J Stroke.
2014 Sep;16(3):161-172. 10.5853/jos.2014.16.3.161.
MRI-based Algorithm for Acute Ischemic Stroke Subtype Classification
- Affiliations
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- 1Department of Neurology, Eulji University Hospital, Eulji University, Daejeon, Korea.
- 2Department of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, Seongnam, Korea. braindoc@snu.ac.kr
- 3Department of Neurology, Eulji General Hospital, Eulji University, Seoul, Korea.
- 4Department of Neurology, Seoul Medical Center, Seoul, Korea.
- 5Department of Neurology, Ilsan Paik Hospital, Inje University, Goyang, Korea.
- 6Department of Neurology, Soonchunhyang University Hospital, Seoul, Korea.
- 7Department of Neurology, Yeungnam University Hospital, Daegu, Korea.
- 8Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea.
- 9Department of Neurology, Dong-A University Hospital, Busan, Korea.
- 10Department of Neurology, Chonnam National University Hospital, Gwangju, Korea.
- 11Department of Neurology, Jeju National University Hospital, Jeju National University School of Medicine, Jeju, Korea.
- 12Department of Neurology, Chungbuk National University College of Medicine, Cheongju, Korea.
- 13Biostatistical Consulting Unit, Soonchunhyang University Medical Center, Seoul, Korea.
- 14Department of Biostatistics, Korea University College of Medicine, Seoul, Korea.
- 15Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea.
- KMID: 2223700
- DOI: http://doi.org/10.5853/jos.2014.16.3.161
Abstract
- BACKGROUND AND PURPOSE
In order to improve inter-rater reliability and minimize diagnosis of undetermined etiology for stroke subtype classification, using a stroke registry, we developed and implemented a magnetic resonance imaging (MRI)-based algorithm for acute ischemic stroke subtype classification (MAGIC).
METHODS
We enrolled patients who experienced an acute ischemic stroke, were hospitalized in the 14 participating centers within 7 days of onset, and had relevant lesions on MR-diffusion weighted imaging (DWI). MAGIC was designed to reflect recent advances in stroke imaging and thrombolytic therapy. The inter-rater reliability was compared with and without MAGIC to classify the Trial of Org 10172 in Acute Stroke Treatment (TOAST) of each stroke patient. MAGIC was then applied to all stroke patients hospitalized since July 2011, and information about stroke subtypes, other clinical characteristics, and stroke recurrence was collected via a web-based registry database.
RESULTS
The overall intra-class correlation coefficient (ICC) value was 0.43 (95% CI, 0.31-0.57) for MAGIC and 0.28 (95% CI, 0.18-0.42) for TOAST. Large artery atherosclerosis (LAA) was the most common cause of acute ischemic stroke (38.3%), followed by cardioembolism (CE, 22.8%), undetermined cause (UD, 22.2%), and small-vessel occlusion (SVO, 14.6%). One-year stroke recurrence rates were the highest for two or more UDs (11.80%), followed by LAA (7.30%), CE (5.60%), and SVO (2.50%).
CONCLUSIONS
Despite several limitations, this study shows that the MAGIC system is feasible and may be helpful to classify stroke subtype in the clinic.
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