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Diffusion magnetic resonance imaging in genetic and idiopathic dystonias1Cardiff University Brain Imaging Centre, Cardiff University, Cardiff, United Kingdom, 2Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom, 3Image Sciences Institute, University Medical Centre Utrecht, Utrecht, Netherlands
Synopsis
Dystonia is a hyperkinetic movement disorder involving repetitive or sustained muscle contractions. Its pathophysiology is poorly understood, limiting therapeutic advancement. A systematic literature review on diffusion MRI in dystonia was performed to gain insight into microstructural white matter changes that may contribute to pathology. Of 403 identified records, 40 met the criteria for inclusion. The most consistent diffusion abnormalities for both genetic and idiopathic dystonia forms were lower FA values or reduced number of tractography streamlines in regions connecting brainstem, cerebellum, basal ganglia and sensorimotor cortex, with some genotype and phenotype specific differences identified.
Introduction
Dystonia is a movement disorder involving repetitive or sustained muscle contractions, affecting up to 120/100,000 population. It causes abnormal posturing, pain and disability, potentially impacting education and employment. There are both Mendelian inherited and idiopathic forms, and single or multiple muscle groups can be affected. Pharmacological treatments have limited efficacy; with injectable neurotoxin for focal/segmental forms and Deep Brain Stimulation (DBS) for more generalised forms. Research to date has demonstrated no macroscopic neuroimaging changes in dystonia, but multimodal imaging implicates the brain motor circuitry, in particular the sensorimotor cortex, basal ganglia and cerebellum, further reinforced by microscopic morphological differences in the same regions in animal model and histopathological studies (figure 1). Here, we systematically review the diffusion MR literature in dystonia, assessing methodological limitations in addition to highlighting consistent findings which may implicate microstructural morphological changes, important in dystonia pathogenesis.Methods
Embase and PubMed databases were searched up to October 2021 for search terms relating to Diffusion MRI and dystonia, including terms for different dystonia phenotypes and known mendelian inherited genetic forms of dystonia. The search terms used, as well as inclusion and exclusion criteria, are shown in figure 2. Of 403 identified records, 40 studies met the criteria for inclusion.Results
Of the 40 studies included (figure 3), all were performed at either 1.5T (n=7)1-7 or 3T (n=33)8-40. The number of diffusion gradient directions ranged from 6 (n=5)1-5, 15-29 (n=4), 30-59 (n=15) and ≥60 (n=13), and were not reported in one study7. B-values used ranged from 700-1000s/mm2 in all but one study, which had a b-value of 1500s/mm2. No studies used multiple b-values. Only 14 of the studies used isotropic or close to isotropic voxels (slice thickness <1.1x in-plane resolution). In-plane voxel dimensions were ≤2mm in all but 3 studies3,12,20, and slice thickness ranged from <2mm (n=15), 2 to ≤5mm (n=19) and 5mm (n=4)1,2,4,5. Preprocessing was generally limited to motion and eddy current correction, with 4 additionally undertaking susceptibility distortion correction. All studies used DTI (diffusion tensor imaging), with only two stating the estimation strategy (both non-linear estimation)17,18; most other studies used software that by default employ an ordinary linear least squares approach.DTI analysis methods involved a targeted region-based approach (n=14), whole brain/white matter approach (n=11) or a combination (n=15, with n=5 using whole brain approach to define ROIs1-3,11,22). These studies analysed DTI measures within an ROI (n= 15), performed tractography (n=18), undertook voxel-by-voxel based analysis (n=11) or performed TBSS (n=13). One study additionally assessed local diffusion homogeneity27, and two used a graph theory approach29,34. Multiple comparison correction involved Bonferroni correction (n=8), false discovery rate correction (n=7), family wise error rate correction (n=8) and correction at the cluster level (with a cluster extent threshold and p<0.025-0.001 n=8, threshold free cluster enhancement n=5). In 9 studies the approach was either not stated (n=1)13 or there was no correction undertaken (n=8)4,5,17,22,23,26,27,36. Cohort sizes varied from ≤10 (n=8)8,10,12,17,20,35,36,39, 10-20 (n=14)1,2,4,6,13-16,18,23,26,30,31,38, 20-30 (n=7)3,7,11,21,27,33,40 and >30 (n=11)5,9,19,22,24,25,28,29,32,34,37. All groups were compared to an age and gender matched control cohort, one which used a disease control rather than healthy control cohort.
Across the genetically homogenous cohorts, key findings included lower FA values and number of tractography streamlines in sensorimotor cortex subgyral white matter, cerebellar outflow tracts, brainstem and tracts between basal ganglia and cortex2,8,10,15,35,36, with some intermediate changes in non-manifesting gene carriers (THAP1 mutations)1,31. Amongst idiopathic cohorts, lower FA values and tractography streamline counts were also observed, most commonly in basal ganglia-cortical pathways and cerebellar regions5-7,12,16,18-20,23-26,37,40; although a number of studies reported higher FA values in regions including the internal capsule, thalamic regions, brainstem and supplementary motor cortex3,4,7,21,24,25,38. Mixed genetic and idiopathic studies (n=6)9,11,30,32-34 have indicated genotype specific differences with lower tractography streamline counts in genetic dystonias, and phenotypic specific differences related to the sensorimotor subcortical white matter.
Discussion
Overall, diffusion imaging findings across genetic and idiopathic forms of dystonia consistently include microstructural changes in pathways between the cerebellum, brainstem, basal ganglia and sensorimotor cortex regions (figure 4), although these represent biologically non-specific measures (figure 5). We identified substantial methodological variability across the studies, with many using large voxels, increasing potential for partial volume effects. A number of potential artefact sources were not accounted for, such as signal drift, Gibbs ringing, Rician noise bias, thermal noise, gradient deviations, b1 bias, Nyquist ghosts and outliers. The ordinary linear least squares approach to diffusion tensor estimation is a routinely used approach, although weighted linear least square or non-linear approaches, especially with a noise estimate included, can improve tensor estimation accuracy and precision. Some studies undertook no multiple comparison correction, heightening the risk of false positive results. Cohort sizes were often fairly limited, and whilst well matched for age and gender, there was little matching for non-motor symptoms such as anxiety and OCD traits which are associated with dystonic disorders.Conclusion
The white matter pathways involved in the motor networks show abnormalities in genetic and idiopathic dystonias compared to controls, with some evidence of genotypic and phenotypic specific differences. Our review demonstrates that there is substantial scope for use of more advanced imaging approaches in future studies.Acknowledgements
No acknowledgement found.References
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Figures
Figure 3: Clinical characteristics and results of studies. Sorted by dystonia type. ROI= region of interest; MC= manifesting carrier; NMC= non-manifesting carrier; WM= white matter; FA= fractional anisotropy; RadD= radial diffusivity; AxD= axial diffusivity; MD= mean diffusivity; (L)= left; (R)= right; BSM= blepharospasm; OMD= oromandibular dystonia; CD= cervical dystonia; HC= healthy control; Add= adductor form; Abd= abductor form
