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MREIT experiments with 200 µA injected currents: a feasibility study using two reconstruction algorithms, SMM and
V E Arpinar1, M J Hamamura, E Degirmenci
1Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA.
Physics in Medicine and Biology
|June 12, 2012
Summary
Magnetic Resonance Electrical Impedance Tomography (MREIT) can image conductivity using low currents. The iterative sensitivity matrix method (SMM) with Tikhonov regularization shows promise for clinical applications by tolerating noisy data better than harmonic B(Z).
Area of Science:
- Biomedical Engineering
- Medical Imaging
- Electrical Impedance Tomography
Background:
- Magnetic Resonance Electrical Impedance Tomography (MREIT) images tissue conductivity by applying electrical currents and measuring magnetic flux density via MRI.
- Current MREIT research is limited to phantoms and animals, with clinical translation hindered by a lack of specific safety standards for current limits.
- Existing medical instrumentation safety standards (e.g., IEC601) limit auxiliary currents to 100 µA, a level significantly lower than currents used in published MREIT studies.
Purpose of the Study:
- To investigate the feasibility of MREIT for accurate relative conductivity reconstruction in a simple agarose phantom using low injected currents.
- To evaluate the performance and noise sensitivity of two MREIT reconstruction algorithms under varying current conditions.
Main Methods:
- MREIT conductivity imaging was performed on an agarose phantom using a total injected current of 200 µA, resulting in 14.7 µA within the imaging slice.
- Two reconstruction algorithms were tested: iterative Sensitivity Matrix Method (SMM) with Tikhonov regularization and harmonic B(Z).
- Algorithm performance was assessed at both low (200 µA) and high (5 mA, 367 µA in slice) current levels to determine noise tolerance.
Main Results:
- Accurate conductivity imaging was achieved at low current levels (200 µA) using the specified imaging parameters.
- The iterative SMM with Tikhonov regularization demonstrated greater tolerance to noisy data compared to the harmonic B(Z) algorithm.
- Reconstruction using iterative SMM with Tikhonov regularization was successful even under high current conditions (5 mA).
Conclusions:
- MREIT is feasible for conductivity imaging at low current levels, suggesting potential for safer clinical applications.
- The iterative SMM with Tikhonov regularization is a robust algorithm for MREIT reconstruction, particularly in the presence of noise.
- Further research into MREIT safety standards is crucial for enabling widespread clinical translation.
