Abstract

Background and Purpose- Predicting the risk of stroke and determining intervention indications are highly important for patients with Moyamoya disease (MMD). Here, we evaluated a novel MMD grading system based on collateral circulation and Suzuki stage to evaluate symptoms and predict prognosis. Methods- In total, 301 idiopathic MMD patients were retrospectively analyzed between 2014 and 2016. A collateral circulation grading system with scores ranging from 1 to 12 was established: the anatomic extent of pial collateral blood flow from posterior cerebral artery to middle cerebral artery and anterior cerebral artery was scored from 1 to 6; perforator collateral and internal cerebral artery flow were scored as 6 to 1, which corresponded to Suzuki stages 1 to 6. Dynamic susceptibility contrast-magnetic resonance imaging was used to evaluate hemodynamic status. We assessed the association between the grading system and clinical characteristics. Results- We analyzed 364 symptomatic hemispheres of 301 patients (146 males, 28±16 years). Ischemic patients who presented with infarction were more likely to score <8 points (P<0.001), whereas those with ischemia symptoms (transient ischemic attack and headache) were more likely to score >8 points. Hemorrhagic patients who presented with intraparenchymal hemorrhage were more likely to score <8 points, whereas those who presented with intraventricular hemorrhage were more likely to score >8 points (P<0.001). According to dynamic susceptibility contrast-magnetic resonance imaging, lower scores were correlated with more severe time to peak delay (P<0.001) and worse relative cerebral blood volume ratio (P=0.016) and cerebral flow ratio (P=0.002). Encephaloduroarteriosynangiosis was performed in 348 symptomatic hemispheres. Patients who had collateral scores <4 points were more likely to have a postoperative stroke and a worse prognosis during the follow-up. Conclusions- This new MMD collateral grading system correlated well with clinical symptoms, hemodynamic status, and therapeutic prognosis and may facilitate risk stratification and prognosis predictions in patients with MMD.

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