J Korean Neurol Assoc.
1998 Aug;16(4):432-438.
Clinical and Neuroimaging Features of Moyamoya Disease
- Affiliations
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- 1Department of Neurology, Gyeongsang National University College of Medicine.
- 2Gyeongsang Institute for Neuroscience, Gyeongsang National University.
Abstract
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BACKGROUND: Moyamoya disease is a chronic cerebrovascular disorders in which stenosis of the major arteries of the circle of Willis at the base of the skull progresses to occlusion. We observed two kinds of collateral pathways from the extracranial to the intracranial arteries. Also we evaluated clinlcal and neuroimaging features of moyamoya disease to give on aid in diagnosis.
METHODS
We analysed 17 patients with moyamoya disease through the medical record and neuroimaging (conventional angiography and/or MR angiography) review. Six out of 17 patients were children(< OR =15 years) and the other 11 patients were adults(15 years). There were 8 males and 9 females.
RESULTS
In our result, moyamoya disease was more common in the adult. There was bimodal age distribution, so average age of onset in children was 8-year-old and in adult 37-year-old. Common clinical features are seizure (66%), TIA (17%), and psychotic behavior (17%) in childrens and hemorrhages (73%), infarction (18%), seizures (9%) in adults. According to angiographic staging classification of Suzuki et al. (1967), our cases showed distribution of stage I (13%), stage II (8.8%), stage III (65.3%), stage IV (4.3%), stage V (4.3%), stage VI (4.3%). In collateral vessels of moyamoya disease, there were 7 cases of ethmoidal moyamoya, 3 of vault moyamoya and 1 of mixed form. It is interesting that there were five cases of unilateral moyamoya disease and one case had pseudoaneurysm.
CONCLUSION
According to our results, we may say that seizures are common in the children and hemorrhages are in the adult. Unilateral moyamoya were mainly occurred in the adult. Ethmoidal collaterals were common among collaterals and stage III had a more cases than others in our neuroimaging data. These clinical and neuroimaging data may help interpretation and diagnosis of moyamoya disease.
