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Neuroanatomical correlates of dystonic tremor: A cross-sectional study
Parkinsonism and Related Disorders 20 (2014) 314e317
Contents lists available at ScienceDirect
Parkinsonism and Related Disorders journal homepage: www.elsevier.com/locate/parkreldis
Neuroanatomical correlates of dystonic tremor: A cross-sectional study Antonio Cerasa a, Rita Nisticò a, Maria Salsone b, Francesco Bono b, Dania Salvino b, Maurizio Morelli b, Gennarina Arabia b, Aldo Quattrone a, b, * a b
Neuroimaging Research Unit, Institute of Bioimaging and Molecular Physiology, National Research Council, Germaneto, Catanzaro, Italy Institute of Neurology, University “Magna Graecia”, Germaneto, Catanzaro, Italy
a r t i c l e i n f o
a b s t r a c t
Article history: Received 2 September 2013 Received in revised form 2 December 2013 Accepted 18 December 2013
Purpose: This study is aimed at investigating the neuroanatomical patterns characterizing dystonic tremor in comparison with essential tremor. Methods: Voxel-based morphometry and cortical thickness data of 12 patients with dystonic tremor, 14 patients with essential tremor and 23 age- and sex-matched healthy control subjects were analyzed. Results: Patients with dystonic tremor showed a thickening and increased gray matter volume (surviving whole-brain correction for multiple comparisons) of the left sensorimotor cortex when compared to other groups. Otherwise, patients with essential tremor were characterized by a subtle atrophy of the anterior cerebellar cortex. Discussion: Our multimodal structural neuroimaging study demonstrated that patients with dystonic tremor and essential tremor are characterized by different neuroanatomical abnormalities. The involvement of the sensorimotor cortex in patients with dystonic tremor suggests that this disorder may share some pathophysiological mechanisms with focal dystonia. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Dystonic tremor Essential tremor Neuroimaging Voxel-based morphometry Sensori-motor cortex
1. Introduction Dystonic tremor (DT) is defined as a postural/kinetic tremor with irregular amplitude and variable frequency occurring in an extremity or body part affected by dystonia [1]. Diagnosing this disorder may be challenging because tremor observed in patients suspected of having DT resembles essential tremor (ET), and dystonia may be subtle and difficult to recognize only on clinical grounds. In the last few years, advances have been reached in the definition of the pathophysiological mechanisms underlying ET and DT. Evidences support the hypothesis that ET is a progressive disease sustained by neurodegenerative processes [2e5]. Neuroimaging [3,4] and post-mortem [5] studies in patients with ET demonstrated the presence of pathological changes mainly involving the cerebellum [6]. Otherwise, very recent studies demonstrated abnormality of sensorimotor integration circuits [7] or increased blink recovery cycle [8] in patients with DT, suggesting that this disorder might be associated with brain dysfunctions different from those detected in ET. * Corresponding author. Institute of Neurology, Department of Medical Sciences, University “Magna Graecia”, 88100 Germaneto, Catanzaro, Italy. Tel.: þ39 0961 3647075; fax: þ39 0961 3647177. E-mail address: [email protected] (A. Quattrone). 1353-8020/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.parkreldis.2013.12.007
The current study is aimed at investigating the presence of neuroanatomical changes in patients with DT with respect to patients with ET and healthy controls by combining two complementary morphologic MR measurements: voxel-based morphometry (VBM) [9] and cortical thickness (FreeSurfer) [10] in a multi-method unbiased approach. We used both methods in order to receive any complementary piece of information. Indeed, whereas VBM provides a general measure of gray matter (GM) volume, which conflates the contributions of thickness and surface, cortical thickness analysis captures the columnar architecture of the cortex. 2. Methods 2.1. Subjects From April 2010 to November 2013, we prospectively identified 12 consecutive patients with a diagnosis of DT (six with neck dystonia associated with head tremor without limbs tremor and six with unilateral dystonic limb tremor without dystonia elsewhere; no patient had facial dystonia) and 14 patients with ET. DT and ET were diagnosed according to the consensus criteria of the Movement Disorders Society on tremor [1]. Tremor and dystonia were assessed by FahneTolosaeMarin rating scale [11] and Unified
A. Cerasa et al. / Parkinsonism and Related Disorders 20 (2014) 314e317
