Spasmodic dysphonia is a neurological disorder characterized by involuntary spasms in the laryngeal muscles during speech production. Although the clinical symptoms are well characterized, the pathophysiology of this voice disorder is unknown. We describe here, for the first time to our knowledge, disorder-specific brain abnormalities in these patients as determined by a combined approach of diffusion tensor imaging (DTI) and postmortem histopathology. We used DTI to identify brain changes and to target those brain regions for neuropathological examination. DTI showed right-sided decrease of fractional anisotropy in the genu of the internal capsule and bilateral increase of overall water diffusivity in the white matter along the corticobulbar/corticospinal tract in 20 spasmodic dysphonia patients compared to 20 healthy subjects. In addition, water diffusivity was bilaterally increased in the lentiform nucleus, ventral thalamus and cerebellar white and grey matter in the patients. These brain changes were substantiated with focal histopathological abnormalities presented as a loss of axonal density and myelin content in the right genu of the internal capsule and clusters of mineral depositions, containing calcium, phosphorus and iron, in the parenchyma and vessel walls of the posterior limb of the internal capsule, putamen, globus pallidus and cerebellum in the postmortem brain tissue from one patient compared to three controls. The specificity of these brain abnormalities is confirmed by their localization, limited only to the corticobulbar/corticospinal tract and its main input/output structures. We also found positive correlation between the diffusivity changes and clinical symptoms of spasmodic dysphonia (r = 0.509, P = 0.037). These brain abnormalities may alter the central control of voluntary voice production and, therefore, may underlie the pathophysiology of this disorder.
Spasmodic dysphonia (SD) is a primary focal dystonia characterized by loss of voluntary control of vocal fold movements during speech production due to involuntary spasms in the laryngeal muscles. After onset in mid-life, symptoms progress gradually and remain chronic for life (Ludlow et al., 1995). This disorder presents most often as the adductor type (ADSD) characterized by spasmodic bursts in the closing muscles of the vocal folds during vowel production, which result in voice breaks (Nash and Ludlow, 1996). The less common abductor type (ABSD) exhibits slow vocal fold closure following voiceless consonants with intermittent breathy voice breaks (Edgar et al., 2001). SD is a task-specific disorder, affecting voice only during speech, while emotional vocal expressions, such as laughter and cry, remain intact (Bloch et al., 1985).
The pathophysiology of SD is poorly understood. Generally, the focal dystonias are assumed to involve basal ganglia dysfunction and disturbances in the sensory system that play an important role in development of motor control abnormalities (Berardelli et al., 1998). Recent functional neuroimaging studies during voice and narrative speech production in ADSD found activation changes in the laryngeal/orofacial sensorimotor cortex and basal ganglia (Haslinger et al., 2005; Ali et al., 2006), which may contribute to the pathophysiology of SD. However, a fundamental question about the neurobiology of primary dystonia is whether an underlying pathology can be identified. Recently, postmortem abnormalities have been found in patients with Meige's syndrome (Kulisevsky et al., 1988) and DYT1 dystonia (Zweig and Hedreen, 1988; McNaught et al., 2004), but these were limited only to the brainstem. Surprisingly, no significant abnormalities have been found in the basal ganglia of these patients. Furthermore, neuropathology has never been reported in isolated focal dystonias, and, in particular, structural brain abnormalities in patients with spasmodic dysphonia have never been investigated.
Despite the paucity of neuropathological studies, an increasing number of neuroimaging studies have reported the presence of structural changes in patients with other forms of dystonia. Using DTI, reduced white matter integrity has been found in the subgyral region of the sensorimotor cortex in both manifesting and unaffected DYT1 carriers (Carbon et al., 2004). In cervical dystonia, white matter changes have been identified in the genu and body of the corpus callosum as well as in the basal ganglia (Colosimo et al., 2005). Another study in a group of patients with cervical dystonia, generalized dystonia and one patient with SD has found abnormalities in the white matter underlying the middle frontal and postcentral gyri and in the basal ganglia and thalamus with adjacent white matter (Bonilha et al., 2007).
In this study, we aimed to examine the organization of white matter in SD using combined DTI and histopathological approaches. We hypothesized that these patients would have abnormalities in white matter tracts connecting the brain regions involved in voluntary voice production for speech. Task-specificity (Bloch et al., 1985) suggests a separation of the affected voluntary voice production system, controlled by the laryngeal motor cortex, from the unaffected emotional voice production system, controlled by the anterior cingulate cortex (Jurgens, 2002). We hypothesized, therefore, that microstructural white matter changes in SD would be found only in the voluntary voice production system for speech, involving the corticobulbar pathway.
Material and Methods
DTI quantifies the random displacement of water molecules and provides an in vivo estimation of axonal organization in brain tissue (Basser et al., 1994). DTI measures include anisotropy indices (e.g. fractional anisotropy, FA) to quantify the directionality of water diffusion and, therefore, reflect axonal integrity and tissue coherence. Diffusivity indices [e.g. Trace of diffusion tensor, Trace (D) and mean diffusivity, MD] quantify the magnitude of water movement independent of direction (Pierpaoli et al., 1996). These measures are sensitive to microstructural brain tissue abnormalities not evident on conventional MRI (Pierpaoli et al., 2001; Pfefferbaum and Sullivan, 2003).
