Feature-based Quality Assessment of Middle Cerebral Artery Occlusion Using 18F-Fluorodeoxyglucose Positron Emission Tomography
Wuxian He1 • Hongtu Tang2 • Jia Li2 • Chenze Hou1 • Xiaoyan Shen4 • Chenrui Li1 • Huafeng Liu5,6 • Weichuan Yu1,31 Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
2 Department of Acupuncture and Moxibustion, Hubei University of Chinese Medicine, Wuhan 430065, China
3 HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute, Futian, Shenzhen, China
4 College of Science, Zhejiang University of Technology, Hangzhou 310023, China
5 State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China
6 Intelligent Optics & Photonics Research Center, Jiaxing Research Institute of Zhejiang University, Jiaxing 314000, China
Abstract
In animal experiments, ischemic stroke is usually induced through middle cerebral artery occlusion (MCAO), and quality assessment of this procedure is crucial. However, an accurate assessment method based on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is still lacking. The difficulty lies in the inconsistent preprocessing pipeline, biased intensity normalization, or unclear spatiotemporal uptake of FDG. Here, we propose an image feature-based protocol to assess the quality of the procedure using a 3D scale-invariant feature transform and support vector machine. This feature-based protocol provides a convenient, accurate, and reliable tool to assess the quality of the MCAO procedure in FDG PET studies. Compared with existing approaches, the proposed protocol is fully quantitative, objective, automatic, and bypasses the intensity normalization step. An online interface was constructed to check images and obtain assessment results.
Keywords
Ischemic stroke; Middle cerebral artery occlusion; Brain metabolism; FDG PET imaging; SIFT classification