Dystonia Rating Scale (URDS), respectively. All enrolled patients underwent an accurate clinical history and videotaped neurological examination to better define clinical characteristics of DT. Exclusion criteria were the presence of brain lesions (evidence of structural abnormalities as revealed by radiological examination) or depression symptoms (as assessed by the Structured Clinical Interview for DSM-IV Axis I disorders). Moreover, every patient underwent DATSPECT. No patients with DT or ET received botulinum toxin injections. Twenty-three volunteers with no previous history of neurological or psychiatric diseases and with normal MRI of the brain were matched for demographical variables with patients. All participants gave written informed consent, which was approved by the Ethical Committee of the University ‘Magna Graecia’ of Catanzaro, according to the Helsinki Declaration. 2.2. MRI data acquisition Brain MRI was performed according to our routine protocol [12] by a 3 T scanner with an 8-channel head coil (Discovery MR-750, GE, Milwaukee, WI, USA). Structural MRI data were acquired using a 3D T1-weighted spoiled gradient echo (SPGR) sequence. Subjects were positioned to lie comfortably in the scanner with a forehead-restraining strap and various foam pads to ensure head fixation. 2.3. VBM data processing and analysis Data were processed and examined using the SPM8 software where we applied VBM implemented in the VBM8 toolbox (http:// dbm.neuro.uni-jena.de/vbm.html) with default parameters incorporating the DARTEL toolbox that was used to obtain a highdimensional normalization protocol. Images were bias-corrected, tissue classified and registered using linear and non-linear transformations, within a unified model [9]. Subsequently, the warped GM segments were affine transformed into Montreal Neurological Institute (MNI) space and were scaled by the Jacobian determinants of the deformations (modulated GM volumes). Finally, the modulated volumes were smoothed with a Gaussian kernel of 8 mm. 2.4. Cortical thickness data processing and analysis To corroborate voxel-based findings we further performed cortical thickness analysis of the cortical mantle by using FreeSurfer v5.1 [10] with a well-established methodology [13]. In particular, we were interested in confirming findings provided by VBM analysis. Briefly, images were first corrected for intensity nonuniformity and registered via affine transformation (12 parameters) to Montreal Neurological Institute (MNI) space. Then, images underwent a further intensity normalization using a different automated algorithm and were automatically skull stripped. Next, the entire cortex was visually inspected prior to analysis by a neuroradiologist with a high level of neuroanatomical expertise, who was blinded from the MRI results. For each subject, thickness measurements across the cortex were computed by finding the point on the grayewhite boundary surface that was closest to a given point on the estimated pial surface and averaging between these two values. Finally, cortical maps were smoothed with a 10-mm full-width at half maximum Gaussian kernel. 2.5. Statistical analysis Statistical analyses were performed with Statistical Version 6.0 (www.statsoft.com). One-way ANOVA, unpaired t-test and c2 were used to assess potential differences between groups for all
315
demographic and clinical variables. All statistical analyses had a two-tailed alpha level of <0.05 for defining significance. 2.6. VBM statistics The GM volume maps were statistically analyzed using the general linear model based on Gaussian random field theory. Statistical analysis consisted of an analysis of covariance (AnCOVA) used for investigating the main effect of group (F-test). Age and total intracranial volume (ICV) were included in the model as covariates of no-interest. Two approaches to statistical threshold maps were applied. First, we applied a conservative approach with a whole-brain statistical threshold correction (P < 0.05, family-wise error (FWE)). Second, since that in vivo evidence of GM abnormalities in DT has never been reported, for exploratory purpose the data were also presented by using a less-stringent, uncorrected threshold (P < 0.001, cluster (k) threshold ¼ 10 voxels) to detect subtle morphological changes. 2.7. Cortical thickness statistics Surface-based group analyses were performed using general linear model. Statistical significance of between-group cortical thickness was evaluated using a clusterwise correction for multiple comparisons from Monte Carlo z-field simulation [14]. To correct for multiple comparisons, spatial clusters of thickness differences were defined as continuous patches of vertices with P-values less than 0.05 (two-tailed). The P-values for these clusters were determined by Monte Carlo simulation (10,000 iterations). Only clusters that survived this correction with P-values less than 0.05 (twotailed) were deemed significant. 3. Results 3.1. Clinical data Demographic and clinical features of all subjects are listed in Table 1. No significant differences were detected in demographical and clinical data between groups. 3.2. VBM data VBM analysis, investigating the neuroanatomical changes occurring when the three groups were analyzed together (AnCOVA,
Table 1 Demographic, clinical and DAT-SPECT imaging characteristics. Variables
DT
ET
Controls
P-Values
Nc Men, n. (%) Age (years) Age at onset (years) Disease duration (years) Familiaritya, n (%) MMSE UDRS FahneTolosa DAT-SPECT Left putamen Right putamen
12 6 (50%) 62.9 15 50.2 15.9 10.9 8.9 6 (50%) 27.4 1.6 5 0.9 11.3 9.1
14 8 (57%) 66.3 9.1 53.2 15.3 12.8 11.9 9 (64%) 26.2 3.7 e 10.1 4.6
23 13 (56%) 64.4 7.1 e e e 27.2 3.7 e e
0.91b 0.27d 0.41c 0.32c 0.73b 0.58d 0.44c
2.16 0.3 2.13 0.51
2.15 0.29 2.21 0.27
2.20 0.29 2.21 0.28
0.85d 0.72d
DT: dystonic tremor; ET: essential tremor. MMSE: mini mental state examination. UDRS: Unified Dystonia Rating Scale. a Positive family history regarding tremor. b c2 test. c Unpaired t test. d One-way ANOVA.