Twenty patients with SD (14 ADSD, 6 ABSD; age 55.0 ± 10.0 years, mean ± standard deviation; 8 males/12 females) and 20 healthy volunteers (HV) (age 52.7 ± 9.5 years, mean ± standard deviation; 8 males/12 females) participated in the study. Physical examination was normal in all participants; none had a history of neurological disorders (other than SD in the patient group), psychiatric or otolaryngological problems. No other forms of primary or secondary dystonia were present in the patients or their immediate family members based on patients’ medical histories.
The median duration of SD was 11.0 years (range from 1.5 to 27 years). All patients had failed to respond to voice and speech therapy; it was, however, unknown whether these patients’ voice symptoms had worsened since onset. Sixteen patients had been on a regimen of botulinum toxin injections into their laryngeal muscles for several years to maintain their voice symptoms reduction. The median interval between the last botulinum toxin treatment and scanning session was 9 months (range from 3 to 42 months). Two ADSD and two ABSD patients had not previously been treated with botulinum toxin.
Video fiberoptic nasolaryngoscopy and speech testing confirmed diagnosis of SD as well as normal laryngeal function in HV. To assure that the patients had SD and not a functional or psychogenic voice disorder, all patients were required to have disorder-specific spasmodic voice breaks during conversational speech (Sapienza et al., 2000; Barkmeier et al., 2001; Edgar et al., 2001). Diagnostic criteria included hyperadduction of the vocal folds during intermittent voice breaks on vowels for ADSD and prolonged vocal fold opening during breathy breaks on voiceless consonants for ABSD. None of the patients reported symptom-free periods after onset of SD or following voice therapy without regular botulinum toxin treatment. For the purposes of this study, patients agreed to forgo their usually scheduled botulinum toxin treatment in order to be symptomatic at the time of voice and speech testing and scanning. All participants provided written informed consent before taking part in the study, which was approved by the Institutional Review Board of the National Institute of Neurological Disorders and Stroke, National Institutes of Health.
Speech symptom recording and measurement
We quantified symptoms specific to SD that is voice breaks on vowels in ADSD patients and on prolonged voiceless consonants in ABSD patients (Barkmeier et al., 2001; Edgar et al., 2001). Before the scanning, voice and speech of 17 patients were recorded digitally, while they repeated two sets of sentences: 10 sentences containing a high number of glottal stops before vowels to elicit symptoms of ADSD, and 10 sentences containing a high number of voiceless consonants (f/s/h/p/t/k) to elicit symptoms of ABSD. In all patients, digital speech recordings were made with a microphone positioned at a constant 2 inch mouth to microphone distance. The recorded samples were randomly ordered and anonymized before voice break counts were made by a speech-language pathologist with more than seven years of specialized experience with SD. The frequency of voice breaks in 20 sentences either on vowels or on voiceless consonants was counted (Bielamowicz and Ludlow, 2000; Barkmeier et al., 2001); voice harshness in ADSD and breathiness in ABSD were rated using the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V) (Karnell et al., 2007). Pearson correlation coefficients were computed to examine relationships between the speech symptoms and diffusion parameters (P ≤ 0.05).
Participants were scanned on a 3.0 Tesla GE Excite scanner using an eight-channel receive-only coil (General Electric Medical System, Milwaukee, WI, USA). A DTI sequence for whole brain coverage used a single-shot spin-echo echo-planar imaging sequence with paired gradient pulses positioned 180° around the refocusing pulse for diffusion weighting and sensitivity-encoding (ASSET) for rate 2 acceleration. Imaging parameters for the diffusion-weighted sequence were TE/TR = 73.4/13 000 ms, FOV = 2.4 × 2.4 cm2; matrix = 96 × 96 mm2 zero-filled to 256 × 256 mm2; 54 contiguous axial slices with slice thickness of 2.4 mm. Diffusion was measured along 33 non-collinear directions with a b factor of 1000 s/mm2. Three reference images were acquired with no diffusion gradients applied (b0 scans). The same acquisition sequence was repeated two times.
For clinical evaluation, the T2-weighted images were acquired (FSE-T2: TE/TR = 120/5100 ms; FOV = 2.4 × 2.4 cm2; matrix = 256 × 256 mm; 54 axial slices with slice thickness of 2.4 mm; FLAIR: TE/TR = 12 000/102 ms; FOV = 2.4 × 2.4 cm2; matrix = 160 × 160 mm; 28 slices with slice thickness of 5.0 mm).
For each subject, DTI images were co-registered to correct for movement artifacts and eddy current distortion effects on EPI readout (Woods et al., 1998; Jiang et al., 2006). Raw diffusion-weighted images were visually inspected slice-by-slice for each subject, and distorted slices were excluded from analysis before tensor calculation. The diffusion tensor for each voxel was calculated based on the eigenvectors (v1, v2, v3) and eigenvalues (λ1, λ2, λ3) using multivariate fitting and diagonalization. After the FA and Trace (D) maps were calculated from the eigenvalues, colour-coded maps were generated from the FA values and the three vector elements of v1 to visualize the white matter tract orientation (DtiStudio software) (Pajevic and Pierpaoli, 1999; Jiang et al., 2006). The derived FA and Trace data were further analysed using two approaches: the unbiased whole-brain tract-based spatial statistics (TBSS) (Smith et al., 2006) and a priori regions of interest (ROI) analyses.
To assess scanner inter-session variability, four HVs were re-scanned at least 2 weeks apart with the post-processing and calculation of the DTI-derived parameters repeated. Inter-session variability for FA and Trace was represented as percent coefficient of variance [CV = (standard deviation/mean) × 100].
