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Abstract #1075

Automatic identification of Moyamoya disease based on time-of-flight MR angiography

Zheng Tan1, Mingming Lu2, Shuai Liu1, Shitong Liu2, Hongtao Zhang2, Xiaoying Tang1, Jianming Cai2, and Fei Shang1
1Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, China, 2Department of Radiology, The Fifth Medical Center of PLA General Hospital, Beijing, China

Synopsis

Keywords: Vessels, StrokeMoyamoya disease (MMD) is a rare chronic progressive cerebrovascular disease that causes strokes. For the diagnosis of MMD, time-of-flight magnetic resonance angiography (TOF-MRA) can be an alternative to digital subtraction angiography (gold standard) owing to its non-invasive and radiation-free attributes. In this study, the deep learning method (ResNet-50) was used for MMD automatic diagnosis on the maximum intensity projection images from 3D TOF-MRA, and five-fold cross-validation was used for validation. The method exhibits the accurate ability (AUC: 0.990 ± 0.008, accuracy: 0.933 ± 0.063) to identify MMD and has the potential to improve the clinical management of MMD.

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Keywords