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A. Cerasa et al. / Parkinsonism and Related Disorders 20 (2014) 314e317
F-test), revealed the presence of a very restricted pattern of difference surviving correction for multiple comparisons at a whole brain level (FWE < 0.05). For this reason, we were allowed to perform additional post-hoc analyses between groups to better describe these anatomical changes. As shown in Fig. 1, DT patients demonstrated an abnormal increase of GM volume in a large cluster encompassing the left somatosensory and primary motor cortices (main effect of group; MNI local maxima: x ¼ 18, y ¼ 46, z ¼ 69, F-value ¼ 20.84, (k) ¼ 252, PFWE ¼ 0.021), either with respect to ET patients (post-hoc analysis; T-value ¼ 4.13, (k) ¼ 25, PFWE ¼ 0.03) or healthy controls (post-hoc analysis; T-value ¼ 6.45, (k) ¼ 414, PFWE < 0.0001). For exploratory purposes, we also reported volumetric changes occurring when a less-stringent uncorrected statistical threshold was considered (Puncorrected < 0.001). DT patients showed additional GM abnormalities in the a) medial premotor cortex when compared either to ET patients (post-hoc analysis; MNI local maxima: x ¼ 4, y ¼ 12, z ¼ 61, T-value ¼ 4.51, (k) ¼ 1484, Puncorrected < 0.001) or healthy controls (post-hoc analysis; MNI local maxima: x ¼ 4, y ¼ 12, z ¼ 58, T-value ¼ 4.6, (k) ¼ 1232, Puncorrected < 0.001) and b) in the midbrain when compared to
Fig. 1. VBM results. 3D/2D surface renders show the significant cluster deriving from the main effect of group. Significant difference (**surviving correction for multiple comparisons at a whole brain level, FWE < 0.05) is found only within the left sensorimotor cortex, where patients with DT display an abnormal increase of the GM volume with respect to other groups. Mean differences (SEM) between groups within regions of statistical significance have been plotted below. A statistical map is superimposed onto the T1-weighted standard template (MNI). Data analyses have been further corrected for age and intracranial volume. The color bar represents F-statistics. DT: dystonic tremor; ET: essential tremor; HC: healthy controls.
controls (MNI local maxima: x ¼ 4, y ¼ 15, z ¼ 18, Tvalue ¼ 4.33, (k) ¼ 525, Puncorrected < 0.001) (see Supplementary materials). Otherwise, patients with ET showed only a reduced GM volume of the cerebellum, involving the anterior lobe, only when compared to controls (MNI local maxima: x ¼ 4, y ¼ 34, z ¼ 27, T-value ¼ 4.58, (k) ¼ 282; Puncorrected < 0.001) (see Supplementary materials). 3.3. Cortical thickness data Cortical thickness analysis confirmed the prevalent cortical abnormalities detected in the left sensorimotor cortex (Fig. 2) but only in the comparison between DT patients with respect to controls (Pcorrected ¼ 0.02). Indeed, when compared to ET, the presence of sensorimotor thickening was confirmed in DT patients but without surviving correction for multiple comparisons. 4. Discussion The present study describes for the first time the neuroanatomical correlates of DT, which are characterized by a different neurodegenerative pattern with respect to those detected in ET. Indeed, DT patients showed a restricted abnormal pattern of GM increase involving the left sensorimotor cortex that differentiated these patients both from healthy controls and from clinically- and demographically-matched ET patients. Considering VBM data, the detected abnormality of the sensorimotor cortex may represent a supportive feature to diagnose DT and a new potential marker to differentiate patients with DT from those with ET. Interestingly, the same neuroanatomical pattern has been described in patients affected by focal dystonia [15]. In fact, patients with cervical dystonia, blepharospasm or writer’s cramp are characterized by an abnormal increase of volume in the sensorimotor cortex [15] together with abnormal activities of this cortical region as detected by functional MRI [16,17], as well as by a disordered cortical representation of digits as detected by magnetoencephalography technique [18]. All this evidence allow us to hypothesize that focal dystonia and DT might share some pathophysiological mechanisms characterized by impaired sensorimotor integration or abnormal sensorimotor somatotopy. Again, our neuroimaging data perfectly match with those reported in a recent
Fig. 2. Statistical map showed left hemisphere clusters with significant cortical thickening (yellow) in the comparisons between DT patients versus healthy controls. These significant clusters from Monte-Carlo simulations are overlaid on the FreeSurfer average subject.
A. Cerasa et al. / Parkinsonism and Related Disorders 20 (2014) 314e317
psychophysiological study [7]. These authors demonstrated deficits during a somatosensory temporal discrimination test in patients with tremor associated with dystonia, while patients with ET were characterized by abnormal performance during a motor temporal discrimination test [7]. Interestingly, these authors proposed that the former test is processed through a specific network involving basal ganglia and the somatosensory cortex and that abnormal values characterized patients with various forms of dystonia [19,20]. In contrast, the motor temporal discrimination test is fundamentally regulated by cerebellarecortical pathways [7], thus highlighting the role of the cerebellum in the pathophysiological mechanisms of ET. Of note, in our patients with DT, VBM analysis also showed the involvement of additional brain regions. Of particular interest is the involvement of the medial premotor cortex. Indeed, several PET, neurophysiological [21] and fMRI studies [22] have demonstrated abnormal reorganization/overactivity in the motor, premotor and supplementary motor cortices in patients with primary and secondary dystonias, which normalized after the application of repetitive transcranial stimulation over the premotor cortex [23]. However, despite the involvement of the sensorimotor cortex, other detected anatomical changes (including cerebellar atrophy in ET) did not persist after whole-brain correction for multiple comparisons, thus making speculative any attempt to delineate definitive conclusions on the role of these brain regions in developing DT. One important limitation of this study needs to be discussed. Indeed, the relatively small sample size of patients with DT may have masked subtle differences between groups. For instance, although VBM and cortical thickness analysis revealed a common neurodegenerative pattern, both methods did not report a convergent precise anatomical localization in the somatosensory and motor homunculus. Nonetheless, considering the magnitude of the detected volumetric changes (surviving correction for multiple comparisons), the employment of two complementary morphologic MR measurements and the fact that all reported anatomical changes are part of well-defined pathophysiological pathways underlying DT, all these evidences speak about the robustness of our work. However, we acknowledge that this is an initial study that requires replication in larger samples and other groups affected by hyperkinetic movement disorders. 5. Conclusions In conclusion, our multimodal structural neuroimaging study showed that patients with DT are neuroanatomically distinct from ET. In particular, the morphology of the sensorimotor cortex would represent a new critical biomarker useful to characterize DT with respect to ET patients. Future imaging and neuropathological studies are strongly warranted to confirm this hypothesis. Moreover, the involvement of the sensorimotor cortex in patients with DT also supports the hypothesis that this form of tremor shares some pathophysiological mechanisms with focal dystonia. Conflicts of interest None declared.
