GOAL: As a multiphysics imaging approach, magnetoacoustic tomography with magnetic induction (MAT-MI) works on the physical mechanism of magnetic excitation, acoustic vibration, and transmission. METHODS: Based on the theoretical analysis of the source vibration, numerical studies are conducted to simulate the pathological changes of tissues for a single-layer cylindrical conductivity gradual-varying model and estimate the strengths of sources inside the model. RESULTS: The results suggest that the inner source is generated by the product of the conductivity and the curl of the induced electric intensity inside conductivity homogeneous medium, while the boundary source is produced by the cross product of the gradient of conductivity and the induced electric intensity at conductivity boundary. CONCLUSION: For a biological tissue with low conductivity, the strength of boundary source is much higher than that of the inner source only when the size of conductivity transition zone is small. In this case, the tissue can be treated as a conductivity abrupt-varying model, ignoring the influence of inner source. Otherwise, the contributions of inner and boundary sources should be evaluated together quantitatively. SIGNIFICANCE: This study provide basis for further study of precise image reconstruction of MAT-MI for pathological tissues.
GOAL: As a multiphysics imaging approach, magnetoacoustic tomography with magnetic induction (MAT-MI) works on the physical mechanism of magnetic excitation, acoustic vibration, and transmission. METHODS: Based on the theoretical analysis of the source vibration, numerical studies are conducted to simulate the pathological changes of tissues for a single-layer cylindrical conductivity gradual-varying model and estimate the strengths of sources inside the model. RESULTS: The results suggest that the inner source is generated by the product of the conductivity and the curl of the induced electric intensity inside conductivity homogeneous medium, while the boundary source is produced by the cross product of the gradient of conductivity and the induced electric intensity at conductivity boundary. CONCLUSION: For a biological tissue with low conductivity, the strength of boundary source is much higher than that of the inner source only when the size of conductivity transition zone is small. In this case, the tissue can be treated as a conductivity abrupt-varying model, ignoring the influence of inner source. Otherwise, the contributions of inner and boundary sources should be evaluated together quantitatively. SIGNIFICANCE: This study provide basis for further study of precise image reconstruction of MAT-MI for pathological tissues.