Unbiased whole-brain analysis
To assess the global differences in the white matter fibre tracts between the SD and HV groups, whole-brain voxelwise statistical analyses of FA and Trace data were conducted using TBSS without an a priori assumption (FSL, FMRIB Software Library) (Smith et al., 2006). Because two comparisons were being conducted, a criterion alpha of 0.025 (P = 0.05/2) was applied for analyses of both the FA and Trace datasets. FA and Trace images were first brain-extracted (Smith, 2002) and registered to a common space (MNI152) using constrained nonlinear registration (Image Registration Toolkit) (Rueckert et al., 1999). The mean of all registered FA maps was generated and used to create a mean FA skeleton, which represented the centers of all tracts common to all subjects. Each subject's aligned FA and Trace data were registered to the common FA skeleton via a perpendicular search from each tract in the mean FA skeleton to each image's local tract center forming a sparse (skeletonized) 4D image. Statistical analyses for each point of the mean skeleton were conducted for both FA and Trace maps using univariate general linear modelling design (FEAT, FSL, FMRIB Software Library) to test for significant differences between the two groups. Correction for multiple comparisons was performed using permutation-based inference (5000 permutations) (Nichols and Holmes, 2002) with a cluster-forming threshold of t > 3 and a corrected cluster size significance level of P ≤ 0.025 (randomize, FSL, FMRIB Software Library) (Smith et al., 2006). This approach controlled for familywise errors (FWE) due to the chance of one or more false positives occurring anywhere on the skeleton while searching over the entire skeleton for regions of significant effect (Smith et al., 2006).
Because we hypothesized that regions involved in the control of voluntary voice production for speech, but not for emotional vocal expressions, would be affected in SD, we identified the two sets of ROIs for analysis. A priori ROIs were defined along the corticobulbar/corticospinal tract (CBT/CST) in the genu and the posterior third quarter of the posterior limb of the internal capsule, the mid-third of the cerebral peduncle and the pyramid. Furthermore, the ROIs were defined in the main input/output structures contributing to the CBT/CST: in the lentiform nucleus, the ventral thalamus and the middle third of the middle cerebellar peduncle. On the other hand, the ROIs in the cingulum underlying the anterior cingulate cortex were chosen to test the hypothesis that changes would not be present in the white matter tracts connecting the brain regions involved in the control of voice initiation and voice expression of emotional states (Jurgens, 2002), which remain unaffected in SD patients.
Prior to ROI analysis, the FA and Trace datasets were anonymized and randomized across the subjects and groups (J.O.). All ROIs were placed by the same rater (K.S.) blind to participants identity and diagnosis using a DTI-MRI atlas of human white matter (Mori, 2005) for determining fibre tract orientation. For each subject, the ROIs were outlined on the colour-coded FA maps in the axial plane as fixed-size squares to avoid arbitrary size of ROIs across participants (25 pixels/ROI along the CBT/CST; 36 pixel/ROI in the lentiform nucleus; 64 pixel/ROI in the thalamus) and then automatically loaded onto the FA and Trace maps (see supplementary Fig. 1 online). All ROIs were visually checked to confirm their location, to ensure that partial volume effects were minimized and that each ROI contained homogeneous fibre populations through examination of slices one dorsal and one caudal from the target. The mean values and standard deviations of FA and Trace measures within each ROI were automatically recorded.
Group differences in fractional anisotropy. (A) TBSS whole-brain and (B) a priori ROI analyses found significant FA decrease in the right genu of the internal capsule in SD patients. Group differences (patients < controls) are overlaid onto the average FA map across all subjects; plane coordinates of axial brain images are in Talairach-Tournoux standard space, respectively; colour bar indicates the significance range at Z > 3.2. Box plots indicate median and upper and lower quartiles. Error bars indicate the range between the 90th and 10th percentiles. Asterisk indicates significant difference between two groups. R = right; L = left.
To control for intra-observer variability, FA and Trace ROI values were re-calculated in six subjects at least 2 weeks apart to assess the percent coefficient of variance as a measure of repeatability.
Regression analyses examined age and gender effects on the FA and Trace values within each group to determine whether these factors needed to be used as covariates in group comparisons (Furutani et al., 2005). Two-way repeated analyses of variance (ANOVA) were used for group (independent) comparisons, including all ROIs (repeated) on the right and left hemispheres (repeated) for both the FA and Trace values. The overall significance level was set at 0.025 (P = 0.05/2) for each of FA and Trace ANOVAs. If the group effects or their interactions on overall ANOVAs were statistically significant at P ≤ 0.025, post hoc univariate F-tests determined which brain regions differed significantly between the groups. Because the Bonferroni correction for multiple comparisons for each of FA and Trace values resulted in an overly conservative correction (P = 0.0016) reducing power on the individual tests and increasing the possibility of a type II error, the statistical significance for post hoc tests was set at P < 0.01. The relationship between the FA and Trace values was assessed using Pearson's correlation coefficients at an alpha level of 0.05.
DTI-guided postmortem brain tissue sampling
To evaluate possible bases for DTI changes in SD, we targeted and sampled postmortem brain tissue in one SD patient and three controls from regions corresponding to FA and Trace changes between SD and HV groups. These matched postmortem tissue samples included regions of the right internal capsule, lentiform nucleus and cerebellum. Postmortem brain tissue from patient's left hemisphere as well as brain tissue from the regions of the sensorimotor cortex, corona radiata, thalamus and cerebral peduncle in the right hemisphere was not available to us for neuropathological examination. Antemortem, the patient (male, 65 years old) diagnosed with ADSD presented with strained voice quality and moderate adductor voice breaks during vowel production. The onset of the disorder was at age 36 years. The patient was diagnosed and treated at the National Institutes of Health with botulinum toxin injections into the thyroarytenoid muscles at regular intervals over 10 years. The brain tissue from this patient was obtained following death, which occurred during cardiac bypass surgery. The control brain tissue was obtained from three subjects (females; age range 58–86 years) without any history of neurological or psychiatric disorders, who died due to cardiovascular disease, disseminated intervascular coagulation, and dehydration with hypernatraemia, respectively.