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Disclosure This study was supported by MIUR (Ministero Universita’ e Ricerca) grants to AQ. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.parkreldis.2013.12.007. References [1] Deuschl G, Bain P, Brin M. Consensus statement of the Movement Disorder Society on tremor: ad hoc scientific. Mov Disord 1998;13:2e23. [2] Louis ED, Faust PL, Vonsattel JP. Purkinje cell loss is a characteristic of essential tremor. Parkinsonism Relat Disord 2011;17:406e9. [3] Quattrone A, Cerasa A, Messina D, Nicoletti G, Hagberg GE, Lemieux L, et al. Essential head tremor is associated with cerebellar vermis atrophy: a volumetric and voxel-based morphometry MR imaging study. AJNR Am J Neuroradiol 2008;29:1692e7. [4] Benito-León J, Alvarez-Linera J, Hernández-Tamames JA, Alonso-Navarro H, Jiménez-Jiménez FJ, Louis ED. Brain structural changes in essential tremor: voxel-based morphometry at 3-Tesla. J Neurol Sci 2009;287:138e42. [5] Louis ED, Faust PL, Ma KJ, Yu M, Cortes E, Vonsattel JP. Torpedoes in the cerebellar vermis in essential tremor cases vs. controls. Cerebellum 2011;10:812e9. [6] Passamonti L, Cerasa A, Quattrone A. Neuroimaging of essential tremor: what is the evidence for cerebellar involvement? Tremor Other Hyperkinet Move 2012;2. pii: 02-67-421-3. [7] Tinazzi M, Fasano A, Di Matteo A, Conte A, Bove F, Bovi T, et al. Temporal discrimination in patients with dystonia and tremor and patients with essential tremor. Neurology 2013;80:76e84. [8] Nisticò R, Pirritano D, Salsone M, Valentino P, Novellino F, Condino F, et al. Blink reflex recovery cycle in patients with dystonic tremor: a cross-sectional study. Neurology 2012;78:1363e5. [9] Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage 2007;38:95e113. [10] Fischl B, Dale AM. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A 2000;97:11050e5. [11] Fahn S, Tolosa E. Clinical rating scale for tremor, in Parkinson’s disease and movement disorders. Baltimore: Williams & Wilkins; 1993. [12] Cerasa A, Passamonti L, Valentino P, Nisticò R, Pirritano D, Gioia MC, et al. Cerebellar-parietal dysfunctions in multiple sclerosis patients with cerebellar signs. Exp Neurol 2012;237:418e26. [13] Cerasa A, Morelli M, Augimeri A, Salsone M, Novellino F, Gioia MC, et al. Prefrontal thickening in PD with levodopa-induced dyskinesias: new evidence from cortical thickness measurement. Parkinsonism Relat Disord 2013;19:123e5. [14] Hagler Jr DJ, Saygin AP, Sereno MI. Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data. Neuroimage 2006;33:1093e103. [15] Zheng Z, Pan P, Wang W, Shang H. Neural network of primary focal dystonia by an anatomic likelihood estimation meta-analysis of gray matter abnormalities. J Neurol Sci 2012;316:51e5. [16] Haslinger B, Erhard P, Dresel C, Castrop F, Roettinger M, CeballosBaumann AO, et al. “Silent event-related” fMRI reveals reduced sensorimotor activation in laryngeal dystonia. Neurology 2005;65:1562e9. [17] Simonyan K, Ludlow CL. Abnormal activation of the primary somatosensory cortex in spasmodic dysphonia: an fMRI study. Cereb Cortex 2010;20:2749e59. [18] Braun C, Schweizer R, Heinz U, Wiech K, Birbaumer N, Topka H. Task-specific plasticity of somatosensory cortex in patients with writer’s cramp. Neuroimage 2003;20:1329e38. [19] Fiorio M, Gambarin M, Valente EM, Liberini P, Loi M, Cossu G, et al. Defective temporal processing of sensory stimuli in DYT1 mutation carriers: a new endophenotype of dystonia? Brain 2007;130:134e42. [20] Fiorio M, Tinazzi M, Scontrini A, Stanzani C, Gambarin M, Fiaschi A, et al. Tactile temporal discrimination in patients with blepharospasm. J Neurol Neurosurg Psychiatry 2008;79:796e8. [21] Byrnes ML, Thickbroom GW, Wilson SA, Sacco P, Shipman JM, Stell R, et al. The corticomotor representation of upper limb muscles in writer’s cramp and changes following botulinum toxin injection. Brain 1998;121:977e88. [22] Breakefield XO, Blood AJ, Li Y, Hallett M, Hanson PI, Standaert DG. The pathophysiological basis of dystonias. Nat Rev Neurosci 2008;9:222e34. [23] Murase N, Rothwell JC, Kaji R, Urushihara R, Nakamura K, Murayama N, et al. Subthreshold low-frequency repetitive transcranial magnetic stimulation over the premotor cortex modulates writer’s cramp. Brain 2005;128:104e15.
