Structural Brain Changes in Blepharospasm: A Cortical Thickness and Diffusion Tensor Imaging Study

Abstract

White matter abnormalities in blepharospasm (BSP) have been evaluated using conventional intra-voxel metrics, and changes in patterns of cortical thickness in BSP remain controversial. We aimed to determine whether local diffusion homogeneity, an inter-voxel diffusivity metric, could be valuable in detecting white matter abnormalities for BSP; whether these changes are related to disease features; and whether cortical thickness changes occur in BSP patients. Diffusion tensor and structural magnetic resonance imaging were collected for 29 patients with BSP and 30 healthy controls. Intergroup diffusion differences were compared using tract-based spatial statistics analysis and measures of cortical thickness were obtained. The relationship among cortical thickness, diffusion metric in significantly different regions, and behavioral measures were further assessed. There were no significant differences in cortical thickness and fractional anisotropy between the groups. Local diffusion homogeneity was higher in BSP patients than controls, primarily in the left superior longitudinal fasciculus, corpus callosum, left posterior corona radiata, and left posterior thalamic radiata (P < 0.05, family-wise error corrected). The local diffusion homogeneity values in these regions were positively correlated with the Jankovic rating scale (r s = 0.416, P = 0.031) and BSP disability index (r s = 0.453, P = 0.018) in BSP patients. These results suggest that intra-and inter-voxel diffusive parameters are differentially sensitive to detecting BSP-related white matter abnormalities and that local diffusion homogeneity might be useful in assessing disability in BSP patients.

Topological Alterations in White Matter Structural Networks in Blepharospasm

“…However, we did not find any significant differences in brain WM network measures at both global ( E glob , L p , and modularity) and regional ( E nodal ) levels between BSP and HFS patients, suggesting that abnormal topological organization in BSP may be correlated with excessive facial motor activity. We postulated that facial hyperkinesia‐related brain network alterations in these patients might be due to the increase in facial activity and secondary plastic changes in the brain WM; this hypothesis is supported by a prior study showing the presence of plastic changes in multiple WM tracts that mainly connect the cortices, basal ganglia, thalamus, and brainstem in patients with BSP 16 . Unfortunately, we did not find any correlations between global and regional properties and the severity/duration of BSP and HFS.…”

“…Ramdhani and colleagues found that gray matter changes were accompanied by more widely observed WM abnormalities in patients with nontask‐specific dystonia (BSP and cervical dystonia) than in those with task‐specific dystonia (writer's cramp and laryngeal dystonia), which are located mainly in the corpus callosum, anterior limb/genu of the internal capsule, brainstem, cerebellum, thalamus, WM of the middle/inferior frontal gyrus, primary sensorimotor cortex, and inferior temporal gyrus 15 . A prior diffusion tensor imaging (DTI) study revealed the presence of abnormalities in multiple WM tracts that mainly connect the cortices, basal ganglia, thalamus, and brainstem in patients with BSP 16 . However, studies addressing overall changes in WM structural networks in BSP, rather than those observed in specific anatomical regions, are lacking.…”

Machine Learning for Predicting Individual Severity of Blepharospasm Using Diffusion Tensor Imaging

“…Nevertheless, a recent DTI study based on 31 BSP patients revealed significant fractional anisotropy (FA) decreases in the white matter of the left anterior lobe of the cerebellum, which was significantly correlated with disease severity (Yang et al, 2014). In addition, our previous study also found widespread white matter abnormalities evaluated by local diffusion homogeneity (LDH) in 29 patients with BSP, which was also significantly correlated with disease severity (Guo et al, 2020). FA, which is one of the most commonly used DTI indexes, quantifies the degree of anisotropy characterized by the random motion of water molecules preferentially directed along the axis of the major axonal pathway, which only reflects diffusion properties within the voxel (Melhem et al, 2002).…”

“…We employed the DTI pipeline software PANDA (Pipeline for Analyzing Brain Diffusion Images) 1 to perform DTI data preprocessing ( Cui et al, 2013 ). More detailed information about the DTI data preprocessing can be found in our previous studies ( Liu et al, 2017 ; Guo et al, 2020 ). A total of 68 white matter regions were extracted from the ICBM-DTI-81 white-matter labels atlas (rICBM_DTI_81_WMPM_90p_FMRIB58; Oishi et al, 2008 ) and then we calculated the averaged FA and LDH values of each region using the normalized diffusion parameter maps.…”

“…LDH quantifies the overall similarity of water molecules diffusion profiles between voxels and their adjacent voxels, which is considered to reflect the local consistency of fiber orientation, density, diameter, or myelination of white matter ( Gong, 2013 ). In general, a higher FA or LDH value represents the microstructural reorganization of brain white matter, and reduced FA or LDH indicates the microstructural disruption of neural fibers ( Tang et al, 2012 ; Liu et al, 2017 ; Guo et al, 2020 ). These studies suggest that DTI has the potential to evaluate the individual severity of BSP, but the specific DTI markers for identifying the individual severity of BSP remain unknown.…”