Use of 3-D magnetic resonance electrical impedance tomography in detecting human cerebral stroke： a simulation study

• Published in: Journal of Zhejiang University. B. Science Vol. 6; no. 5; pp. 438 - 445
• Main Author: 高诺 朱善安 贺斌
• Format: Journal Article
• Language: English
• Published: China Springer Nature B.V 01.05.2005; School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China%Department of Biomedical Engineering, University of Minnesota, MN, USA; Zhejiang University Press
• Subjects: 3D磁共振电阻抗X线断层摄影术; Algorithms; Biotechnology; Brain Ischemia - pathology; Computer Simulation; Conductivity; Correlation coefficient; Correlation coefficients; Electric Impedance; Electrical impedance; Hemorrhage; Hemorrhage - pathology; Humans; Imaging, Three-Dimensional; Impedance; Ischemia; Iterative methods; Magnetic resonance; Magnetic Resonance Imaging; Medical imaging; Neuroimaging; Radio signals; Resonance; Signal to noise ratio; Stroke; Stroke - diagnosis; Stroke - pathology; Tomography; Tomography - instrumentation; Tomography - methods; White noise; 传导性; 模拟技术; 电流密度; Conductivity; Magnetic Resonance Electrical Impedance Tomography; Ischemic stroke; Current density imaging; Acute cerebral stroke; Hemorrhagic stroke
• ISSN: 1673-1581; 1862-1783
• DOI: 10.1631/jzus.2005.B0438

We have developed a new three dimensional (3-D) conductivity imaging approach and have used it to detect human brain conductivity changes corresponding to acute cerebral stroke. The proposed Magnetic Resonance Electrical Impedance Tomography (MREIT) approach is based on the J-Substitution algorithm and is expanded to imaging 3-D subject conductivity distribution changes. Computer simulation studies have been conducted to evaluate the present MREIT imaging approach.Simulations of both types of cerebral stroke, hemorrhagic stroke and ischemic stroke, were performed on a four-sphere head model.Simulation results showed that the correlation coefficient (CC) and relative error (RE) between target and estimated conductivity distributions were 0.9245±0.0068 and 8.9997%±0.0084%, for hemorrhagic stroke, and 0.6748±0.0197 and 8.8986%±0.0089%,for ischemic stroke, when the SNR (signal-to-noise radio) of added GWN (Gaussian White Noise) was 40. The convergence characteristic was also evaluated according to the changes of CC and RE with different iteration numbers. The CC increases and RE decreases monotonously with the increasing number of iterations. The present simulation results show the feasibility of the proposed 3-D MREIT approach in hemorrhagic and ischemic stroke detection and suggest that the method may become a useful alternative in clinical diagnosis of acute cerebral stroke in humans.