Contents lists available at ScienceDirect
Parkinsonism and Related Disorders journal homepage: www.elsevier.com/locate/parkreldis
Neuroanatomical correlates of dystonic tremor: A cross-sectional study Antonio Cerasa a, Rita Nisticò a, Maria Salsone b, Francesco Bono b, Dania Salvino b, Maurizio Morelli b, Gennarina Arabia b, Aldo Quattrone a, b, * a b
Neuroimaging Research Unit, Institute of Bioimaging and Molecular Physiology, National Research Council, Germaneto, Catanzaro, Italy Institute of Neurology, University “Magna Graecia”, Germaneto, Catanzaro, Italy
a r t i c l e i n f o
a b s t r a c t
Article history: Received 2 September 2013 Received in revised form 2 December 2013 Accepted 18 December 2013
Purpose: This study is aimed at investigating the neuroanatomical patterns characterizing dystonic tremor in comparison with essential tremor. Methods: Voxel-based morphometry and cortical thickness data of 12 patients with dystonic tremor, 14 patients with essential tremor and 23 age- and sex-matched healthy control subjects were analyzed. Results: Patients with dystonic tremor showed a thickening and increased gray matter volume (surviving whole-brain correction for multiple comparisons) of the left sensorimotor cortex when compared to other groups. Otherwise, patients with essential tremor were characterized by a subtle atrophy of the anterior cerebellar cortex. Discussion: Our multimodal structural neuroimaging study demonstrated that patients with dystonic tremor and essential tremor are characterized by different neuroanatomical abnormalities. The involvement of the sensorimotor cortex in patients with dystonic tremor suggests that this disorder may share some pathophysiological mechanisms with focal dystonia. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Dystonic tremor Essential tremor Neuroimaging Voxel-based morphometry Sensori-motor cortex
1. Introduction Dystonic tremor (DT) is defined as a postural/kinetic tremor with irregular amplitude and variable frequency occurring in an extremity or body part affected by dystonia [1]. Diagnosing this disorder may be challenging because tremor observed in patients suspected of having DT resembles essential tremor (ET), and dystonia may be subtle and difficult to recognize only on clinical grounds. In the last few years, advances have been reached in the definition of the pathophysiological mechanisms underlying ET and DT. Evidences support the hypothesis that ET is a progressive disease sustained by neurodegenerative processes [2e5]. Neuroimaging [3,4] and post-mortem [5] studies in patients with ET demonstrated the presence of pathological changes mainly involving the cerebellum [6]. Otherwise, very recent studies demonstrated abnormality of sensorimotor integration circuits [7] or increased blink recovery cycle [8] in patients with DT, suggesting that this disorder might be associated with brain dysfunctions different from those detected in ET. * Corresponding author. Institute of Neurology, Department of Medical Sciences, University “Magna Graecia”, 88100 Germaneto, Catanzaro, Italy. Tel.: þ39 0961 3647075; fax: þ39 0961 3647177. E-mail address: [email protected] (A. Quattrone). 1353-8020/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.parkreldis.2013.12.007
The current study is aimed at investigating the presence of neuroanatomical changes in patients with DT with respect to patients with ET and healthy controls by combining two complementary morphologic MR measurements: voxel-based morphometry (VBM) [9] and cortical thickness (FreeSurfer) [10] in a multi-method unbiased approach. We used both methods in order to receive any complementary piece of information. Indeed, whereas VBM provides a general measure of gray matter (GM) volume, which conflates the contributions of thickness and surface, cortical thickness analysis captures the columnar architecture of the cortex. 2. Methods 2.1. Subjects From April 2010 to November 2013, we prospectively identified 12 consecutive patients with a diagnosis of DT (six with neck dystonia associated with head tremor without limbs tremor and six with unilateral dystonic limb tremor without dystonia elsewhere; no patient had facial dystonia) and 14 patients with ET. DT and ET were diagnosed according to the consensus criteria of the Movement Disorders Society on tremor [1]. Tremor and dystonia were assessed by FahneTolosaeMarin rating scale [11] and Unified
A. Cerasa et al. / Parkinsonism and Related Disorders 20 (2014) 314e317