The brain tissue from all subjects was fixed in 10% formalin solution and sectioned into 2-cm thick coronal slices for gross examination. Guided by the hardcopy of the T1-weighted images in coronal plane with overlaid FA and Trace group differences, tissue samples were dissected from the right genu and posterior limb of the internal capsule, the lentiform nucleus and the cerebellum for paraffin embedding. For histopathological examination, paraffin sections (thickness 5 µm) were stained with hematoxylin and eosin (H&E) and luxol-fast blue/periodic acid Schiff (LFB/PAS) to assess cell morphology and myelin changes. The immunohistochemical markers, KP1 (anti-CD68) and anti-neurofilament triplet protein (anti-NFTP), were used for visualization of microglia/macrophage activation and the intermediate filament proteins of neuronal differentiation, respectively. In brief, sections were pre-treated with DAKO Target Retrieval Solution (DakoCytomation, Carpinteria, CA) at 95°C for 20 min, cooled at room temperature and incubated with primary antibody at dilution of 1 : 100 for 30 min (monoclonal mouse anti-human CD68, Clone KP1; monoclonal mouse anti-human neurofilament protein, Clone 2F11; DakoCytomation, Denmark). Primary antibodies were omitted for negative controls. The sections were then incubated with a refined avidin-biotin visualization kit (LSAB+ System-HRP, DakoCytomation, Carpinteria, CA) for 1 h.
For evaluation of Trace differences between SD and HV groups, subsequent sections from the internal capsule, lentiform nucleus and cerebellum were additionally processed with alizarin red S stain for visualization of calcium deposition, with von Kossa stain for phosphates and other anions, and with Prussian blue stain for iron accumulations, respectively. Furthermore, infrared spectroscopy was performed for routine molecular characterization of tissue depositions. Infrared spectra were obtained by focusing the infrared light onto tissue sections mounted on aluminium-coated glass slides (ThermoNicolet, Madison, WI). Spectra were recorded at 4 cm−1 spectral resolution. The measured infrared spectra were compared with those of the authentic samples and to spectra stored in a digital spectral library. To obtain the broader spectrum of elemental compositions of depositions found on H&E sections, a scanning electron microscope (Hitachi Instruments, Inc., San Jose, CA) with energy dispersive X-ray analysis (ThermoNoran, Madison, WI) (SEM-EDXA) was used to determine the particles with atomic numbers as low as that of beryllium. However, because of the difficulties in co-localization of the clusters on unstained section using SEM-EDXA, the analysis was limited to the parenchymal clusters located closely to the identifiable vessels in an unstained tissue sample. The EDXA detected the X-rays produced by the elements in the tissue samples when exposed to a 20 kV electron beam. X-rays were directed to the liquid-nitrogen-cooled silicon detector fitted with a Norvar® window.
Conventional MRI was normal without any structural differences between patients and controls based on radiological evaluation. The inter-session variability results showed good reproducibility for both FA (CV of 4%) and Trace (CV of 2.1%). The intra-observer variability results also showed good reproducibility for both FA (CV of 2.30%) and Trace (CV of 0.53%). No significant relationships were found in either group between the diffusion parameters and age (FA: rSD = 0.088, PSD = 0.713; rcontrol = 0.300, Pcontrol = 0.199; Trace: rSD = 0.141, PSD = 0.552; rcontrol = 0.282, Pcontrol = 0.228) or gender (FA: rSD = 0.133, PSD = 0.577; rcontrol = 0.084, Pcontrol = 0.725; Trace: rSD = 0.208, PSD = 0.379; rcontrol = 0.137, Pcontrol = 0.564). Therefore, group comparisons were conducted without covariates.
The TBSS whole-brain analysis showed decreased FA only in the right genu of the internal capsule in SD patients compared with HV (Fig. 1A). The ANOVA comparison of ROI FA values did not demonstrate significant overall group differences (F1,38 = 0.057, P = 0.812), but determined significant ROI effect (F7,266 = 584.525, P = 0.0005) and group by ROI interaction (F7,32 = 2.727, P = 0.024) as well as a trend for a group by hemispheric laterality interaction (F1,38 = 4.201, P = 0.047). Significant regional differences between the two groups were again found in the right genu of the internal capsule (F1,38 = 9.494, P = 0.004) (Fig. 1B).
Trace (D) diffusivity
The TBSS whole-brain group comparison found increased Trace values in the corona radiata, the genu and posterior third quarter of the internal capsule, the middle third of cerebral peduncle, the cerebellar white and grey matter, and the ventral thalamus bilaterally in SD patients (Fig. 2A). The ANOVA overall group effect for the ROI analysis of Trace measures was significant (F1,38 = 10.161, P = 0.003) with non-significant group by ROI (F7,32 = 1.433, P = 0.227) or group by hemispheric laterality (F1,38 = 1.812, P = 0.186) interactions. Because of the lack of hemispheric differences, the right and left ROIs for Trace values were combined for univariate comparisons. Regional differences in Trace were found in the genu (F1,38 = 10.601, P = 0.002) and the posterior limb of the internal capsule (F1,38 = 7.743, P = 0.008), the lentiform nucleus (F1,38 = 9.360, P = 0.004) and the ventral thalamus (F1,38 = 8.959, P = 0.005). A group trend was found in the middle cerebellar peduncle (F1,38 = 6.156, P = 0.018) (Fig. 2B). Mean and standard deviation of FA and Trace values in SD patients and healthy controls are reported in Table 1.
