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Abstract
Background and Objectives Brain lesions are a well-recognized etiology of dystonia. These cases are especially valuable because they offer causal insight into the neuroanatomical substrates of dystonia. To date, knowledge of lesion-induced dystonia comes mainly from isolated case reports or small case series, restricting broader description and analysis.
Methods Cases of lesion-induced dystonia were first identified from a systematic review of published literature. Latent class analysis then investigated whether patients could be classified into subgroups based on lesion location and body regions affected by dystonia. Regression analyses subsequently investigated whether subgroup membership predicted clinical characteristics of dystonia.
Results Three hundred fifty-nine published cases were included. Lesions causing dystonia occurred in heterogeneous locations, most commonly in the basal ganglia (46.2%), followed by the thalamus (28.1%), brainstem (22.6%), and white matter (21.2%). The most common form of lesion-induced dystonia was focal dystonia (53.2%), with the hand (49.9%) and arm (44.3%) most commonly affected. Of all cases, 86.6% reported co-occurring neurologic manifestations and 26.1% reported other movement disorders. Latent class analysis identified 3 distinct subgroups of patients: those with predominantly limb dystonias, which were associated with basal ganglia lesions; those with hand dystonia, associated with thalamic lesions; and those with predominantly cervical dystonia, associated with brainstem and cerebellar lesions. Regression demonstrated significant differences between these subgroups on a range of dystonia symptoms, including dystonic tremor, symptom latency, other movement disorders, and dystonia variability.
Discussion Although dystonia can be induced by lesions to numerous brain regions, there are distinct relationships between lesion locations and dystonic body parts. This suggests that the affected brain networks are different between types of dystonia.
Glossary
- AIC=
- Akaike information criterion;
- BIC=
- Bayesian information criterion;
- LCA=
- latent class analysis;
- LMR=
- Lo-Mendell-Rubin
Footnotes
Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
Submitted and externally peer reviewed. The handling editor was Peter Hedera, MD, PhD.
Editorial, page 777
CME Course: NPub.org/cmelist
- Received November 17, 2021.
- Accepted in final form June 15, 2022.
- © 2022 American Academy of Neurology
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