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DOI 10.1016/j.jns.2016.08.020

Медицинская библиотека · Journal of the neurological sciences · 2016

Adult moyamoya-atherosclerosis syndrome: Clinical and vessel wall imaging features.

Han Cong, Li Ming-Li, Xu Yu-Yuan, Ye Ting, Xie Chen-Fan, Gao Shan, Duan Lian, Xu Wei-Hai

СтатьяНаблюдательное исследованиеПеревод в очереди

Аннотация

INTRODUCTION

We sought to incorporate high-resolution magnetic resonance imaging (HRMRI) into the diagnostic process of intracranial atherosclerosis associated moyamoya syndrome in adult patients.

METHODS

From March 2013 to March 2014, HRMRI was consecutively performed on adult patients with angiographic moyamoya. The patients were classified as moyamoya - plaques (MMD-P) if a plaque could be identified or as moyamoya - no plaques (MMD-NP) if a plaque could not be identified. The angiography, HRMRI findings and atherogenic risk factors of these patients were analyzed.

RESULTS

Fifty-one patients (mean age 39±9, 20 males) were enrolled. On traditional angiography, probable intracranial atherosclerosis was identified in 5 patients, no definite diagnosis in 12 patients, and moyamoya disease in 34 patients. On HRMRI, 15 out of 32 patients with risk factors and 4 out of 19 patients without risk factors were found to have plaques and were diagnosed as MMD-P, while the other 32 patients were diagnosed as MMD-NP. The MMD-P patients were more likely to be older (P=0.033) and male (P=0.0353) and were less likely to have cerebral hemorrhage (P=0.0066) and a history of disease progression (P=0.0012).

CONCLUSIONS

Our study suggests that HRMRI can help diagnose intracranial atherosclerosis more accurately in moyamoya disease patients with atherogenic risk factors. The distinct clinical features between MMD-P and MMD-NP patients suggest different underlying pathophysiology and therefore potentially different treatment strategies.

Для цитирования: Han Cong, Li Ming-Li, Xu Yu-Yuan, Ye Ting, Xie Chen-Fan, Gao Shan, Duan Lian, Xu Wei-Hai. Adult moyamoya-atherosclerosis syndrome: Clinical and vessel wall imaging features.. Journal of the neurological sciences. 2016. DOI: 10.1016/j.jns.2016.08.020.

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