Group differences in Trace (D). (A) TBSS whole-brain analysis found significant increase of overall diffusivity in the corona radiata, genu and posterior limb of the internal capsule, cerebral peduncle, ventral thalamus, and cerebellum. Group differences (patients > control) are overlaid onto the average FA map across all subjects; plane coordinates of axial brain images are in Talairach-Tournoux standard space, respectively; colour bar indicates the significance range at Z > 3.2. (B) A priori ROI analysis found significant increase of Trace values (×10−3 mm2/s) in the genu (GIC) and posterior limb (PLIC) of the internal capsule, lentiform nucleus (LN), and ventral thalamus (VTh) with a trend in the middle cerebellar peduncle (MCP) in SD patients. Box plots indicate median and upper and lower quartiles. Error bars indicate the range between the 90th and 10th percentiles. Asterisks indicate significant difference between two groups. R = right; L = left.
DTI-derived measures in healthy controls and SD patients based on ROI analysis
Trace (D) (×10−3 mm2/s)
Genu of internal capsule
0.61 ± 0.07
0.55 ± 0.05a
2.10 ± 0.20
2.22 ± 0.14a
0.65 ± 0.05
0.63 ± 0.07
2.14 ± 0.17
2.34 ± 0.18a
Posterior limb of internal capsule
0.69 ± 0.05
0.70 ± 0.03
1.99 ± 0.15
2.11 ± 0.11a
0.69 ± 0.04
0.70 ± 0.04
2.03 ± 0.15
2.12 ± 0.11a
0.74 ± 0.04
0.74 ± 0.05
2.14 ± 0.15
2.17 ± 0.14
0.76 ± 0.05
0.76 ± 0.05
2.09 ± 0.17
2.17 ± 0.21
0.51 ± 0.08
0.52 ± 0.05
2.06 ± 0.18
2.15 ± 0.21
0.51 ± 0.08
0.54 ± 0.07
2.09 ± 0.19
2.13 ± 0.14
Middle cerebellar peduncle
0.66 ± 0.05
0.66 ± 0.11
1.94 ± 0.11
2.04 ± 0.10
0.62 ± 0.06
0.62 ± 0.08
1.94 ± 0.11
1.97 ± 0.08
0.19 ± 0.03
0.19 ± 0.07
2.11 ± 0.18
2.41 ± 0.21a
0.15 ± 0.03
0.15 ± 0.04
2.17 ± 0.17
2.32 ± 0.11a
0.28 ± 0.05
0.26 ± 0.03
2.04 ± 0.31
2.19 ± 0.19a
0.31 ± 0.04
0.29 ± 0.05
2.10 ± 0.15
2.20 ± 0.27a
0.46 ± 0.09
0.49 ± 0.07
2.20 ± 0.30
2.26 ± 0.21
0.52 ± 0.11
0.53 ± 0.08
2.30 ± 0.25
2.41 ± 0.21
Values report mean ± standard deviation. (a) indicates brain regions significantly different between patients and controls (P ≤ 0.01). R = right, L = left.
Correlations between diffusion parameters and clinical scores
In all ROIs taken together, the mean FA and Trace values had significant inverse correlation, which was greater in SD patients (r = −0.737, P = 0.0005) than in HVs (r = −0.465, P = 0.039) (Fig. 3A). When the relationship between FA and Trace was examined in the regions that differed between the two groups, a significant inverse correlation was observed in the genu of the internal capsule in the patients (r = −0.639, P = 0.002), which was greater than the correlation in the HVs (r = −0.454, P = 0.044) (Fig. 3B).
Correlation between diffusion parameters. (A) Significant inverse correlation between overall mean values of fractional anisotropy (FA) and Trace (D) was stronger in SD patients than in HV. (B) Significant inverse correlation between the FA and Trace values were found in the genu of the internal capsule. (C) Positive significant correlation was determined between the Trace values in the ventral thalamus (VTh) and number of breaks in SD patients.
The FA and Trace measures in the regions that differed between the two groups (FA in the right genu and Trace in the genu and posterior limb of the internal capsule, the lentiform nucleus and the ventral thalamus) were also examined for their relationships with numbers of voice breaks in sentences and duration of disorder in SD patients. We found positive correlation between the Trace values in the ventral thalamus and number of breaks during speech production (r = 0.509, P = 0.037) in SD patients (Fig. 3C).
No gross abnormalities were found in either the patient or the control brains. Histopathological analysis of the genu of the right internal capsule revealed reduced white matter density due to moderate reduction of myelin content surrounded by scattered microglial/macrophage activation in the SD patient. Moderate focal reduction of axonal density was observed in the same locus in the SD patient (Fig. 4). No such changes were found in the tissue sampled from the anterior and posterior limbs of the internal capsule in either a patient or controls.
