on prophylactic medication for migraine, including flunarizine and ginkgolide B. All participants were assessed clinically a few days prior to the MRI scan by a single neurologist who was unaware of the MRI results.

MRI acquisition Using a 3.0 Tesla Intera scanner (Philips Medical Systems, Best, the Netherlands), the following sequences of the brain were obtained from all participants: 1) axial T2-weighted turbo-spin echo (repetition time (TR)/echo time (TE) ¼ 3000/120 ms, flip angle (FA) ¼ 90 degrees, matrix size ¼ 512  512, field of view (FOV) ¼ 230 mm2, 28 4 mm thick, contiguous slices); 2) axial fluid-attenuated inversion recovery (FLAIR) (TR/TE ¼ 11000/120 ms, inversion time¼ 2800 ms, FA ¼ 90 degrees, matrix size ¼ 256  256, FOV ¼ 230 mm2, 28 4 mm thick, contiguous slices); and 3) pulsed-gradient spin-echo, echo-planar (TE/ TR ¼ 58/8775.5 ms; flip angle ¼ 90 degrees; matrix size ¼ 96  96; FOV ¼ 240  240 mm2; 55 contiguous, 2.3 mm thick axial slices) with sensitivity encoding (SENSE) (acceleration factor ¼ 2) and diffusion gradients applied in 35 non-collinear directions. Two optimized b factors were used for acquiring diffusionweighted images (b1 ¼ 0, b2 ¼ 900 s/mm2).

MRI analysis T2-weighted scans were analyzed for the presence of lesions and FLAIR scans were always used to increase confidence in their identification. T2-hyperintense lesion volumes (LV) were measured using a local

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Messina et al. thresholding segmentation technique (Jim 5.0, Xinapse System, Northants, UK).

Statistical analysis

Individual FA images were non-linearly registered to the FMRIB58_FA atlas provided within FSL and averaged to obtain a customized atlas. The resulting mean FA image was thinned to create a WM tract ‘‘skeleton,’’ which was thresholded at an FA > 0.2 to include only WM voxels. Individual-participant normalized FA maps were warped onto the FA skeleton before statistical comparisons, by searching perpendicularly from the skeleton for maximum FA values (8). The individual registration and projection vectors obtained during the above-described process were also applied to MD, AD and RD data.

Normal distribution assumption was checked for continuous variables by using Kolmogorov-Smirov and Shapiro-Wilk tests, as well as with graphical inspection of Q-Q plots, and between-group comparisons were performed using parametric and nonparametric tests as appropriate. Categorical variables were compared between groups using the Fisher exact test (SPSS software, version 21.0). Voxel-wise differences in FA, MD, AD and RD values between migraine patients and controls were tested using a permutation-based inference for nonparametric statistical thresholding (‘‘randomise’’ program within FSL) (11) and two-sample t tests, adjusting for age. The number of permutations was set to 5000. TBSS results were also confirmed with 10,000 permutations. The resulting statistical maps were thresholded at p < 0.05, with correction for multiple comparisons (family-wise error (FWE) corrected) at a cluster level using the threshold-free cluster enhancement (12). The WM tracts were identified using WM atlases, provided within FSL (13). For tract-specific statistics, between-group comparisons were performed using a general linear model adjusted for age. P values were adjusted for multiple comparisons using the Bonferroni correction (SPSS software, version 21.0). In migraine patients, correlations between voxel-wise DT MRI abnormalities vs disease duration and attack frequency were assessed using regression models in FSL (p < 0.05, corrected for multiple comparisons at the cluster level).

DT probabilistic tractography analysis

Results

FA, MD, AD and RD average values were estimated in WM tracts, which were derived using an atlas-based approach, as previously described (9,10). In detail, an FA atlas was created based on data from 24 healthy individuals with no previous history of neurological dysfunction (reference group). Then, using DT MRI tractography, probability maps of the left and right corticospinal tract (CST), superior longitudinal fasciculus (SLF), inferior fronto-occipital fasciculus (IFOF), uncinate fasciculus (UNC), optic radiation (OR), cerebellar peduncles (CP) (superior, middle and inferior), fornix (FX), cingulum (CIN) and corpus callosum (CC) were produced. The reference FA atlas was non-linearly transformed to the FA maps from controls and patients. These transformations were also applied to the probability maps of the WM tracts that were thresholded at 40%. Then, using WM tract maps, average FA, MD, AD and RD were derived.

The main demographic and clinical characteristics of pediatric patients with migraine and healthy controls are summarized in Table 1. Age (p ¼ 0.8) and gender (p ¼ 1) did not differ between migraine patients and controls or between MWA and MWoA patients. Patients with MWoA had a higher attack frequency (p ¼ 0.01) than those with MWA. No WM hyperintense lesions were found in healthy controls and 13 (87%) of the 15 pediatric migraine patients. Two pediatric patients with MWoA had a few small, punctate T2 hyperintense lesions in deep and subcortical WM. Mean T2 LV in these patients was 0.08 ml (SD ¼ 0.03 ml).