Dystonia Rating Scale (URDS), respectively. All enrolled patients underwent an accurate clinical history and videotaped neurological examination to better define clinical characteristics of DT. Exclusion criteria were the presence of brain lesions (evidence of structural abnormalities as revealed by radiological examination) or depression symptoms (as assessed by the Structured Clinical Interview for DSM-IV Axis I disorders). Moreover, every patient underwent DATSPECT. No patients with DT or ET received botulinum toxin injections. Twenty-three volunteers with no previous history of neurological or psychiatric diseases and with normal MRI of the brain were matched for demographical variables with patients. All participants gave written informed consent, which was approved by the Ethical Committee of the University ‘Magna Graecia’ of Catanzaro, according to the Helsinki Declaration. 2.2. MRI data acquisition Brain MRI was performed according to our routine protocol [12] by a 3 T scanner with an 8-channel head coil (Discovery MR-750, GE, Milwaukee, WI, USA). Structural MRI data were acquired using a 3D T1-weighted spoiled gradient echo (SPGR) sequence. Subjects were positioned to lie comfortably in the scanner with a forehead-restraining strap and various foam pads to ensure head fixation. 2.3. VBM data processing and analysis Data were processed and examined using the SPM8 software where we applied VBM implemented in the VBM8 toolbox (http:// dbm.neuro.uni-jena.de/vbm.html) with default parameters incorporating the DARTEL toolbox that was used to obtain a highdimensional normalization protocol. Images were bias-corrected, tissue classified and registered using linear and non-linear transformations, within a unified model [9]. Subsequently, the warped GM segments were affine transformed into Montreal Neurological Institute (MNI) space and were scaled by the Jacobian determinants of the deformations (modulated GM volumes). Finally, the modulated volumes were smoothed with a Gaussian kernel of 8 mm. 2.4. Cortical thickness data processing and analysis To corroborate voxel-based findings we further performed cortical thickness analysis of the cortical mantle by using FreeSurfer v5.1 [10] with a well-established methodology [13]. In particular, we were interested in confirming findings provided by VBM analysis. Briefly, images were first corrected for intensity nonuniformity and registered via affine transformation (12 parameters) to Montreal Neurological Institute (MNI) space. Then, images underwent a further intensity normalization using a different automated algorithm and were automatically skull stripped. Next, the entire cortex was visually inspected prior to analysis by a neuroradiologist with a high level of neuroanatomical expertise, who was blinded from the MRI results. For each subject, thickness measurements across the cortex were computed by finding the point on the grayewhite boundary surface that was closest to a given point on the estimated pial surface and averaging between these two values. Finally, cortical maps were smoothed with a 10-mm full-width at half maximum Gaussian kernel. 2.5. Statistical analysis Statistical analyses were performed with Statistical Version 6.0 (www.statsoft.com). One-way ANOVA, unpaired t-test and c2 were used to assess potential differences between groups for all
315
demographic and clinical variables. All statistical analyses had a two-tailed alpha level of <0.05 for defining significance. 2.6. VBM statistics The GM volume maps were statistically analyzed using the general linear model based on Gaussian random field theory. Statistical analysis consisted of an analysis of covariance (AnCOVA) used for investigating the main effect of group (F-test). Age and total intracranial volume (ICV) were included in the model as covariates of no-interest. Two approaches to statistical threshold maps were applied. First, we applied a conservative approach with a whole-brain statistical threshold correction (P < 0.05, family-wise error (FWE)). Second, since that in vivo evidence of GM abnormalities in DT has never been reported, for exploratory purpose the data were also presented by using a less-stringent, uncorrected threshold (P < 0.001, cluster (k) threshold ¼ 10 voxels) to detect subtle morphological changes. 2.7. Cortical thickness statistics Surface-based group analyses were performed using general linear model. Statistical significance of between-group cortical thickness was evaluated using a clusterwise correction for multiple comparisons from Monte Carlo z-field simulation [14]. To correct for multiple comparisons, spatial clusters of thickness differences were defined as continuous patches of vertices with P-values less than 0.05 (two-tailed). The P-values for these clusters were determined by Monte Carlo simulation (10,000 iterations). Only clusters that survived this correction with P-values less than 0.05 (twotailed) were deemed significant. 3. Results 3.1. Clinical data Demographic and clinical features of all subjects are listed in Table 1. No significant differences were detected in demographical and clinical data between groups. 3.2. VBM data VBM analysis, investigating the neuroanatomical changes occurring when the three groups were analyzed together (AnCOVA,
Table 1 Demographic, clinical and DAT-SPECT imaging characteristics. Variables
DT
ET
Controls
P-Values
Nc Men, n. (%) Age (years) Age at onset (years) Disease duration (years) Familiaritya, n (%) MMSE UDRS FahneTolosa DAT-SPECT Left putamen Right putamen
12 6 (50%) 62.9 15 50.2 15.9 10.9 8.9 6 (50%) 27.4 1.6 5 0.9 11.3 9.1
14 8 (57%) 66.3 9.1 53.2 15.3 12.8 11.9 9 (64%) 26.2 3.7 e 10.1 4.6
23 13 (56%) 64.4 7.1 e e e 27.2 3.7 e e
0.91b 0.27d 0.41c 0.32c 0.73b 0.58d 0.44c
2.16 0.3 2.13 0.51
2.15 0.29 2.21 0.27
2.20 0.29 2.21 0.28
0.85d 0.72d
DT: dystonic tremor; ET: essential tremor. MMSE: mini mental state examination. UDRS: Unified Dystonia Rating Scale. a Positive family history regarding tremor. b c2 test. c Unpaired t test. d One-way ANOVA.