DTI-guided postmortem neuropathological examination of FA changes in the genu of the internal capsule. (A) An example of T1-weighted image in coronal plane with overlaid FA group differences (left) and visually matched postmortem coronal brain slice (right). The black box indicates the region of tissue extraction from the postmortem specimen. (B) Photomicrograph of the control sample shows well-organized white matter in the genu of the internal capsule (GIC) and (C) reduced white matter density (*) in the GIC in an SD patient (H&E stain). Area of reduced white matter density in the GIC reveals (D) reduction of myelin content (LFB/PAS stain), (E) diffusely scattered reactive microglial/macrophage cells (KP1 stain) and (F) moderate reduction of axonal density (anti-NFTP stain).
Neuropathological examination of the H&E sections, where Trace differences were found, identified clusters of dark-blue/black basophilic precipitates in the parenchyma and small-caliber vessels in the putamen, globus pallidus and the posterior limb of the internal capsule in the SD patient compared to controls (Fig. 5A–C). In the patient's cerebellum, small areas of basophilic deposits were distributed in the cortex and white matter. No axonal loss or demyelination was found in either of these brain regions. Histochemical stains of the brain sections from the putamen, globus pallidus and cerebellum with adjacent white matter demonstrated that the parenchymal clusters were selectively positive for calcium and phosphate with single scattered iron deposits. Depositions in the vessel wall were stronger positive for iron in addition to calcium and phosphorus (Fig. 5D and F). None of these changes was found in controls.
DTI-guided postmortem neuropathological examination of Trace (D) changes in an SD patient. Photomicrographs of the mineral depositions (dark-blue/black visualization product) in the parenchyma of the putamen (A) and globus pallidus (B) and in the vessel wall in the posterior limb of the internal capsule (C) (H&E stain). An example from putaminal tissue shows accumulations of phosphorus (von Kossa stain) (D) and calcium (alizarin red S stain) (E) in the parenchyma and deposition of iron in the vessel wall (Prussian blue stain) (F) with scattered single iron-positive cells in the parenchyma (arrowheads).
By infrared spectroscopy, spectra characteristic of phosphate were obtained from both the parenchymal and vessel wall deposits in the putamen, globus pallidus, internal capsule and cerebellum of the patient's tissue. The phosphate spectra most closely resembled the authentic infrared spectrum of apatite. SEM-EDXA of the representative deposition in the parenchyma demonstrated focal collocation of phosphorus and calcium in SD brain (Fig. 6A). This calcium phosphate was present admixed with protein, probably representing degenerated tissue protein. In the vessel wall, the SEM-EDXA map showed presence of iron in addition to calcium and phosphorus (Fig. 6B).
Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDXA) of tissue depositions in an SD patient. (A) Photomicrograph of the deposition (*) in the putaminal parenchyma on H&E stain (I) and SEM (II) (scale 100 μm). EDXA shows accumulation of phosphorus (P) and calcium (Ca). (B) Vessel wall deposition in the putamen (*) shown on H&E stain (I) and SEM (II) (scale 50 μm). EDXA detected collocation of phosphorus (P), calcium (Ca), and iron (Fe).
In this study, we combined, for the first time to our knowledge, the neuroimaging and neuropathological approaches to examine the structural brain organization in patients with SD. Using DTI, we identified white matter changes along the CBT/CST and in the brain regions directly or indirectly contributing to this tract in SD patients. Consequently, we substantiated these findings with postmortem histopathological abnormalities presented as a focal reduction of axonal density and myelin content in the genu of the internal capsule and clusters of mineral accumulations in the parenchyma and vessel walls in the internal capsule, putamen, globus pallidus and cerebellum in SD. We also identified a significant statistical relationship between disorder symptom severity and the brain water diffusivity changes in SD. The brain abnormalities in SD found here could, therefore, be considered as primary brain changes contributing to the pathophysiology of this disorder.
Significant microstructural abnormalities were found in the CBT/CST in SD patients compared with controls. We suggest that SD may be associated with alterations in anatomical connectivity of the corticobulbar tract (CBT) descending from the laryngeal/orofacial motor cortex to the brainstem phonatory nuclei (Kuypers, 1958; Iwatsubo et al., 1990). The CBT descends together with the CST via the corona radiata, internal capsule, cerebral peduncle and pyramids to subcortical structures, including the striatum, thalamus, midbrain and brainstem nuclei (Ross, 1980; Manelfe et al., 1981; Tredici et al., 1982; Davidoff, 1990). In the internal capsule, the CBT and CST fibres are organized somatotopically with the CBT of head and neck representation occupying the genu and the CST of hand and foot representation traversing the posterior third quarter of the posterior limb (Tredici et al., 1982; Bogousslavsky and Regli, 1990; Aoki et al., 2005; Holodny et al., 2005). Focal ischaemic lesions in the genu of the internal capsule have been reported to cause orofacial and laryngeal paresis in stroke patients due to massive disruption of the corticobulbar tract (Manelfe et al., 1981; Soisson et al., 1982; Tredici et al., 1982; Bogousslavsky and Regli, 1990). The microstructural abnormalities in the internal capsule in SD patients reported here are relatively subtle and confined, suggesting the presence of the different pathological process.