DT MRI analysis Diffusion-weighted images were first corrected for distortions caused by eddy currents and movements. Then, using the FMRIB’s Diffusion Toolbox (FDT tool, FSL 4.1, http://www.fmrib.ox.ac.uk), the DT was estimated in each voxel by linear regression (7) and FA, MD, AD and RD maps derived. WM microstructure abnormalities were explored using tract-based spatial statistics (TBSS) analysis, which performs a voxel-wise analysis of the whole brain WM DT MRI measures (http://www.fmrib.ox. ac.uk/fsl/tbss/index.html). To confirm TBSS results, we also performed a DT probabilistic tractography analysis, which allows us to investigate DT MRI abnormalities of individual WM tracts.

TBSS voxel-wise analysis

TBSS voxel-wise analysis The results of the voxel-wise analysis of WM DT MRI measures are shown in Figure 1. Compared to controls, pediatric migraine patients had a distributed pattern of

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Table 1. Main demographic and clinical characteristics of individuals enrolled in the study. Migraine patients Healthy controls Number of participants Girls/Boys Mean age (SD) (years) Mean attack frequency per year (SD) Mean disease duration (SD) (years)

15 8/7 13.8 (2.7) – –

p values

All patients

MWA

15 8/7 14.1 (2.7) 21 (16.2) 3.1 (2.7)

8 5/3 14.9 (1.5) 11 (12.3) 3.3 (2.3)

MwoA 7 3/4 13.1 (3.5) 33 (12.4) 2.8 (3.3)

Patients vs controls

MWA vs MWoA

– 1 0.8

– 0.5 0.3



0.01



0.4

MWA: migraine with aura; MWoA: migraine without aura.

R

R

MD

AD

L

L

RD R

L

Figure 1. Areas of significant reduced white matter (WM) mean (red), axial (green) and radial (yellow) diffusivity (p < 0.05, FWE corrected) in pediatric patients with migraine vs healthy controls, superimposed on a fractional anisotropy template in the Montreal Neurological Institute space. MD: mean diffusivity, AD: axial diffusivity, RD: radial diffusivity, L: left, R: right; FWE: family-wise error rate.

DT MRI abnormalities of the WM (p < 0.05, FWE corrected), characterized by: 1) a decreased MD of the bilateral optic tract, OR, CST, thalamic radiation, CIN, inferior longitudinal fasciculus (ILF) and IFOF, left SLF and CC; 2) a decreased AD of the bilateral optic tract and OR, left CST, ILF and IFOF, right CIN and CC; 3) a decreased RD of the bilateral OR, trigeminothalamic tract, CST, thalamic radiation, ILF and IFOF, right CIN and CC. No WM FA abnormalities were detected in pediatric migraine patients compared to healthy controls. Although this analysis has to be considered exploratory, given the low number of patients/group, no

differences were found between MWA and MWoA patients.

DT probabilistic tractography analysis Table 2 summarizes the results of the comparisons of tract-average DT MRI metrics values between pediatric migraine patients and healthy controls (only significant tracts/indexes are reported). This analysis confirmed the presence of a distributed pattern of WM abnormalities in pediatric migraine patients, characterized by decreased MD, RD and AD values when compared to healthy controls. Pediatric migraine patients also

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Messina et al. Table 2. Diffusion tensor (DT) magnetic resonance imaging (MRI) metrics (mean values and standard deviations (SD)) of white matter (WM) tracts significantly different between pediatric patients with migraine and healthy controls. WM tracts

Side

Variable

Pediatric healthy controls

Pediatric migraine patients

p values

Cingulum

Right

MD AD MD AD MD AD MD MD RD MD RD MD RD AD MD RD FA MD RD FA MD RD

0.82 1.38 0.83 1.41 0.78 1.64 0.76 0.75 0.38 0.82 0.51 0.81 0.50 1.44 0.85 0.46 0.67 0.84 0.47 0.65 0.74 0.49

0.80 1.34 0.80 1.35 0.76 1.61 0.74 0.73 0.37 0.79 0.47 0.79 0.48 1.40 0.80 0.41 0.69 0.81 0.43 0.68 0.72 0.47

0.02 0.04 0.05 0.01 0.03 0.03 0.04 0.04 0.04 0.001 0.002 0.004 0.05 0.04

White matter microstructure abnormalities in pediatric migraine patients.

Diffusion tensor (DT) magnetic resonance imaging (MRI) provides several quantities with the potential to disclose white matter (WM) microstructural ab...
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