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F-test), revealed the presence of a very restricted pattern of difference surviving correction for multiple comparisons at a whole brain level (FWE < 0.05). For this reason, we were allowed to perform additional post-hoc analyses between groups to better describe these anatomical changes. As shown in Fig. 1, DT patients demonstrated an abnormal increase of GM volume in a large cluster encompassing the left somatosensory and primary motor cortices (main effect of group; MNI local maxima: x ¼ 18, y ¼ 46, z ¼ 69, F-value ¼ 20.84, (k) ¼ 252, PFWE ¼ 0.021), either with respect to ET patients (post-hoc analysis; T-value ¼ 4.13, (k) ¼ 25, PFWE ¼ 0.03) or healthy controls (post-hoc analysis; T-value ¼ 6.45, (k) ¼ 414, PFWE < 0.0001). For exploratory purposes, we also reported volumetric changes occurring when a less-stringent uncorrected statistical threshold was considered (Puncorrected < 0.001). DT patients showed additional GM abnormalities in the a) medial premotor cortex when compared either to ET patients (post-hoc analysis; MNI local maxima: x ¼ 4, y ¼ 12, z ¼ 61, T-value ¼ 4.51, (k) ¼ 1484, Puncorrected < 0.001) or healthy controls (post-hoc analysis; MNI local maxima: x ¼ 4, y ¼ 12, z ¼ 58, T-value ¼ 4.6, (k) ¼ 1232, Puncorrected < 0.001) and b) in the midbrain when compared to
Fig. 1. VBM results. 3D/2D surface renders show the significant cluster deriving from the main effect of group. Significant difference (**surviving correction for multiple comparisons at a whole brain level, FWE < 0.05) is found only within the left sensorimotor cortex, where patients with DT display an abnormal increase of the GM volume with respect to other groups. Mean differences (SEM) between groups within regions of statistical significance have been plotted below. A statistical map is superimposed onto the T1-weighted standard template (MNI). Data analyses have been further corrected for age and intracranial volume. The color bar represents F-statistics. DT: dystonic tremor; ET: essential tremor; HC: healthy controls.
controls (MNI local maxima: x ¼ 4, y ¼ 15, z ¼ 18, Tvalue ¼ 4.33, (k) ¼ 525, Puncorrected < 0.001) (see Supplementary materials). Otherwise, patients with ET showed only a reduced GM volume of the cerebellum, involving the anterior lobe, only when compared to controls (MNI local maxima: x ¼ 4, y ¼ 34, z ¼ 27, T-value ¼ 4.58, (k) ¼ 282; Puncorrected < 0.001) (see Supplementary materials). 3.3. Cortical thickness data Cortical thickness analysis confirmed the prevalent cortical abnormalities detected in the left sensorimotor cortex (Fig. 2) but only in the comparison between DT patients with respect to controls (Pcorrected ¼ 0.02). Indeed, when compared to ET, the presence of sensorimotor thickening was confirmed in DT patients but without surviving correction for multiple comparisons. 4. Discussion The present study describes for the first time the neuroanatomical correlates of DT, which are characterized by a different neurodegenerative pattern with respect to those detected in ET. Indeed, DT patients showed a restricted abnormal pattern of GM increase involving the left sensorimotor cortex that differentiated these patients both from healthy controls and from clinically- and demographically-matched ET patients. Considering VBM data, the detected abnormality of the sensorimotor cortex may represent a supportive feature to diagnose DT and a new potential marker to differentiate patients with DT from those with ET. Interestingly, the same neuroanatomical pattern has been described in patients affected by focal dystonia [15]. In fact, patients with cervical dystonia, blepharospasm or writer’s cramp are characterized by an abnormal increase of volume in the sensorimotor cortex [15] together with abnormal activities of this cortical region as detected by functional MRI [16,17], as well as by a disordered cortical representation of digits as detected by magnetoencephalography technique [18]. All this evidence allow us to hypothesize that focal dystonia and DT might share some pathophysiological mechanisms characterized by impaired sensorimotor integration or abnormal sensorimotor somatotopy. Again, our neuroimaging data perfectly match with those reported in a recent
Fig. 2. Statistical map showed left hemisphere clusters with significant cortical thickening (yellow) in the comparisons between DT patients versus healthy controls. These significant clusters from Monte-Carlo simulations are overlaid on the FreeSurfer average subject.
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psychophysiological study [7]. These authors demonstrated deficits during a somatosensory temporal discrimination test in patients with tremor associated with dystonia, while patients with ET were characterized by abnormal performance during a motor temporal discrimination test [7]. Interestingly, these authors proposed that the former test is processed through a specific network involving basal ganglia and the somatosensory cortex and that abnormal values characterized patients with various forms of dystonia [19,20]. In contrast, the motor temporal discrimination test is fundamentally regulated by cerebellarecortical pathways [7], thus highlighting the role of the cerebellum in the pathophysiological mechanisms of ET. Of note, in our patients with DT, VBM analysis also showed the involvement of additional brain regions. Of particular interest is the involvement of the medial premotor cortex. Indeed, several PET, neurophysiological [21] and fMRI studies [22] have demonstrated abnormal reorganization/overactivity in the motor, premotor and supplementary motor cortices in patients with primary and secondary dystonias, which normalized after the application of repetitive transcranial stimulation over the premotor cortex [23]. However, despite the involvement of the sensorimotor cortex, other detected anatomical changes (including cerebellar atrophy in ET) did not persist after whole-brain correction for multiple comparisons, thus making speculative any attempt to delineate definitive conclusions on the role of these brain regions in developing DT. One important limitation of this study needs to be discussed. Indeed, the relatively small sample size of patients with DT may have masked subtle differences between groups. For instance, although VBM and cortical thickness analysis revealed a common neurodegenerative pattern, both methods did not report a convergent precise anatomical localization in the somatosensory and motor homunculus. Nonetheless, considering the magnitude of the detected volumetric changes (surviving correction for multiple comparisons), the employment of two complementary morphologic MR measurements and the fact that all reported anatomical changes are part of well-defined pathophysiological pathways underlying DT, all these evidences speak about the robustness of our work. However, we acknowledge that this is an initial study that requires replication in larger samples and other groups affected by hyperkinetic movement disorders. 5. Conclusions In conclusion, our multimodal structural neuroimaging study showed that patients with DT are neuroanatomically distinct from ET. In particular, the morphology of the sensorimotor cortex would represent a new critical biomarker useful to characterize DT with respect to ET patients. Future imaging and neuropathological studies are strongly warranted to confirm this hypothesis. Moreover, the involvement of the sensorimotor cortex in patients with DT also supports the hypothesis that this form of tremor shares some pathophysiological mechanisms with focal dystonia. Conflicts of interest None declared.