The most specific disorganization of CBT/CST in SD was found in the genu of the internal capsule demonstrating right-localized anisotropy decrease, bilateral diffusivity increase and white matter thinning. Although the precise neural correlates of altered anisotropy and diffusivity are not well understood, these measures are thought to be linked to the quality and density of axonal tracts in the brain (Horsfield and Jones, 2002; Le Bihan and van Zijl, 2002). This was confirmed by our postmortem findings in an SD patient, which demonstrated reduced axonal course and myelin content in the right genu of the internal capsule, where DTI changes were identified in a larger group of living SD patients. The observed increase in microglial activation in the region of these focal changes may suggest that axonal degeneration could be secondary to a slow demyelination process in this region. Alternatively, the loss of myelin could be secondary to a cell loss within the laryngeal motor cortex and concomitant axonal degeneration. A limitation of this study is the unavailability of the patient's postmortem tissue from the laryngeal/orofacial sensorimotor cortex, which rendered us unable to further examine the possible motor cortical involvement that may have been related to white matter changes in the genu of the internal capsule in SD. Detailed interpretation of these findings will require future access to the postmortem tissue from the laryngeal motor cortex and internal capsule of both hemispheres for stereological analyses of cortical neuron distribution and axonal density, respectively, in SD patients compared to controls.
Although the DTI study found a highly significant right-lateralized FA abnormalities in SD patients compared to controls, these results were rather unexpected in a disorder, which is task-specific to speech production, usually dominant to the left hemisphere (Binder et al., 1995; Desmond et al., 1995; Bookheimer et al., 1997; Price, 2000; Vernooij et al., 2007). However, our finding is in line with a recent fMRI study in patients with ADSD, which has reported symptom-specific functional activation changes localized to the right ventral sensorimotor region during voluntary voice production (Haslinger et al., 2005).
Increased diffusivity along the CBT/CST is thought to reflect changes in relative intracellular/extracellular volumes or net loss of structural barriers of diffusion due to cell loss and impaired connectivity within the white matter (Pierpaoli et al., 1996; Gass et al., 2001; Kantarci et al., 2001; Beaulieu, 2002; Sykova, 2004). Mineral accumulations in the internal capsule of the SD patient found in this study may contribute to water diffusivity changes. Mineral depositions were not observed in our control brain tissue samples, therefore, these abnormalities in the patient's brain may be due to a primary neurological process or a generalized metabolic disorder associated with a disruption in the blood-brain barrier (Casanova and Araque, 2003).
DTI measures were not significantly different between the SD and HV groups in the region of cingulum underlying the anterior cingulate cortex (ACC). The ACC controls voluntary voice initiation and vocal expression of emotional states (Jurgens and von Cramon, 1982; Jurgens, 2002). Although the ACC is reciprocally connected with the laryngeal motor cortex (Simonyan and Jurgens, 2002, 2005), absence of microstructural differences in the white matter underlying the ACC demonstrates a separation of the affected voluntary vocal motor control from unaffected voluntary vocal emotional control in SD patients.
Our study points to the selective abnormalities affecting the voluntary vocal motor control pathway with the abnormalities in the genu of the internal capsule appearing as the most specific disorder-related finding in SD.
Basal ganglia and thalamus
The link between dystonia and basal ganglia dysfunction has been apparent (Berardelli et al., 1998; Hallett, 1998). Basal ganglia balance excitation and inhibition of the thalamo-cortical circuit involved in motor execution. This balance is thought to be altered in task-specific dystonias due to reduced GABAergic metabolism (Levy and Hallett, 2002) and dopaminergic receptor binding (Perlmutter et al., 1997), leading to excessive motor cortical excitation (Hallett, 1998). In a review of 240 cases of lesions in basal ganglia from various causes, Bhatia and Marsden found secondary dystonia to be the most common symptom, occurring in 36% of lesions (Bhatia and Marsden, 1994). Most of these small lesions were located in the lentiform nucleus, particularly in the putamen. Recent neuroimaging studies in other forms of primary dystonia have confirmed the presence of functional and structural changes in the basal ganglia (Black et al., 1998; Eidelberg, 1998; Meunier et al., 2003; Colosimo et al., 2005; Blood et al., 2006; Bonilha et al., 2007).
In this study, diffusivity changes and correlated histopathological abnormalities presented as mineral accumulations of calcium, phosphorus and iron in the parenchyma and vessels of the putamen and globus pallidus were found in SD patients. Equilibrium of calcium and iron distribution is of biological importance for electron exchange and oxidation–reduction reactions. Increases in calcium and iron levels enhance lipid peroxidation and, therefore, can mediate cell membrane damage and degeneration (Casanova and Araque, 2003). Excitotoxic effect of calcium accumulation has been reported in a wide variety of neurological diseases (Casanova and Araque, 2003), including a family with autosomal dominant dystonia-plus syndrome (Wszolek et al., 2006). Iron-induced oxidative processes have been shown to reduce GABAergic inhibition (Zhang et al., 1989) and cause degeneration of the dopaminergic neurons (Sastry and Arendash, 1995). Mineral accumulation in the putamen and globus pallidus found here in SD, therefore, likely underlie the abnormal metabolic processes within the basal ganglia-thalamo-cortical circuitry in SD. Future studies will need to elucidate the relationship between the neurotransmitter and mineral levels in SD and other forms of dystonia. Together with common findings of neuroimaging changes in the basal ganglia and thalamus in other forms of dystonia (Black et al., 1998; Carbon et al., 2004; Colosimo et al., 2005; Blood et al., 2006; Bonilha et al., 2007), our finding of specific histopathological abnormalities in SD underlines a critical involvement of these brain regions in the pathophysiology of primary dystonias (Hallett, 2004).