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Disclosure This study was supported by MIUR (Ministero Universita’ e Ricerca) grants to AQ. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.parkreldis.2013.12.007. References [1] Deuschl G, Bain P, Brin M. Consensus statement of the Movement Disorder Society on tremor: ad hoc scientific. Mov Disord 1998;13:2e23. [2] Louis ED, Faust PL, Vonsattel JP. Purkinje cell loss is a characteristic of essential tremor. Parkinsonism Relat Disord 2011;17:406e9. [3] Quattrone A, Cerasa A, Messina D, Nicoletti G, Hagberg GE, Lemieux L, et al. Essential head tremor is associated with cerebellar vermis atrophy: a volumetric and voxel-based morphometry MR imaging study. AJNR Am J Neuroradiol 2008;29:1692e7. [4] Benito-León J, Alvarez-Linera J, Hernández-Tamames JA, Alonso-Navarro H, Jiménez-Jiménez FJ, Louis ED. Brain structural changes in essential tremor: voxel-based morphometry at 3-Tesla. J Neurol Sci 2009;287:138e42. [5] Louis ED, Faust PL, Ma KJ, Yu M, Cortes E, Vonsattel JP. Torpedoes in the cerebellar vermis in essential tremor cases vs. controls. Cerebellum 2011;10:812e9. [6] Passamonti L, Cerasa A, Quattrone A. Neuroimaging of essential tremor: what is the evidence for cerebellar involvement? Tremor Other Hyperkinet Move 2012;2. pii: 02-67-421-3. [7] Tinazzi M, Fasano A, Di Matteo A, Conte A, Bove F, Bovi T, et al. Temporal discrimination in patients with dystonia and tremor and patients with essential tremor. Neurology 2013;80:76e84. [8] Nisticò R, Pirritano D, Salsone M, Valentino P, Novellino F, Condino F, et al. Blink reflex recovery cycle in patients with dystonic tremor: a cross-sectional study. Neurology 2012;78:1363e5. [9] Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage 2007;38:95e113. [10] Fischl B, Dale AM. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A 2000;97:11050e5. [11] Fahn S, Tolosa E. Clinical rating scale for tremor, in Parkinson’s disease and movement disorders. Baltimore: Williams & Wilkins; 1993. [12] Cerasa A, Passamonti L, Valentino P, Nisticò R, Pirritano D, Gioia MC, et al. Cerebellar-parietal dysfunctions in multiple sclerosis patients with cerebellar signs. Exp Neurol 2012;237:418e26. [13] Cerasa A, Morelli M, Augimeri A, Salsone M, Novellino F, Gioia MC, et al. Prefrontal thickening in PD with levodopa-induced dyskinesias: new evidence from cortical thickness measurement. Parkinsonism Relat Disord 2013;19:123e5. [14] Hagler Jr DJ, Saygin AP, Sereno MI. Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data. Neuroimage 2006;33:1093e103. [15] Zheng Z, Pan P, Wang W, Shang H. Neural network of primary focal dystonia by an anatomic likelihood estimation meta-analysis of gray matter abnormalities. J Neurol Sci 2012;316:51e5. [16] Haslinger B, Erhard P, Dresel C, Castrop F, Roettinger M, CeballosBaumann AO, et al. “Silent event-related” fMRI reveals reduced sensorimotor activation in laryngeal dystonia. Neurology 2005;65:1562e9. [17] Simonyan K, Ludlow CL. Abnormal activation of the primary somatosensory cortex in spasmodic dysphonia: an fMRI study. Cereb Cortex 2010;20:2749e59. [18] Braun C, Schweizer R, Heinz U, Wiech K, Birbaumer N, Topka H. Task-specific plasticity of somatosensory cortex in patients with writer’s cramp. Neuroimage 2003;20:1329e38. [19] Fiorio M, Gambarin M, Valente EM, Liberini P, Loi M, Cossu G, et al. Defective temporal processing of sensory stimuli in DYT1 mutation carriers: a new endophenotype of dystonia? Brain 2007;130:134e42. [20] Fiorio M, Tinazzi M, Scontrini A, Stanzani C, Gambarin M, Fiaschi A, et al. Tactile temporal discrimination in patients with blepharospasm. J Neurol Neurosurg Psychiatry 2008;79:796e8. [21] Byrnes ML, Thickbroom GW, Wilson SA, Sacco P, Shipman JM, Stell R, et al. The corticomotor representation of upper limb muscles in writer’s cramp and changes following botulinum toxin injection. Brain 1998;121:977e88. [22] Breakefield XO, Blood AJ, Li Y, Hallett M, Hanson PI, Standaert DG. The pathophysiological basis of dystonias. Nat Rev Neurosci 2008;9:222e34. [23] Murase N, Rothwell JC, Kaji R, Urushihara R, Nakamura K, Murayama N, et al. Subthreshold low-frequency repetitive transcranial magnetic stimulation over the premotor cortex modulates writer’s cramp. Brain 2005;128:104e15.