We found increased diffusivity in the middle cerebellar peduncle and the deep cerebellar white and grey matter in the patient group, associated with mineral accumulations found in our single SD patient. The cerebellum is involved in the motor control via the ventrolateral thalamus and has a modulatory role in coordination of voice and speech production (Arbib, 1981; Wildgruber et al., 2001; Guenther et al., 2006). Cerebellar dysfunction (Galardi et al., 1996; Ceballos-Baumann et al., 1997; Eidelberg, 1998; Odergren et al., 1998; Hutchinson et al., 2000; Preibisch et al., 2001; Ali et al., 2006) and atrophy (Fletcher et al., 1988; Le Ber et al., 2006) have been reported in a heterogeneous group of patients with dystonia suggesting that this disorder may arise from cerebellar disorganization. This has been supported by studies in rodent models of dystonia showing that primarily cerebellar dysfunction can cause dystonia (Brown and Lorden, 1989; Campbell and Hess, 1998; Richter et al., 1998; Pizoli et al., 2002; Jinnah and Hess, 2006), while cerebellectomy and selective destruction of Purkinje cells can eliminate dystonic symptoms (LeDoux et al., 1993; Campbell et al., 1999). Microstructural abnormalities in the cerebellum and ventral thalamus found in the present study may possibly weaken the cerebello-thalamo-cortical modulatory input in SD and, therefore, play a role in the pathophysiology of dystonia.
Measures of water diffusivity were positively correlated with the clinical symptoms of SD, e.g. with the number of voice breaks in sentences. These results together with postmortem findings of focal abnormalities in an SD patient treated with botulinum toxin over 10 years until death suggest that microstructural changes may represent primary brain changes contributing to the pathophysiology of this disorder. Discrepancies between our results and recent DTI findings in four patients with cervical dystonia reporting reversal of white matter changes after botulinum toxin treatment (Blood et al., 2006) may be explained by a larger sample size and more detailed evaluation of the white matter organization in the present study.
It is notable that our study included patients with adductor and abductor SD. Although symptoms of these two types of SD differ, both are characterized by the loss of the voluntary control of voice production. This learned behaviour in humans, involving both voluntary adductor and abductor laryngeal movements for speech production, is under control of the laryngeal motor cortex with direct input to the nucleus ambiguus and reticular formation of the brainstem via the CBT (Kuypers, 1958; Jurgens and Ehrenreich, 2007). Therefore, it is unlikely that the differential changes would be found in the white matter tracts between the patients with adductor and abductor SD.
The present study is among the first detailed investigations of the neuropathological basis of SD. Our findings suggest that altered microstructural integrity of the CBT/CST may represent primary neurological changes in SD. Focal microstructural changes along the CBT/CST as well as in the regions directly or indirectly contributing to the CBT/CST are likely to alter the communication between cortical and subcortical brain regions that are essential for voluntary voice control for speech production (Fig. 7). A slow progressive neurodegenerative or metabolic processes in these brain regions may underlie the abnormalities in the microstructural brain organization and, therefore, contribute to the pathophysiology of this disorder. White matter abnormalities in the genu of the internal capsule, where head and neck muscles are represented, are the most specific disorder-related findings in SD. On the other hand, DTI changes in the basal ganglia, thalamus and cerebellum in SD represent a common neuroimaging finding in patients with primary dystonias. We substantiated these neuroimaging findings with specific histopathological abnormalities presented as clusters of mineral accumulations in these brain regions in SD, which may contribute to a common neuropathological process in the focal dystonias.
Simplified schematic illustration of the neural network of voluntary laryngeal control in humans. Direct projections from the laryngeal motor cortex (LM1) to the phonatory motor nuclei (nucleus ambiguus, NA) descend via the corticobulbar/corticospinal tract (CBT/CST). Several connections exist between the LM1 and the subcortical motor system. The putamen (Put) receives input from the LM1 and projects back to the LM1 via the globus pallidus (Gp) and ventral lateral thalamus (VTh) forming striato-pallido-thalamo-cortical loop. Cerebellar motor input (Cbl) to the LM1 is via the VTh. Microstructural changes along the CBT/CST as well as in the regions directly or indirectly contributing to the CBT/CST found in this study (dashed areas) may affect voluntary laryngeal control in patients with SD.
Supplementary material is available at Brain online.
We thank Drs Susumu Mori and Xin Li for software support, Drs Noriaki Hattori and S. Lalith Talagala for image acquisition support, Dr Carlo Pierpaoli for advice in data analysis, Dr Pamela R. Kearney for participants’ clinical screening, Sandra B. Martin for assistance with patient recruitment and Kimberly Finnegan for rating the voice and speech samples. We are grateful to Viktoria Baker, Laboratory of Pathology, NCI, for histology preparations, and to Dr Mark Raffeld and Cynthia Harris, Molecular Pathology Section, NCI, for immunohistochemistry preparations. Tissue specimens were obtained from the NICHD Brain and Tissue Bank for Developmental Disorders at University of Maryland, Baltimore, MD and from the Human Brain and Spinal Fluid Resource Center, VAMC, Los Angeles, CA, sponsored by NINDS/NIMH, National Multiple Sclerosis Society, VA Greater Los Angeles Healthcare System and Veterans Health Services and Research Administration, Department of Veterans Affairs. This work was supported by the Intramural Program of the National Institute of Neurological Disorders and Stroke.
abductor spasmodic dysphonia
adductor spasmodic dysphonia
coefficient of variance
diffusion tensor imaging
region of interest
scanning electron microscopy with energy dispersive X-ray analysis
tract-based spatial statistics
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447-459DOI: http://dx.doi.org/10.1093/brain/awm303First published online: 14 December 2007 (13 pages)